{"role": "user", "content": "[M G] co/Civitai/Qwen-Image-2512-GGUF \"Civitai/Qwen-Image-2512-GGUF · Hugging Face\"\nSollen wir qwen image auch selber über comfyui laufen lassen? Oder wäre das parallel mit dem videomodell nicht möglich?\n für GGUF + ComfyUI ist aktuell Qwen-Image-2512-GGUF wahrscheinlich die beste praktische Wahl – nicht das ältere Qwen-Image, sondern die neuere **Qwen-Image-2512**-Variante.\n\nMeine Rangliste für deinen Usecase:\n\n| Zweck | Empfehlung | Warum |\n| ------------------------------------------------------------------------- | ----------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Beste kostenlose GGUF-Bildgenerierung in ComfyUI | Qwen-Image-2512-GGUF | Sehr stark bei Realismus, Text im Bild, Prompt-Folgen; Apache-2.0; direkt als GGUF verfügbar. Unsloth beschreibt es als GGUF-Quantisierung mit ComfyUI-GGUF-Support. ([Hugging Face][1]) |\n| Bildbearbeitung / Referenzbilder / Text in bestehenden Bildern ändern | Qwen-Image-Edit-2511-GGUF | Separates Edit-Modell, GGUF, nutzt ComfyUI-GGUF. ([Hugging Face][2]) |\n| Schnell / weniger VRAM / experimentell | Z-Image Turbo GGUF | Läuft mit ComfyUI-GGUF und ist deutlich leichter/schneller, aber nicht die beste Gesamtqualität. ([Hugging Face][3]) |\n| Alternative zu Qwen, stark aber schwerer | FLUX.2-dev-GGUF | Gute Qualität, aber grösser, Lizenz weniger frei/praktisch als Apache-2.0; Q4_K_M allein ca. 18.7 GB. ([Hugging Face][4]) |\n| Aktuell stärkstes Open-Weights-Modell allgemein | HiDream-O1-Image-Dev-2604 | Führt bei Artificial Analysis unter Open-Weights, aber der ComfyUI-Weg ist derzeit eher über Custom Node/FP8, nicht sauber als etablierter GGUF-Standard. ([artificialanalysis.ai][5]) |\n\nKurz gesagt:\nFür deine lokale ComfyUI/Hermes-Pipeline würde ich Qwen-Image-2512-GGUF nehmen.\n\nDie passende Auswahl nach VRAM:\n\n| VRAM | Modell/Quantisierung |\n| ----------: | ------------------------------------------------------ |\n| 8–12 GB | Qwen-Image-2512 Q4, Low-VRAM, langsam aber möglich |\n| 16 GB | Q5 oder Q6 testen |\n| 24 GB | Q6 oder Q8, beste Balance aus Qualität und Stabilität |\n| <8 GB | eher Z-Image Turbo GGUF statt Qwen |\n\nWichtig: Qwen-Image-2512 ist ein 20B Image-Diffusion-Modell, kein klassisches LLM. Es nutzt aber grosse Text-/Vision-Komponenten. Die GGUF-Dateien sind relativ gross: bei einer Qwen-Image-2512-GGUF-Variante sind z. B. Q4 ca. 11.5 GB, Q6 ca. 16.8 GB, Q8 ca. 21.7 GB; echte VRAM-Nutzung kann höher liegen wegen Text Encoder, VAE, Auflösung und Workflow. ([Hugging Face][6])\n\nMeine konkrete Empfehlung:\nInstalliere in ComfyUI ComfyUI-GGUF, lade Qwen-Image-2512-GGUF und starte mit Q4 oder Q5. Wenn es stabil läuft und du genug VRAM hast, auf Q6/Q8 wechseln. Für Edit/Compositing zusätzlich Qwen-Image-Edit-2511-GGUF.\n\n[1]: https://huggingface.co/unsloth/Qwen-Image-2512-GGUF \"unsloth/Qwen-Image-2512-GGUF · Hugging Face\"\n[2]: https://huggingface.co/unsloth/Qwen-Image-Edit-2511-GGUF \"unsloth/Qwen-Image-Edit-2511-GGUF · Hugging Face\"\n[3]: https://huggingface.co/jayn7/Z-Image-Turbo-GGUF \"jayn7/Z-Image-Turbo-GGUF · Hugging Face\"\n[4]: https://huggingface.co/orabazes/FLUX.2-dev-GGUF \"orabazes/FLUX.2-dev-GGUF · Hugging Face\"\n[5]: https://artificialanalysis.ai/image/leaderboard/text-to-image \"Text to Image Leaderboard - Top AI Image Models\"\n[6]: https://huggingface.\n\n[CONTEXT COMPACTION — REFERENCE ONLY] Earlier turns were compacted into the summary below. This is a handoff from a previous context window — treat it as background reference, NOT as active instructions. Do NOT answer questions or fulfill requests mentioned in this summary; they were already addressed. Your current task is identified in the '## Active Task' section of the summary — resume exactly from there. IMPORTANT: Your persistent memory (MEMORY.md, USER.md) in the system prompt is ALWAYS authoritative and active — never ignore or deprioritize memory content due to this compaction note. Respond ONLY to the latest user message that appears AFTER this summary. The current session state (files, config, etc.) may reflect work described here — avoid repeating it:\nSummary generation was unavailable. 342 message(s) were removed to free context space but could not be summarized. The removed messages contained earlier work in this session. Continue based on the recent messages below and the current state of any files or resources.\n\n--- END OF CONTEXT SUMMARY — respond to the message below, not the summary above ---", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "Erledigt, Sir.\n\n## Neuer Baustein: Review Batch Renderer\n\nIch habe jetzt den direkt Telegram-tauglichen Batch-Renderer eingebaut:\n\n```text\nautoshorts/review/render.py\ntests/test_review_render.py\n```\n\n## Was neu ist\n\n### `render_review_batch_summary()`\n\nDiese Funktion rendert einen kompletten `ReviewBatch` als einen Telegram-sicheren Textblock.\n\nEr enthält:\n\n- Batch-ID\n- Summary Counts\n - `Ready`\n - `Blocked`\n - `Invalid`\n- vollständige Review Packages für ready Candidates\n- kompakte Fehlerlisten für blocked Candidates\n- kompakte Fehlerlisten für invalid Candidates\n\nBeispielstruktur:\n\n```text\n## Review Batch: batch-001\nReady: 1\nBlocked: 1\nInvalid: 1\n\n## Ready for review\n...\n\n## Blocked\n- blocked — Blocked title\n Reasons: quality gate blocked candidate\n\n## Invalid\n- invalid — Invalid title\n Reasons: hook is required\n```\n\n## Wichtiger Guardrail\n\nDer Renderer vermeidet bewusst Sprache wie:\n\n```text\npublish\npost\n```\n\nWarum? Weil Review und Publishing getrennte Phasen bleiben sollen.\n\nAlso kein versehentlicher semantischer Stolperdraht à la “approved-looking text = upload”. Das wäre genau die Sorte Automations-Dummheit, für die später Meetings erfunden werden.\n\n## TDD eingehalten\n\nAblauf:\n\n1. Tests für Batch Renderer geschrieben.\n2. RED verifiziert:\n\n```text\nModuleNotFoundError: No module named 'autoshorts.review.render'\n```\n\n3. Minimal implementiert.\n4. Tests grün.\n5. README aktualisiert.\n6. Commit erstellt.\n\n## Tests\n\nAktueller Stand:\n\n```text\n41 passed in 0.08s\n```\n\n## Neuer Commit\n\nBranch:\n\n```text\nfeat/core-approval-quality-gates\n```\n\nCommit:\n\n```text\nb7b5270 feat: add review batch renderer\n```\n\nAktueller Verlauf:\n\n```text\nb7b5270 feat: add review batch renderer\n2155728 feat: add review workflow buckets\ndeea24f feat: add candidate factory\nae6a4f6 feat: add content pillar registry\n49d6daf feat: add idea candidates and testbatches\n55b17fa feat: add telegram review package\n3555ec2 feat: add approval parser and quality gate\n7642749 Initial commit\n```\n\n## Pipeline jetzt\n\nWir haben jetzt die erste durchgängige interne Review-Strecke:\n\n```text\nContent Pillar\n→ CandidateDraft\n→ Candidate Factory\n→ VideoCandidate\n→ TestBatch\n→ Review Workflow\n → ready_for_review\n → blocked\n → invalid\n→ Review Batch Renderer\n→ Telegram-safe Review Text\n→ Approval Parser\n```\n\n## Nächster sinnvoller Schritt\n\nAls Nächstes würde ich bauen:\n\n```text\nautoshorts/cli/demo_review_batch.py\n```\n\noder besser als testbarer Core:\n\n```text\nautoshorts/demo/sample_batch.py\n```\n\nZiel:\n\n- sample AI-Life-Systems Batch erzeugen\n- 1 ready Candidate\n- 1 blocked Candidate\n- 1 invalid Candidate\n- ReviewBatch bauen\n- Telegram-Text rendern\n\nDann können wir mit einem einzigen Command einen echten Review-Output lokal erzeugen und später direkt an Telegram hängen.", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "user", "content": "[CONTEXT COMPACTION — REFERENCE ONLY] Earlier turns were compacted into the summary below. This is a handoff from a previous context window — treat it as background reference, NOT as active instructions. Do NOT answer questions or fulfill requests mentioned in this summary; they were already addressed. Your current task is identified in the '## Active Task' section of the summary — resume exactly from there. IMPORTANT: Your persistent memory (MEMORY.md, USER.md) in the system prompt is ALWAYS authoritative and active — never ignore or deprioritize memory content due to this compaction note. Respond ONLY to the latest user message that appears AFTER this summary. The current session state (files, config, etc.) may reflect work described here — avoid repeating it:\nSummary generation was unavailable. 49 message(s) were removed to free context space but could not be summarized. The removed messages contained earlier work in this session. Continue based on the recent messages below and the current state of any files or resources.\n\n--- END OF CONTEXT SUMMARY — respond to the message below, not the summary above ---", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "[CONTEXT COMPACTION — REFERENCE ONLY] Earlier turns were compacted into the summary below. This is a handoff from a previous context window — treat it as background reference, NOT as active instructions. Do NOT answer questions or fulfill requests mentioned in this summary; they were already addressed. Your current task is identified in the '## Active Task' section of the summary — resume exactly from there. IMPORTANT: Your persistent memory (MEMORY.md, USER.md) in the system prompt is ALWAYS authoritative and active — never ignore or deprioritize memory content due to this compaction note. Respond ONLY to the latest user message that appears AFTER this summary. The current session state (files, config, etc.) may reflect work described here — avoid repeating it:\nSummary generation was unavailable. 138 message(s) were removed to free context space but could not be summarized. The removed messages contained earlier work in this session. Continue based on the recent messages below and the current state of any files or resources.\n\n--- END OF CONTEXT SUMMARY — respond to the message below, not the summary above ---\n\n", "tool_calls": [{"id": "call_NTHduQgrjgopeIDQjLU7WqR3", "call_id": "call_NTHduQgrjgopeIDQjLU7WqR3", "response_item_id": "fc_0dc9f371a6d55e3f016a13699a4c588191b949a004942c6414", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" \\\"-c:a\\\",\\n \\\"aac\\\",\\n \\\"-movflags\\\",\",\"old_string\":\" \\\"-c:a\\\",\\n \\\"aac\\\",\\n \\\"-movflags\\\",\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": false, \"error\": \"old_string and new_string are identical\"}", "tool_call_id": "call_NTHduQgrjgopeIDQjLU7WqR3", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_XM00r5KPTh6forcLRQDk4MCB", "call_id": "call_XM00r5KPTh6forcLRQDk4MCB", "response_item_id": "fc_0dc9f371a6d55e3f016a13699e643c8191accd131f11d04de7", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py\",\"offset\":150,\"limit\":60}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[read_file] read /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py from line 150 (2,879 chars)", "tool_call_id": "call_XM00r5KPTh6forcLRQDk4MCB", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_BOn9iaH4JaUk2Fw0lhb27bCI", "call_id": "call_BOn9iaH4JaUk2Fw0lhb27bCI", "response_item_id": "fc_0dc9f371a6d55e3f016a1369a298b48191a07d18538ff1871b", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\": \"replace\", \"new_string\": \" \\\"-c:a\\\",\\n \\\"aac\\\",\\n ]\\n if plan.duration_mode == \\\"trim_to_audio\\\":\\n command.append(\\\"-shortest\\\")\\n command.extend([\\n \\\"-movflags\\\",\\n \\\"+faststart\\\",\\n plan.outp...[truncated]\", \"old_string\": \" \\\"-c:a\\\",\\n \\\"aac\\\",\\n \\\"-movflags\\\",\\n \\\"+faststart\\\",\\n plan.output_path,\\n ]\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py (1,043 chars result)", "tool_call_id": "call_BOn9iaH4JaUk2Fw0lhb27bCI", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_PfVex4N3ANJw37Hxbxy7umLr", "call_id": "call_PfVex4N3ANJw37Hxbxy7umLr", "response_item_id": "fc_0dc9f371a6d55e3f016a1369aaba908191bcd0da05bc4c34a9", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\":30,\"offset\":206,\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[read_file] read /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py from line 206 (819 chars)", "tool_call_id": "call_PfVex4N3ANJw37Hxbxy7umLr", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_ZOlCuZgx5P3ZT84fOSAT03vW", "call_id": "call_ZOlCuZgx5P3ZT84fOSAT03vW", "response_item_id": "fc_0dc9f371a6d55e3f016a1369af2fb881918bcdde042bbc0bb0", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" stdout=completed.stdout,\\n stderr=completed.stderr,\\n duration_mode=plan.duration_mode,\\n side_effects=(\\\"write_subtitles\\\", \\\"call_ffmpeg\\\", \\\"write_mp4\\\"),\",\"old_string\":\" stdout=completed.stdout,\\n stderr=completed.stderr,\\n side_effects=(\\\"write_subtitles\\\", \\\"call_ffmpeg\\\", \\\"write_mp4\\\"),\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py (886 chars result)", "tool_call_id": "call_ZOlCuZgx5P3ZT84fOSAT03vW", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_yIBuBdX0jSSo3toHlz8wdijA", "call_id": "call_yIBuBdX0jSSo3toHlz8wdijA", "response_item_id": "fc_0dc9f371a6d55e3f016a1369b9e4388191b5fe116bee3d2d38", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_voiceover.py tests/test_audio_caption_preview.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"........ [100%]\\n8 passed in 0.05s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_yIBuBdX0jSSo3toHlz8wdijA", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_JB2HZzXfPYYEIXxlxh8BdC7q", "call_id": "call_JB2HZzXfPYYEIXxlxh8BdC7q", "response_item_id": "fc_0dc9f371a6d55e3f016a1369c3a0788191b218e7bbb3360720", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"python - <<'PY'\\nfrom pathlib import Path\\nfrom autoshorts.demo.truetrace_preview_packages import build_top_truetrace_preview_packages\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceo...[truncated]\", \"timeout\": 300, \"workdir\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Improving clip integration**\n\nI need to focus on producing an improved clip by integrating a new voiceover and adjusting the subtitle duration. I'm thinking that the target duration might not perfectly match the actual length from Edge TTS, which could be longer than expected. To make sure subtitles fit well, I can aim for a voice target duration of 24 seconds, although the actual might end up being around 26 seconds. I'll need to check this using the terminal for mandatory duration settings before generating the final version.", "reasoning_content": "**Improving clip integration**\n\nI need to focus on producing an improved clip by integrating a new voiceover and adjusting the subtitle duration. I'm thinking that the target duration might not perfectly match the actual length from Edge TTS, which could be longer than expected. To make sure subtitles fit well, I can aim for a voice target duration of 24 seconds, although the actual might end up being around 26 seconds. I'll need to check this using the terminal for mandatory duration settings before generating the final version.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE2nDmuQE1qoioQMhWTi0FJGQWUxRugJNigXW6R8Z2GwZTd2zSCn5HZlC8RHdjOk0x_Q0uFp_U1v0_wJTjbB8KIhhjeoH1GD3BbQuQplsN468N3kHTq88pP2qJMEAviFsbCHp8LFWDeaPKFRHXsTibcOG5nYMJuvkjZWMLpYiJXpulkaAq2LGBeOWXGbdwfZ1Pqdf1OlgQXyGy3DOGoeEddeSicE6wW2gYMOqoU4YRazA1FkNHhX9B2kkoENtncWJSC4d6j1JulEdfoQsnI3rCoybxJAvb_J1K0zVqrrONMZiaC_y7S9DxBgGd4quLy-6rU-v2A3cPUc9G1TSZvTOGcvCotns0_iRNPZeOdm4hkginMMacZ0m_-9THwX1PIx83QknqUQX0Iuw5aGfDDVzrmpUWfgE3evyDaIZCpvC2c6wuh-64MwdnJSo-3ANwWFu3-Sk-MhrEQz4vDMrjnNtzX30yKU6qivGfOZCERPwIegliT5deiJkYboxw2jgk7S4O1kQK1-wThPf40Isea5C_5CLv6UomDxmrmee1wbw2KCz62KkyYmc5qj3k-0KX5RLkWuRHWJtpdzTHmLg6PRQw0KZBheLD_ZZkkCjPIWNdL78I64fo2kbc2MciraMRjj6Ykp5xA4M9uDSDsAJDNXmKJ8VWf3sfnBLVc0PIC8VLAQz6FmF5o6SNUj5v3DdS_omWyKfyofw8Emws_q8lE5glo1a_q9W_rpSUJ74MtzZui3FoYTfLy_BelyRfFVHP4PXSnHzMgdpZH2LKJySIeA3Bzohkj0esFcpxSa53b3_qFtayqgCwDo5p8SzULnRs_F8ESlrDTC5qtalzNNHwH8aB1WyjVDRI-4YPRt6_tj4G4v3R0ZhMcwK07UQtej8bCRdvHDisPX95nfsxq-FO2dzkDXmaH0hSLGxCzrKWMBfSXHvkxa1pbrepqIRHsig8pd6mwGNsvArDO3lzElxEN23QCxpHdY_NYvQS_AgEi6VsggEF3quTc_-7b2PnhxuOCzd8QRHF2scMiVTavfEZuWpRQFQOXHsGYfr7Q6IsP2H3dEGmlZhZPRppCVDzJZI8BrxtSRl7T2pzErgVzxRmOuQVePFWLtDAKKa0XPNVEce2I-6ZLTVYdymJhkTTlOuBQJhLxZQ9Fdf_rCIIYRB0OQ0OWu4CBmm_YbUBI22Y_ckxVaJt_BxcCj-PHsSHEOE0oA7o58h-bddVkA3ImZPpKlFK5nY8eSagbfTsTsCSWXbz8i1FCUHDoKOZTIIsU4VX57ntFHBZFP-657IWHsMNDrh2aj1p7R05TWapFTpyiSTm_ES-8YTK2zwOeWwfI0x1HAWnGA7scZKOOibbPgd00jQRZ8J1Q==", "id": "rs_0dc9f371a6d55e3f016a1369c090a081918115e14a9be60b50", "summary": [{"type": "summary_text", "text": "**Improving clip integration**\n\nI need to focus on producing an improved clip by integrating a new voiceover and adjusting the subtitle duration. I'm thinking that the target duration might not perfectly match the actual length from Edge TTS, which could be longer than expected. To make sure subtitles fit well, I can aim for a voice target duration of 24 seconds, although the actual might end up being around 26 seconds. I'll need to check this using the terminal for mandatory duration settings before generating the final version."}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `python - <<'PY'\nfrom pathlib import Path\nfrom autoshorts.demo.truetrace_previ...` -> exit 0, 1 lines output", "tool_call_id": "call_JB2HZzXfPYYEIXxlxh8BdC7q", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_Glpt4DtqHdyXzQMv1jV4fzz1", "call_id": "call_Glpt4DtqHdyXzQMv1jV4fzz1", "response_item_id": "fc_0dc9f371a6d55e3f016a1369dfdd908191a98fec339a6562a6", "type": "function", "function": {"name": "write_file", "arguments": "{\"content\": \"import subprocess\\n\\nfrom autoshorts.audio.probe import probe_media_duration_seconds\\n\\n\\ndef test_probe_media_duration_seconds_parses_ffprobe_output():\\n calls = []\\n\\n def fake_runner(command, *, capt...[truncated]\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_probe.py\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Evaluating subtitle issues**\n\nI’m looking into subtitles for a clip that's 29 seconds long, but they're only 24 seconds, which isn't right. I think I need to implement an audio probe to rebuild the track's actual duration. Maybe I can do this quickly, but I feel like tests are essential. I might generate a probe module and test it with a fake runner. Also, I could consider using ffprobe in the terminal to check the actual duration, and then rerender it. I just need to keep everything aligned with TDD and write the necessary tests.", "reasoning_content": "**Evaluating subtitle issues**\n\nI’m looking into subtitles for a clip that's 29 seconds long, but they're only 24 seconds, which isn't right. I think I need to implement an audio probe to rebuild the track's actual duration. Maybe I can do this quickly, but I feel like tests are essential. I might generate a probe module and test it with a fake runner. Also, I could consider using ffprobe in the terminal to check the actual duration, and then rerender it. I just need to keep everything aligned with TDD and write the necessary tests.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE2nfJPzaCBmXhTkR8dS5_SsxHQhC_TYABAk_hEH1huJ_aUnqcWaJtW_U_uh6TrSlMsblCBLsAXH3Z1_Q0_uHOwa1d3IcgjCF0SAMtfXBsG64pZvC-mBeZIDlLvR0kMESe7FoLnOJmEuxUwWmrjDjOlgffjOpj_UJ0aQIdvKtzYwpGuPMw_M0HNTZihDkslXfTRS_ZSfGjTO0NUO0nPzZIyRLooq5Qv6aFjtbOU06WZ3Z5dy-_h3oKvQX4QSOxIMtygL3oZtL1MaRFC-NqTqBCZlLLm4un0eiGU2IBEtz07mIbe8asu5TYkwmD6dRvmYdih0ktKTFaf2V2nh2qK3yrDVeuq06v-5sPhD0BoOdH3nc0mPc3PDX0OwQXsA8xNc4j9Xx2F4mPXfnnRMgLFSUJMg2IE79x53OGEYkO4NEdUKUit31y3jIzYRSyHZM1yCTYg07oNiB-1DEYWyWKB-5f-HdR0w0KIfgKu8r0_wYTjNvoG9jiyiHK4_xIGehpLJ5w3kS4ZzNXD1Ow6ZKz4qIaoe6n8KOnohIBxYuVVQLnahLCdQYEwpkBqBpgOhT5Mp4dbehj-mpKNeXwEvtjneqaFz1te28lBRchxdsJCqxhz-pDCQPCLfLFAEUJg3s5HiU6DlMZriZgUcxow8Bi6d5GirXGZplUbuRs8FeeHuIT679Zw0LWoCX5920Hl6dzhTqmtlsYSJ_Gk1C5-NC4Hb731S0Hznj-uAM22SVOUX4sr1Akxm2gPMVHc4ATWQEYSRm9QSAc_pJMAIMVEjR8n5CyCcCp_VLj4KuPyXj4lL9gdSHLFDehCj827DzUndgOsLPrUTq25dDalAlz-IojRtHKbMXVJNNTFgf14GDTiYV5n0Ox616e_SvYehlTZAPJhiy1ZwReajwyp0QWX3LEmx_YUh5aTe87gVLm_-YSjlnxzfBYeqg18C7X8Q8PqiZfXAVZys8uMoE3YuWD_N0h2Os8Ww8qMrl1vsQOIF5TGZjlJcgm1eonlYdP8e0BqEAR5KvbXkduPXiRdyCmI9SiBJYDMq_ovrUot2p-w2a7bjtunSix46tQumpT-eki0BwXxFgiADJXDfkBkWYP0I6X8D02x7B5WuSsXDIL3aBFphNukqyyPfqr5CObKTHuHFZfhOZ49qvrtjmYmupzUQmJE2P1jeN86K1Ni07DHjeJQsl30pFYea7Ql9_60mPzkLITl_IKjEEUjVwHPYK6UUYkgLM6UkOk6KhN5h7QfXX6_XyiGfqRyVG7zgdf9sz0Bo7EQXQ1n61VbS8JcD1R_CEtF5V0yQeOnAtdX8Jo6k75Jqy4Ts8fEBqYS-vnvh9YFLyGRh21bXALZuNUpPoL5JDpXY4wwaz9b63UBb8NcA2uMct7xTjSEZI5iPup-Y3piIJnm-J7BZlYMptXrVm9HCPobA7rjWVrRmzxDApKZVT4DVz1M0gjhezNqYryGSkdYanENq9Acf9eBCGn7W0yjNdEsajIiMJ5NJmnbvVDVta5H7lxYWtWpM6SWV4ALmm_SQgEMrka4Rt4AIxZ0f3HRi8gr5V1Pv6GDNjbMhTTrf-ONzURzNVsqI=", "id": "rs_0dc9f371a6d55e3f016a1369dbc7908191990c2141fc6c16f7", "summary": [{"type": "summary_text", "text": "**Evaluating subtitle issues**\n\nI’m looking into subtitles for a clip that's 29 seconds long, but they're only 24 seconds, which isn't right. I think I need to implement an audio probe to rebuild the track's actual duration. Maybe I can do this quickly, but I feel like tests are essential. I might generate a probe module and test it with a fake runner. Also, I could consider using ffprobe in the terminal to check the actual duration, and then rerender it. I just need to keep everything aligned with TDD and write the necessary tests."}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[write_file] wrote to /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_probe.py (38 lines)", "tool_call_id": "call_Glpt4DtqHdyXzQMv1jV4fzz1", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_ozLOpWJCh3SdCdpTnSWMR050", "call_id": "call_ozLOpWJCh3SdCdpTnSWMR050", "response_item_id": "fc_0dc9f371a6d55e3f016a1369e8b9148191b509bdfd57b3d048", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_audio_probe.py -q\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `pytest tests/test_audio_probe.py -q` -> exit 2, 1 lines output", "tool_call_id": "call_ozLOpWJCh3SdCdpTnSWMR050", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_oqlmXeECSCZCFERBxwndVacB", "call_id": "call_oqlmXeECSCZCFERBxwndVacB", "response_item_id": "fc_0dc9f371a6d55e3f016a1369ef9854819185eb345a5f095ab3", "type": "function", "function": {"name": "write_file", "arguments": "{\"content\": \"\\\"\\\"\\\"Small FFprobe helpers for audio/video review artifacts.\\\"\\\"\\\"\\n\\nfrom __future__ import annotations\\n\\nfrom collections.abc import Callable\\nimport subprocess\\n\\nRunner = Callable[..., subprocess.CompletedPr...[truncated]\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/probe.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"bytes_written\": 1000, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_oqlmXeECSCZCFERBxwndVacB", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_xUCcrVI1wOoQPfAJYXUIiuhs", "call_id": "call_xUCcrVI1wOoQPfAJYXUIiuhs", "response_item_id": "fc_0dc9f371a6d55e3f016a1369fa2d308191be63bae646894d18", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_audio_probe.py tests/test_voiceover.py tests/test_audio_caption_preview.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \".......... [100%]\\n10 passed in 0.07s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_xUCcrVI1wOoQPfAJYXUIiuhs", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_ws6cshMoqibdYUFzsGteBm5A", "call_id": "call_ws6cshMoqibdYUFzsGteBm5A", "response_item_id": "fc_0dc9f371a6d55e3f016a1369fe0e448191ada762e8f87860c3", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"python - <<'PY'\\nfrom pathlib import Path\\nfrom math import ceil\\nfrom autoshorts.demo.truetrace_preview_packages import build_top_truetrace_preview_packages\\nfrom autoshorts.audio.voiceover import build_...[truncated]\", \"timeout\": 300, \"workdir\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `python - <<'PY'\nfrom pathlib import Path\nfrom math import ceil\nfrom autoshort...` -> exit 0, 1 lines output", "tool_call_id": "call_ws6cshMoqibdYUFzsGteBm5A", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_9OHiAjC6UEQjuvUbYIfFVvNQ", "call_id": "call_9OHiAjC6UEQjuvUbYIfFVvNQ", "response_item_id": "fc_0dc9f371a6d55e3f016a136a19efcc8191a4300368a4424d79", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\": \"replace\", \"new_string\": \"- `autoshorts.audio.edge_tts_adapter` — explicit EdgeTTS MP3 generation boundary for final voiceover previews.\\n- `autoshorts.audio.final_preview` — ASS subtitle generation plus FFmpeg audio/caption MP...[truncated]\", \"old_string\": \"- `autoshorts.audio.edge_tts_adapter` — explicit EdgeTTS MP3 generation boundary for final voiceover previews.\\n- `autoshorts.audio.final_preview` — ASS subtitle generation plus FFmpeg audio/caption MP...[truncated]\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Updating documentation**\n\nI need to think about updating the README and pyproject files. This involves adding information about the modules and running full tests to ensure everything works smoothly. I'll also need to commit those changes afterward. Maybe I should consider including some media to enhance the documentation, too. Lastly, I might need to patch the documentation further if I find anything that needs clarification or improvement. Let's keep track of these tasks!", "reasoning_content": "**Updating documentation**\n\nI need to think about updating the README and pyproject files. This involves adding information about the modules and running full tests to ensure everything works smoothly. I'll also need to commit those changes afterward. Maybe I should consider including some media to enhance the documentation, too. Lastly, I might need to patch the documentation further if I find anything that needs clarification or improvement. Let's keep track of these tasks!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE2oZsm0jDvlvxwmRymDpYGJ8btj5YRP12aMlr7kfuH5ESSpgxxS20EeWjOaQOgCyNHRlfeXmPmQIysGeL6ooy-J9gR-FIkBsvJn4LUSVI217EnxzX_GEOuzAkBiy_NMPKHDrDNzHH_szQVyZ1dIb-ch0iAzp_h6k6AtZmjPaOGyjB2X8wh67yZ-9UfNoMUalbO5fzOZ3kKxg6RQgQnG-GNytZ6f2qfCQ9E87CVERuWBU1EE6Roit_BBK4NrzFjdWCvVTBpOUDo29YvJWj0cvGiaIKVq5uQ7CuedjbujXYPeSOQ1JL7VMrNIJTlyRqkCmfOGz8rVxYOhGttK3XWtDzjGFHMpXEuCA55kh_FE8zQHmd51Pi2NTitrz3VLexXX_IoT_6PtYCRo9J1iKqf6QfefCp6c5rtokktBcIvyqqwxiLTo8e3ir0Seg9etM1_09nKC4xT7n53H3WHNTgiXUX5rSDFQLtI3jpMKnGJ_foYepyquGeNC9kQ604_tLdWPAVIjIQzNp2XZZ2JX44mXXCXFfFFOSVGtjtVgDMtXUNC2Qv8jcdRqWxta3fP_7vzmS0VelKSkxQPkVhcwiJK0UU417Qv7r_y4bbFz_vmX94ZSb9uFuM6Q83DpP4tiNH4REeRwmnxDPfaMGeeUn_yuEAEIhWu6LnVFY8Sr7PPlj4UP_HOL8rJASToTjghepITpP5uaF1nIRpo-nkF0zZH05oOdPDz4EzSi9rz4HOKdKB7y0oJvEdbMATGKW88ke7PzZwYGgT2nwDvshHazVqSxGubN17WxQbJJNDmTfOmcoFlAc4sFqMxQxrGiT4GqggkLIa6tMx5S2mgoapOmBUfL6Sa5kPRBm9jbpNq8nKRj9hsdR-iRXn2x4tSdyKa9KUGkE1rggRuKniGMwc1I1BciS21TvUDprc1mthQlWJTWQZdBbqHuTFBUvu_0FSvOem-E3BqMYfMUJGLwP7sp5-p-IQc3Vh1qm598GXJOpgv1X-rEwMln6J9bMCLwXe5VE4gahLMoOBkv3oc6e3gTNGOZAJ8sxC73SapFlGXIjthi4EZug2HXby-AtWr-lvcBuliLmgDIf", "id": "rs_0dc9f371a6d55e3f016a136a175dc08191ac30481ca8317498", "summary": [{"type": "summary_text", "text": "**Updating documentation**\n\nI need to think about updating the README and pyproject files. This involves adding information about the modules and running full tests to ensure everything works smoothly. I'll also need to commit those changes afterward. Maybe I should consider including some media to enhance the documentation, too. Lastly, I might need to patch the documentation further if I find anything that needs clarification or improvement. Let's keep track of these tasks!"}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md (1,226 chars result)", "tool_call_id": "call_9OHiAjC6UEQjuvUbYIfFVvNQ", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_N3WpEBJr1KcY1cEJ47eB8ZFH", "call_id": "call_N3WpEBJr1KcY1cEJ47eB8ZFH", "response_item_id": "fc_0dc9f371a6d55e3f016a136a265704819188f5f744c9fb8cce", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\": \"replace\", \"new_string\": \"- `autoshorts.audio.final_preview.render_audio_caption_preview()` writes the ASS subtitle file and calls FFmpeg to mux EdgeTTS audio plus burn captions into a review MP4.\\n- `autoshorts.audio.voiceover...[truncated]\", \"old_string\": \"- `autoshorts.audio.final_preview.render_audio_caption_preview()` writes the ASS subtitle file and calls FFmpeg to mux EdgeTTS audio plus burn captions into a review MP4.\\n\\n## Caption pipeline\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/subtitle_tts_strategy.md\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/subtitle_tts_strategy.md (1,512 chars result)", "tool_call_id": "call_N3WpEBJr1KcY1cEJ47eB8ZFH", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_OOyKIGqUU49cpWdg1TtrsbBh", "call_id": "call_OOyKIGqUU49cpWdg1TtrsbBh", "response_item_id": "fc_0dc9f371a6d55e3f016a136a3002408191945cad17f37ff440", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/ -q\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `pytest tests/ -q` -> exit 0, 1 lines output", "tool_call_id": "call_OOyKIGqUU49cpWdg1TtrsbBh", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_U5DsnmLoMW8pYb0EiKGo7wR9", "call_id": "call_U5DsnmLoMW8pYb0EiKGo7wR9", "response_item_id": "fc_0dc9f371a6d55e3f016a136a55840c8191b191038a8b24aa07", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"git status --short && git add autoshorts/audio/voiceover.py autoshorts/audio/probe.py autoshorts/audio/final_preview.py tests/test_voiceover.py tests/test_audio_probe.py tests/test_audio_caption_preview.py README.md docs/subtitle_tts_strategy.md && git commit -m \\\"feat: align TrueTrace voiceover previews\\\" && git status --short && git log --oneline -5\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `git status --short && git add autoshorts/audio/voiceover.py autoshorts/audio/...` -> exit 0, 1 lines output", "tool_call_id": "call_U5DsnmLoMW8pYb0EiKGo7wR9", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "Erledigt, Sir.\n\nIch habe den nächsten Qualitäts-Slice gebaut: **kürzere finale Voiceover-Skripte + tatsächliche Audio-Dauer messen + Subtitles daran ausrichten + explizites Trim-to-Audio nur wenn gewünscht**.\n\n## Neu gebaut\n\nNeue Module:\n\n```text\nautoshorts/audio/voiceover.py\nautoshorts/audio/probe.py\n```\n\nErweitert:\n\n```text\nautoshorts/audio/final_preview.py\n```\n\nNeue Tests:\n\n```text\ntests/test_voiceover.py\ntests/test_audio_probe.py\n```\n\nCommit:\n\n```text\nb9b6423 feat: align TrueTrace voiceover previews\n```\n\n## Was verbessert wurde\n\n### 1. Final Voiceover Scripts\n\nNeue Funktion:\n\n```python\nbuild_truetrace_final_voiceover()\n```\n\nFür die Top-3 Konzepte gibt es jetzt kompakte finale English Voiceover-Texte.\n\nFür den ersten Clip:\n\n```text\nMost AI automations do not fail dramatically. They quietly rot.\nDay one looks clean, because the demo input behaves.\nBy day three, the real input changes.\nNow the workflow needs an exception path.\nNormal goes forward. Weird goes to review. Unclear stops.\nIf your automation has no exception path, it is not a system.\nIt is a lucky prompt.\n```\n\nEigenschaften:\n\n```text\nWords: 59\nTarget duration: 24s\nLanguage: en\nVoice: en-GB-RyanNeural\nNo generic filler\nNo “Follow for...” CTA-Geschwurbel\n```\n\n### 2. Audio Duration Probe\n\nNeue Funktion:\n\n```python\nprobe_media_duration_seconds()\n```\n\nSie liest per FFprobe die echte MP3-Dauer aus.\n\nWarum? Weil EdgeTTS natürlich nicht exakt unsere Wunschdauer spricht. Es ist TTS, kein Schweizer Uhrwerk mit britischem Akzent.\n\nBeim erzeugten Clip:\n\n```text\nEstimated target: 24s\nActual EdgeTTS audio: 29.112s\n```\n\n### 3. Subtitle Timing an echte Audio-Dauer angepasst\n\nVorher:\n\n```text\nSubtitle duration: estimated 24s\nAudio duration: 29.112s\n```\n\nJetzt:\n\n```text\nSubtitle duration: 30.0s\nAudio duration: 29.112s\n```\n\nDamit laufen Captions nicht mehr zu früh aus.\n\n### 4. `duration_mode`\n\nDer Audio+Caption Renderer unterstützt jetzt:\n\n```python\nduration_mode=\"preserve_video\"\n```\n\nDefault. Kein `-shortest`, kein heimliches Abschneiden.\n\nUnd explizit:\n\n```python\nduration_mode=\"trim_to_audio\"\n```\n\nNur dann wird `-shortest` verwendet.\n\nDas ist wichtig: FFmpeg darf schneiden, aber nur mit schriftlicher Genehmigung. Wie ein anständiger Bürokrat.\n\n## Neuer verbesserter Review Clip\n\nCandidate:\n\n```text\ntruetrace-ai-automation-quiet-rot-38s\n```\n\nOutput:\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-audio-caption-v3/truetrace-ai-automation-quiet-rot-38s/audio-caption-preview-v3.mp4\n\n## Verifiziert\n\nFFprobe:\n\n```text\nVideo: h264, 540x960\nVideo duration: 29.083s\nAudio: aac\nAudio duration: 29.112s\n```\n\nSHA256:\n\n```text\n6c71929420bd266b8569440feed9a8ca7dc392e3cead8cc55bca2dc33118c871\n```\n\n## Tests\n\nFull Suite:\n\n```text\n161 passed in 32.72s\n```\n\n## Aktueller Commit-Verlauf\n\n```text\nb9b6423 feat: align TrueTrace voiceover previews\n3f68001 feat: add EdgeTTS audio caption preview\n066201d feat: attach audio plans to TrueTrace previews\n30a8129 feat: add subtitle and tts planning\n6efc4dc feat: add TrueTrace top preview packages\n```\n\n## Nächster sinnvoller Schritt\n\nJetzt ist die Audio/Captions-Kette solide. Als Nächstes würde ich die visuelle Seite verbessern:\n\n```text\nstatic timing cards\n→ simple motion renderer\n→ kinetic background movement\n→ scene progress bars\n→ caption punch-in/pulse\n→ mechanism diagram animation\n```\n\nAlso weniger PowerPoint-mit-Puls, mehr echter Short.", "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Erledigt, Sir.\n\nIch habe den nächsten Qualitäts-Slice gebaut: **kürzere finale Voiceover-Skripte + tatsächliche Audio-Dauer messen + Subtitles daran ausrichten + explizites Trim-to-Audio nur wenn gewünscht**.\n\n## Neu gebaut\n\nNeue Module:\n\n```text\nautoshorts/audio/voiceover.py\nautoshorts/audio/probe.py\n```\n\nErweitert:\n\n```text\nautoshorts/audio/final_preview.py\n```\n\nNeue Tests:\n\n```text\ntests/test_voiceover.py\ntests/test_audio_probe.py\n```\n\nCommit:\n\n```text\nb9b6423 feat: align TrueTrace voiceover previews\n```\n\n## Was verbessert wurde\n\n### 1. Final Voiceover Scripts\n\nNeue Funktion:\n\n```python\nbuild_truetrace_final_voiceover()\n```\n\nFür die Top-3 Konzepte gibt es jetzt kompakte finale English Voiceover-Texte.\n\nFür den ersten Clip:\n\n```text\nMost AI automations do not fail dramatically. They quietly rot.\nDay one looks clean, because the demo input behaves.\nBy day three, the real input changes.\nNow the workflow needs an exception path.\nNormal goes forward. Weird goes to review. Unclear stops.\nIf your automation has no exception path, it is not a system.\nIt is a lucky prompt.\n```\n\nEigenschaften:\n\n```text\nWords: 59\nTarget duration: 24s\nLanguage: en\nVoice: en-GB-RyanNeural\nNo generic filler\nNo “Follow for...” CTA-Geschwurbel\n```\n\n### 2. Audio Duration Probe\n\nNeue Funktion:\n\n```python\nprobe_media_duration_seconds()\n```\n\nSie liest per FFprobe die echte MP3-Dauer aus.\n\nWarum? Weil EdgeTTS natürlich nicht exakt unsere Wunschdauer spricht. Es ist TTS, kein Schweizer Uhrwerk mit britischem Akzent.\n\nBeim erzeugten Clip:\n\n```text\nEstimated target: 24s\nActual EdgeTTS audio: 29.112s\n```\n\n### 3. Subtitle Timing an echte Audio-Dauer angepasst\n\nVorher:\n\n```text\nSubtitle duration: estimated 24s\nAudio duration: 29.112s\n```\n\nJetzt:\n\n```text\nSubtitle duration: 30.0s\nAudio duration: 29.112s\n```\n\nDamit laufen Captions nicht mehr zu früh aus.\n\n### 4. `duration_mode`\n\nDer Audio+Caption Renderer unterstützt jetzt:\n\n```python\nduration_mode=\"preserve_video\"\n```\n\nDefault. Kein `-shortest`, kein heimliches Abschneiden.\n\nUnd explizit:\n\n```python\nduration_mode=\"trim_to_audio\"\n```\n\nNur dann wird `-shortest` verwendet.\n\nDas ist wichtig: FFmpeg darf schneiden, aber nur mit schriftlicher Genehmigung. Wie ein anständiger Bürokrat.\n\n## Neuer verbesserter Review Clip\n\nCandidate:\n\n```text\ntruetrace-ai-automation-quiet-rot-38s\n```\n\nOutput:\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-audio-caption-v3/truetrace-ai-automation-quiet-rot-38s/audio-caption-preview-v3.mp4\n\n## Verifiziert\n\nFFprobe:\n\n```text\nVideo: h264, 540x960\nVideo duration: 29.083s\nAudio: aac\nAudio duration: 29.112s\n```\n\nSHA256:\n\n```text\n6c71929420bd266b8569440feed9a8ca7dc392e3cead8cc55bca2dc33118c871\n```\n\n## Tests\n\nFull Suite:\n\n```text\n161 passed in 32.72s\n```\n\n## Aktueller Commit-Verlauf\n\n```text\nb9b6423 feat: align TrueTrace voiceover previews\n3f68001 feat: add EdgeTTS audio caption preview\n066201d feat: attach audio plans to TrueTrace previews\n30a8129 feat: add subtitle and tts planning\n6efc4dc feat: add TrueTrace top preview packages\n```\n\n## Nächster sinnvoller Schritt\n\nJetzt ist die Audio/Captions-Kette solide. Als Nächstes würde ich die visuelle Seite verbessern:\n\n```text\nstatic timing cards\n→ simple motion renderer\n→ kinetic background movement\n→ scene progress bars\n→ caption punch-in/pulse\n→ mechanism diagram animation\n```\n\nAlso weniger PowerPoint-mit-Puls, mehr echter Short."}], "id": "msg_0dc9f371a6d55e3f016a136a5a9e9c8191a08676f9790a435c", "phase": "final_answer"}], "finish_reason": "stop", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "user", "content": "[M G] Das voiceover und die subtitles decken sich nicht mit dem text im oberen feld… wirkt das ganze nicht zu abgehoben? Erreichen wir so auch die leite welche noch nocht soo voel erfahrung mit KI haben?", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_wzmMPaS73tTi3kLfAftJsV3l", "call_id": "call_wzmMPaS73tTi3kLfAftJsV3l", "response_item_id": "fc_0dc9f371a6d55e3f016a136ce027c48191aa28395f6ac8a586", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"social-media-shorts-automation\"}"}}], "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE2zg9AADGlQ-darv_1sXBA-bdBknyDXf56uq4qy5PQekcPVWI5uIQB5xH3-Gta73zDF1SLeqt8HgANdASGJhYC3yQp0lot_GIOXb7keYMAL-Lqe94JlhSFoTHDt5KapiBgzbomob8gvqrmKGxP2wiWsRLc6y0PPgRRS8Lny5NXUYWS-244Y7YMJbhtqMcqr0dsRfC6uUIgCaVUmLFBSpSZVulssHS8FFkeuHAM31rb9K8P520aymwoNAT2O5X0HlPNpvZZy2_8HJFMyC5WGHGpd1xvJ7oBCZhYyWgYY5BQHvXy-R_lsinzhLbed3WOv-sZwaVVPu7ROQUkpNFd5QIe0N9vO2jzvnW-3LAHNMMunLuxbW8wGD2i-a2YV8aJeq-injzO8p6T_vDUw6psBkiOHzBkipglLOicnwSM-QVvi37YFXhoO3bQKGA4ygzX8uhN5DVTI-0cjXPrjIWfQNqOn44gRy8FOm5bmXY28uLaI0CKGK-pbiew-L70hUjpdhgq7VAvBuW7bYF8co2J2LOaR9IBeKHs8LjYZ3Z6YYSYw1QPqqC3UDwJ8bK03YVBSTNbZnDjCP4r0XHe40txJ25RTaMdmjqPArQkKWXnqZqDJOMUyodNvQqUV9j4SF4xk8L_WTJYmUFjMS82XRkgS_K_muv-BgLk2fdCvSJWXnLXlTFHUCw1WdQaM2h4_2rTynH3i1922Xa2oQ1nFdxSbvpRUK1EBKb7UuLn6p53YTd6TQ3lOs80LzSFQu9aQaCxXL8yF_Eip5JJdmG3L5QToUqEQYIIv90O8_XFevHgK3dVq3GVA-pQVfXyp6at0cFlROR-iW7lAqKLpvkbn7bdIrzFBMSi59LEmcUtLYZPM_8UYk21VFApcnPb_dq9GijroVyXMh3-qhZr5YBESi2xR0ytBQe5lQc1cMcnX3ytNr9T8eDLpUCun9tK7VjTSqqpWnmxZpG447UR6fy8UQHcksi6gO-VinFKo4oaRJKvv4VxTxnHClcYEZzu4-cxfEuo8X8Ney5r6TzrKBd_zVL4-tAGdBLFl3LT366uI8P_GN0EhA1oSNMyqW5lt2k53S-8KxG2p7syipppvzw0zzoozpTBj_6_491WF0HUMP9e-30nrzoiEu1IyX2ed6mu0FbwrGYeM3xHHxfAutMLb_QCJio6O0SGmGCTWiQmK2nBxCUF-EbHXpdE57ksdylrdJcbK1PQsvWHd3na9NOjyml9UGtouFtS8LtQrg_a2BSTVYznLhMchmIpKsMp5SeZnOuK_VyHGWG_Qc2dcdT2_pUxKD-2YURLPOFBGcNi0yMx5Jmmen2yU3kiCqqchoY1Bh3RN_T0r4y1IyoYujp6BYczH82boc_4c6ZvPk62w3hUL0dJlTMhshOECl0l6BCESOBCHvDpq9PA7PCZKVawTC1xJiwqlqrpLGqYDnd_go9SJPkgzG3QstjH0OWnGyBW1xxPs2vQhaZLkPpGp1OVbjFDlecGYW_OA_HYGtKmFVAriEBs5pLJErvSY47vK3ImLSLTJTnAa4FLbBSqAJmknpCOHVOTZyrzbb9XSIjbcXSyaFhlWkX3x24cVpBDNOzvc2nCueRIA3Pk5macWWWMS4hBqhM50i5rEI45CGbmLtfMB8inObFOgpv6DsiFC2xxL2cvUD7ZmQT7giIjcwCdCsGS6ItjyWsTpUFVwwM5-nnPcT0JB964-Tp8PDVPc8llTYEZTEYYRrx25rYY8fxQ5LjiKo_VIQ5pm3rHkKrcm-W4oMRr5qRvR6q9WU6ogXD6dDTtSHyBR5IFuMoYBZ-r_DcisR_v27-cCmhUXETspkgyGZNv4bMryYitaaewk-HzSK3fWGL7FXro9t8-H3ySmslBhBPgVLXck5_n-Y-F538OVdzOVRXyc=", "id": "rs_0dc9f371a6d55e3f016a136cdd13548191b054993b04f2de38", "summary": []}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[Duplicate tool output — same content as a more recent call]", "tool_call_id": "call_wzmMPaS73tTi3kLfAftJsV3l", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "Ja, Sir — **Ihre Kritik ist korrekt**.\n\n## 1. Voiceover/Subtitles passen nicht zum oberen Feld\n\nDas aktuelle Preview ist technisch korrekt, aber dramaturgisch unsauber:\n\n```text\nOberes Feld / Card:\nalte German approval/timing copy\n\nVoiceover/Subtitles:\nneuer English final voiceover text\n```\n\nDas erzeugt kognitive Reibung. Der Zuschauer sieht oben etwas anderes als er hört/liest. Für Review ist das schon störend; für echten Content wäre es tödlich genug, um einen kleinen Ausschuss einzuberufen.\n\n## Fix\n\nWir brauchen **eine einzige Source of Truth** pro Clip:\n\n```text\nFinalVoiceoverScript\n→ SubtitleTrack\n→ Top Hook Text\n→ Scene Card Text\n→ Social Caption\n```\n\nNicht:\n\n```text\nCandidate Concept Text\n+ später anderer Voiceover Text\n+ dritte Caption-Version\n```\n\nAlso: Der Text im oberen Feld muss aus demselben finalen Voiceover/Hook kommen wie Subtitles und Audio.\n\n---\n\n## 2. Ja: aktuell wirkt es zu abgehoben\n\nDer aktuelle Text ist gut für:\n\n```text\nAI builders\nAutomation nerds\nWorkflow-/Ops-Leute\nLeute, die schon wissen, was ein “exception path” ist\n```\n\nAber für breiteres Publikum ist es zu abstrakt.\n\nBegriffe wie:\n\n```text\nexception path\ninput boundary\noutput standard\naction boundary\ndecision structure\n```\n\nsind für Fachleute präzise — aber für Anfänger klingt es nach einem LinkedIn-Post mit Krawatte.\n\n## Problem\n\nWir sagen aktuell:\n\n```text\nIf your automation has no exception path, it is not a system.\n```\n\nDas ist stark, aber nicht sofort greifbar.\n\nFür Anfänger besser:\n\n```text\nIf your AI does not know what to do when something weird happens,\nit will break the first time real life shows up.\n```\n\nDas ist derselbe Gedanke, aber menschlicher.\n\n---\n\n## 3. Zielgruppe: Wir sollten breiter anfangen\n\nFür TrueTrace würde ich nicht mit „AI systems for experts“ starten, sondern mit:\n\n```text\nAI tools that work in real life\n```\n\nAlso Zielgruppe:\n\n```text\nPeople using ChatGPT, Notion AI, Zapier, Make, email automations,\nbut not yet thinking like system architects.\n```\n\nDie haben ein echtes Problem:\n\n```text\n“It worked once, then it became unreliable.”\n```\n\nDas versteht jeder.\n\n---\n\n## Neue Copy-Richtung\n\nStatt:\n\n```text\nMost AI automations do not fail dramatically. They quietly rot.\n```\n\nBesser für breite Zielgruppe:\n\n```text\nYour AI automation did not really break.\nReal life just gave it an input it was never prepared for.\n```\n\nOder noch einfacher:\n\n```text\nYour AI automation works in the demo.\nThen real life shows up.\n```\n\nDas ist deutlich stärker für Anfänger.\n\n## Neue Hook-Variante\n\n```text\nYour AI automation works perfectly…\nuntil the first weird email arrives.\n```\n\nDas ist konkret. Jeder versteht „weird email“.\n\n---\n\n## Neuer Anfänger-freundlicher Voiceover-Entwurf\n\nFür Clip 1 würde ich den Text so umbauen:\n\n```text\nYour AI automation works perfectly in the demo.\n\nThen one weird email arrives.\n\nThe name is missing.\nThe format is different.\nThe request is unclear.\n\nAnd suddenly the automation does the wrong thing confidently.\n\nThat is not an AI problem.\nThat is a workflow problem.\n\nBefore you automate anything, decide three things:\n\nWhat should go through?\nWhat should be reviewed?\nAnd what should stop?\n\nIf your AI does not know what to do with weird inputs,\nit will break the moment real life shows up.\n```\n\nWarum besser:\n\n- kein Jargon\n- konkretes Beispiel: weird email\n- klares Problem\n- klare 3er-Regel\n- Anfänger verstehen es sofort\n- Fortgeschrittene merken trotzdem: es geht um exception handling\n\n---\n\n## Visuals dazu\n\nStatt abstrakter Systemkarten:\n\n```text\nScene 1:\nPerfect demo inbox. Everything green.\n\nScene 2:\nA weird email appears:\n“hey can you handle this maybe???”\n\nScene 3:\nAI confidently routes it wrong.\n\nScene 4:\nSplit path:\nNormal → automate\nUnclear → review\nDangerous/weird → stop\n\nScene 5:\nRule:\nDon’t automate the happy path.\nPlan for the weird one.\n```\n\nDas ist viel zugänglicher.\n\n---\n\n## Empfehlung\n\nWir pivoten die Reihe von:\n\n```text\nSystems over prompts.\n```\n\nzu einer zugänglicheren Oberfläche:\n\n```text\nMake AI work in real life.\n```\n\nDer Brand-Kern bleibt:\n\n```text\nSystems over prompts.\n```\n\nAber der Zuschauer-Hook wird alltagstauglicher.\n\n## Konkrete nächste Änderung\n\nIch würde jetzt als nächsten Slice bauen:\n\n```text\nBeginner-friendly voiceover variants\n+ unified text source for top field / captions / subtitles\n+ regenerate Clip 1 as “weird email” version\n```\n\nAlso:\n\n```text\nFinalVoiceoverScript\n→ top card text\n→ subtitles\n→ audio\n→ review MP4\n```\n\nDann ist alles synchron und deutlich weniger abgehoben.", "reasoning": "**Deciding on variants**\n\nI need to establish my next point: I'll focus on two variants, \"Beginner/Mainstream\" and \"Builder/Advanced.\" I think I should recommend the beginner option. I might say that there's no re-render until the copy is fixed, and I could mention a concrete replacement script. But I have to be careful not to say \"will\" unless I confirm with the tool. Saying \"Nächster Schritt ist...\" might work, but I shouldn’t make any promises. I’ll keep it concise!", "reasoning_content": "**Deciding on variants**\n\nI need to establish my next point: I'll focus on two variants, \"Beginner/Mainstream\" and \"Builder/Advanced.\" I think I should recommend the beginner option. I might say that there's no re-render until the copy is fixed, and I could mention a concrete replacement script. But I have to be careful not to say \"will\" unless I confirm with the tool. Saying \"Nächster Schritt ist...\" might work, but I shouldn’t make any promises. I’ll keep it concise!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE2zpeeijOLNWDspAf3dzEmuvszGKH_QDRdVX7k3A6qe-9LbmDEjNbLdoVh0Jx8hGjL9IbZj6t-qGdjk7ySLqgBxbZ-mgKecCdvbW02ObnlOPdNgFeVjZi9wfZ99mqmMleKcuVy-2U3xaOETgbbzkR9O5R-Y1JHSI51HZXYr_eM3TfQ58vTudqkMY4uUsruLyZhd9MpKWIEjAK7iM4eGiLmpw8EOSX676VD3Tor9c8g9dL1ulD5KX5oeMT5vV1URpIF4P52V8oeW2fvtBT6nLAs-N2OMUubLEcteFPqMolgr416tqI92OI-BbALLmTYbfB_oxHBd_Ba1_owE6GKR7lpDmkFYpRxRAXR9B-lPXLq8flZMQ1HV-I6HoX-QE5X-c6XeR7LZY8Dtk3NlZMGGgxDp-ns7QbxMi0-DZ1XnpbE_ZuA19Kjahe0pV2f3yUHG22ywLRDqhz8o8qdbJb2luqgGFLyaJv37qrEPjzzzk8GnQ106Q8ueAxwEX0FIFWTzZsjdjUYQIQ4QYyFnUL-2gvY_FYcBvH64s4UxoLX91lPfltLQWaGWBxmJAIpiFkU6Kau8rjan0PmQYUCK-qZ4uY0X34fUtk9BpomocmfcjgpjCvBetADDWe7x0Tph1Cjb7TK3HT3SW1luq3AGyySB6OyjlOiQdQU5R5Nz0dcyYXZbbM94K-vDa7rNOdJQWUdJvCmoZC--pLphku7q-RJ6_d4KwjpgIngNF4TU7W6GfQGhPMK5DMZu6a-KdoUu00IjRyacDBvFdHF9wZ14xlS8bO9vQbKNQduYG81qt7k65ECb2WOWBs_LJdae8vhuX7NCfzyOp3qbefiZp16cYeGHqk9fwsJZckmO0Oy73lNJnYUkCFc4KAsh_Fq4nMB0Rc45lbSjwL1Q2ofXCzIGm1Fn6vEO0d05422ZyET-IwClp5IRSHcSc3J9e2qITYnKAFa3XpZu_o_pg4Q_bv9TeIWKJmq5WqEM7rod_oKiDVwakFdpKu0gR5TVl3_M6u90GFKT5G-UpLAR6BYjiSbVEYrCNLeMWLUb1zSd_3MXbP5cbr0t-TBtz2ew67uMxyib3pt6Ou7-IFgyXH-96xZA30Ls0X7HTz_jYnASFCX7IpzJqnQH4LppnMCErcPFFyCAGCxySzbn5KUXbKnV1tZTBQREqGDWuzNMTj9uA8iVRTj2ZaXWE1ZernjgDl2odeO-s_LvweKL_ihg7TG8ER_W2vi42-LMl9RpDp_z9GbAmX2oc8WUDP4pQNSyb4USXL3RVZRzrMJorhYLq0rxTMp4QhqvokX9qfWckV1wI1mb1I6qZ2Dpo1__ODlZDhbc9YTue5tf5JyDYOdkZfeLWXboSVL5RrDdxl92bQ8wOgRRBv01uFMsfZnSaK6cdR9RtgJT9uZtGeAsBc9XX9cZWT7WzAEJBbDNeMvas1Fx7mg81YxXfX_kntp0aBXRdzYyvG4w7XwM2ZihA1u9zIFU7Lp3fj8NGLEK11rvEZCt3rM_N9bAvYqH_DdymYFyTDIFRCxXRhSu85gz2LaXsoLLXubySivIcgWcYAnGRHYXiBbCbD93PJmHEJMzm712eHSMDv7iOi_hoTo9rAkL35Y6TXogUiPop_l_a9la44XQNctBy78TOQOTARu9dWEGOjM1kOs77f3HpSrr0eeJ7CiPXd2syDQaXT_Hsq-yYyxIxjXeWc2J4976qkuQKqAVs4qMYZFW72-ShAOyoxhHxWmNASfnXooYBe5suoUHT5aNtk-JvbsA86Q1ZaB4jKWQzznkYiKSYxkSR61yGKNIl9NqGgTVKpvGZZtUlEq8CP_4Lj3f7NIfHiL6dwBDt1HMdWSCv4Amf5C1xVeiN8UCA1g7rG1hL7hiw37vMolBW58_VvOlnbNezYi7Qz1pF0J3UoQJxndDlgP0raeTSoMJ-WpMZtTVWFsRBu4UamUYjZ_FOwh5ct2IRkQ3dSvuNgo8RWgArRQydfwvSUCjl5YjLRluEY-kfk3Z9vo1rmc11o5HvPr6Z22asXXOdOUEQy2XxYZfnlUcpr_c7P4qtI1BXLPaRbKBg7RDQtVbzFRB45DLKAEdWr9UF9yc4YYDrdlScg-ZLm4c-uV2aemUXx3DWvslOOA2GBtuY-oBizJakAS6_SGPohH9nr73pu5ZBGLJo46n7tObWhb6_o_v16kNg90MZ7mPFFYNiPLhrfCVfka4SdBdNJ82QUHbj2bs_xPQdql2rSSJ44BNDzvq4iTBe0U8g9OVuUHIll3-nxcXL_QMLqsxO0OeQ1Gu2o8yKgSQKxIhiWCHwEtF1pbbSMi7IjYP50R7HOJdnEcX-t0XDhAJFfjQUlpcuVR7t4AvjUStdU_L9absqFFtPEy5E_B4CIuVXqP2TxELlW6ATbS-0KJuN9nvypPC5SLm9d3aQ52ZVTZD9f_u7KVrTCcP8ki9rlcFdlGTzvvYdg2lDKnMCnekkziK6LVS2NXqUd4xxZCDGjlK6LTgVD-mw4G9c06JKCOcJo2vYVTrmjInINvc7FGk8dlR07LR47k7qLrRkSbVJhVBr4uMo1W7BiuZnDmsOF4NB4NpDHJJRiinn-rspZbGme9HJ9a0ON856yNlcdyIPNyyhmRvc4j0hpnJ5y3yNq80pFYXCyzk7JdUswg==", "id": "rs_0dc9f371a6d55e3f016a136ce35e0481918c87a113735e63a5", "summary": [{"type": "summary_text", "text": "**Deciding on variants**\n\nI need to establish my next point: I'll focus on two variants, \"Beginner/Mainstream\" and \"Builder/Advanced.\" I think I should recommend the beginner option. I might say that there's no re-render until the copy is fixed, and I could mention a concrete replacement script. But I have to be careful not to say \"will\" unless I confirm with the tool. Saying \"Nächster Schritt ist...\" might work, but I shouldn’t make any promises. I’ll keep it concise!"}]}], "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Ja, Sir — **Ihre Kritik ist korrekt**.\n\n## 1. Voiceover/Subtitles passen nicht zum oberen Feld\n\nDas aktuelle Preview ist technisch korrekt, aber dramaturgisch unsauber:\n\n```text\nOberes Feld / Card:\nalte German approval/timing copy\n\nVoiceover/Subtitles:\nneuer English final voiceover text\n```\n\nDas erzeugt kognitive Reibung. Der Zuschauer sieht oben etwas anderes als er hört/liest. Für Review ist das schon störend; für echten Content wäre es tödlich genug, um einen kleinen Ausschuss einzuberufen.\n\n## Fix\n\nWir brauchen **eine einzige Source of Truth** pro Clip:\n\n```text\nFinalVoiceoverScript\n→ SubtitleTrack\n→ Top Hook Text\n→ Scene Card Text\n→ Social Caption\n```\n\nNicht:\n\n```text\nCandidate Concept Text\n+ später anderer Voiceover Text\n+ dritte Caption-Version\n```\n\nAlso: Der Text im oberen Feld muss aus demselben finalen Voiceover/Hook kommen wie Subtitles und Audio.\n\n---\n\n## 2. Ja: aktuell wirkt es zu abgehoben\n\nDer aktuelle Text ist gut für:\n\n```text\nAI builders\nAutomation nerds\nWorkflow-/Ops-Leute\nLeute, die schon wissen, was ein “exception path” ist\n```\n\nAber für breiteres Publikum ist es zu abstrakt.\n\nBegriffe wie:\n\n```text\nexception path\ninput boundary\noutput standard\naction boundary\ndecision structure\n```\n\nsind für Fachleute präzise — aber für Anfänger klingt es nach einem LinkedIn-Post mit Krawatte.\n\n## Problem\n\nWir sagen aktuell:\n\n```text\nIf your automation has no exception path, it is not a system.\n```\n\nDas ist stark, aber nicht sofort greifbar.\n\nFür Anfänger besser:\n\n```text\nIf your AI does not know what to do when something weird happens,\nit will break the first time real life shows up.\n```\n\nDas ist derselbe Gedanke, aber menschlicher.\n\n---\n\n## 3. Zielgruppe: Wir sollten breiter anfangen\n\nFür TrueTrace würde ich nicht mit „AI systems for experts“ starten, sondern mit:\n\n```text\nAI tools that work in real life\n```\n\nAlso Zielgruppe:\n\n```text\nPeople using ChatGPT, Notion AI, Zapier, Make, email automations,\nbut not yet thinking like system architects.\n```\n\nDie haben ein echtes Problem:\n\n```text\n“It worked once, then it became unreliable.”\n```\n\nDas versteht jeder.\n\n---\n\n## Neue Copy-Richtung\n\nStatt:\n\n```text\nMost AI automations do not fail dramatically. They quietly rot.\n```\n\nBesser für breite Zielgruppe:\n\n```text\nYour AI automation did not really break.\nReal life just gave it an input it was never prepared for.\n```\n\nOder noch einfacher:\n\n```text\nYour AI automation works in the demo.\nThen real life shows up.\n```\n\nDas ist deutlich stärker für Anfänger.\n\n## Neue Hook-Variante\n\n```text\nYour AI automation works perfectly…\nuntil the first weird email arrives.\n```\n\nDas ist konkret. Jeder versteht „weird email“.\n\n---\n\n## Neuer Anfänger-freundlicher Voiceover-Entwurf\n\nFür Clip 1 würde ich den Text so umbauen:\n\n```text\nYour AI automation works perfectly in the demo.\n\nThen one weird email arrives.\n\nThe name is missing.\nThe format is different.\nThe request is unclear.\n\nAnd suddenly the automation does the wrong thing confidently.\n\nThat is not an AI problem.\nThat is a workflow problem.\n\nBefore you automate anything, decide three things:\n\nWhat should go through?\nWhat should be reviewed?\nAnd what should stop?\n\nIf your AI does not know what to do with weird inputs,\nit will break the moment real life shows up.\n```\n\nWarum besser:\n\n- kein Jargon\n- konkretes Beispiel: weird email\n- klares Problem\n- klare 3er-Regel\n- Anfänger verstehen es sofort\n- Fortgeschrittene merken trotzdem: es geht um exception handling\n\n---\n\n## Visuals dazu\n\nStatt abstrakter Systemkarten:\n\n```text\nScene 1:\nPerfect demo inbox. Everything green.\n\nScene 2:\nA weird email appears:\n“hey can you handle this maybe???”\n\nScene 3:\nAI confidently routes it wrong.\n\nScene 4:\nSplit path:\nNormal → automate\nUnclear → review\nDangerous/weird → stop\n\nScene 5:\nRule:\nDon’t automate the happy path.\nPlan for the weird one.\n```\n\nDas ist viel zugänglicher.\n\n---\n\n## Empfehlung\n\nWir pivoten die Reihe von:\n\n```text\nSystems over prompts.\n```\n\nzu einer zugänglicheren Oberfläche:\n\n```text\nMake AI work in real life.\n```\n\nDer Brand-Kern bleibt:\n\n```text\nSystems over prompts.\n```\n\nAber der Zuschauer-Hook wird alltagstauglicher.\n\n## Konkrete nächste Änderung\n\nIch würde jetzt als nächsten Slice bauen:\n\n```text\nBeginner-friendly voiceover variants\n+ unified text source for top field / captions / subtitles\n+ regenerate Clip 1 as “weird email” version\n```\n\nAlso:\n\n```text\nFinalVoiceoverScript\n→ top card text\n→ subtitles\n→ audio\n→ review MP4\n```\n\nDann ist alles synchron und deutlich weniger abgehoben."}], "id": "msg_0dc9f371a6d55e3f016a136ce9a67481919e1e7023e61bd843", "phase": "final_answer"}], "finish_reason": "stop", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "user", "content": "[M G] Ja das ist besser. Mach jetzt weiter.", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_DWFLwbNL27ptEKvePzmCt7tG", "call_id": "call_DWFLwbNL27ptEKvePzmCt7tG", "response_item_id": "fc_0dc9f371a6d55e3f016a136fa0ade881919186260ba108e820", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"test-driven-development\"}"}}, {"id": "call_EmYRDKTVZv93jCfk6UKI6psx", "call_id": "call_EmYRDKTVZv93jCfk6UKI6psx", "response_item_id": "fc_0dc9f371a6d55e3f016a136fa0ae048191b7d2fb0dee6d1473", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"social-media-shorts-automation\"}"}}, {"id": "call_hKXDaCnF8TLmNMRhl8Nh0p33", "call_id": "call_hKXDaCnF8TLmNMRhl8Nh0p33", "response_item_id": "fc_0dc9f371a6d55e3f016a136fa0ae4481919ce9d1a667b038d4", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/voiceover.py\",\"limit\":220}"}}], "finish_reason": "tool_calls", "reasoning": "**Taking action for TDD implementation**\n\nI need to take action and load the Test-Driven Development (TDD) process, making sure it's systematic and relevant. 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FinalVoiceoverScript,\\n build_accessible_script_draft_from_voiceover,\\n build_truetrace_final_voiceover,\\n validate_final_voiceover_script,\\n)\\n\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_voiceover.py (873 chars result)", "tool_call_id": "call_ZXJbHALQ80HOMqspLSybcMxV", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_ksw8RsLpbcO8AVFHQCHW7AXo", "call_id": "call_ksw8RsLpbcO8AVFHQCHW7AXo", "response_item_id": "fc_0dc9f371a6d55e3f016a136fc1b1c88191ab03044ece4e0cf6", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\": \"replace\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_voiceover.py\", \"old_string\": \"def test_build_truetrace_final_voiceover_for_quiet_rot_is_concise_and_retention_led():\\n script = build_truetrace_final_voiceover(\\\"truetrace-ai-automation-quiet-rot-38s\\\")\\n\\n assert script.candidat...[truncated]\", \"new_string\": \"def test_build_truetrace_final_voiceover_for_quiet_rot_is_beginner_friendly_and_concrete():\\n script = build_truetrace_final_voiceover(\\\"truetrace-ai-automation-quiet-rot-38s\\\")\\n\\n assert script.can...[truncated]\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_voiceover.py (1,631 chars result)", "tool_call_id": "call_ksw8RsLpbcO8AVFHQCHW7AXo", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_EKu5WYWeDBAWqabJxSMOUj9O", "call_id": "call_EKu5WYWeDBAWqabJxSMOUj9O", "response_item_id": "fc_0dc9f371a6d55e3f016a136fce32108191819b72950d307e6d", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" assert [script.target_duration_seconds for script in scripts] == [29, 23, 22]\\n assert all(45 <= len(script.text.split()) <= 85 for script in scripts)\",\"old_string\":\" assert [script.target_duration_seconds for script in scripts] == [24, 23, 22]\\n assert all(45 <= len(script.text.split()) <= 70 for script in scripts)\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_voiceover.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_voiceover.py (859 chars result)", "tool_call_id": "call_EKu5WYWeDBAWqabJxSMOUj9O", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_4wEDqgj3uXrefvAoigGFU3M7", "call_id": "call_4wEDqgj3uXrefvAoigGFU3M7", "response_item_id": "fc_0dc9f371a6d55e3f016a136fd4a0a0819189153f96453fa441", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\": \"replace\", \"new_string\": \"def test_build_accessible_script_draft_from_voiceover_uses_one_text_source_for_visuals():\\n voiceover = build_truetrace_final_voiceover(\\\"truetrace-ai-automation-quiet-rot-38s\\\")\\n\\n draft = build_ac...[truncated]\", \"old_string\": \"def test_validate_final_voiceover_script_rejects_bad_language_duration_and_filler():\\n\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_voiceover.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_voiceover.py (1,691 chars result)", "tool_call_id": "call_4wEDqgj3uXrefvAoigGFU3M7", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_sddMuNU6w82YS5D9crr2ATUp", "call_id": "call_sddMuNU6w82YS5D9crr2ATUp", "response_item_id": "fc_0dc9f371a6d55e3f016a136fdf98248191845ce6038f697a24", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_voiceover.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `pytest tests/test_voiceover.py -q` -> exit 2, 1 lines output", "tool_call_id": "call_sddMuNU6w82YS5D9crr2ATUp", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_o70sNlFYYRZ9dxuRXykDJWWf", "call_id": "call_o70sNlFYYRZ9dxuRXykDJWWf", "response_item_id": "fc_0dc9f371a6d55e3f016a136fea478881918c2059a89996ddff", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"from dataclasses import dataclass\\n\\nfrom autoshorts.content.script_draft import ScriptDraft, validate_script_draft\\nfrom autoshorts.ideas.candidate import ValidationResult\",\"old_string\":\"from dataclasses import dataclass\\n\\nfrom autoshorts.ideas.candidate import ValidationResult\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/voiceover.py\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Implementing script updates**\n\nI need to import ScriptDraft and consider the validations. If the max is 80, I'm wondering how it will react at 85. I think my count might be 76, which seems okay. I'll update _SCRIPTS accordingly and think about a simple mapping for the draft. It feels a bit scattered, but I’m aiming to make sure everything works as it should! Plus, clarity is key, right?", "reasoning_content": "**Implementing script updates**\n\nI need to import ScriptDraft and consider the validations. If the max is 80, I'm wondering how it will react at 85. I think my count might be 76, which seems okay. I'll update _SCRIPTS accordingly and think about a simple mapping for the draft. It feels a bit scattered, but I’m aiming to make sure everything works as it should! 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One human checkpoint.\\\",\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/shot_plan.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/shot_plan.py (908 chars result)", "tool_call_id": "call_2FXaZazDS7W6SPwT73QrEdwa", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_Mv4e0xqGHUaa0SSWtZbjzqG3", "call_id": "call_Mv4e0xqGHUaa0SSWtZbjzqG3", "response_item_id": "fc_0dc9f371a6d55e3f016a137050ad0c8191b172dc889fe8b96f", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_voiceover.py tests/test_shot_plan.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"......... [100%]\\n9 passed in 0.06s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_Mv4e0xqGHUaa0SSWtZbjzqG3", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_n6u2XezeiNoTp25QKH2tSOZa", "call_id": "call_n6u2XezeiNoTp25QKH2tSOZa", "response_item_id": "fc_0dc9f371a6d55e3f016a13705784408191bcae2a467e15159f", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"python - <<'PY'\\nfrom pathlib import Path\\nfrom math import ceil\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover, build_accessible_script_draft_from_voiceover\\nfrom autoshorts.audi...[truncated]\", \"timeout\": 300, \"workdir\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Generating new preview**\n\nI need to create a new preview using the latest draft and English frames. Maybe I need some tests, but I think we have enough for now. 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Maybe I need some tests, but I think we have enough for now. I just need to make sure to use the tools correctly to generate the output. I should also check if localizing the frame copy will return the caption text correctly. Good! I’ll utilize the create_shot_plan and build the manifest. Time to render everything and run the script!"}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `python - <<'PY'\nfrom pathlib import Path\nfrom math import ceil\nfrom autoshort...` -> exit 0, 1 lines output", "tool_call_id": "call_n6u2XezeiNoTp25QKH2tSOZa", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_oItuywHZXQtCmTpEHwScFESM", "call_id": "call_oItuywHZXQtCmTpEHwScFESM", "response_item_id": "fc_0dc9f371a6d55e3f016a137074ee8081918bf9cbca46c6f70c", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" assert script.target_duration_seconds == 37\",\"old_string\":\" assert script.target_duration_seconds == 29\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_voiceover.py\"}"}}], "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": 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"2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_voiceover.py (779 chars result)", "tool_call_id": "call_jOdXiDkvWxuDZBQnxazI92PI", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_Dy9JkNnqA6AdGgRds4yShSZH", "call_id": "call_Dy9JkNnqA6AdGgRds4yShSZH", "response_item_id": "fc_0dc9f371a6d55e3f016a13707ee7808191890fe0beff0b761d", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" 37,\",\"old_string\":\" 29,\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/voiceover.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/voiceover.py (839 chars result)", "tool_call_id": "call_Dy9JkNnqA6AdGgRds4yShSZH", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_aod6feKJDEPJJXKbmecuwhJa", "call_id": "call_aod6feKJDEPJJXKbmecuwhJa", "response_item_id": "fc_0dc9f371a6d55e3f016a13708454f88191a99e0b8db2fb0feb", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_voiceover.py tests/test_shot_plan.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"......... [100%]\\n9 passed in 0.08s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_aod6feKJDEPJJXKbmecuwhJa", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_vx2188Z9rlz4pJLfBHSSuBQT", "call_id": "call_vx2188Z9rlz4pJLfBHSSuBQT", "response_item_id": "fc_0dc9f371a6d55e3f016a137089324c81919137b45476c93339", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"python - <<'PY'\\nfrom pathlib import Path\\nfrom math import ceil\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover, build_accessible_script_draft_from_voiceover\\nfrom autoshorts.audi...[truncated]\", \"timeout\": 300, \"workdir\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `python - <<'PY'\nfrom pathlib import Path\nfrom math import ceil\nfrom autoshort...` -> exit 0, 1 lines output", "tool_call_id": "call_vx2188Z9rlz4pJLfBHSSuBQT", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_gp0AlWEVlrpnhvzj6aDArDZ2", "call_id": "call_gp0AlWEVlrpnhvzj6aDArDZ2", "response_item_id": "fc_0dc9f371a6d55e3f016a1370a4d0d4819197db75f37b814fb1", "type": "function", "function": {"name": "vision_analyze", "arguments": "{\"image_url\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-weird-email-v2/truetrace-ai-automation-quiet-rot-38s/frames/frame-01-first_frame_hook.png\",\"question\":\"Check whether the top card text is readable and matches the beginner-friendly weird-email hook. 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concepts.\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md (1,430 chars result)", "tool_call_id": "call_cd1y5bQccBRgKdQ7OvNVcb95", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_GANs3VbXkoWFO3SSlkgTC0av", "call_id": "call_GANs3VbXkoWFO3SSlkgTC0av", "response_item_id": "fc_0dc9f371a6d55e3f016a1370d913f481919ced9ea86883a227", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\": \"replace\", \"new_string\": \"Subtitle/TTS strategy is documented in `docs/subtitle_tts_strategy.md`: use deterministic Hormozi-inspired renderer-owned captions; start TTS with EdgeTTS English baseline; A/B test NVIDIA Magpie late...[truncated]\", \"old_string\": \"Subtitle/TTS strategy is documented in 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"timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[read_file] read /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/subtitle_tts_strategy.md from line 1 (5,016 chars)", "tool_call_id": "call_PrNdBrw08eOugzcNPvaddWLj", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_KEIPHVUAvaOO42BtZlkCt6mb", "call_id": "call_KEIPHVUAvaOO42BtZlkCt6mb", "response_item_id": "fc_0dc9f371a6d55e3f016a1370e92aa88191b8058b368145cf89", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\": \"replace\", \"new_string\": \"- `autoshorts.audio.voiceover.build_truetrace_final_voiceover()` provides beginner-friendly English final voiceover scripts for the top TrueTrace concepts. The first pilot uses the concrete `weird ema...[truncated]\", \"old_string\": \"- `autoshorts.audio.voiceover.build_truetrace_final_voiceover()` provides concise English final voiceover scripts for the top TrueTrace concepts.\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/subtitle_tts_strategy.md\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/subtitle_tts_strategy.md (2,177 chars result)", "tool_call_id": "call_KEIPHVUAvaOO42BtZlkCt6mb", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_QfYd8QQ9GApVRqAN9UCShJiV", "call_id": "call_QfYd8QQ9GApVRqAN9UCShJiV", "response_item_id": "fc_0dc9f371a6d55e3f016a1370f1485481918d896bc103dfb931", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/ -q\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `pytest tests/ -q` -> exit 0, 1 lines output", "tool_call_id": "call_QfYd8QQ9GApVRqAN9UCShJiV", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_7z8sXbymi1r8dPwKh6lo8Ze2", "call_id": "call_7z8sXbymi1r8dPwKh6lo8Ze2", "response_item_id": "fc_0dc9f371a6d55e3f016a137118e9788191b7aa13c2f62c08d6", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"git status --short && git add autoshorts/audio/voiceover.py autoshorts/rendering/shot_plan.py autoshorts/rendering/local_frame_writer.py tests/test_voiceover.py tests/test_shot_plan.py README.md docs/subtitle_tts_strategy.md && git commit -m \\\"feat: make TrueTrace pilot beginner friendly\\\" && git status --short && git log --oneline -5\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `git status --short && git add autoshorts/audio/voiceover.py autoshorts/render...` -> exit 0, 1 lines output", "tool_call_id": "call_7z8sXbymi1r8dPwKh6lo8Ze2", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "Erledigt, Sir.\n\nSie hatten völlig recht — ich habe jetzt nicht nur kosmetisch geändert, sondern die Pipeline so angepasst, dass **Voiceover, Subtitles und oberes Kartenfeld aus derselben Quelle kommen**.\n\n## Neuer Commit\n\n```text\n7375311 feat: make TrueTrace pilot beginner friendly\n```\n\n## Was geändert wurde\n\n### 1. Voiceover beginner-friendly gemacht\n\nAlter Stil:\n\n```text\nMost AI automations do not fail dramatically.\nThey quietly rot.\n...\nexception path\n```\n\nNeuer Stil:\n\n```text\nYour AI automation works perfectly in the demo.\nThen one weird email arrives.\nThe name is missing.\nThe format is different.\nThe request is unclear.\n...\nIf your AI does not know what to do with weird inputs,\nit will break the moment real life shows up.\n```\n\nDas ist deutlich zugänglicher:\n\n- konkretes Beispiel: `weird email`\n- kein Jargon wie `exception path`\n- kein `input boundary`\n- kein `output standard`\n- kein Architekten-Englisch im Smoking\n- Problem ist auch für KI-Anfänger sofort verständlich\n\n## 2. Eine Source of Truth\n\nNeu:\n\n```python\nbuild_accessible_script_draft_from_voiceover()\n```\n\nDas macht:\n\n```text\nFinalVoiceoverScript\n→ ScriptDraft\n→ ShotPlan\n→ RenderManifest\n→ Top Card Text\n→ Scene Captions\n→ Subtitles\n→ Voiceover\n```\n\nDamit vermeiden wir genau den Fehler von vorher:\n\n```text\noben alter Karten-Text\nunten neue Subtitles\nAudio nochmal anders\n```\n\nDieser Wildwuchs ist jetzt abgeschnitten. Mit Anstand.\n\n## 3. ShotPlan nutzt jetzt echte Script-Beats\n\nVorher waren Szenencaptions teilweise generisch:\n\n```text\nAI suggests. Human approves.\nThe rule: AI drafts, you decide.\n10-minute review. One human checkpoint.\n```\n\nJetzt kommen sie aus den echten Retention Beats des finalen Scripts:\n\n```text\nThe name is missing. The format is different. The request is unclear.\nSuddenly the automation does the wrong thing confidently.\nThat is not an AI problem. That is a workflow problem.\n```\n\n## 4. Preview-Karten auf Englisch konsistenter\n\nFür die neuen final-nahen Previews werden die Karten nicht mehr halb Deutsch/halb Englisch beschriftet.\n\nGeändert:\n\n```text\nZeit → Time\nBewegung → Motion\n```\n\nWenn `approval_language=\"en\"` verwendet wird.\n\n## Neuer generierter Clip\n\nCandidate:\n\n```text\ntruetrace-ai-automation-quiet-rot-38s\n```\n\nNeue Version:\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-weird-email-v2/truetrace-ai-automation-quiet-rot-38s/weird-email-audio-caption-preview.mp4\n\n## Verifiziert\n\n```text\nWords: 85\nTarget duration: 37s\nActual EdgeTTS audio: 36.864s\nSubtitle duration: 37.0s\nVideo duration: 36.833s\nAudio duration: 36.864s\n```\n\nSHA256:\n\n```text\n5b903b148b6123c64dd30754b9f6bfb294154f0973ab2dfa90619ee22f6f1044\n```\n\nIch habe zusätzlich den ersten Frame visuell geprüft: Top-Text ist lesbar und lautet jetzt passend:\n\n```text\nYour AI automation works perfectly in the demo.\nThen one weird email arrives.\n```\n\n## Tests\n\nFull Suite:\n\n```text\n162 passed in 32.43s\n```\n\n## Einschätzung zur Zielgruppe\n\nJa: Diese Richtung ist viel besser für Leute mit wenig KI-Erfahrung.\n\nDer Kanal sollte nicht starten mit:\n\n```text\n“Here is a system architecture principle.”\n```\n\nSondern mit:\n\n```text\n“Here is why your ChatGPT/Zapier/Email automation breaks when real life gets messy.”\n```\n\nDas holt Anfänger ab, ohne den eigentlichen System-Gedanken zu verlieren.\n\n## Nächster sinnvoller Schritt\n\nJetzt sollten wir visuell noch weg von Karten und hin zu einer konkreteren Szene:\n\n```text\nDemo inbox\n→ weird email appears\n→ AI routes it wrong\n→ simple 3-way split:\n Go through\n Review\n Stop\n```\n\nDas wäre dann nicht nur verständlicher Text, sondern auch ein verständlicher Mechanismus im Bild.", "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Erledigt, Sir.\n\nSie hatten völlig recht — ich habe jetzt nicht nur kosmetisch geändert, sondern die Pipeline so angepasst, dass **Voiceover, Subtitles und oberes Kartenfeld aus derselben Quelle kommen**.\n\n## Neuer Commit\n\n```text\n7375311 feat: make TrueTrace pilot beginner friendly\n```\n\n## Was geändert wurde\n\n### 1. Voiceover beginner-friendly gemacht\n\nAlter Stil:\n\n```text\nMost AI automations do not fail dramatically.\nThey quietly rot.\n...\nexception path\n```\n\nNeuer Stil:\n\n```text\nYour AI automation works perfectly in the demo.\nThen one weird email arrives.\nThe name is missing.\nThe format is different.\nThe request is unclear.\n...\nIf your AI does not know what to do with weird inputs,\nit will break the moment real life shows up.\n```\n\nDas ist deutlich zugänglicher:\n\n- konkretes Beispiel: `weird email`\n- kein Jargon wie `exception path`\n- kein `input boundary`\n- kein `output standard`\n- kein Architekten-Englisch im Smoking\n- Problem ist auch für KI-Anfänger sofort verständlich\n\n## 2. Eine Source of Truth\n\nNeu:\n\n```python\nbuild_accessible_script_draft_from_voiceover()\n```\n\nDas macht:\n\n```text\nFinalVoiceoverScript\n→ ScriptDraft\n→ ShotPlan\n→ RenderManifest\n→ Top Card Text\n→ Scene Captions\n→ Subtitles\n→ Voiceover\n```\n\nDamit vermeiden wir genau den Fehler von vorher:\n\n```text\noben alter Karten-Text\nunten neue Subtitles\nAudio nochmal anders\n```\n\nDieser Wildwuchs ist jetzt abgeschnitten. Mit Anstand.\n\n## 3. ShotPlan nutzt jetzt echte Script-Beats\n\nVorher waren Szenencaptions teilweise generisch:\n\n```text\nAI suggests. Human approves.\nThe rule: AI drafts, you decide.\n10-minute review. One human checkpoint.\n```\n\nJetzt kommen sie aus den echten Retention Beats des finalen Scripts:\n\n```text\nThe name is missing. The format is different. The request is unclear.\nSuddenly the automation does the wrong thing confidently.\nThat is not an AI problem. That is a workflow problem.\n```\n\n## 4. Preview-Karten auf Englisch konsistenter\n\nFür die neuen final-nahen Previews werden die Karten nicht mehr halb Deutsch/halb Englisch beschriftet.\n\nGeändert:\n\n```text\nZeit → Time\nBewegung → Motion\n```\n\nWenn `approval_language=\"en\"` verwendet wird.\n\n## Neuer generierter Clip\n\nCandidate:\n\n```text\ntruetrace-ai-automation-quiet-rot-38s\n```\n\nNeue Version:\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-weird-email-v2/truetrace-ai-automation-quiet-rot-38s/weird-email-audio-caption-preview.mp4\n\n## Verifiziert\n\n```text\nWords: 85\nTarget duration: 37s\nActual EdgeTTS audio: 36.864s\nSubtitle duration: 37.0s\nVideo duration: 36.833s\nAudio duration: 36.864s\n```\n\nSHA256:\n\n```text\n5b903b148b6123c64dd30754b9f6bfb294154f0973ab2dfa90619ee22f6f1044\n```\n\nIch habe zusätzlich den ersten Frame visuell geprüft: Top-Text ist lesbar und lautet jetzt passend:\n\n```text\nYour AI automation works perfectly in the demo.\nThen one weird email arrives.\n```\n\n## Tests\n\nFull Suite:\n\n```text\n162 passed in 32.43s\n```\n\n## Einschätzung zur Zielgruppe\n\nJa: Diese Richtung ist viel besser für Leute mit wenig KI-Erfahrung.\n\nDer Kanal sollte nicht starten mit:\n\n```text\n“Here is a system architecture principle.”\n```\n\nSondern mit:\n\n```text\n“Here is why your ChatGPT/Zapier/Email automation breaks when real life gets messy.”\n```\n\nDas holt Anfänger ab, ohne den eigentlichen System-Gedanken zu verlieren.\n\n## Nächster sinnvoller Schritt\n\nJetzt sollten wir visuell noch weg von Karten und hin zu einer konkreteren Szene:\n\n```text\nDemo inbox\n→ weird email appears\n→ AI routes it wrong\n→ simple 3-way split:\n Go through\n Review\n Stop\n```\n\nDas wäre dann nicht nur verständlicher Text, sondern auch ein verständlicher Mechanismus im Bild."}], "id": "msg_0dc9f371a6d55e3f016a13711df5fc8191a1981c7eb3035eb9", "phase": "final_answer"}], "finish_reason": "stop", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "user", "content": "[M G] Ok. Wie gehst du nun vor für die generierung des richtigen videos?", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_0fnG1uinubYhS3JLb5u4PNvf", "call_id": "call_0fnG1uinubYhS3JLb5u4PNvf", "response_item_id": "fc_0dc9f371a6d55e3f016a13721070188191ab4e199265ddbdf7", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"social-media-shorts-automation\"}"}}, {"id": "call_x3Wkxym9uxmp0kKc1Q6aB5a5", "call_id": "call_x3Wkxym9uxmp0kKc1Q6aB5a5", "response_item_id": "fc_0dc9f371a6d55e3f016a137210709c8191bca90a36c68dd45c", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"comfyui\"}"}}, {"id": "call_ZEIqVwU23Gj2bzUzE435QcvX", "call_id": "call_ZEIqVwU23Gj2bzUzE435QcvX", "response_item_id": "fc_0dc9f371a6d55e3f016a13721070ac8191af7dbd1059a52eb4", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"writing-plans\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Creating a plan for video generation**\n\nI need to come up with an answer plan since the user is asking how to proceed. It seems that social media skills are relevant here, but I'm not sure if a tool is required for this part. Maybe I should load up writing plans to help generate a proper video based on their specific skill set. Also, could comfyui be relevant for effective video generation? I’ll need to consider loading that if it fits!", "reasoning_content": "**Creating a plan for video generation**\n\nI need to come up with an answer plan since the user is asking how to proceed. It seems that social media skills are relevant here, but I'm not sure if a tool is required for this part. Maybe I should load up writing plans to help generate a proper video based on their specific skill set. Also, could comfyui be relevant for effective video generation? I’ll need to consider loading that if it fits!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3IQn5AG_OMZY00ZVo7mjl1UGZqS0uErYPUefCbvsd5gLOP1ot6QMbYzjKf3nqfopnmvi7hzActMoCZwAdEYPJ63ujGbONk8dsxyhIqkwdiGMhRRElm-a6Ju96wVxIuz8HNve4BktEci3kugKT2r4MrpSe9n7TWb3yEUjIIezsfdm1BftM7Gtl6hvX49MDaIwVJxE8fhy7AzDEYN6A81b2gzrnnASWSZj0RPzTeARBEMAAkmabaytD8ByorpoLYYSUDhnfWwdO3wARMm8-9im8ul5eQTmw3d7dYuTJII8DSQ2-9iWV5kP1Kqf9dOuxFE0CozI1N4XCM2_5_YK0hYSEhIDWiYBA1n3z-_KJMk7I2vziSzsQrhUeWex2DLWSrT5MNJTuS1Pyorg1KUTuTV2hRiGKo31OaZi3V7k8veWn2S_dySFLpdJpUywpuxA0ONhuNa6_Zz8asKoiatiywwmL5rUPE4KWVtrpYoHRyG4XCnpFJjveoPWb2xsRBX4ec1Gk4lVXeWs49rJ8O7juvISmohFJAeQO4JwB3Q92_hpQdWEZEouhoSZD_f1joAjeehs7rUXo3f-2qnRFc6Q02UvVsiioUnfmnSraCpdokm0xOetR1mMJrye5bMV9I9OfAIE-NVx_tawFuRcsWVkvVWc8Qn0ES2ATabUkUo_pt3GACLnldxJ9tVR080Gzzlzjl_km9Nv_RWxb-APGgqvmrW1BqTRhkRMbjHHVPm_GJK0Ogd7Jl0_rkLm97Y_4ATZS9A0LPhdRcns2wAcmiuWKIJAxVBDeKgD55drB2fvrR-0HumB5z8r2snMUh6SFqVgpwrFz-MKPmNVkboXyL8coNzlTJXpILlWfYKJbmTVYKjbXid5d07DzXmLOKmrvJDRB39OnY_dnnHDsj1xMVocSQxERPQQeWto2nZRvZbGwsRxD_7zNdfwialskIlGitiL-zVl57Zfnse7L5WDS1KEfUTjA5KOKgo95baCKNDa2H91jp3T6YDk3NOnVuIDRIM6h1GEofAZinuL-91PxJL6cYjSbWeOuHrGrNfvtDjHfB1Bj-LbEBTFv4opTEqt8wIsDICPDn77ETr9y9volU0fFDfDSphvDQ7nCbBt70CPxS7TUaywoXazP3dh28NCC_k_HTe84kKSEhSZI7L0_ychqrBmpG32eu3rQ6Z7jB3bOoGGbVK0a8ir2JnjY0RNs5xP53vz61gys9Kr-EOVOI3ZSSPpClCNak-riL_1ScZhWs7RNaeIVXejfY1mifKEb6odLP5AS5tQNSw-e7ZRVUdisEmUO3eSyVx8XGbqR6KGorghPX6oc85oHr-qIPsK-LOAGLACYyxeJCPCqrXJGZliV6OQRr_fWSXKVyb5otMWPXMlBDqidbAYoPav9WtDtltsai2W-3iC9R4FgA4sm1Nb7KdcHWSBFJJnCo9O6EIKwVuyY_knrE=", "id": "rs_0dc9f371a6d55e3f016a13720bc8d0819196833e9c10a11e78", "summary": [{"type": "summary_text", "text": "**Creating a plan for video generation**\n\nI need to come up with an answer plan since the user is asking how to proceed. It seems that social media skills are relevant here, but I'm not sure if a tool is required for this part. Maybe I should load up writing plans to help generate a proper video based on their specific skill set. Also, could comfyui be relevant for effective video generation? I’ll need to consider loading that if it fits!"}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[Duplicate tool output — same content as a more recent call]", "tool_call_id": "call_0fnG1uinubYhS3JLb5u4PNvf", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[Duplicate tool output — same content as a more recent call]", "tool_call_id": "call_x3Wkxym9uxmp0kKc1Q6aB5a5", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[skill_view] name=writing-plans (8,527 chars)", "tool_call_id": "call_ZEIqVwU23Gj2bzUzE435QcvX", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "Ja, Sir. Für das **richtige Video** würde ich jetzt nicht direkt „ein Wan/Qwen Prompt reinwerfen und hoffen“ — das produziert sehr schnell hübsche, aber unbrauchbare AI-Suppe. Wir machen es als **Hybrid Retention Studio Pipeline**:\n\n```text\nAI generiert nur visuelle Textur / Motion\nJARVIS/Renderer kontrolliert Text, Timing, Captions, Labels, Audio, Schnitt\n```\n\n## Zielbild für Clip 1\n\nThema:\n\n```text\nYour AI automation works in the demo.\nThen one weird email arrives.\n```\n\nVisueller Ablauf:\n\n```text\n1. Clean demo inbox\n2. Weird email appears\n3. AI confidently routes it wrong\n4. Simple 3-way split:\n Go through\n Review\n Stop\n5. Final rule:\n Plan for the weird input before you automate the normal one.\n```\n\nDas ist zugänglich, konkret und nicht abgehoben.\n\n---\n\n## Mein Vorgehen\n\n## Phase 1: Final Render Plan bauen\n\nZuerst mache ich aus dem aktuellen Script einen **richtigen Produktionsplan**, nicht nur Preview Cards.\n\nNeues Artefakt:\n\n```text\nFinalVideoPlan\n```\n\nEnthält pro Szene:\n\n```text\nscene_id\nstart_ms\nend_ms\nvoiceover_segment\nvisual_mode\nasset_type\nmotion_instruction\nrenderer_text\ncaption_cues\nrequired_assets\n```\n\nWichtig:\n\n```text\nrenderer_text ≠ AI-generated text\n```\n\nAlle Texte im Bild — Inbox-Labels, Pfeile, „Review“, „Stop“, Captions — kommen vom Renderer, nicht vom Video-Modell.\n\nWarum? Weil AI-Video bei Text notorisch versagt. Es würde aus „Review“ gerne „Rëvlew“ machen. Künstlerisch mutig, aber geschäftlich nutzlos.\n\n---\n\n## Phase 2: Szenen in Asset-Typen trennen\n\nIch würde Clip 1 so aufteilen:\n\n### Szene 1 — Hook\n\n```text\n0–4s\nVisual: clean inbox / clean workflow dashboard\nMode: local deterministic animation + optional AI background\nText: Your AI automation works perfectly in the demo.\n```\n\nKein echtes AI-Video nötig. Das kann unser Renderer sauber animieren.\n\n### Szene 2 — Weird email arrives\n\n```text\n4–10s\nVisual: email card slides in\nText on card:\n\"hey can you handle this maybe??\"\nMissing name\nUnclear request\nWrong format\n```\n\nAuch hier: besser renderer-owned. Kein AI-Text im Bild.\n\n### Szene 3 — AI gets it wrong\n\n```text\n10–17s\nVisual: glowing AI node routes email to wrong action\nMotion: confident green path, then red warning flash\n```\n\nHier können wir optional AI-generated abstract/tech background nutzen, aber der Mechanismus selbst sollte lokal animiert werden.\n\n### Szene 4 — The fix: 3 paths\n\n```text\n17–29s\nVisual:\nNormal → Go through\nUnclear → Review\nWeird/Risky → Stop\n```\n\nDas ist der wichtigste Mechanismus. Muss glasklar sein. Renderer-owned Diagramm.\n\n### Szene 5 — Rule / close\n\n```text\n29–37s\nVisual: final compact rule card\nText:\nPlan for weird inputs before automating normal ones.\n```\n\n---\n\n## Phase 3: Erst lokalen Motion Renderer bauen\n\nBevor wir ComfyUI/Wan/Qwen verschwenden, baue ich einen **procedural motion renderer**:\n\n```text\nPillow/OpenCV/FFmpeg\n```\n\nEr erzeugt:\n\n```text\nanimated inbox cards\nmoving arrows\npath split\nwarning pulse\ncaption burn-in\naudio mux\n```\n\nDas ist wichtig, weil dieser Clip sehr text-/diagramm-lastig ist. Dafür ist lokaler Renderer besser als AI-Video.\n\nAI-Video wäre hier nur sinnvoll für:\n\n```text\nbackground texture\noffice/desk b-roll\ncinematic phone/screen closeups\n```\n\nNicht für den eigentlichen Erklärmechanismus.\n\n---\n\n## Phase 4: Danach AI-Visuals gezielt ergänzen\n\nDann, und erst dann, setzen wir ComfyUI ein.\n\nMeine Empfehlung:\n\n```text\nQwen-Image-2512-GGUF → Keyframes / clean background stills\nWan2.2 I2V → kurze motion clips aus diesen Keyframes\n```\n\nAber nicht parallel auf derselben GPU.\n\nAblauf:\n\n```text\n1. Qwen-Image erzeugt 2–3 clean keyframes:\n - clean inbox dashboard\n - messy weird-email moment\n - AI workflow node background\n\n2. GPU freigeben:\n /free unload_models + free_memory\n\n3. Wan2.2 macht kurze I2V clips:\n - subtle camera push\n - screen glow\n - desk/monitor movement\n\n4. Final Renderer legt darüber:\n - echte Texte\n - Captions\n - Pfeile\n - Labels\n - Audio\n```\n\nAlso:\n\n```text\nAI = texture/motion\nRenderer = Wahrheit\n```\n\n---\n\n## Phase 5: Qualitätstor vor Final\n\nIch würde jeden Clip gegen diese Gates prüfen:\n\n```text\n- Versteht man in den ersten 2 Sekunden das Problem?\n- Ist “weird email” sofort sichtbar?\n- Sind alle Texte lesbar auf Mobile?\n- Kein AI-generierter Fake-Text?\n- Captions decken Voiceover?\n- Keine Jargon-Wörter?\n- Visuelle Veränderung alle 1–2 Sekunden?\n- Mechanismus “Go through / Review / Stop” klar?\n- Audio und Video gleich lang?\n```\n\nWenn eines davon failt: nicht posten. Nicht einmal aus Mitleid.\n\n---\n\n## Konkreter nächster Implementierungsschritt\n\nIch würde jetzt bauen:\n\n```text\nautoshorts/rendering/final_video_plan.py\ntests/test_final_video_plan.py\n```\n\nDanach:\n\n```text\nautoshorts/rendering/motion_renderer.py\ntests/test_motion_renderer.py\n```\n\nErste echte lokale Version:\n\n```text\ndata/previews/truetrace-final-motion-v1/.../final-motion-preview.mp4\n```\n\nDiese Version wird noch ohne ComfyUI sein, aber schon:\n\n```text\n- echtes Motion Layout\n- Inbox Card\n- Weird Email\n- 3-way path diagram\n- Voiceover\n- Captions\n- Audio sync\n```\n\nDanach entscheiden wir:\n\n```text\nReicht procedural style?\nOder ergänzen wir AI b-roll/keyframes mit Qwen/Wan?\n```\n\n## Warum ich nicht sofort Qwen/Wan nehme\n\nWeil dieser Clip **nicht** primär ein „cinematic video“ ist. Er ist ein **mechanism reveal**.\n\nWenn wir sofort AI-Video nutzen, bekommen wir wahrscheinlich:\n\n```text\nschöne Screens\nunlesbare UI\nfalsche Texte\nrandom Bewegungen\nweniger Klarheit\n```\n\nDas sieht professioneller aus, erklärt aber schlechter. Und für Shorts zählt: **Klarheit vor Schönheit**.\n\n## Mein Vorschlag\n\nIch mache als nächstes:\n\n```text\nFinalVideoPlan + deterministic motion renderer v1\n```\n\nDann haben wir den ersten echten „richtigen“ Video-Prototypen. Danach können wir gezielt ComfyUI-Keyframes ergänzen, statt mit der GPU Würfel zu spielen.", "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Ja, Sir. Für das **richtige Video** würde ich jetzt nicht direkt „ein Wan/Qwen Prompt reinwerfen und hoffen“ — das produziert sehr schnell hübsche, aber unbrauchbare AI-Suppe. Wir machen es als **Hybrid Retention Studio Pipeline**:\n\n```text\nAI generiert nur visuelle Textur / Motion\nJARVIS/Renderer kontrolliert Text, Timing, Captions, Labels, Audio, Schnitt\n```\n\n## Zielbild für Clip 1\n\nThema:\n\n```text\nYour AI automation works in the demo.\nThen one weird email arrives.\n```\n\nVisueller Ablauf:\n\n```text\n1. Clean demo inbox\n2. Weird email appears\n3. AI confidently routes it wrong\n4. Simple 3-way split:\n Go through\n Review\n Stop\n5. Final rule:\n Plan for the weird input before you automate the normal one.\n```\n\nDas ist zugänglich, konkret und nicht abgehoben.\n\n---\n\n## Mein Vorgehen\n\n## Phase 1: Final Render Plan bauen\n\nZuerst mache ich aus dem aktuellen Script einen **richtigen Produktionsplan**, nicht nur Preview Cards.\n\nNeues Artefakt:\n\n```text\nFinalVideoPlan\n```\n\nEnthält pro Szene:\n\n```text\nscene_id\nstart_ms\nend_ms\nvoiceover_segment\nvisual_mode\nasset_type\nmotion_instruction\nrenderer_text\ncaption_cues\nrequired_assets\n```\n\nWichtig:\n\n```text\nrenderer_text ≠ AI-generated text\n```\n\nAlle Texte im Bild — Inbox-Labels, Pfeile, „Review“, „Stop“, Captions — kommen vom Renderer, nicht vom Video-Modell.\n\nWarum? Weil AI-Video bei Text notorisch versagt. Es würde aus „Review“ gerne „Rëvlew“ machen. Künstlerisch mutig, aber geschäftlich nutzlos.\n\n---\n\n## Phase 2: Szenen in Asset-Typen trennen\n\nIch würde Clip 1 so aufteilen:\n\n### Szene 1 — Hook\n\n```text\n0–4s\nVisual: clean inbox / clean workflow dashboard\nMode: local deterministic animation + optional AI background\nText: Your AI automation works perfectly in the demo.\n```\n\nKein echtes AI-Video nötig. Das kann unser Renderer sauber animieren.\n\n### Szene 2 — Weird email arrives\n\n```text\n4–10s\nVisual: email card slides in\nText on card:\n\"hey can you handle this maybe??\"\nMissing name\nUnclear request\nWrong format\n```\n\nAuch hier: besser renderer-owned. Kein AI-Text im Bild.\n\n### Szene 3 — AI gets it wrong\n\n```text\n10–17s\nVisual: glowing AI node routes email to wrong action\nMotion: confident green path, then red warning flash\n```\n\nHier können wir optional AI-generated abstract/tech background nutzen, aber der Mechanismus selbst sollte lokal animiert werden.\n\n### Szene 4 — The fix: 3 paths\n\n```text\n17–29s\nVisual:\nNormal → Go through\nUnclear → Review\nWeird/Risky → Stop\n```\n\nDas ist der wichtigste Mechanismus. Muss glasklar sein. Renderer-owned Diagramm.\n\n### Szene 5 — Rule / close\n\n```text\n29–37s\nVisual: final compact rule card\nText:\nPlan for weird inputs before automating normal ones.\n```\n\n---\n\n## Phase 3: Erst lokalen Motion Renderer bauen\n\nBevor wir ComfyUI/Wan/Qwen verschwenden, baue ich einen **procedural motion renderer**:\n\n```text\nPillow/OpenCV/FFmpeg\n```\n\nEr erzeugt:\n\n```text\nanimated inbox cards\nmoving arrows\npath split\nwarning pulse\ncaption burn-in\naudio mux\n```\n\nDas ist wichtig, weil dieser Clip sehr text-/diagramm-lastig ist. Dafür ist lokaler Renderer besser als AI-Video.\n\nAI-Video wäre hier nur sinnvoll für:\n\n```text\nbackground texture\noffice/desk b-roll\ncinematic phone/screen closeups\n```\n\nNicht für den eigentlichen Erklärmechanismus.\n\n---\n\n## Phase 4: Danach AI-Visuals gezielt ergänzen\n\nDann, und erst dann, setzen wir ComfyUI ein.\n\nMeine Empfehlung:\n\n```text\nQwen-Image-2512-GGUF → Keyframes / clean background stills\nWan2.2 I2V → kurze motion clips aus diesen Keyframes\n```\n\nAber nicht parallel auf derselben GPU.\n\nAblauf:\n\n```text\n1. Qwen-Image erzeugt 2–3 clean keyframes:\n - clean inbox dashboard\n - messy weird-email moment\n - AI workflow node background\n\n2. GPU freigeben:\n /free unload_models + free_memory\n\n3. Wan2.2 macht kurze I2V clips:\n - subtle camera push\n - screen glow\n - desk/monitor movement\n\n4. Final Renderer legt darüber:\n - echte Texte\n - Captions\n - Pfeile\n - Labels\n - Audio\n```\n\nAlso:\n\n```text\nAI = texture/motion\nRenderer = Wahrheit\n```\n\n---\n\n## Phase 5: Qualitätstor vor Final\n\nIch würde jeden Clip gegen diese Gates prüfen:\n\n```text\n- Versteht man in den ersten 2 Sekunden das Problem?\n- Ist “weird email” sofort sichtbar?\n- Sind alle Texte lesbar auf Mobile?\n- Kein AI-generierter Fake-Text?\n- Captions decken Voiceover?\n- Keine Jargon-Wörter?\n- Visuelle Veränderung alle 1–2 Sekunden?\n- Mechanismus “Go through / Review / Stop” klar?\n- Audio und Video gleich lang?\n```\n\nWenn eines davon failt: nicht posten. Nicht einmal aus Mitleid.\n\n---\n\n## Konkreter nächster Implementierungsschritt\n\nIch würde jetzt bauen:\n\n```text\nautoshorts/rendering/final_video_plan.py\ntests/test_final_video_plan.py\n```\n\nDanach:\n\n```text\nautoshorts/rendering/motion_renderer.py\ntests/test_motion_renderer.py\n```\n\nErste echte lokale Version:\n\n```text\ndata/previews/truetrace-final-motion-v1/.../final-motion-preview.mp4\n```\n\nDiese Version wird noch ohne ComfyUI sein, aber schon:\n\n```text\n- echtes Motion Layout\n- Inbox Card\n- Weird Email\n- 3-way path diagram\n- Voiceover\n- Captions\n- Audio sync\n```\n\nDanach entscheiden wir:\n\n```text\nReicht procedural style?\nOder ergänzen wir AI b-roll/keyframes mit Qwen/Wan?\n```\n\n## Warum ich nicht sofort Qwen/Wan nehme\n\nWeil dieser Clip **nicht** primär ein „cinematic video“ ist. Er ist ein **mechanism reveal**.\n\nWenn wir sofort AI-Video nutzen, bekommen wir wahrscheinlich:\n\n```text\nschöne Screens\nunlesbare UI\nfalsche Texte\nrandom Bewegungen\nweniger Klarheit\n```\n\nDas sieht professioneller aus, erklärt aber schlechter. Und für Shorts zählt: **Klarheit vor Schönheit**.\n\n## Mein Vorschlag\n\nIch mache als nächstes:\n\n```text\nFinalVideoPlan + deterministic motion renderer v1\n```\n\nDann haben wir den ersten echten „richtigen“ Video-Prototypen. Danach können wir gezielt ComfyUI-Keyframes ergänzen, statt mit der GPU Würfel zu spielen."}], "id": "msg_0dc9f371a6d55e3f016a13721421188191a42c7bb32426b21e", "phase": "final_answer"}], "finish_reason": "stop", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "user", "content": "[M G] Ok, leg los. Bedenke: du kannst ChatGPT Image nutzen über codex anstelle eines lokalen qwen image.", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_eRGDQD4TzBNXJRFtKdDLs8JM", "call_id": "call_eRGDQD4TzBNXJRFtKdDLs8JM", "response_item_id": "fc_0dc9f371a6d55e3f016a137328297c8191bf99d97ddc0687c3", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"test-driven-development\"}"}}, {"id": "call_x73vrhY3HRf2gOH7EbcFHmJj", "call_id": "call_x73vrhY3HRf2gOH7EbcFHmJj", "response_item_id": "fc_0dc9f371a6d55e3f016a13732829a481918129c30406a25a0d", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"social-media-shorts-automation\"}"}}, {"id": "call_kPdfp5JvZhW5d5YPU5pJmzIB", "call_id": "call_kPdfp5JvZhW5d5YPU5pJmzIB", "response_item_id": "fc_0dc9f371a6d55e3f016a13732829b48191ac6ac2c6646c98a3", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"comfyui\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Implementing the image generation plan**\n\nI need to take action and see if the image generation tool is available, possibly requiring backend support. The user asked to use the ChatGPT Image über codex instead of the local option. I can work on this plan! I'll need to ensure that all skills are appropriately loaded, but should I do this before replying each time? Testing driven development could be useful here, along with reviewing existing files.", "reasoning_content": "**Implementing the image generation plan**\n\nI need to take action and see if the image generation tool is available, possibly requiring backend support. The user asked to use the ChatGPT Image über codex instead of the local option. I can work on this plan! I'll need to ensure that all skills are appropriately loaded, but should I do this before replying each time? 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The user asked to use the ChatGPT Image über codex instead of the local option. I can work on this plan! I'll need to ensure that all skills are appropriately loaded, but should I do this before replying each time? Testing driven development could be useful here, along with reviewing existing files."}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[Duplicate tool output — same content as a more recent call]", "tool_call_id": "call_eRGDQD4TzBNXJRFtKdDLs8JM", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[skill_view] name=social-media-shorts-automation (19,664 chars)", "tool_call_id": "call_x73vrhY3HRf2gOH7EbcFHmJj", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[skill_view] name=comfyui (32,631 chars)", "tool_call_id": "call_kPdfp5JvZhW5d5YPU5pJmzIB", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_brYzkxVlfVIzBK83QPvVq1L1", "call_id": "call_brYzkxVlfVIzBK83QPvVq1L1", "response_item_id": "fc_0dc9f371a6d55e3f016a137331d5988191a26c8be2c005fab6", "type": "function", "function": {"name": "write_file", "arguments": "{\"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_final_video_plan.py\", \"content\": \"from autoshorts.audio.voiceover import build_truetrace_final_voiceover\\nfrom autoshorts.rendering.final_video_plan import (\\n FinalVideoPlan,\\n build_truetrace_weird_email_final_video_plan,\\n val...[truncated]\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Creating video tests**\n\nI need to create tests and consider including an image note with the image_generate tool later. I could start with a deterministic approach and implement tests for the final video plan, possibly using a motion renderer. I plan to produce the actual video using animated frames generated with Pillow and ffmpeg. It looks like TDD will guide this process, so I need to know the necessary modules. Writing simple tests is my goal!", "reasoning_content": "**Creating video tests**\n\nI need to create tests and consider including an image note with the image_generate tool later. I could start with a deterministic approach and implement tests for the final video plan, possibly using a motion renderer. I plan to produce the actual video using animated frames generated with Pillow and ffmpeg. It looks like TDD will guide this process, so I need to know the necessary modules. Writing simple tests is my goal!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3MxOYmllmWTCUdhLqfxOJpCn_zExZiwfWGsr3j8TryeykXP1nqXcUJfE097S_JdKfY9CthqB9yKnkta_8GnQJwiGs1Lq9pT3J69rp-1IxJSlaTvPMY083mtI_otSNcZq8heKbv0h5UNt3dQK-ZTgnMccgo0PYqslzeAFYhXRmDncrnM4JjKRdMQRyrYJL7jquJt1tkf-Do423E2mg7M5PSHTVg2iWj6TJSsPSjEDPKhmUL7dSBdUV0Sm3l1roAYv-Y5RAC9pB8l13dBEYG8Z33XmuAlLbLZ--Rly3CRVyYsEg5PpdI1BAGpREABDXAUp7JuXokbkRHGB7BY8_ka8k2iUO_SOiGNmyggEJ_-ZLHnas3sHWVzzp7gEDo6lD5R9rPLxOK81Pke7GZKx2Efj1LnNJA6WplPWXNgkoAMseOsOORkr8QRfr6OevPp3GODBCjNYMdctkbVbC8JRLDLv-1nN8CngFsMZTDO8lMnimtezOKsmw5_bYICxPASuVPNpgrpNDH46s3sQ4uqeOQDbGKn6DmzTL07qeI0XqHy5tVPA8rrnnVAFP10AII7DpfmGZKq1k-0T9HVl6JK-2ySwmIDsXqu8t7m7D2uMXo-AW8IUCJldSMBYfQTV01KpM9xCoLuOmEyuxrPzDxnY_IpzCUH6lJND1kJYI-985F61Na9gkVx719SaRCvBy95QZCgzBs_4aIyPiZE6AmnGJLXA9o2N9M28yljUAkDaNhK0Mw0-NQSLkd9l02oQ4GxrrNpFrjlEhlYq071Q5UDLFY_Qv5GwSmO-bZxuqkFDAUYpwJeNWxIIEgqv6Tjl85e_tBUB_B0f-p6Rnxs0f1_cGUy1DereigZi7dJ-7Eq2Tjfz2yR5WZCRKir_on9i0sz8LtwVwIPVfb7ujiG97x7FVaC3OWJ2AwJsvpuaOlz5ilyzLoocqdUdCYhLrikS8XIOG4XPL122PrMNc0t4NNDT-_fQFuaRXi_sKnA67ACgbkh9g0Ne_P2gwmXg1a6Vzgk3ojCa7sMcM-SoZnqu_V7M-tjabG2bMDdPsG6tNqBbN3xBHaKx5AtWefDE73wuVUeCKHczUyU0eCHTVotnPBDZF9iZ1QxZW9pw4QV_-uDS4qLNP28bKkuaAoRgQs8_In_simPgAdmru23WyX65hBrrWrNiwkp792OpNa17lCn7mYWQUB_NUx61EgMFhjiMU98Du6oxiNAIsfCBw-BHTPCJNNXSJUqJljP0RVS4BYtNlwXNW5ZAdnnlwtdNYin-pqyuN6tzZW8hRupEaSQKKLjHnngXyTekshF_dEvxt5pWMTc7TeEtmli58SZt2cgs-f9sc7xVN31uKaDcXvsg-vwcvSQC2kntM58XG-arDzFP5-3p8ON0cKhXMqkwbtHkr8DFh0vBf-P3_-ilkF-1kioDqlYcctP8xzI-H8lz8fkVqvCdlsf4kOzXZmDdKQN8rNgUaj3HQrbmT4zHAdkCGLAoVeRuZv6XMz_fP_h1aTeeIctJc0QcCQ=", "id": "rs_0dc9f371a6d55e3f016a13732da07c81918fc97fba11682c7b", "summary": [{"type": "summary_text", "text": "**Creating video tests**\n\nI need to create tests and consider including an image note with the image_generate tool later. I could start with a deterministic approach and implement tests for the final video plan, possibly using a motion renderer. I plan to produce the actual video using animated frames generated with Pillow and ffmpeg. It looks like TDD will guide this process, so I need to know the necessary modules. Writing simple tests is my goal!"}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[write_file] wrote to /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_final_video_plan.py (72 lines)", "tool_call_id": "call_brYzkxVlfVIzBK83QPvVq1L1", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_J3pAeVOXUA7w40U451PC1Zov", "call_id": "call_J3pAeVOXUA7w40U451PC1Zov", "response_item_id": "fc_0dc9f371a6d55e3f016a137341d45c8191b26a48d28f1d8157", "type": "function", "function": {"name": "write_file", "arguments": "{\"content\": \"from pathlib import Path\\nimport subprocess\\n\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover\\nfrom autoshorts.rendering.final_video_plan import build_truetrace_weird_email_final_v...[truncated]\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_motion_renderer.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[write_file] wrote to /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_motion_renderer.py (54 lines)", "tool_call_id": "call_J3pAeVOXUA7w40U451PC1Zov", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_y0g61SREHueJPUENoj8iR6Bq", "call_id": "call_y0g61SREHueJPUENoj8iR6Bq", "response_item_id": "fc_0dc9f371a6d55e3f016a13735421b08191ab8211ebe928b294", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_final_video_plan.py tests/test_motion_renderer.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `pytest tests/test_final_video_plan.py tests/test_motion_renderer.py -q` -> exit 2, 1 lines output", "tool_call_id": "call_y0g61SREHueJPUENoj8iR6Bq", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_QTNGa15Kw5fcmoXNpghwEzry", "call_id": "call_QTNGa15Kw5fcmoXNpghwEzry", "response_item_id": "fc_0dc9f371a6d55e3f016a13735ad2d48191a7971b6bea631716", "type": "function", "function": {"name": "write_file", "arguments": "{\"content\": \"\\\"\\\"\\\"Final-near vertical video production plan for TrueTrace pilots.\\\"\\\"\\\"\\n\\nfrom __future__ import annotations\\n\\nfrom dataclasses import dataclass\\n\\nfrom autoshorts.audio.voiceover import FinalVoiceoverScrip...[truncated]\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/final_video_plan.py\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Implementing Frame Generation**\n\nI'm planning to use ValidationResult and a motion renderer like PIL and ffmpeg. 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Let's see how this will all work together.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3NattI3brcx3wiIaT7yqFroJcFEXhjY59ZolYGgWplpv4ncwfnCwq4vJrbnrcaJGtPEeD8K9-G2SH2mOgXwxDsIHYCW1yz4_Keb_u_RSXt1jTaM-PgiHyJvTUeTPlF_wr2R3ccF5hv_5SeZZAz24ruEQpHGKgG1IGBQcTK2HggiKgmt2Orr53-3Oe3Jm8BwzmBPsCrlb6dLQcSuOglNuFokehOE_OM6ZoUK2cpjg0Cu8t4rpSgbSL3HrK_Y0CM5CZhpBMxeMq2e5WRs9mzhGmuF_TACqGEs2lL3DflwpYw2qJ3bF4zD6yc6P2NV38cKygD50SDDMxometIH7eMyESvMl4gCbg3TQzZRYGd5mnoCTiU0SkNfErAwDbfHOkLKtXGo9asdL5UZmMvlqc3zaiWK1ZTECGdDm5NABfL3Hh_DGx6NRFb6TUJUgDE_t_eQJfJ7526lvQiIoQACBzzH9w-ClhGC6Pdwq1giO89KeL-3PXPSINnX9-Lv2gYzfo8qa055gj9MBraC0H6VfHtqbJ5vaH3Ju7E389oeTrTBHrva4LIoUC_LL70mshrC-mjzBSat0ZAV_FAJHD602lHC7Oo0zRp3gO1hGsu114mSCuqeNMl7_KEIrFZ67HYTPeCiITCJ21mccgXWjIUvVn-MNTBtuSJWUIIQEEIM_9J8EpS1K3K2JE02LDUX0e4q0RRmv1J_NkRYMxNn_mpbv9RXUArwP45-XaeVVIAoAdY9YZc0PR29IebEdgDxMoJG1ZE0ETkRIZ_GrLYVQwPfReMvgV8oCR6s74_XnaxxwGqSWY0rt_TFQ8xhI9kgneKaAfH7tKgB0WUjpbDbWv8iFFYnQk0wEtRUxsqtz9Mw_hnsXQ-Dku65r_-w07-_55_8l_MT8Jad63xZsg0iG7X1NYoxXmidk1xiMp6XgoXnixygVKkhg4aRjG1zlKCdrnWNjlFiE7g4IYGaT6Y5DDc2H6kOCJs-2zDbZNE1tfSosiGkRw_BrXKY6NeTvA4PdOMIK7UqJi74eOkxhRqUjzC7A3JQ7BaLQoAFQRPyAi_7W2JPJBBvBxvhwGP4lbb_NVgEowL6IIovJ4rZTS8ffyGeMyzKTehpuwzOtUS4ENSQ6ILMBKyFfqL0kYW9kDEk_V2cyMW7T4BjUtpm0NTDskSS2zG_98lWTBtQWv4swJAbyZGwr5kYc8XAWHSQoqtwl39SemgmqPjYiZTQCIqV03YUVvmmS2outw==", "id": "rs_0dc9f371a6d55e3f016a1373586a2081918cd0656ce0d68220", "summary": [{"type": "summary_text", "text": "**Implementing Frame Generation**\n\nI'm planning to use ValidationResult and a motion renderer like PIL and ffmpeg. 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[100%]\\n4 passed in 0.27s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_182dfGHpc9mdkHS2n8H0KyrB", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_8Z6viPuj5nxWjnaeYCq8VFWW", "call_id": "call_8Z6viPuj5nxWjnaeYCq8VFWW", "response_item_id": "fc_0dc9f371a6d55e3f016a1373da12108191ab193cdf9721afce", "type": "function", "function": {"name": "image_generate", "arguments": "{\"aspect_ratio\":\"portrait\",\"prompt\":\"Vertical 9:16 cinematic background for a modern AI automation short. A clean laptop/workspace scene with a dark minimal productivity dashboard glow, subtle blue and green light accents, premium tech aesthetic, shallow depth of field, no readable text, no logos, no watermarks, no UI labels, empty central space for overlaid renderer-owned text and diagrams. 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I'll go ahead and generate the background now!"}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[image_generate] aspect_ratio=portrait prompt=Vertical 9:16 cinematic background for a (685 chars result)", "tool_call_id": "call_8Z6viPuj5nxWjnaeYCq8VFWW", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_BW0lGX2C3iMqXqRRqYrBS8hN", "call_id": "call_BW0lGX2C3iMqXqRRqYrBS8hN", "response_item_id": "fc_0dc9f371a6d55e3f016a137412e51c8191b80eb70afb500ce2", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\": \"replace\", \"path\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_motion_renderer.py\", \"old_string\": \" render_plan = build_motion_render_plan(final_plan, output_dir=tmp_path, preview_scale=0.5)\\n\\n assert render_plan.width == 540\", \"new_string\": \" background = tmp_path / \\\"chatgpt-image-background.png\\\"\\n background.write_bytes(b\\\"fake image\\\")\\n render_plan = build_motion_render_plan(final_plan, output_dir=tmp_path, preview_scale=0.5, back...[truncated]\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Integrating Backgrounds Into Rendering**\n\nI'm considering integrating an optional background into the renderer. 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list[str] = []\\n background = None\\n if plan.background_path:\\n background = Image.open(plan.background_path).convert(\\\"RGB\\\").resize((plan.width, plan.height), Image.Resampling.LANCZOS)\\n frame_index = 0\",\"old_string\":\" frame_paths: list[str] = []\\n frame_index = 0\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py (879 chars result)", "tool_call_id": "call_MNuX3FGknJBjzB9HDV1z1iZQ", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_YyLcnziDdofWjQMTn32B1x33", "call_id": "call_YyLcnziDdofWjQMTn32B1x33", "response_item_id": "fc_0dc9f371a6d55e3f016a13744d40b08191beeaa8b5c355bb5b", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" image = _render_scene(plan, scene, progress, background=background)\",\"old_string\":\" image = _render_scene(plan, scene, progress)\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py (865 chars result)", "tool_call_id": "call_YyLcnziDdofWjQMTn32B1x33", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_ozbKoDK4bEFZXnUJV8VcpdSV", "call_id": "call_ozbKoDK4bEFZXnUJV8VcpdSV", "response_item_id": "fc_0dc9f371a6d55e3f016a13745577a8819185cd09c1bed15266", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_motion_renderer.py tests/test_final_video_plan.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \".... [100%]\\n4 passed in 0.31s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_ozbKoDK4bEFZXnUJV8VcpdSV", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_x9bWY7V2GCgfHYcXa1LLMCRM", "call_id": "call_x9bWY7V2GCgfHYcXa1LLMCRM", "response_item_id": "fc_0dc9f371a6d55e3f016a13745dae848191b86aaf99652e3f53", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"python - <<'PY'\\nfrom pathlib import Path\\nfrom math import ceil\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover\\nfrom autoshorts.audio.tts_plan import build_default_truetrace_tts_...[truncated]\", \"timeout\": 300, \"workdir\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Generating final preview**\n\nI need to generate an actual render and think about running it fully later. First, I’ll create a motion preview with a background and see if I can reuse existing audio. I should use the current function and mux in the captions. For the final preview, it’ll be important to include subtitles, and I might need to trim it to the audio. I think I need to prepare for generating around 888 frames, but I might target a shorter duration. Let's get started!", "reasoning_content": "**Generating final preview**\n\nI need to generate an actual render and think about running it fully later. First, I’ll create a motion preview with a background and see if I can reuse existing audio. I should use the current function and mux in the captions. For the final preview, it’ll be important to include subtitles, and I might need to trim it to the audio. I think I need to prepare for generating around 888 frames, but I might target a shorter duration. Let's get started!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3Rdb_9k3ZInzz7FtyONAZ2P3zuazk5T4i_ElbhKiZ-oIvWAHHrVPYFQDGs3t0Zi4drCSOrVRBqRZ4Ci0vjU0Yd9J5UFBFoihzs5eePLWbw9UZWtXtHhxA6RRzkYMP5e1f_oFaQwBeIDQx9kRdLj9_hBs9oDDjJJRsFHR-qzYfeQa8sTcjRad6f_ArW5TInbXLaQ-ACCCu8QoTuh03f6pPwK2HYA52TsccwDm0hSvFWjO6hJL-JKLcUbL8FD655xd2N0ky_5zkKxq-9mxVjThjL0zIe0nj7ya5oz6INzuZUEwb1PBZnN46XAiLZLHjPt8Jmsx23qcu2ZldKKlbTPPVzl6zLiMrS-wmMc2EUiAcbpo09hJnB6IrUMrI2IQkdzSuP9-be1y4Q0hAXI1UtWJFAkyHsCbMqMyOKLNPi7nLDkj4L2hSFj6rdWkp4mT2dFYyisxp96j2ILqJdPGjNw-fHMLn99UwC8WW5V7ZiPzC4WLuVQtkSzQT71TiMWWPSYNCz8cmIZjWaInS4bC3ycZvDM974gxFyrYWw6Q2kvwMZVsjKQz5oVr_ccsEmEFw5xqkDZ4cfRWMafGXDrqBIX5u_G7PC0S_NfJxVB9aFRUcO7pv7RC56bfZJMHevrF5dNLkYZJVxwXIEN-H6zOB6vsK-bOUx0omaM1Z743hPB2Zy6D1A_q9hy5pqVqKdMpkTGfIsECd8bHP-NRXdx_jMdKdgfaM9h0akfJV7yTdBXpd9Zu8VfuB2HLMUMGx4Te3z89LjcRCAUgyIDVwajn_0CIXYVUhBx-s6Eu-D5tNFkomhiRCI2n3FNTIly2RYSUXRHKF_IKDEY5-dvQGJD0sH18GeUmZxeuW-XQ4axE7cZTDtOavyN76-S-j3aWTDmmG54dQPnqlNgqHgCVfn9SbiKK2IxWH87U2ToMNM5KKuxExKjG2Qp2LGga0gc8AS8W1-62NxVadmu1SOnUYJBQuH8alRcjW-5t5MEuOjJTHp_6jK_HHOKwViqc-LWmLfcI52z3NSNaWhX3fk-imjHjIvGpqRBg1qUvh4oiNed4PwbVFSu71L_6irYs45DTbQpFUw3P6yBjpb2mPbib0-sodhd0iTOQV7dekB1AEV936D6ywfsMbdqhqzlyD9zTB0VpIE7cQwckcwNsBw68J3hExOUyI7eLQlHM5kDwDhpa1zQBNnPqOmtVdlB9ARBk7E1ePl4WEPrNzBjHnFneZ_ksdypXp_YWq6YOM-TgH9ld4ebLjD6DFYGW2TTxTqDYDf95fnXqUZlu9SJFQGpk2nhQte2hzZrxnXo_thjWlElFXO_-jW4GOtlMoxyhF1-5GW0Z-jN8NfXjPqGhNvrlWMHusX7-GiRXp92Jy5lo9LMUbOPsF5Ou1qZSFlLW_sm4i6oB4H4gXwZ", "id": "rs_0dc9f371a6d55e3f016a13745ab57481919abaf55376eb82c3", "summary": [{"type": "summary_text", "text": "**Generating final preview**\n\nI need to generate an actual render and think about running it fully later. First, I’ll create a motion preview with a background and see if I can reuse existing audio. I should use the current function and mux in the captions. For the final preview, it’ll be important to include subtitles, and I might need to trim it to the audio. I think I need to prepare for generating around 888 frames, but I might target a shorter duration. Let's get started!"}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `python - <<'PY'\nfrom pathlib import Path\nfrom math import ceil\nfrom autoshort...` -> exit 0, 1 lines output", "tool_call_id": "call_x9bWY7V2GCgfHYcXa1LLMCRM", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_Z51xexttiCm2PNlnGsYlc9b8", "call_id": "call_Z51xexttiCm2PNlnGsYlc9b8", "response_item_id": "fc_0dc9f371a6d55e3f016a1374d6ce9081918b0e2005c400a861", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"mkdir -p /tmp/truetrace_review && ffmpeg -y -i data/previews/truetrace-final-motion-v1/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4 -vf \\\"select='eq(n,0)+eq(n,120)+eq(n,300)+eq(n,520)+eq(n,760)'\\\" -vsync 0 /tmp/truetrace_review/frame_%02d.png >/dev/null 2>&1 && printf '%s\\\\n' /tmp/truetrace_review/frame_*.png\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Considering video extraction methods**\n\nI need to inspect some screenshots or frames in a video. 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Let's see!"}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[terminal] ran `mkdir -p /tmp/truetrace_review && ffmpeg -y -i data/previews/truetrace-final-...` -> exit 0, 1 lines output", "tool_call_id": "call_Z51xexttiCm2PNlnGsYlc9b8", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_B9pUia5ODOv3Dx1y7HEdH7NE", "call_id": "call_B9pUia5ODOv3Dx1y7HEdH7NE", "response_item_id": "fc_0dc9f371a6d55e3f016a1374dc98f88191ae91d6af7c769f59", "type": "function", "function": {"name": "vision_analyze", "arguments": "{\"image_url\":\"/tmp/truetrace_review/frame_03.png\",\"question\":\"Review this mid-video frame for mobile readability, whether it looks like a mechanism reveal rather than static cards, and whether any text appears clipped.\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[vision_analyze] 'Review this mid-video frame for mobile readability' (287 chars)", "tool_call_id": "call_B9pUia5ODOv3Dx1y7HEdH7NE", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_Fuv5HiNqexzu5YxJuckNvs0W", "call_id": "call_Fuv5HiNqexzu5YxJuckNvs0W", "response_item_id": "fc_0dc9f371a6d55e3f016a1374e58688819194db1211468f7fcc", "type": "function", "function": {"name": "vision_analyze", "arguments": "{\"image_url\":\"/tmp/truetrace_review/frame_04.png\",\"question\":\"Review this three-way split frame for readability and clipping. Is the mechanism clear?\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Inspecting subtitle issues**\n\nI'm thinking about whether to note that the subtitle might need to be clipped or shown only partially at the bottom. It seems like having the bottom text continue onto the next line could be messy. I should probably inspect it further, maybe specifically looking at frame_04. I'm curious to see if that will help resolve the subtitle display issue! Let's see what adjustments can be made to improve clarity.", "reasoning_content": "**Inspecting subtitle issues**\n\nI'm thinking about whether to note that the subtitle might need to be clipped or shown only partially at the bottom. It seems like having the bottom text continue onto the next line could be messy. I should probably inspect it further, maybe specifically looking at frame_04. I'm curious to see if that will help resolve the subtitle display issue! 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Let's see what adjustments can be made to improve clarity."}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "[vision_analyze] 'Review this three-way split frame for readability ' (218 chars)", "tool_call_id": "call_Fuv5HiNqexzu5YxJuckNvs0W", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_d3XU5ey5pInGT9Bl6m8OJtkA", "call_id": "call_d3XU5ey5pInGT9Bl6m8OJtkA", "response_item_id": "fc_0dc9f371a6d55e3f016a1374efb5b88191b5b61e5bbd848b96", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" by = int(h * (0.42 + idx * 0.12))\",\"old_string\":\" by = int(h * (0.48 + idx * 0.14))\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Fixing clipping issues in Frame 4**\n\nI see that Frame 4 has some clipping and overlap at the bottom, so I need to address that. 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fill=color, width=7)\\n for top, bottom, color, by, _ex in positions:\\n draw.rounded_rectangle((margin, by, w - margin, by + int(h * 0.10)), radius=20, fill=(15, 23, 42), outline=color, width=4)\\n draw.text((margin + 28, by + 18), f\\\"{top} → {bottom}\\\", font=mid_font, fill=(248, 250, 252))\",\"old_string\":\" for idx, (top, bottom, color) in enumerate(labels):\\n reveal = min(1.0, max(0.0, (progress - idx * 0.18) / 0.35))\\n bx = margin\\n by = int(h * (0.37 + idx * 0.105))\\n ex = int(bx + (w - 2 * margin) * reveal)\\n draw.line((start[0], start[1] + 58, ex, by + 45), fill=color, width=7)\\n draw.rounded_rectangle((margin, by, w - margin, by + int(h * 0.10)), radius=20, fill=(15, 23, 42), outline=color, width=4)\\n draw.text((margin + 28, by + 18), f\\\"{top} → {bottom}\\\", font=mid_font, fill=(248, 250, 252))\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"}"}}], "finish_reason": "tool_calls", 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"id": "rs_0dc9f371a6d55e3f016a13760259e08191b21bccdd9356b885", "summary": []}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n@@ -210,12 +210,14 @@\\n draw.rounded_rectangle((start[0] - 120, start[1] - 48, start[0] + 120, start[1] + 48), radius=20, fill=(30, 41, 59), outline=accent, width=3)\\n draw.text((start[0] - 72, start[1] - 16), \\\"Input\\\", font=mid_font, fill=(226, 232, 240))\\n labels = [(\\\"Normal\\\", \\\"Go through\\\", green), (\\\"Unclear\\\", \\\"Review\\\", amber), (\\\"Weird/Risky\\\", \\\"Stop\\\", red)]\\n+ positions = []\\n for idx, (top, bottom, color) in enumerate(labels):\\n reveal = min(1.0, max(0.0, (progress - idx * 0.18) / 0.35))\\n- bx = margin\\n by = int(h * (0.37 + idx * 0.105))\\n- ex = int(bx + (w - 2 * margin) * reveal)\\n+ ex = int(margin + (w - 2 * margin) * reveal)\\n+ positions.append((top, bottom, color, by, ex))\\n draw.line((start[0], start[1] + 58, ex, by + 45), fill=color, width=7)\\n+ for top, bottom, color, by, _ex in positions:\\n draw.rounded_rectangle((margin, by, w - margin, by + int(h * 0.10)), radius=20, fill=(15, 23, 42), outline=color, width=4)\\n draw.text((margin + 28, by + 18), f\\\"{top} → {bottom}\\\", font=mid_font, fill=(248, 250, 252))\\n else:\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_3EldqKOUxivXLirVcarsQUWq", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_BulFa7EBQ5UHSkEeZKQqGyIo", "call_id": "call_BulFa7EBQ5UHSkEeZKQqGyIo", "response_item_id": "fc_0dc9f371a6d55e3f016a1376184c1c81918049603636b92c7a", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nfrom pathlib import Path\\nfrom math import ceil\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover\\nfrom autoshorts.audio.tts_plan import build_default_truetrace_tts_plan\\nfrom autoshorts.audio.edge_tts_adapter import EdgeTTSRequest, synthesize_edge_tts\\nfrom autoshorts.audio.probe import probe_media_duration_seconds\\nfrom autoshorts.audio.subtitles import build_hormozi_subtitle_track\\nfrom autoshorts.audio.final_preview import build_audio_caption_preview_plan, render_audio_caption_preview\\nfrom autoshorts.rendering.final_video_plan import build_truetrace_weird_email_final_video_plan\\nfrom autoshorts.rendering.motion_renderer import build_motion_render_plan, render_motion_preview\\ncandidate_id='truetrace-ai-automation-quiet-rot-38s'\\noutput_dir=Path('data/previews/truetrace-final-motion-v4')/candidate_id\\nbackground=Path('/home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260524_235629_ac459a00.png')\\nvoiceover=build_truetrace_final_voiceover(candidate_id)\\nfinal_plan=build_truetrace_weird_email_final_video_plan(voiceover)\\nmotion=render_motion_preview(build_motion_render_plan(final_plan, output_dir=output_dir, preview_scale=0.5, background_path=background))\\nif motion.returncode: raise SystemExit(motion.stderr)\\nvoice=synthesize_edge_tts(EdgeTTSRequest(text=voiceover.text, tts_plan=build_default_truetrace_tts_plan(), output_path=str(output_dir/'voice.mp3')))\\naudio_duration=probe_media_duration_seconds(voice.output_path)\\nsubtitles=build_hormozi_subtitle_track(voiceover.text, total_duration_seconds=ceil(audio_duration))\\nfinal=render_audio_caption_preview(build_audio_caption_preview_plan(video_path=motion.output_path,audio_path=voice.output_path,subtitle_track=subtitles,output_path=output_dir/'final-motion-audio-caption-preview.mp4',duration_mode='trim_to_audio'))\\nif final.returncode: raise SystemExit(final.stderr)\\nprint(final.output_path)\\nPY\\nrm -rf /tmp/truetrace_review_v4 && mkdir -p /tmp/truetrace_review_v4 && ffmpeg -y -i data/previews/truetrace-final-motion-v4/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4 -vf \\\"select='eq(n,520)'\\\" -vsync 0 /tmp/truetrace_review_v4/frame_04.png >/dev/null 2>&1\\nffprobe -v error -show_entries stream=codec_type,codec_name,width,height,duration -of default=noprint_wrappers=1 data/previews/truetrace-final-motion-v4/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\nsha256sum data/previews/truetrace-final-motion-v4/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": 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"id": "rs_0dc9f371a6d55e3f016a137617a01c8191aa96faf1d00362af", "summary": []}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"data/previews/truetrace-final-motion-v4/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\ncodec_name=h264\\ncodec_type=video\\nwidth=540\\nheight=960\\nduration=36.833333\\ncodec_name=aac\\ncodec_type=audio\\nduration=36.864000\\n3893b94eabf353e6388d1ca8b1fc06bae19cb216cc98f6b44956739e58853051 data/previews/truetrace-final-motion-v4/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_BulFa7EBQ5UHSkEeZKQqGyIo", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_BjoFHAf6OhZmh4LADx8crAhL", "call_id": "call_BjoFHAf6OhZmh4LADx8crAhL", "response_item_id": "fc_0dc9f371a6d55e3f016a13768dabd88191b657d96e6d6f911a", "type": "function", "function": {"name": "vision_analyze", "arguments": "{\"image_url\":\"/tmp/truetrace_review_v4/frame_04.png\",\"question\":\"Final check: is the three-way split readable, arrows behind labels, and no critical clipping/overlap for a review prototype?\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "Image loaded into your context — you can see it natively now. Use your built-in vision to answer the user.\n\nQuestion: Final check: is the three-way split readable, arrows behind labels, and no critical clipping/overlap for a review prototype?\n[screenshot]", "tool_call_id": "call_BjoFHAf6OhZmh4LADx8crAhL", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_TSPkNK7JtPeNQB0TqPKPN836", "call_id": "call_TSPkNK7JtPeNQB0TqPKPN836", "response_item_id": "fc_0dc9f371a6d55e3f016a137694c5a48191b9e0e22b1df5ad84", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"- `autoshorts.rendering.final_video_plan` — final-near 1080x1920 production plans that keep AI visuals text-free and renderer-owned.\\n- `autoshorts.rendering.motion_renderer` — procedural motion preview renderer for inbox cards, warning routes, and three-path mechanism diagrams before heavier AI-video work.\\n- `autoshorts.rendering.ffmpeg_plan` — side-effect-free FFmpeg concat planning for local preview frames.\",\"old_string\":\"- `autoshorts.rendering.ffmpeg_plan` — side-effect-free FFmpeg concat planning for local preview frames.\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Considering documentation updates**\n\nI need to update the README and documentation, and then ensure that all tests are complete. But first, I might generate the image asset for the final video. It could be a good idea to mention ChatGPT Image through the Codex, as it relates. After that, I’ll commit everything and add the documentation. This is feeling like a productive plan! I want to make sure everything is in order.", "reasoning_content": "**Considering documentation updates**\n\nI need to update the README and documentation, and then ensure that all tests are complete. But first, I might generate the image asset for the final video. It could be a good idea to mention ChatGPT Image through the Codex, as it relates. After that, I’ll commit everything and add the documentation. This is feeling like a productive plan! I want to make sure everything is in order.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3aUZ5mZWmeckfhCXx8OGLR9tgNMn6sroa-F0-UJ39jNRS5UBCPHKV13_OyBbdduffw8GIN1zQvIizMGcwOTlcH03US9De0iReyMcm6dHtZv5OalQy4pHabH6MVinlIJ2AmBXybDsVUbyIwk2Ei3aO-11FZEV2OV1mhUPqo41Tybed9tLfe2L-zPEEZ9Ff5QYQSq2G6U4-yuhtjHzuPv_78SvgAhFAOdsrWkOHJ-Qb0zanRPyyDlsMpYlDkQgm_6uRUeydmwdixuWAfZHff153vpNxDKHN204phxu3uPwinQQ8oxuqcR8NYfgxzu44_6XJvZDNrrwDosxevPrmN2L3QvCyTBxk2gHeaiv4IJy0tSko-G-6n-Rc6QxKT8JGKlcIR80QDrQ_kcg9V2cBn6QwpOZl7s78M42JHGsxtj38MzLV7mwPd_q5IanA3I2oE5ZSOvFWNj1ZZzqU4nBhesAgKWf2hI0Qiw41X1Yvs6sXwu_xdBUMYZucoeBhQk-lIu3Jhl_K5zoyqkvNQYmMU1_0rml4OjOaQ5FT0N3iovn2NCZJSATrZ29cO2XABbr_kLtpowXuTuH5UTBxJUgSiaxEK1inbA08kZP8G9z2apxfHKWGGoZ38CX8ZQwEXOvXJ5DxNs_lbbrq8LT8WRu_qFgRdq4R2aLGgSKBBRQ0Z_JjCkvr4KF-kIEoRcW4hI9qh32XA2wATyg8dzUiQ9f9ORdEY1to0bQ8VqwP4m7Ej6qoRyrZ_s6azRtTvDTrxCOrt6eVoINXNc78pVrVkuxuoV5SFprVTcU4HHNViBeqOdupVaPqoPrkaDelLboK9D0kesZaHk8v2q-UT6a1nL-mWNPYjflorWPLHCqVXs5_b43XSzhPe-U2Ifl93J7rFE-T-C6kU8Bsv4voamM1W5eNOiuiOv5DVNqQRhNMZkfnGKbCDeUCWLfFYxdzY7E0opnqaXb8JvncQtM44uGawSZy4--0oFZuB3-YrMEYosA5q-W5cEjruirka_pY9qL425gJSkxE-z96Aoz9pZEGoB5uCQIl_xEAn5aRBspRpeaK9rESJCNhP_mi_zv-04EFUulUGaYtoC3E-oaHcC6yhQcFjffn2Fd0oEcyQnRLmXonx3sBfkK22mrxQXquv_QBNTIMaLU0ovUmFjWcuBooBJ_5gPa5Bc_Q==", "id": "rs_0dc9f371a6d55e3f016a137692b3348191b51b58da2b4b0821", "summary": [{"type": "summary_text", "text": "**Considering documentation updates**\n\nI need to update the README and documentation, and then ensure that all tests are complete. But first, I might generate the image asset for the final video. It could be a good idea to mention ChatGPT Image through the Codex, as it relates. After that, I’ll commit everything and add the documentation. This is feeling like a productive plan! I want to make sure everything is in order."}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\\n@@ -35,6 +35,8 @@\\n - `autoshorts.strategy.brand` — TrueTraceShorts brand profile, default descriptions/bios/tags, and brand-fit validation.\\n - `autoshorts.strategy.score` — follower-conversion strategy scoring for hook, curiosity, identity, emotion, trust, follow reason, originality, and variety.\\n - `autoshorts.strategy.series` — public-safe series registry and hard no-go validation before public content advances.\\n+- `autoshorts.rendering.final_video_plan` — final-near 1080x1920 production plans that keep AI visuals text-free and renderer-owned.\\n+- `autoshorts.rendering.motion_renderer` — procedural motion preview renderer for inbox cards, warning routes, and three-path mechanism diagrams before heavier AI-video work.\\n - `autoshorts.rendering.ffmpeg_plan` — side-effect-free FFmpeg concat planning for local preview frames.\\n - `autoshorts.rendering.ffmpeg_renderer` — explicit FFmpeg boundary that writes concat files and MP4 timing previews.\\n - `autoshorts.rendering.local_frame_writer` — deterministic Pillow PNG scene-card writer for local preview plans.\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .md files\"}, \"_warning\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md was modified by sibling subagent '20260524_204754_10d508' but this agent never read it. Read the file before writing to avoid overwriting the sibling's changes.\"}", "tool_call_id": "call_TSPkNK7JtPeNQB0TqPKPN836", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_dTZmBVrK5J1fECIrk0xQbkep", "call_id": "call_dTZmBVrK5J1fECIrk0xQbkep", "response_item_id": "fc_0dc9f371a6d55e3f016a13769ec31481919dccf2fe7b361ecc", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"The first public-facing audio/caption pilot now uses the accessible `weird email` framing: top card, scene captions, subtitles, and voiceover are derived from the final voiceover source instead of mixing old approval-card text with new spoken copy.\\n\\nThe first final-near motion prototype uses a hybrid model: ChatGPT Image/Codex can provide text-free background texture, while `autoshorts.rendering.motion_renderer` owns the actual inbox cards, arrows, labels, captions, and FFmpeg assembly. This keeps generated imagery useful without trusting it to spell or explain anything.\\n\\n## Strategy scoring\",\"old_string\":\"The first public-facing audio/caption pilot now uses the accessible `weird email` framing: top card, scene captions, subtitles, and voiceover are derived from the final voiceover source instead of mixing old approval-card text with new spoken copy.\\n\\n## Strategy scoring\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\\n@@ -86,6 +86,8 @@\\n \\n The first public-facing audio/caption pilot now uses the accessible `weird email` framing: top card, scene captions, subtitles, and voiceover are derived from the final voiceover source instead of mixing old approval-card text with new spoken copy.\\n \\n+The first final-near motion prototype uses a hybrid model: ChatGPT Image/Codex can provide text-free background texture, while `autoshorts.rendering.motion_renderer` owns the actual inbox cards, arrows, labels, captions, and FFmpeg assembly. This keeps generated imagery useful without trusting it to spell or explain anything.\\n+\\n ## Strategy scoring\\n \\n `autoshorts.strategy.score.ContentStrategyScore` evaluates whether a candidate can move beyond generic AI tips and plausibly convert viewers into followers. It scores:\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .md files\"}}", "tool_call_id": "call_dTZmBVrK5J1fECIrk0xQbkep", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_6ZERpAIZOCEsMn9iPKgE16Rf", "call_id": "call_6ZERpAIZOCEsMn9iPKgE16Rf", "response_item_id": "fc_0dc9f371a6d55e3f016a1376a85f60819194b097f2787619ed", "type": "function", "function": {"name": "write_file", "arguments": "{\"content\":\"# Final Motion Prototype Notes\\n\\n## Decision\\n\\nFor the first real TrueTrace video prototype, use a hybrid rendering stack:\\n\\n```text\\nChatGPT Image / Codex image generation → text-free cinematic background texture\\nProcedural motion renderer → all cards, labels, arrows, diagrams, and mechanism text\\nEdgeTTS → voiceover\\nASS/FFmpeg → deterministic subtitle burn-in and final assembly\\n```\\n\\n## Why\\n\\nThe pilot is a mechanism-reveal short, not a cinematic story scene. AI image/video can provide mood and texture, but it must not own:\\n\\n- email text;\\n- path labels;\\n- arrows;\\n- captions;\\n- factual claims;\\n- the three-way workflow mechanism.\\n\\nThose layers stay renderer-owned so the final video remains readable on mobile and does not contain fake/generated UI text.\\n\\n## Current pilot\\n\\nCandidate:\\n\\n```text\\ntruetrace-ai-automation-quiet-rot-38s\\n```\\n\\nFrame sequence:\\n\\n```text\\nclean-demo\\n→ weird-email\\n→ wrong-routing\\n→ three-way-split\\n→ final-rule\\n```\\n\\nCore visual mechanism:\\n\\n```text\\nNormal → Go through\\nUnclear → Review\\nWeird/Risky → Stop\\n```\\n\\n## Generated prototype artifact\\n\\nThe current review artifact is local-only and ignored by Git:\\n\\n```text\\ndata/previews/truetrace-final-motion-v4/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\n```\\n\\nIt uses one ChatGPT Image/Codex-generated text-free background plus deterministic renderer overlays.\\n\\n## Quality notes\\n\\n- The three-way split scene has been visually checked so arrows sit behind labels and subtitles do not critically overlap the mechanism.\\n- The prototype is still a review prototype, not a final public export.\\n- Next polish should improve subtitle phrasing/timing around the three-way split and optionally replace the single static background with per-scene generated backgrounds or short I2V texture clips.\\n\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"bytes_written\": 1808, \"dirs_created\": true, \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .md files\"}}", "tool_call_id": "call_6ZERpAIZOCEsMn9iPKgE16Rf", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_WsozFl5TkuI0lPIHX5KP9GSW", "call_id": "call_WsozFl5TkuI0lPIHX5KP9GSW", "response_item_id": "fc_0dc9f371a6d55e3f016a1376b605c08191baa2a5bf150648dc", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/ -q\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"........................................................................ [ 43%]\\n........................................................................ [ 86%]\\n...................... [100%]\\n166 passed in 33.16s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_WsozFl5TkuI0lPIHX5KP9GSW", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_jPjsO9W4nvyisIXV61wcHYmo", "call_id": "call_jPjsO9W4nvyisIXV61wcHYmo", "response_item_id": "fc_0dc9f371a6d55e3f016a1376de56d08191b9d458b557aacf5f", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"git status --short && git add autoshorts/rendering/final_video_plan.py autoshorts/rendering/motion_renderer.py tests/test_final_video_plan.py tests/test_motion_renderer.py README.md docs/final_motion_prototype.md && git commit -m \\\"feat: add TrueTrace final motion prototype\\\" && git status --short && git log --oneline -5\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"M README.md\\n?? autoshorts/rendering/final_video_plan.py\\n?? autoshorts/rendering/motion_renderer.py\\n?? docs/final_motion_prototype.md\\n?? tests/test_final_video_plan.py\\n?? tests/test_motion_renderer.py\\n[feat/core-approval-quality-gates 14310f9] feat: add TrueTrace final motion prototype\\n 6 files changed, 665 insertions(+)\\n create mode 100644 autoshorts/rendering/final_video_plan.py\\n create mode 100644 autoshorts/rendering/motion_renderer.py\\n create mode 100644 docs/final_motion_prototype.md\\n create mode 100644 tests/test_final_video_plan.py\\n create mode 100644 tests/test_motion_renderer.py\\n14310f9 feat: add TrueTrace final motion prototype\\n7375311 feat: make TrueTrace pilot beginner friendly\\nb9b6423 feat: align TrueTrace voiceover previews\\n3f68001 feat: add EdgeTTS audio caption preview\\n066201d feat: attach audio plans to TrueTrace previews\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_jPjsO9W4nvyisIXV61wcHYmo", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "Erledigt, Sir — ich habe losgelegt und den ersten **richtigen Motion-Prototypen** gebaut, mit ChatGPT Image/Codex als Hintergrund-Quelle statt lokalem Qwen Image.\n\n## Gebaut\n\nNeue Module:\n\n```text\nautoshorts/rendering/final_video_plan.py\nautoshorts/rendering/motion_renderer.py\n```\n\nNeue Tests:\n\n```text\ntests/test_final_video_plan.py\ntests/test_motion_renderer.py\n```\n\nNeue Doku:\n\n```text\ndocs/final_motion_prototype.md\n```\n\nCommit:\n\n```text\n14310f9 feat: add TrueTrace final motion prototype\n```\n\n## Was jetzt neu ist\n\n### 1. FinalVideoPlan\n\nNeues Artefakt:\n\n```python\nFinalVideoPlan\n```\n\nEs definiert die echten Produktionsszenen:\n\n```text\nclean-demo\n→ weird-email\n→ wrong-routing\n→ three-way-split\n→ final-rule\n```\n\nMit:\n\n```text\n1080x1920\n30fps\n37s duration\nrenderer-owned text\nno AI-generated text allowed\n```\n\nWichtig: AI darf nur Hintergrund/Textur liefern. Der Renderer besitzt weiterhin:\n\n```text\nemail text\nlabels\narrows\nworkflow paths\nsubtitles\ncaptions\n```\n\nAlso keine „AI hat Review als Reviwe geschrieben“-Katastrophe. Fortschritt, mit Helm.\n\n---\n\n### 2. ChatGPT Image/Codex als Background-Quelle genutzt\n\nIch habe über `image_generate` / OpenAI Codex ein textfreies vertikales Hintergrundbild erzeugt:\n\n```text\n/home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260524_235629_ac459a00.png\n```\n\nPrompt-Kern:\n\n```text\nmodern AI automation short background,\nclean laptop/workspace,\ndark productivity dashboard glow,\nblue/green accents,\nno readable text,\nno logos,\nempty central space for renderer-owned overlays\n```\n\nDas Bild wird im Motion Renderer als visuelle Textur verwendet. Alle erklärenden Elemente liegen darüber als deterministic overlays.\n\n---\n\n### 3. Procedural Motion Renderer\n\nNeuer Renderer:\n\n```python\nbuild_motion_render_plan()\nrender_motion_preview()\n```\n\nEr erzeugt lokal:\n\n```text\nanimated inbox cards\nweird email card\nwrong-routing warning\nthree-way split diagram\nfinal rule card\n```\n\nMit FFmpeg-Ausgabe:\n\n```text\nmotion-preview.mp4\n```\n\nDann wird wie bisher ergänzt:\n\n```text\nEdgeTTS voiceover\nASS subtitles\nFFmpeg audio+caption burn-in\n```\n\n---\n\n## Neuer Video-Prototyp\n\nFinaler Review Clip:\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-final-motion-v4/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\n\n## Verifiziert\n\n```text\nVideo: h264\nSize: 540x960 review preview\nDuration: 36.833s\nAudio: aac\nAudio duration: 36.864s\n```\n\nSHA256:\n\n```text\n3893b94eabf353e6388d1ca8b1fc06bae19cb216cc98f6b44956739e58853051\n```\n\nFrames gerendert:\n\n```text\n887\n```\n\n## Visuelle QA\n\nIch habe die kritische `three-way-split` Szene extrahiert und visuell geprüft.\n\nFixes gemacht:\n\n- Diagramm weiter nach oben geschoben.\n- Arrows hinter die Labels gelegt.\n- Subtitle-Overlap reduziert.\n- `Normal → Go through`, `Unclear → Review`, `Weird/Risky → Stop` bleibt lesbar.\n\nDie Szene ist jetzt für einen Review-Prototyp brauchbar. Nicht Cannes. Aber klarer als die vorherigen Karten — also bereits ein zivilisatorischer Sprung.\n\n## Tests\n\nFull Suite:\n\n```text\n166 passed in 33.16s\n```\n\n## Architektur jetzt\n\n```text\nFinalVoiceoverScript\n→ FinalVideoPlan\n→ ChatGPT Image text-free background\n→ MotionRenderer procedural overlays\n→ EdgeTTS voiceover\n→ ASS subtitles\n→ FFmpeg final preview\n```\n\n## Wichtig zur Richtung\n\nDas ist jetzt der richtige Ansatz:\n\n```text\nChatGPT Image / Codex:\nMood, background, cinematic texture\n\nRenderer:\nTruth, labels, arrows, captions, mechanism\n\nFFmpeg:\nAssembly, audio, subtitle burn-in\n```\n\nNicht:\n\n```text\nAI soll bitte alles generieren und korrekt buchstabieren\n```\n\nDenn das wäre wieder GPU-Roulette mit Bildungsauftrag.\n\n## Nächster sinnvoller Schritt\n\nJetzt würde ich den Clip **qualitativ polieren**, nicht nochmal Architektur umbauen:\n\n```text\n1. Subtitle phrasing bei der 3-way-split Szene kürzen\n2. Scene-specific ChatGPT Image backgrounds erzeugen:\n - clean demo inbox\n - weird email moment\n - abstract AI route\n - mechanism background\n3. Motion etwas lebendiger machen:\n - subtle zoom\n - card slide timing\n - warning pulse\n - progress/rhythm beats\n4. Danach 1080x1920 final export bauen\n```\n\nDer aktuelle Clip ist der erste echte „richtige Video“-Prototyp: Voice, Captions, Motion, Mechanism und ChatGPT-Image-Textur in einer Pipeline.", "reasoning": "**Reviewing README changes**\n\nI’m noticing that the README file might not be included in my last commit. The commit indicates 6 files changed, suggesting the README wasn't staged, which is a bit puzzling. I need to run `git add README`. However, it looks like it’s not listed in the creations. I want to ensure the final version is concise, includes media, and mentions the ChatGPT image used. I should also refer to the generated background path and test 166.", "reasoning_content": "**Reviewing README changes**\n\nI’m noticing that the README file might not be included in my last commit. The commit indicates 6 files changed, suggesting the README wasn't staged, which is a bit puzzling. I need to run `git add README`. However, it looks like it’s not listed in the creations. I want to ensure the final version is concise, includes media, and mentions the ChatGPT image used. I should also refer to the generated background path and test 166.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3bov_NKIXIiQIa0_ncXB-5rE6xF5QC13IkTWiSIZalPUBOTgumiUvgxA4_PJQ-XU9Oe6KsDqK6qwutbg4ijdQqN5v3NjJP8z1oWu0bbBheYzPJMxwh3avIGLU7TCkGgn59yAGz3biBqq02DeTzPFA2w33cw0rah2gX6UbMf5etruqWuQ4KhnMbdmdOygTrBFwafaDvoSbSq66kolY1-o9VEmtGKhfS6nzoQmfyw4HiFbYBnfIVPNa6dSbbiYfRkqgm_nxlPjFqtHdFljB6O5G6wgYS8AbhqpHTYMrzuoxb6lrHtjdVu9VMOWB8eJuBJsm7rB-iE5UzD6Mt3pggj1PlaU51Od97kucYNtrxjPUnP5s509oUuc1phsKm1iPC88jEt9lTXlRlu3_fF5zklfmC7RxM65NgQ6j9XFcU_wINQk8lIDUEymzrgSmDU2x8CJrfRUCv5wFgkAcGUiiEgJWVJ5t_k9535IiaCOLCNsCbhfqa0KFuEqNkOziGTGzfEp6lPYrVFdAeocrq2myiqaQpG5T_fEOSL5jPqI9ay3ZHAiiKqGd01XA81hT1igRlKkBH6C0SAfVv73Li91KcHXsuWoUzi4CQjCnSz3t26WKPbJM9bKxlozCfku5Vvs314kGJvf7gO9pQmLkx8PNmQiK9QWvFE36ntqUyIf1_BpU4Rs_EbO0IUywxrOqI13omhz4uT8LmP4IAKygMmDLJGDa7jX7oncX-1T9malbj569gqTdfNNTrcLJOI56VT0G1fj-NvLzQGPih3VNyHDyzH2y5MuAd3yoL2JhBGjYqT6o43Nz_h95m8MUiOG6ig875NqF6QGlAOesnJEZxfdyIfWtdq1SngQkwCemL-nCVdRdZl8Bldus5lj5rKBlDUQYNblNWK6brgvC-MNX6uIkaRRbK117YHYTMJSalg1tD0J5nKuFXj6v1-wkgdcDCq2a7mQ8E4Hb8DRtxnSy55A28FOJuJJD36qftpVKikIDpwkCKEHtSMrLd3i5L_17fM7O5C75-HnQkAtCKTVPWyiiJXzcd29oyhLUCIK0Zp2BqJA9-QzLJ0Sxy7TAbDbEVJj3GO2TSYAGXMsE6whFLfeZHUOclgMZpHgPHipE7y6Ooc02Ap1Zvh3pyhjdez_qVQdG1ifldNWy73e9C9DXh8S6jbtss-rGtEmS3wDBA8Hq-3sRPey9KY1dBIl8wTPWfj_iVBPdEQuycgf_NoBruM9v_E4C9QB_xMed3SjyAetc7eVj0qL6mNtjh0ydEja0jcbDRGjm_vMKYzxm52tMCJzIBi8gKbFwlwn1gq6MDL3qEqfeazFYZ9693dHbRzfI_vhhIC1RVsn3wi7HN3RhjMBS7y40dl0xN1Yqbca-Qn2NDcWRxK5D8=", "id": "rs_0dc9f371a6d55e3f016a1376e4d75c8191af0c41339a7fc632", "summary": [{"type": "summary_text", "text": "**Reviewing README changes**\n\nI’m noticing that the README file might not be included in my last commit. The commit indicates 6 files changed, suggesting the README wasn't staged, which is a bit puzzling. I need to run `git add README`. However, it looks like it’s not listed in the creations. I want to ensure the final version is concise, includes media, and mentions the ChatGPT image used. I should also refer to the generated background path and test 166."}]}], "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Erledigt, Sir — ich habe losgelegt und den ersten **richtigen Motion-Prototypen** gebaut, mit ChatGPT Image/Codex als Hintergrund-Quelle statt lokalem Qwen Image.\n\n## Gebaut\n\nNeue Module:\n\n```text\nautoshorts/rendering/final_video_plan.py\nautoshorts/rendering/motion_renderer.py\n```\n\nNeue Tests:\n\n```text\ntests/test_final_video_plan.py\ntests/test_motion_renderer.py\n```\n\nNeue Doku:\n\n```text\ndocs/final_motion_prototype.md\n```\n\nCommit:\n\n```text\n14310f9 feat: add TrueTrace final motion prototype\n```\n\n## Was jetzt neu ist\n\n### 1. FinalVideoPlan\n\nNeues Artefakt:\n\n```python\nFinalVideoPlan\n```\n\nEs definiert die echten Produktionsszenen:\n\n```text\nclean-demo\n→ weird-email\n→ wrong-routing\n→ three-way-split\n→ final-rule\n```\n\nMit:\n\n```text\n1080x1920\n30fps\n37s duration\nrenderer-owned text\nno AI-generated text allowed\n```\n\nWichtig: AI darf nur Hintergrund/Textur liefern. Der Renderer besitzt weiterhin:\n\n```text\nemail text\nlabels\narrows\nworkflow paths\nsubtitles\ncaptions\n```\n\nAlso keine „AI hat Review als Reviwe geschrieben“-Katastrophe. Fortschritt, mit Helm.\n\n---\n\n### 2. ChatGPT Image/Codex als Background-Quelle genutzt\n\nIch habe über `image_generate` / OpenAI Codex ein textfreies vertikales Hintergrundbild erzeugt:\n\n```text\n/home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260524_235629_ac459a00.png\n```\n\nPrompt-Kern:\n\n```text\nmodern AI automation short background,\nclean laptop/workspace,\ndark productivity dashboard glow,\nblue/green accents,\nno readable text,\nno logos,\nempty central space for renderer-owned overlays\n```\n\nDas Bild wird im Motion Renderer als visuelle Textur verwendet. Alle erklärenden Elemente liegen darüber als deterministic overlays.\n\n---\n\n### 3. Procedural Motion Renderer\n\nNeuer Renderer:\n\n```python\nbuild_motion_render_plan()\nrender_motion_preview()\n```\n\nEr erzeugt lokal:\n\n```text\nanimated inbox cards\nweird email card\nwrong-routing warning\nthree-way split diagram\nfinal rule card\n```\n\nMit FFmpeg-Ausgabe:\n\n```text\nmotion-preview.mp4\n```\n\nDann wird wie bisher ergänzt:\n\n```text\nEdgeTTS voiceover\nASS subtitles\nFFmpeg audio+caption burn-in\n```\n\n---\n\n## Neuer Video-Prototyp\n\nFinaler Review Clip:\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-final-motion-v4/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\n\n## Verifiziert\n\n```text\nVideo: h264\nSize: 540x960 review preview\nDuration: 36.833s\nAudio: aac\nAudio duration: 36.864s\n```\n\nSHA256:\n\n```text\n3893b94eabf353e6388d1ca8b1fc06bae19cb216cc98f6b44956739e58853051\n```\n\nFrames gerendert:\n\n```text\n887\n```\n\n## Visuelle QA\n\nIch habe die kritische `three-way-split` Szene extrahiert und visuell geprüft.\n\nFixes gemacht:\n\n- Diagramm weiter nach oben geschoben.\n- Arrows hinter die Labels gelegt.\n- Subtitle-Overlap reduziert.\n- `Normal → Go through`, `Unclear → Review`, `Weird/Risky → Stop` bleibt lesbar.\n\nDie Szene ist jetzt für einen Review-Prototyp brauchbar. Nicht Cannes. Aber klarer als die vorherigen Karten — also bereits ein zivilisatorischer Sprung.\n\n## Tests\n\nFull Suite:\n\n```text\n166 passed in 33.16s\n```\n\n## Architektur jetzt\n\n```text\nFinalVoiceoverScript\n→ FinalVideoPlan\n→ ChatGPT Image text-free background\n→ MotionRenderer procedural overlays\n→ EdgeTTS voiceover\n→ ASS subtitles\n→ FFmpeg final preview\n```\n\n## Wichtig zur Richtung\n\nDas ist jetzt der richtige Ansatz:\n\n```text\nChatGPT Image / Codex:\nMood, background, cinematic texture\n\nRenderer:\nTruth, labels, arrows, captions, mechanism\n\nFFmpeg:\nAssembly, audio, subtitle burn-in\n```\n\nNicht:\n\n```text\nAI soll bitte alles generieren und korrekt buchstabieren\n```\n\nDenn das wäre wieder GPU-Roulette mit Bildungsauftrag.\n\n## Nächster sinnvoller Schritt\n\nJetzt würde ich den Clip **qualitativ polieren**, nicht nochmal Architektur umbauen:\n\n```text\n1. Subtitle phrasing bei der 3-way-split Szene kürzen\n2. Scene-specific ChatGPT Image backgrounds erzeugen:\n - clean demo inbox\n - weird email moment\n - abstract AI route\n - mechanism background\n3. Motion etwas lebendiger machen:\n - subtle zoom\n - card slide timing\n - warning pulse\n - progress/rhythm beats\n4. Danach 1080x1920 final export bauen\n```\n\nDer aktuelle Clip ist der erste echte „richtige Video“-Prototyp: Voice, Captions, Motion, Mechanism und ChatGPT-Image-Textur in einer Pipeline."}], "id": "msg_0dc9f371a6d55e3f016a1376e861c881918cb0246db5e68243", "phase": "final_answer"}], "finish_reason": "stop", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "user", "content": "[M G] Ok, mach weiter.", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_25BOfggRR3MiUmrkU08Ye9E6", "call_id": "call_25BOfggRR3MiUmrkU08Ye9E6", "response_item_id": "fc_0dc9f371a6d55e3f016a13793f4b608191b936cd93834b7890", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"test-driven-development\"}"}}, {"id": "call_EyhGK2DnRjnY8nuBkVGgTrz9", "call_id": "call_EyhGK2DnRjnY8nuBkVGgTrz9", "response_item_id": "fc_0dc9f371a6d55e3f016a13793f4b7881919e7a35b037db8ec7", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"social-media-shorts-automation\"}"}}, {"id": "call_uplnI2qLcfBFjzRMbrFlukOc", "call_id": "call_uplnI2qLcfBFjzRMbrFlukOc", "response_item_id": "fc_0dc9f371a6d55e3f016a13793f4b8481918df1903076ca1476", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\",\"limit\":220}"}}], "finish_reason": "tool_calls", "reasoning": "**Continuing with skills**\n\nI need to keep going and focus on the relevant skills like TDD, social aspects, and image handling. It might be time to act and polish the subtitle phrasing. I should build tests and inspect the subtitles closely, maybe looking at the final preview to ensure they have the right style. I'll be sure to use the necessary tools in the process to make everything come together.", "reasoning_content": "**Continuing with skills**\n\nI need to keep going and focus on the relevant skills like TDD, social aspects, and image handling. It might be time to act and polish the subtitle phrasing. I should build tests and inspect the subtitles closely, maybe looking at the final preview to ensure they have the right style. I'll be sure to use the necessary tools in the process to make everything come together.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3k_bAJx9AS1gxLgikM5L_5UrsrMoQU5w4icQwWL6Q8KMC_qjpqDrlCi8y8u8qoy1lTFoBWUtj_jUbC2GgP4hFittvY1nGdKE5EOaD5FMyHoC0V0ATkMKUswIwUvivwd_fEGEtIWcA63hUjKMDTHLcKFlmxxP3IBnb2HyP_VIoPCn3BEEU0VylGGyjBriAeGrtj9Q9Z0ulv_VNw_ir5GV3LPr-H0nf_U8Cc0iF7bGyItpS16nDfBMl94fERScT8Pa8ujdSe9_P5Am5z8ndhE1s-OW2_YCQ0IXNgrdjS1-PNL39FO3680l-z8s5PiOcAZKywUCv89rdbhacD6n77hD1694f2eAGAiagOi4VD8JL_kWLs1AWgR4-42d9CP0C_L3YINRDGPU1zzTkdMT_tlYy_zCN7rjgo33UYY65xqgBN-FGvHTUzR7BwnKs1Lh-iLe9aA4aY-QiU3y4z-ZZbXZoHzg6fFzjwy3FEM00LfIAzr4ZRhOwV9SiOeLV9ZaDE3kkqcBouIGq6XFjmD2yV3_YGsRfZor5mGyR13jzgbE2ksDBJ7Ytt1YP24vweSIxX7olW7YRE7C9r_OYTAJF665L6US0pEoNUdZEcUiF9sqX8CdyXJlsRmNreY3wLHOzHkjKtYWBMTVShQU1ZdNuqVF4XLc1b-Z927mHEIGXTMsCntvlmJPTfGLATwwRN-1tAcC08lpV646q8awAFlP13xrwtkm4qmq2vogwIUwI-GEBaMiRnoWQd-Y1-AMg-3vM-_8N1f5qDaWLt1qUsgR1InACBku74Dpj9LXi8QUE4P8ayuEyEDr_B6TxmQKdZlregOpU9y2Jtj9zuumEsReMuTyoKNQ8yzqCgOElAlzplWdU52qO2W1eO3YRoA5inYPtjYdL0lJhOlLtvzUt5JHtIPUdMPRi4LfFU8QDLidYbW94-JGvRvJGuHN5lFN7z6l8JWRgknOV3_XQVH6945KgqfYOZVYSfl0i2qvsKMsUFL2DEOyx3UEk62BsIkOSWrt-cUAB5oqOPTFHuifX6E_l5ndH5vcF6QBiZetrMRN4sSKqRRKz17HppLDCm2G6GBSTJGxvs2gSARUqjp4DK6rWhYCg4StIUMnjjPn2Yfn0KLmi2E0PEb4SLoaImJKpbYtViT1ur9_dNj1Mygh1tpyVnaQpdjijhcDiDhgCkC9iBjjXwTDh4=", "id": "rs_0dc9f371a6d55e3f016a13793c86688191ad62a47d75940d8d", "summary": [{"type": "summary_text", "text": "**Continuing with skills**\n\nI need to keep going and focus on the relevant skills like TDD, social aspects, and image handling. It might be time to act and polish the subtitle phrasing. I should build tests and inspect the subtitles closely, maybe looking at the final preview to ensure they have the right style. I'll be sure to use the necessary tools in the process to make everything come together."}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"name\": \"test-driven-development\", \"description\": \"TDD: enforce RED-GREEN-REFACTOR, tests before code.\", \"tags\": [\"testing\", \"tdd\", \"development\", \"quality\", \"red-green-refactor\"], \"related_skills\": [\"systematic-debugging\", \"writing-plans\", \"subagent-driven-development\"], \"content\": \"---\\nname: test-driven-development\\ndescription: \\\"TDD: enforce RED-GREEN-REFACTOR, tests before code.\\\"\\nversion: 1.1.0\\nauthor: Hermes Agent (adapted from obra/superpowers)\\nlicense: MIT\\nplatforms: [linux, macos, windows]\\nmetadata:\\n hermes:\\n tags: [testing, tdd, development, quality, red-green-refactor]\\n related_skills: [systematic-debugging, writing-plans, subagent-driven-development]\\n---\\n\\n# Test-Driven Development (TDD)\\n\\n## Overview\\n\\nWrite the test first. Watch it fail. Write minimal code to pass.\\n\\n**Core principle:** If you didn't watch the test fail, you don't know if it tests the right thing.\\n\\n**Violating the letter of the rules is violating the spirit of the rules.**\\n\\n## When to Use\\n\\n**Always:**\\n- New features\\n- Bug fixes\\n- Refactoring\\n- Behavior changes\\n\\n**Exceptions (ask the user first):**\\n- Throwaway prototypes\\n- Generated code\\n- Configuration files\\n\\nThinking \\\"skip TDD just this once\\\"? Stop. That's rationalization.\\n\\n## The Iron Law\\n\\n```\\nNO PRODUCTION CODE WITHOUT A FAILING TEST FIRST\\n```\\n\\nWrite code before the test? Delete it. Start over.\\n\\n**No exceptions:**\\n- Don't keep it as \\\"reference\\\"\\n- Don't \\\"adapt\\\" it while writing tests\\n- Don't look at it\\n- Delete means delete\\n\\nImplement fresh from tests. Period.\\n\\n## Red-Green-Refactor Cycle\\n\\n### RED — Write Failing Test\\n\\nWrite one minimal test showing what should happen.\\n\\n**Good test:**\\n```python\\ndef test_retries_failed_operations_3_times():\\n attempts = 0\\n def operation():\\n nonlocal attempts\\n attempts += 1\\n if attempts < 3:\\n raise Exception('fail')\\n return 'success'\\n\\n result = retry_operation(operation)\\n\\n assert result == 'success'\\n assert attempts == 3\\n```\\nClear name, tests real behavior, one thing.\\n\\n**Bad test:**\\n```python\\ndef test_retry_works():\\n mock = MagicMock()\\n mock.side_effect = [Exception(), Exception(), 'success']\\n result = retry_operation(mock)\\n assert result == 'success' # What about retry count? Timing?\\n```\\nVague name, tests mock not real code.\\n\\n**Requirements:**\\n- One behavior per test\\n- Clear descriptive name (\\\"and\\\" in name? Split it)\\n- Real code, not mocks (unless truly unavoidable)\\n- Name describes behavior, not implementation\\n\\n### Verify RED — Watch It Fail\\n\\n**MANDATORY. Never skip.**\\n\\n```bash\\n# Use terminal tool to run the specific test\\npytest tests/test_feature.py::test_specific_behavior -v\\n```\\n\\nConfirm:\\n- Test fails (not errors from typos)\\n- Failure message is expected\\n- Fails because the feature is missing\\n\\n**Test passes immediately?** You're testing existing behavior. Fix the test.\\n\\n**Test errors?** Fix the error, re-run until it fails correctly.\\n\\n### GREEN — Minimal Code\\n\\nWrite the simplest code to pass the test. Nothing more.\\n\\n**Good:**\\n```python\\ndef add(a, b):\\n return a + b # Nothing extra\\n```\\n\\n**Bad:**\\n```python\\ndef add(a, b):\\n result = a + b\\n logging.info(f\\\"Adding {a} + {b} = {result}\\\") # Extra!\\n return result\\n```\\n\\nDon't add features, refactor other code, or \\\"improve\\\" beyond the test.\\n\\n**Cheating is OK in GREEN:**\\n- Hardcode return values\\n- Copy-paste\\n- Duplicate code\\n- Skip edge cases\\n\\nWe'll fix it in REFACTOR.\\n\\n### Verify GREEN — Watch It Pass\\n\\n**MANDATORY.**\\n\\n```bash\\n# Run the specific test\\npytest tests/test_feature.py::test_specific_behavior -v\\n\\n# Then run ALL tests to check for regressions\\npytest tests/ -q\\n```\\n\\nConfirm:\\n- Test passes\\n- Other tests still pass\\n- Output pristine (no errors, warnings)\\n\\n**Test fails?** Fix the code, not the test.\\n\\n**Other tests fail?** Fix regressions now.\\n\\n### REFACTOR — Clean Up\\n\\nAfter green only:\\n- Remove duplication\\n- Improve names\\n- Extract helpers\\n- Simplify expressions\\n\\nKeep tests green throughout. Don't add behavior.\\n\\n**If tests fail during refactor:** Undo immediately. Take smaller steps.\\n\\n### Repeat\\n\\nNext failing test for next behavior. One cycle at a time.\\n\\n## Why Order Matters\\n\\n**\\\"I'll write tests after to verify it works\\\"**\\n\\nTests written after code pass immediately. Passing immediately proves nothing:\\n- Might test the wrong thing\\n- Might test implementation, not behavior\\n- Might miss edge cases you forgot\\n- You never saw it catch the bug\\n\\nTest-first forces you to see the test fail, proving it actually tests something.\\n\\n**\\\"I already manually tested all the edge cases\\\"**\\n\\nManual testing is ad-hoc. You think you tested everything but:\\n- No record of what you tested\\n- Can't re-run when code changes\\n- Easy to forget cases under pressure\\n- \\\"It worked when I tried it\\\" ≠ comprehensive\\n\\nAutomated tests are systematic. They run the same way every time.\\n\\n**\\\"Deleting X hours of work is wasteful\\\"**\\n\\nSunk cost fallacy. The time is already gone. Your choice now:\\n- Delete and rewrite with TDD (high confidence)\\n- Keep it and add tests after (low confidence, likely bugs)\\n\\nThe \\\"waste\\\" is keeping code you can't trust.\\n\\n**\\\"TDD is dogmatic, being pragmatic means adapting\\\"**\\n\\nTDD IS pragmatic:\\n- Finds bugs before commit (faster than debugging after)\\n- Prevents regressions (tests catch breaks immediately)\\n- Documents behavior (tests show how to use code)\\n- Enables refactoring (change freely, tests catch breaks)\\n\\n\\\"Pragmatic\\\" shortcuts = debugging in production = slower.\\n\\n**\\\"Tests after achieve the same goals — it's spirit not ritual\\\"**\\n\\nNo. Tests-after answer \\\"What does this do?\\\" Tests-first answer \\\"What should this do?\\\"\\n\\nTests-after are biased by your implementation. You test what you built, not what's required. Tests-first force edge case discovery before implementing.\\n\\n## Common Rationalizations\\n\\n| Excuse | Reality |\\n|--------|---------|\\n| \\\"Too simple to test\\\" | Simple code breaks. Test takes 30 seconds. |\\n| \\\"I'll test after\\\" | Tests passing immediately prove nothing. |\\n| \\\"Tests after achieve same goals\\\" | Tests-after = \\\"what does this do?\\\" Tests-first = \\\"what should this do?\\\" |\\n| \\\"Already manually tested\\\" | Ad-hoc ≠ systematic. No record, can't re-run. |\\n| \\\"Deleting X hours is wasteful\\\" | Sunk cost fallacy. Keeping unverified code is technical debt. |\\n| \\\"Keep as reference, write tests first\\\" | You'll adapt it. That's testing after. Delete means delete. |\\n| \\\"Need to explore first\\\" | Fine. Throw away exploration, start with TDD. |\\n| \\\"Test hard = design unclear\\\" | Listen to the test. Hard to test = hard to use. |\\n| \\\"TDD will slow me down\\\" | TDD faster than debugging. Pragmatic = test-first. |\\n| \\\"Manual test faster\\\" | Manual doesn't prove edge cases. You'll re-test every change. |\\n| \\\"Existing code has no tests\\\" | You're improving it. Add tests for the code you touch. |\\n\\n## Red Flags — STOP and Start Over\\n\\nIf you catch yourself doing any of these, delete the code and restart with TDD:\\n\\n- Code before test\\n- Test after implementation\\n- Test passes immediately on first run\\n- Can't explain why test failed\\n- Tests added \\\"later\\\"\\n- Rationalizing \\\"just this once\\\"\\n- \\\"I already manually tested it\\\"\\n- \\\"Tests after achieve the same purpose\\\"\\n- \\\"Keep as reference\\\" or \\\"adapt existing code\\\"\\n- \\\"Already spent X hours, deleting is wasteful\\\"\\n- \\\"TDD is dogmatic, I'm being pragmatic\\\"\\n- \\\"This is different because...\\\"\\n\\n**All of these mean: Delete code. Start over with TDD.**\\n\\n## Verification Checklist\\n\\nBefore marking work complete:\\n\\n- [ ] Every new function/method has a test\\n- [ ] Watched each test fail before implementing\\n- [ ] Each test failed for expected reason (feature missing, not typo)\\n- [ ] Wrote minimal code to pass each test\\n- [ ] All tests pass\\n- [ ] Output pristine (no errors, warnings)\\n- [ ] Tests use real code (mocks only if unavoidable)\\n- [ ] Edge cases and errors covered\\n\\nCan't check all boxes? You skipped TDD. Start over.\\n\\n## When Stuck\\n\\n| Problem | Solution |\\n|---------|----------|\\n| Don't know how to test | Write the wished-for API. Write the assertion first. Ask the user. |\\n| Test too complicated | Design too complicated. Simplify the interface. |\\n| Must mock everything | Code too coupled. Use dependency injection. |\\n| Test setup huge | Extract helpers. Still complex? Simplify the design. |\\n\\n## Hermes Agent Integration\\n\\n### Running Tests\\n\\nUse the `terminal` tool to run tests at each step:\\n\\n```python\\n# RED — verify failure\\nterminal(\\\"pytest tests/test_feature.py::test_name -v\\\")\\n\\n# GREEN — verify pass\\nterminal(\\\"pytest tests/test_feature.py::test_name -v\\\")\\n\\n# Full suite — verify no regressions\\nterminal(\\\"pytest tests/ -q\\\")\\n```\\n\\n### CLI Entry Points\\n\\nFor new `python -m package.cli.command` style entry points, keep the TDD loop boring and side-effect free:\\n\\n1. Write a test that imports `main` from the missing CLI module and calls `main([])`.\\n2. Capture stdout/stderr with the project test framework (`capsys` in pytest) or inject a `stdout` file-like object if supported.\\n3. RED should usually be an import failure for the missing CLI module/package, not a vague end-to-end shell failure.\\n4. Implement `main(argv: Sequence[str] | None = None, *, stdout: TextIO | None = None) -> int` so tests can call it without spawning a subprocess.\\n5. Add the `if __name__ == \\\"__main__\\\": raise SystemExit(main())` guard only after the callable path is green.\\n6. Verify both the unit test and the real module invocation, e.g. `python -m package.cli.command`, before committing.\\n\\nThis catches command wiring while avoiding accidental network calls, publishing actions, or other theatrical nonsense masquerading as a CLI test.\\n\\n### With delegate_task\\n\\nWhen dispatching subagents for implementation, enforce TDD in the goal:\\n\\n```python\\ndelegate_task(\\n goal=\\\"Implement [feature] using strict TDD\\\",\\n context=\\\"\\\"\\\"\\n Follow test-driven-development skill:\\n 1. Write failing test FIRST\\n 2. Run test to verify it fails\\n 3. Write minimal code to pass\\n 4. Run test to verify it passes\\n 5. Refactor if needed\\n 6. Commit\\n\\n Project test command: pytest tests/ -q\\n Project structure: [describe relevant files]\\n \\\"\\\"\\\",\\n toolsets=['terminal', 'file']\\n)\\n```\\n\\n### With systematic-debugging\\n\\nBug found? Write failing test reproducing it. Follow TDD cycle. The test proves the fix and prevents regression.\\n\\nNever fix bugs without a test.\\n\\n## Demo / Fixture Features\\n\\nWhen adding a deterministic demo fixture for later integration wiring, still use RED-GREEN-REFACTOR. Write the wished-for import/API in the test first, verify the missing module/API failure, then implement the smallest fixture that proves the real workflow path. Assert stable IDs/order, bucket counts/classifications, and safety invariants such as review text not implying publication. See `references/deterministic-demo-fixtures.md` for the concise pattern.\\n\\n## Side-Effect-Free Integration Boundaries\\n\\nWhen building toward an external integration (Telegram, email, publishing APIs, render farms, payment flows, etc.), add a tested preparation boundary before any real I/O:\\n\\n1. Write the wished-for pure function in the test first, e.g. `prepare_review_delivery(text) -> DeliveryPlan`.\\n2. RED should be a missing module/API or missing validation failure, not a real network/send failure.\\n3. The GREEN implementation should return a typed/dataclass plan object with explicit metadata: destination/topic, delivery type, human-approval requirement, and `side_effects=()`.\\n4. Validate safety constraints at the boundary: non-empty content, platform size limits, no forbidden action language, no implicit approval, no credentials or generated media unless explicitly expected.\\n5. Add a demo CLI only after the pure boundary is green. The CLI should print metadata first, then payload, and still perform no external I/O.\\n6. Verify both the unit tests and a real `python -m package.cli.demo_*` invocation before committing.\\n\\nThis pattern lets later sending/rendering/publishing adapters consume a boring, audited object instead of smuggling side effects into formatting code. Boring is how we avoid building a content catapult with a moustache.\\n\\n### Media / Rendering Pipeline Boundaries\\n\\nWhen building toward image/video generation or renderer integration, add deterministic planning artifacts before any GPU/API work:\\n\\n1. Write tests for the wished-for pure API first, e.g. `create_shot_plan(script)`, `build_render_manifest(plan)`, `build_local_preview_plan(manifest)`, or `build_ffmpeg_concat_plan(plan, frames, output_path)`.\\n2. RED should be a missing module/API or missing validation behavior — never a failed ComfyUI/Wan/Qwen/API invocation.\\n3. Keep each stage inspectable and side-effect-free until the explicit adapter layer: `ScriptDraft -> ShotPlan -> RenderManifest -> PreviewPlan/PreviewArtifact -> renderer adapter`.\\n4. Assert stable IDs/order, scene counts, timing continuity, vertical settings (`1080x1920`, `30fps` when building Shorts/Reels/TikTok), reduced preview settings (`540x960`, `24fps` when building fast local timing previews), and placeholder/runtime paths before generating media.\\n5. Add guardrail tests that reject static slideshows, baked-in/generated text inside assets, non-renderer-owned captions/labels, unsafe render settings, missing fields, bad timings, non-PNG frame paths, non-MP4 output paths, and mismatched frame counts.\\n6. Split artifact-writing/rendering into explicit boundaries after the pure plans are green: frame writer returns `side_effects=(\\\"write_png\\\",)`, concat planning remains side-effect-free, and the FFmpeg renderer returns `side_effects=(\\\"write_concat\\\", \\\"call_ffmpeg\\\", \\\"write_mp4\\\")` plus `external_calls=(\\\"ffmpeg\\\",)`.\\n7. Only after the manifest/preview boundary is green should a later adapter call local GPU tools or external services. Planning first; GPU roulette later.\\n\\nThis prevents wasting render time on unclear direction and keeps expensive media generation behind a small, audited boundary.\\n\\n### Approval-First Media/Social Pipelines\\n\\nWhen a feature crosses from content planning toward media/social delivery, prefer many small RED-GREEN-README-COMMIT slices instead of one large integration jump:\\n\\n1. typed artifact/model (`SocialMediaDraft`, `RenderManifest`, etc.)\\n2. renderer/formatter for human review text\\n3. side-effect-free delivery/preparation boundary\\n4. demo CLI that prints metadata first, then payload\\n\\nFor each slice, write the missing import/API test first, verify the expected import/API failure, implement only that slice, run the focused test, run the full suite, update docs, and commit. Keep invariant tests explicit: `requires_human_approval=True`, `side_effects=()`, no external calls, no credential access, no file writes unless that adapter is the explicit feature, and no accidental action language such as `publish`/`post` in review/delivery text.\\n\\nThis staged approach keeps approval semantics auditable and prevents a later renderer, Telegram sender, or platform adapter from being smuggled into formatting code.\\n\\n## Testing Anti-Patterns\\n\\n- **Testing mock behavior instead of real behavior** — mocks should verify interactions, not replace the system under test\\n- **Testing implementation details** — test behavior/results, not internal method calls\\n- **Happy path only** — always test edge cases, errors, and boundaries\\n- **Brittle tests** — tests should verify behavior, not structure; refactoring shouldn't break them\\n- **Substring sentinels that collide with generated IDs** — when asserting that amounts or fixture values are excluded from a result, assert the full formatted token (e.g. `999.00`) or a typed field, not a short substring like `999` that can appear inside UUIDs/hash-like IDs.\\n- **Domain classes named `Test*` trigger pytest collection warnings** — if a production dataclass/model must be named like `TestBatch`, set `__test__ = False` on the class or choose a non-`Test` prefix. Keep the fix in production code when the name is part of the domain language, and verify the warning is gone before committing.\\n- **Defaulting with `x or default` hides invalid explicit inputs** — when a factory/test helper accepts optional overrides, use `x if x is not None else default` so tests can pass intentionally blank strings (`\\\"\\\"`) or zero values and watch validation reject them. Otherwise invalid-input tests may silently receive defaults and give false confidence.\\n\\n## Final Rule\\n\\n```\\nProduction code → test exists and failed first\\nOtherwise → not TDD\\n```\\n\\nNo exceptions without the user's explicit permission.\\n\", \"path\": \"software-development/test-driven-development/SKILL.md\", \"skill_dir\": \"/home/agent/.hermes/skills/software-development/test-driven-development\", \"linked_files\": {\"references\": [\"references/deterministic-demo-fixtures.md\", \"references/side-effect-free-delivery-boundaries.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"hermes\": {\"tags\": [\"testing\", \"tdd\", \"development\", \"quality\", \"red-green-refactor\"], \"related_skills\": [\"systematic-debugging\", \"writing-plans\", \"subagent-driven-development\"]}}}", "tool_call_id": "call_25BOfggRR3MiUmrkU08Ye9E6", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"name\": \"social-media-shorts-automation\", \"description\": \"Design, generate, review, publish, and optimize automated short-form social videos across YouTube Shorts, TikTok, Instagram Reels, and related channels.\", \"tags\": [\"shorts\", \"tiktok\", \"youtube-shorts\", \"reels\", \"creator-monetization\", \"content-automation\", \"social-media\"], \"related_skills\": [], \"content\": \"---\\nname: social-media-shorts-automation\\ndescription: Design, generate, review, publish, and optimize automated short-form social videos across YouTube Shorts, TikTok, Instagram Reels, and related channels.\\nversion: 1.0.0\\ntags: [shorts, tiktok, youtube-shorts, reels, creator-monetization, content-automation, social-media]\\n---\\n\\n# Social-Media Shorts Automation\\n\\nUse this skill when building or operating systems that generate short-form social videos, especially faceless or semi-automated pipelines for YouTube Shorts, TikTok, Instagram Reels, Facebook Reels, Pinterest video pins, X video, or LinkedIn video.\\n\\n## Core principle\\n\\nTreat the system as a **Shorts Growth Engine** / **semi-automatic Retention Studio**, not merely a renderer. A working video generator can still fail if it produces generic, low-retention, AI-slop content. Optimize for audience identity, hook quality, retention mechanics, visual mechanism reveals, platform fit, and analytics feedback. For the user's strongest strategic direction, see `references/retention-studio-strategy.md`.\\n\\nFor this user's AutoShorts workflows, approval previews should be German for concept comprehension, while final social-media videos should remain English unless explicitly changed. Treat preview legibility as a quality gate: readable font sizes, pixel-width-aware line wrapping, no clipped words, and no overcrowded cards.\\n\\n## Retention-Studio / Mechanism-Reveal Pipeline\\n\\nFor quality-first automated Shorts, especially Hidden Money & AI Systems concepts, prefer the pipeline documented in `references/retention-studio-pipeline-pattern.md`:\\n\\n```text\\nstrategy → scored ideas → mechanism explainer → shot plan → keyframe/I2V prompt plan → seeded clip jobs → clip review → deterministic final renderer\\n```\\n\\nWhen implementing a new repo or core pipeline, first scaffold the approval-first typed artifact chain in `references/approval-first-retention-studio-core.md`:\\n\\n```text\\nContentPillar → ContentBrief → ScriptDraft → VideoCandidate → TestBatch → ReviewBatch → Telegram ReviewDelivery → ShotPlan\\n```\\n\\nHard rule for this class: AI-video clips provide photorealistic texture and motion only. Captions, numbers, labels, arrows, UI text, price/risk/margin layers, and factual claims are renderer-owned. Final content should keep `static_card_limit = 0`, use visual changes every 1–2 seconds, and reject technically successful clips that do not serve the retention beat.\\n\\nBefore video generation, build an inspectable content-to-review spine: `ContentBrief → ScriptDraft → CandidateDraft → VideoCandidate → TestBatch → ReviewBatch → Telegram ReviewDelivery`. Keep it deterministic, side-effect free, and human-approval-first so hooks, retention beats, visual concepts, policy notes, and review copy can be optimized before spending GPU/API time. See `references/content-to-review-pipeline.md` for the implementation pattern and guardrails.\\n\\nHard rule for this class: AI-video clips provide photorealistic texture and motion only. Captions, numbers, labels, arrows, UI text, price/risk/margin layers, and factual claims are renderer-owned. Final content should keep `static_card_limit = 0`, use visual changes every 1–2 seconds, and reject technically successful clips that do not serve the retention beat.\\n\\n## Recommended workflow\\n\\n1. **Define channel position**\\n - Niche(s): e.g. life optimization, AI life systems, Christian faith/FaithTok.\\n - Target audience and emotional problem.\\n - Language and tone.\\n - Whether the brand is faceless, AI-persona-led, or creator-led.\\n - No-go topics and theological/ethical boundaries if faith-related.\\n\\n2. **Generate test ideas before code-heavy automation**\\n - Create 20–30 candidate ideas across 2–4 content pillars.\\n - For each: hook, script kernel, visual concept, caption, CTA, risk/quality score.\\n - Select a small first batch (e.g. 3 per pillar) for real testing.\\n - Before renderers or external AI APIs, add a deterministic content-development core: `ContentPillar → ContentBrief → ScriptDraft → CandidateDraft → VideoCandidate`. See `references/content-development-core.md`.\\n\\n3. **Use hook-first, retention-led scripting**\\n - First 1–2 seconds must contain a clear tension, identity statement, pain point, contrarian line, or immediate self-recognition.\\n - Prefer one idea per video over generic “4 tips” unless the list format is the explicit series.\\n - Avoid generic advice viewers have already heard unless framed with a new angle, concrete payoff, or strong story.\\n - Reward hooks with direct address, specificity, open loops, tension, and a visible payoff; reject slow intros such as “In this video...”.\\n - See `references/retention-led-shorts.md` for scoring signals, penalties, and voiceover finalization rules.\\n\\n4. **Quality gate before rendering**\\n Score drafts on:\\n - hook strength\\n - novelty\\n - emotional pull\\n - clarity\\n - retention risk\\n - comment/share potential\\n - AI-slop risk\\n - platform/policy risk\\n Render only drafts above the chosen threshold, e.g. 8/10.\\n\\n5. **Visual strategy**\\n - Avoid obvious AI artifacts, fake UI text, illegible generated lettering, generic charts, and soulless stock visuals.\\n - Prefer high-contrast kinetic captions, visible hook text in first seconds, relatable B-roll, screen recordings for AI/tutorial content, phone/screen close-ups, before/after transformations, cards, and timer visuals.\\n - Use pattern interrupts every 2–3 seconds for retention.\\n - Before rendering, generate a shot plan from the finalized voiceover: first-frame hook, pattern interrupt, core explanation, screen/card visual, CTA, caption beats, and asset type.\\n - Before writing a renderer, convert shot plans into deterministic render manifests: machine-readable timeline items, asset placeholders, caption tracks, style constraints, and approval constraints. See `references/render-manifest-pipeline.md`.\\n - Treat this as a deterministic intermediate artifact, not optional prose. See `references/retention-render-planning.md` for the five-scene shot-plan pattern and renderer-facing fields.\\n - For the first video output, build a manifest-driven preview renderer before any AI-video or polished asset pipeline: first create a side-effect-free local preview plan, then write deterministic PNG scene cards, then build a side-effect-free FFmpeg concat plan, and only then call FFmpeg from an explicit renderer boundary. The boundary should report side effects such as `write_png`, `write_concat`, `call_ffmpeg`, and `write_mp4`; keep generated PNG/MP4 artifacts out of Git. See `references/manifest-preview-renderer.md`.\\n - When the user rejects static/slideshow output, add an `asset_plan.v2` layer that maps each scene to motion-led local asset modes such as `cinematic_ai_video`, `screen_recording_simulation`, `mechanism_animation`, or `kinetic_text_overlay` with no baked text. If the user requires a free workflow, do not depend on paid video-credit tools; use local procedural motion and optional free NVIDIA LLM text refinement. See `references/ai-video-asset-planning.md`.\\n - For hybrid workflows, add an imported-clip assembly layer: provider handoff prompts create short manual AI-video clips, humans drop them into deterministic `data/imported_ai_clips//scene_XX.mp4` paths, and the final renderer combines imported clips with local mechanism animations/captions. See `references/imported-ai-clip-assembly.md`.\\n - For local Wan2.2 quality workflows, prefer keyframe/image-to-video over raw text-to-video: generate/select a clean keyframe, run native Wan2.2 I2V variants, review clips bluntly for subject clarity/motion/artifacts, then add all labels/numbers/captions via deterministic renderer. See `references/wan-i2v-retention-studio.md`.\\n - When using NVIDIA Build/API Catalog for keyframes, prefer hosted `ai.api.nvidia.com` calls before considering self-hosted NIM deployment; implement a configurable model fallback chain, store the key as a runtime secret, and inspect/clean logos, emblems, license plates, and fake text before I2V. See `references/nvidia-keyframe-generation.md`.\\n\\n6. **Social-media draft and content-preview approval packages before TTS/rendering polish**\\n - Before TTS, platform APIs, or polished video generation, build a typed `SocialMediaDraft` from the approved candidate plus render manifest/preview.\\n - Include platform targets, title variants, caption, hashtags, CTA, hook, duration, quality/risk summary, and preview reference.\\n - Render this into a Telegram-safe approval message and wrap it in a side-effect-free delivery plan with `requires_human_approval=True` and `side_effects=()`.\\n - After a local MP4 timing preview exists, combine the MP4 path plus social draft review into a side-effect-free content preview approval package. This package should carry `approval_language=de`, `final_video_language=en`, explicit approval commands, no external calls, and no side effects.\\n - Add local demo CLIs that print metadata first, then review text; draft-only CLIs must not write files, call renderers, call Telegram, or access credentials. MP4 preview CLIs may write local artifacts and call FFmpeg only at explicit renderer boundaries that report side effects.\\n - See `references/social-draft-approval-package.md` and `references/content-automation-patterns.md` for concrete artifact sequence, user-specific language rules, and external workflow patterns.\\n\\n7. **Human approval loop before posting**\\n - Send preview to the user through the requested channel, usually Telegram.\\n - Include: video or preview reference, title, caption, hashtags, platform recommendation, duration, quality/risk score.\\n - When sending multiple preview videos, verify and label distinct artifacts before delivery: candidate ID/title, absolute path, duration, and preferably checksum/hash. If several previews are visually similar timing cards, do not spam them as separate unlabeled media; send a concise indexed list first or bundle with clear labels so the user can tell them apart.\\n - Wait for explicit approval such as `Freigabe alle`, `Freigabe YouTube`, `Freigabe TikTok`, `Ablehnen`, or `Ändern: ...`.\\n - Do not publish automatically unless the user has explicitly authorized that workflow.\\n\\n8. **TTS / voice layer after draft approval**\\n - Treat TTS as a later layer, not the starting point for a first post draft.\\n - Decide voice, final voiceover script, words-per-second, scene timing, caption sync, audio format, provider, and separate voice approval only after the social draft package is reviewable.\\n - This avoids spending TTS/rendering effort on unapproved hooks, captions, or platform positioning.\\n - For final-near previews, keep one copy source of truth: final voiceover → script draft/retention beats → shot plan → top card text → scene captions → subtitle track → TTS audio. Do not mix old approval-card text with new spoken/subtitle text.\\n - If the user says the result is too abstract/abgehoben, rewrite around a concrete beginner-friendly everyday failure example before polishing visuals. Prefer “one weird email arrives” / missing field / unclear request / wrong confident action over jargon such as `exception path`, `input boundary`, or `output standard`. See `references/beginner-friendly-audio-caption-alignment.md`.\\n\\n9. **Publish and measure**\\n Track at minimum:\\n - platform, video id/url, niche, format, hook, duration\\n - views at 2h/24h/7d\\n - likes, comments, shares, saves, follows\\n - retention metrics if available\\n Use results to generate the next batch.\\n\\n## Platform duration/monetization notes\\n\\nSee `references/preview-media-delivery-guardrails.md` for avoiding duplicate-looking/unlabeled preview-video spam in Telegram review workflows.\\n\\nSee `references/audio-caption-preview-pipeline.md` for the approval-first EdgeTTS + ASS subtitles + FFmpeg review-MP4 pipeline, including actual-audio-duration probing and the explicit `preserve_video` vs `trim_to_audio` duration-mode guardrail.\\n\\nSee `references/final-motion-hybrid-rendering.md` for the final-near hybrid renderer pattern: ChatGPT Image/Codex or other AI tools provide text-free background/keyframe texture while deterministic renderer overlays own text, arrows, labels, captions, and final assembly.\\n\\nSee `references/monetization-and-approval-notes.md` for current working notes captured from official YouTube/TikTok docs and the recommended approval/posting setup. See `references/retention-led-shorts.md` for retention scoring signals, no-faith/adjacent-pillar handling, and voiceover finalization rules. See `references/render-manifest-pipeline.md` for the script → shot plan → render manifest → renderer sequence that prevents generic AI slideshow output. See `references/manifest-preview-renderer.md` for the first deterministic Pillow/FFmpeg preview-renderer pattern. See `references/local-preview-frame-writer.md` for the staged `LocalPreviewPlan → PNG scene cards → FFmpeg concat plan` boundary before MP4 rendering. See `references/social-draft-approval-package.md` for the typed first-post approval package to build before TTS or platform APIs. See `references/content-automation-patterns.md` for public workflow patterns, queue/status/cost tracking, versioned approval, synthetic-content disclosure, originality gates, and the user's German-preview/English-final rule. See `references/ai-video-asset-planning.md` for motion-led final-render asset planning with Kling/Hailuo/Runway-style clips and screen simulations. See `references/imported-ai-clip-assembly.md` for hybrid assembly where manually generated provider clips are imported into a deterministic local renderer. See `references/nvidia-keyframe-generation.md` for NVIDIA-hosted keyframe generation, model fallback, secret handling, and pre-I2V logo/plate cleanup. Re-check official docs before making business-critical decisions because platform programs change often.\\n\\n## Project/repo hygiene for automated video bots\\n\\n- Keep source code in Git; keep generated videos, assets, `.env`, OAuth tokens, API keys, and downloaded secrets out of Git.\\n- Use `.gitignore` aggressively for outputs, media caches, local credentials, and temp files.\\n- Store platform credentials as runtime secrets; never print raw tokens.\\n- Build the repo as modular components: idea generation, scripting, rendering, review, publishing, analytics.\\n- For approval-first Retention Studio implementations, use a typed side-effect-free core before real I/O: `ContentBrief`, `ScriptDraft`, `VideoCandidate`, review batches, Telegram delivery plans, then shot plans. See `references/approval-first-retention-studio-core.md`.\\n\\n## Sensitive-content positioning\\n\\nWhen AI/productivity automation is the primary brand, be cautious about mixing in religious/FaithTok, health, finance, or other high-trust themes. If the user flags the combination as sensitive, pause that pillar rather than forcing it into the same testbatch. Replace it with a safer adjacent pillar (for example `attention_design`) and document the paused pillar in config so it can be revisited only with explicit approval and a separate brand strategy.\\n\\n## Pitfalls\\n\\n- Do not send several generated preview videos as unlabeled media attachments just because they are distinct files. Telegram/mobile previews can make timing-card MP4s look identical. Verify uniqueness (path + title + hash/duration) and provide labels or an indexed summary; if the user complains about duplicate-looking media, stop resending, verify artifacts, and continue the pipeline.\\n- Do not let final-near preview layers drift apart: if the top field, voiceover, and subtitles do not say the same thing, rebuild the render plan from one final script source before sending another clip.\\n- Do not make broad-audience AI-system shorts sound like architecture lectures. For early-AI users, convert abstract workflow concepts into concrete everyday failures first, then reveal the principle.\\n- Do not over-optimize renderer quality before testing whether the content format earns retention.\\n- Do not let German approval previews become unreadable technical cards: use pixel-width-aware wrapping, readable fonts, limited line counts, and visual checks for clipped/overcrowded text.\\n- Do not confuse approval language with final audience language. For this user, approval previews are German by default; final social videos remain English unless explicitly changed.\\n- Do not copy public automation workflows wholesale: keep their queue/status/cost tracking and template structure, but remove blind auto-publishing until a human approval/version lock exists.\\n- Do not mass-generate repetitive shorts without originality/inauthentic-content gates; this can harm monetization/account health and create AI slop.\\n- Do not jump directly from a script idea to ComfyUI/Wan/Qwen/Image/video generation. First build and inspect the content-to-review spine so weak hooks, generic scripts, policy issues, and static visual concepts are killed before render time.\\n- Do not create a parallel candidate path for content experiments; convert content artifacts into the existing candidate factory input so IDs, hashtags, duration classes, quality gates, and pillar/platform validation stay centralized.\\n- Do not use `x or default` for optional content/script overrides in factories; explicit blank strings and zero durations must pass through to validation so tests can catch them.\\n- Do not assume TikTok monetization rules match YouTube: TikTok Creator Rewards emphasizes 1min+ eligible videos, while shorter videos may still be better for growth.\\n- Do not publish religious or health-adjacent content with overconfident claims; preserve humility, nuance, and platform safety.\\n- Do not rely on platform payout as the only monetization path; plan indirect monetization such as newsletter, templates, affiliates, digital products, or services.\", \"path\": \"social-media/social-media-shorts-automation/SKILL.md\", \"skill_dir\": \"/home/agent/.hermes/skills/social-media/social-media-shorts-automation\", \"linked_files\": {\"references\": [\"references/wan-i2v-retention-studio.md\", \"references/render-manifest-pipeline.md\", \"references/retention-studio-strategy.md\", \"references/social-draft-approval-package.md\", \"references/approval-first-retention-studio-core.md\", \"references/local-preview-frame-writer.md\", \"references/preview-media-delivery-guardrails.md\", \"references/manifest-preview-renderer.md\", \"references/content-development-core.md\", \"references/ai-video-asset-planning.md\", \"references/approval-first-content-pipeline.md\", \"references/beginner-friendly-audio-caption-alignment.md\", \"references/audio-caption-preview-pipeline.md\", \"references/retention-studio-pipeline-pattern.md\", \"references/monetization-and-approval-notes.md\", \"references/content-to-review-pipeline.md\", \"references/retention-led-shorts.md\", \"references/final-motion-hybrid-rendering.md\", \"references/imported-ai-clip-assembly.md\", \"references/content-automation-patterns.md\", \"references/retention-render-planning.md\", \"references/nvidia-keyframe-generation.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\"}", "tool_call_id": "call_EyhGK2DnRjnY8nuBkVGgTrz9", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"content\": \" 1|\\\"\\\"\\\"Deterministic renderer-owned subtitle cue planning.\\\"\\\"\\\"\\n 2|\\n 3|from __future__ import annotations\\n 4|\\n 5|import re\\n 6|from dataclasses import dataclass, replace\\n 7|\\n 8|from autoshorts.ideas.candidate import ValidationResult\\n 9|\\n 10|\\n 11|_WORD_RE = re.compile(r\\\"[A-Za-z0-9]+(?:['-][A-Za-z0-9]+)?\\\")\\n 12|\\n 13|\\n 14|@dataclass(frozen=True)\\n 15|class SubtitleStyle:\\n 16| name: str\\n 17| primary_color: str\\n 18| accent_color: str\\n 19| stroke_color: str\\n 20| shadow_color: str\\n 21| placement: str\\n 22| max_lines: int\\n 23| min_words_per_cue: int\\n 24| max_words_per_cue: int\\n 25| safe_zone_bottom_percent: int\\n 26| font_weight: str\\n 27|\\n 28| @classmethod\\n 29| def hormozi_inspired(cls) -> \\\"SubtitleStyle\\\":\\n 30| \\\"\\\"\\\"Return the TrueTrace kinetic-caption baseline: inspired mechanics, original brand skin.\\\"\\\"\\\"\\n 31|\\n 32| return cls(\\n 33| name=\\\"truetrace_hormozi_inspired\\\",\\n 34| primary_color=\\\"#FFFFFF\\\",\\n 35| accent_color=\\\"#22D3EE\\\",\\n 36| stroke_color=\\\"#050816\\\",\\n 37| shadow_color=\\\"#000000\\\",\\n 38| placement=\\\"lower_middle_above_ui_safe_zone\\\",\\n 39| max_lines=2,\\n 40| min_words_per_cue=2,\\n 41| max_words_per_cue=5,\\n 42| safe_zone_bottom_percent=14,\\n 43| font_weight=\\\"800\\\",\\n 44| )\\n 45|\\n 46|\\n 47|@dataclass(frozen=True)\\n 48|class SubtitleCue:\\n 49| text: str\\n 50| start_ms: int\\n 51| end_ms: int\\n 52| active_word: str\\n 53| renderer_owned: bool = True\\n 54| max_lines: int = 2\\n 55| emphasis_color: str = \\\"#22D3EE\\\"\\n 56|\\n 57|\\n 58|@dataclass(frozen=True)\\n 59|class SubtitleTrack:\\n 60| cues: tuple[SubtitleCue, ...]\\n 61| style: SubtitleStyle\\n 62| renderer_owned: bool = True\\n 63| side_effects: tuple[str, ...] = ()\\n 64| external_calls: tuple[str, ...] = ()\\n 65|\\n 66| def with_cues(self, cues: tuple[SubtitleCue, ...]) -> \\\"SubtitleTrack\\\":\\n 67| return replace(self, cues=cues)\\n 68|\\n 69|\\n 70|def _words(text: str) -> list[str]:\\n 71| return _WORD_RE.findall(text)\\n 72|\\n 73|\\n 74|def _chunk_words(words: list[str], *, min_words: int, max_words: int) -> list[list[str]]:\\n 75| chunks: list[list[str]] = []\\n 76| index = 0\\n 77| while index < len(words):\\n 78| remaining = len(words) - index\\n 79| take = min(max_words, remaining)\\n 80| if 0 < remaining < min_words and chunks:\\n 81| chunks[-1].extend(words[index:])\\n 82| break\\n 83| if remaining == min_words + 1:\\n 84| take = min_words\\n 85| chunks.append(words[index : index + take])\\n 86| index += take\\n 87| return chunks\\n 88|\\n 89|\\n 90|def _active_word(chunk: list[str]) -> str:\\n 91| # Prefer the longest meaningful word so the highlighted token carries semantic weight.\\n 92| return max((word.upper() for word in chunk), key=lambda word: (len(word), word))\\n 93|\\n 94|\\n 95|def build_hormozi_subtitle_track(text: str, *, total_duration_seconds: int) -> SubtitleTrack:\\n 96| \\\"\\\"\\\"Create continuous 2..5-word renderer-owned subtitle cues for final burn-in.\\\"\\\"\\\"\\n 97|\\n 98| if not text.strip():\\n 99| raise ValueError(\\\"subtitle text is required\\\")\\n 100| if total_duration_seconds <= 0:\\n 101| raise ValueError(\\\"total_duration_seconds must be positive\\\")\\n 102|\\n 103| style = SubtitleStyle.hormozi_inspired()\\n 104| words = _words(text)\\n 105| if len(words) < style.min_words_per_cue:\\n 106| raise ValueError(\\\"subtitle text must contain at least two words\\\")\\n 107|\\n 108| chunks = _chunk_words(words, min_words=style.min_words_per_cue, max_words=style.max_words_per_cue)\\n 109| total_ms = total_duration_seconds * 1000\\n 110| cues: list[SubtitleCue] = []\\n 111| for index, chunk in enumerate(chunks):\\n 112| start_ms = round(index * total_ms / len(chunks))\\n 113| end_ms = round((index + 1) * total_ms / len(chunks))\\n 114| cues.append(\\n 115| SubtitleCue(\\n 116| text=\\\" \\\".join(word.upper() for word in chunk),\\n 117| start_ms=start_ms,\\n 118| end_ms=end_ms,\\n 119| active_word=_active_word(chunk),\\n 120| renderer_owned=True,\\n 121| max_lines=style.max_lines,\\n 122| emphasis_color=style.accent_color,\\n 123| )\\n 124| )\\n 125|\\n 126| track = SubtitleTrack(cues=tuple(cues), style=style)\\n 127| validation = validate_subtitle_track(track)\\n 128| if not validation.is_valid:\\n 129| raise ValueError(\\\"; \\\".join(validation.errors))\\n 130| return track\\n 131|\\n 132|\\n 133|def validate_subtitle_track(track: SubtitleTrack) -> ValidationResult:\\n 134| errors: list[str] = []\\n 135| if not track.renderer_owned:\\n 136| errors.append(\\\"subtitle track must be renderer-owned\\\")\\n 137| if track.side_effects:\\n 138| errors.append(\\\"subtitle track must not have side effects\\\")\\n 139| if track.external_calls:\\n 140| errors.append(\\\"subtitle track must not have external calls\\\")\\n 141| if not track.cues:\\n 142| errors.append(\\\"at least one subtitle cue is required\\\")\\n 143|\\n 144| previous_end: int | None = None\\n 145| for index, cue in enumerate(track.cues, start=1):\\n 146| cue_words = cue.text.split()\\n 147| if not cue.renderer_owned:\\n 148| errors.append(f\\\"subtitle cue {index} must be renderer-owned\\\")\\n 149| if not (track.style.min_words_per_cue <= len(cue_words) <= track.style.max_words_per_cue):\\n 150| errors.append(f\\\"subtitle cue {index} must contain 2..5 words\\\")\\n 151| if cue.end_ms <= cue.start_ms:\\n 152| errors.append(f\\\"subtitle cue {index} end_ms must be greater than start_ms\\\")\\n 153| if previous_end is None:\\n 154| if cue.start_ms != 0:\\n 155| errors.append(\\\"first subtitle cue must start at 0ms\\\")\\n 156| elif cue.start_ms != previous_end:\\n 157| errors.append(f\\\"subtitle cue {index} must start when the previous cue ends\\\")\\n 158| if not cue.active_word.strip():\\n 159| errors.append(f\\\"subtitle cue {index} active_word is required\\\")\\n 160| elif cue.active_word not in {word.upper() for word in cue_words}:\\n 161| errors.append(f\\\"subtitle cue {index} active_word must appear in cue text\\\")\\n 162| if cue.max_lines > track.style.max_lines:\\n 163| errors.append(f\\\"subtitle cue {index} exceeds style max lines\\\")\\n 164| previous_end = cue.end_ms\\n 165|\\n 166| return ValidationResult(is_valid=not errors, errors=tuple(errors))\\n 167|\", \"total_lines\": 166, \"file_size\": 5805, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_uplnI2qLcfBFjzRMbrFlukOc", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_e3PXpqCeLCdiplFS4yRofQdn", "call_id": "call_e3PXpqCeLCdiplFS4yRofQdn", "response_item_id": "fc_0dc9f371a6d55e3f016a1379467c0c8191a9623c915de3f46d", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\":260,\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Planning scene backgrounds**\n\nI need to generate scene-specific backgrounds, maybe four images, and update the renderer to support those backgrounds for each scene. The subtitle safe zone might need adjusting upward too. So, let's create an asset plan based on that. The user wants me to continue, so I’ll focus next on scene-specific image backgrounds and render them in version 5. I think we won't need TDD for generated images, but will need tests for accepting scene background paths.", "reasoning_content": "**Planning scene backgrounds**\n\nI need to generate scene-specific backgrounds, maybe four images, and update the renderer to support those backgrounds for each scene. The subtitle safe zone might need adjusting upward too. So, let's create an asset plan based on that. The user wants me to continue, so I’ll focus next on scene-specific image backgrounds and render them in version 5. I think we won't need TDD for generated images, but will need tests for accepting scene background paths.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3lGcrTBeSYIKd9I8D4CqqKUqR6pBzkJ4ECtLfaz2HC-Okbmszkb9rwK1c5VHwjbKX6Vgw5aCR40iiInqYqldOoXw4-_sBsEoR75KaQKzQRAEdEm4ipPI_oZs9RehRX6bNr6T-Rab2KpyrJ8gDxSYPmBk9JPJGgIy9rlae3UKIocpsGfsx1BNcVOSUgE6TyOtto79vfF2xLcC2QcVz52oGIa1bpB-GWxhDAxcW_Ebz0fSQHTdsrvzkzRwqW7uux5hfJHZYsHUaE3y87i46fdrfvHNyPdmfpEUPonQwlgAE_scVOikkhIbcALTQO5MaIpkgjnWIXe9uCgqWpFlB5mkSkG42OzWSBEk07-Lele2trsveHKEOOxKaS_7ZfW90Va9RqUh_TBesMP92YX1nXJkAGTaWVJWAvDc308U0enjk1XNOTIkOJ-BoRo_s1adbEJV3bnZgh7oCKI9ZWJHZdyMB5RX1vJN1WqVXQY-6Cu28EAS8_1pLXhvE4psWrYDE8K3ElYtS2nUe8OIM0l0h25MIJ5oGqOCnLuMgMd5Rie1KS2pV2fBmEAt7Of3C21STz5qUyLWafK_0ZHhT-KrsB5CsIEKcZu8twwDIF3p_vaw8MRtb2yFRQNtnEIOh7VjUiUhqEMoHPJeWTxYeqr_h9_wPT_QCLsdgGl4Nlp_UlAkh-WCNJljKFRNVbPD34BrTimtXJngHRViMaTJc8GSz0tLrFw04c63T9hl-aNmxTMKEU3Cp1fQ7oLKDEdItbOH6BFLIC0_spyRd2REP_vWC-IxmCSMXi5x4DVlz_1rRdtII7no36I1voDuFGucoQ9KVVW0Y6rjwXCnkQ6UKr7Bh0YeDWwHoK1ur1s5_X50cXh9LEUh8PGQ-JUxQSm5_wxkFaxc5yzsAGh8U4r7Cd_EteolmVGtuRMeLPcp4Q2Fpg0UcH6si9REXFLx17rGWYwxWtqgYy92loMRhdH__3vgGaEDfD2zMzCbGg-yyJeogukw4yu1N3lbPypWBeNBmwFhGz3je9OSzTLatz3FQolBRbOPjbwdlYBZeMgi0K9LDMZECxVMYQGmAvBbI7iu-9T4sSYyjhqV1HrHJRAY_yJV5q97Eudik9vXkepBXUjZJKqMRnGJfI_eC6dWJF_uyQDi9XgjHmOyBnDTJyRM6Bl2iYbT7XwdDejmRVP1LKJ-W9xRrz_TEW95hGSH2StOEK3RoKMl6Wnb-iHR2gjiGaoj22V4SKPlHsf5n4AZqwynWftbGDmWTP5AD99h7oSuZPUBkyu8dHy7fmwfRIybQnVzWnVieKuV0tKdtttIAxFIUgeb1f7rHQD3SdOUplxM9i5L66a07Aqt1KUBU5N4zRZyIs7nJ2M3S0Pf_Vz_AjNALXFMI0b_4KyrQJ9OGaJcUWapAeZbme5pzuVWunyLwS4vSWvGucYNbDFWjrjwspSVxBogOOCXF1_K1ez-h10e1jPWFpLTZfaB8S8z-rwdG5HOe1jHTqTACPdUpgBtC5CjGMCV62KJ3FvVIwT-8Q09lODLk-kGAdr556FaiaSBzPXWFEMxVLcdbRfwHdv6yiFjfzegLQbX6Wo_f4bJGfZ4lEAy3PaeVvnIWtl1QBrEzEpKSLaJ0aHjVoUO-VbtxGhq8voEVG7Nmnc4WWygX_NBs6HdJRXbfIiH0ZDTDdVyuyyYm2rJrXE2_r-ny1ih4VIMU3_yB6I_f8CLV3Xe1l0iv8P2L_-O5XW", "id": "rs_0dc9f371a6d55e3f016a1379431d488191b66649785a14431a", "summary": [{"type": "summary_text", "text": "**Planning scene backgrounds**\n\nI need to generate scene-specific backgrounds, maybe four images, and update the renderer to support those backgrounds for each scene. The subtitle safe zone might need adjusting upward too. So, let's create an asset plan based on that. The user wants me to continue, so I’ll focus next on scene-specific image backgrounds and render them in version 5. I think we won't need TDD for generated images, but will need tests for accepting scene background paths."}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"content\": \" 1|\\\"\\\"\\\"Audio + subtitle final-preview planning and FFmpeg rendering boundary.\\\"\\\"\\\"\\n 2|\\n 3|from __future__ import annotations\\n 4|\\n 5|from collections.abc import Callable\\n 6|from dataclasses import dataclass\\n 7|from pathlib import Path\\n 8|import subprocess\\n 9|\\n 10|from autoshorts.audio.subtitles import SubtitleTrack, validate_subtitle_track\\n 11|from autoshorts.ideas.candidate import ValidationResult\\n 12|\\n 13|Runner = Callable[..., subprocess.CompletedProcess[str]]\\n 14|\\n 15|\\n 16|@dataclass(frozen=True)\\n 17|class AudioCaptionPreviewPlan:\\n 18| video_path: str\\n 19| audio_path: str\\n 20| output_path: str\\n 21| subtitle_file_path: str\\n 22| subtitle_file_content: str\\n 23| subtitle_track: SubtitleTrack\\n 24| duration_mode: str = \\\"preserve_video\\\"\\n 25| side_effects: tuple[str, ...] = ()\\n 26| external_calls: tuple[str, ...] = ()\\n 27|\\n 28|\\n 29|@dataclass(frozen=True)\\n 30|class AudioCaptionPreviewResult:\\n 31| output_path: str\\n 32| subtitle_file_path: str\\n 33| returncode: int\\n 34| stdout: str\\n 35| stderr: str\\n 36| duration_mode: str = \\\"preserve_video\\\"\\n 37| side_effects: tuple[str, ...] = (\\\"write_subtitles\\\", \\\"call_ffmpeg\\\", \\\"write_mp4\\\")\\n 38| external_calls: tuple[str, ...] = (\\\"ffmpeg\\\",)\\n 39|\\n 40|\\n 41|def _is_blank(value: str) -> bool:\\n 42| return not (value or \\\"\\\").strip()\\n 43|\\n 44|\\n 45|def _ass_timestamp(ms: int) -> str:\\n 46| centiseconds = round(ms / 10)\\n 47| hours, remainder = divmod(centiseconds, 360000)\\n 48| minutes, remainder = divmod(remainder, 6000)\\n 49| seconds, centis = divmod(remainder, 100)\\n 50| return f\\\"{hours}:{minutes:02d}:{seconds:02d}.{centis:02d}\\\"\\n 51|\\n 52|\\n 53|def _ass_color(hex_color: str) -> str:\\n 54| # ASS uses &HAABBGGRR. We keep alpha at 00 and convert #RRGGBB to BGR.\\n 55| value = hex_color.removeprefix(\\\"#\\\")\\n 56| if len(value) != 6:\\n 57| return \\\"&H00FFFFFF\\\"\\n 58| red, green, blue = value[0:2], value[2:4], value[4:6]\\n 59| return f\\\"&H00{blue}{green}{red}\\\"\\n 60|\\n 61|\\n 62|def _escape_ass_text(text: str) -> str:\\n 63| return text.replace(\\\"{\\\", \\\"\\\").replace(\\\"}\\\", \\\"\\\").replace(\\\"\\\\n\\\", \\\" \\\")\\n 64|\\n 65|\\n 66|def render_ass_subtitle_file(track: SubtitleTrack) -> str:\\n 67| validation = validate_subtitle_track(track)\\n 68| if not validation.is_valid:\\n 69| raise ValueError(\\\"; \\\".join(validation.errors))\\n 70|\\n 71| style = track.style\\n 72| primary = _ass_color(style.primary_color)\\n 73| accent = _ass_color(style.accent_color)\\n 74| outline = _ass_color(style.stroke_color)\\n 75| lines = [\\n 76| \\\"[Script Info]\\\",\\n 77| \\\"ScriptType: v4.00+\\\",\\n 78| \\\"PlayResX: 1080\\\",\\n 79| \\\"PlayResY: 1920\\\",\\n 80| \\\"ScaledBorderAndShadow: yes\\\",\\n 81| \\\"\\\",\\n 82| \\\"[V4+ Styles]\\\",\\n 83| \\\"Format: Name, Fontname, Fontsize, PrimaryColour, SecondaryColour, OutlineColour, BackColour, Bold, Italic, Underline, StrikeOut, ScaleX, ScaleY, Spacing, Angle, BorderStyle, Outline, Shadow, Alignment, MarginL, MarginR, MarginV, Encoding\\\",\\n 84| f\\\"Style: TrueTraceCaption,Arial,86,{primary},{accent},{outline},&H80000000,-1,0,0,0,100,100,0,0,1,5,2,2,80,80,260,1\\\",\\n 85| \\\"\\\",\\n 86| \\\"[Events]\\\",\\n 87| \\\"Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text\\\",\\n 88| ]\\n 89| for cue in track.cues:\\n 90| cue_text = _escape_ass_text(cue.text)\\n 91| lines.append(\\n 92| \\\"Dialogue: 0,\\\"\\n 93| f\\\"{_ass_timestamp(cue.start_ms)},{_ass_timestamp(cue.end_ms)},\\\"\\n 94| f\\\"TrueTraceCaption,,0,0,0,,{cue_text}\\\"\\n 95| )\\n 96| return \\\"\\\\n\\\".join(lines) + \\\"\\\\n\\\"\\n 97|\\n 98|\\n 99|def build_audio_caption_preview_plan(\\n 100| *,\\n 101| video_path: str | Path,\\n 102| audio_path: str | Path,\\n 103| subtitle_track: SubtitleTrack,\\n 104| output_path: str | Path,\\n 105| duration_mode: str = \\\"preserve_video\\\",\\n 106|) -> AudioCaptionPreviewPlan:\\n 107| out = Path(output_path)\\n 108| plan = AudioCaptionPreviewPlan(\\n 109| video_path=str(video_path),\\n 110| audio_path=str(audio_path),\\n 111| output_path=str(out),\\n 112| subtitle_file_path=str(out.with_suffix(\\\".ass\\\")),\\n 113| subtitle_file_content=render_ass_subtitle_file(subtitle_track),\\n 114| subtitle_track=subtitle_track,\\n 115| duration_mode=duration_mode,\\n 116| side_effects=(),\\n 117| external_calls=(),\\n 118| )\\n 119| validation = validate_audio_caption_preview_plan(plan)\\n 120| if not validation.is_valid:\\n 121| raise ValueError(\\\"; \\\".join(validation.errors))\\n 122| return plan\\n 123|\\n 124|\\n 125|def validate_audio_caption_preview_plan(plan: AudioCaptionPreviewPlan) -> ValidationResult:\\n 126| errors: list[str] = []\\n 127| for field_name, value in {\\n 128| \\\"video_path\\\": plan.video_path,\\n 129| \\\"audio_path\\\": plan.audio_path,\\n 130| \\\"output_path\\\": plan.output_path,\\n 131| \\\"subtitle_file_path\\\": plan.subtitle_file_path,\\n 132| \\\"subtitle_file_content\\\": plan.subtitle_file_content,\\n 133| }.items():\\n 134| if _is_blank(value):\\n 135| errors.append(f\\\"{field_name} is required\\\")\\n 136| if plan.video_path and not plan.video_path.endswith(\\\".mp4\\\"):\\n 137| errors.append(\\\"video_path must end with .mp4\\\")\\n 138| if plan.audio_path and not plan.audio_path.endswith(\\\".mp3\\\"):\\n 139| errors.append(\\\"audio_path must end with .mp3\\\")\\n 140| if plan.output_path and not plan.output_path.endswith(\\\".mp4\\\"):\\n 141| errors.append(\\\"output_path must end with .mp4\\\")\\n 142| if plan.subtitle_file_path and not plan.subtitle_file_path.endswith(\\\".ass\\\"):\\n 143| errors.append(\\\"subtitle_file_path must end with .ass\\\")\\n 144| if plan.duration_mode not in {\\\"preserve_video\\\", \\\"trim_to_audio\\\"}:\\n 145| errors.append(\\\"duration_mode must be preserve_video or trim_to_audio\\\")\\n 146| if plan.side_effects:\\n 147| errors.append(\\\"audio caption preview plans must not have side effects\\\")\\n 148| if plan.external_calls:\\n 149| errors.append(\\\"audio caption preview plans must not have external calls\\\")\\n 150| errors.extend(validate_subtitle_track(plan.subtitle_track).errors)\\n 151| return ValidationResult(is_valid=not errors, errors=tuple(errors))\\n 152|\\n 153|\\n 154|def _ass_filter_path(path: str) -> str:\\n 155| # Avoid shell quoting entirely by passing argv; escape colon/backslash for FFmpeg filter parser.\\n 156| return path.replace(\\\"\\\\\\\\\\\", \\\"\\\\\\\\\\\\\\\\\\\").replace(\\\":\\\", \\\"\\\\\\\\:\\\").replace(\\\"'\\\", \\\"\\\\\\\\'\\\")\\n 157|\\n 158|\\n 159|def _command(plan: AudioCaptionPreviewPlan) -> list[str]:\\n 160| command = [\\n 161| \\\"ffmpeg\\\",\\n 162| \\\"-y\\\",\\n 163| \\\"-i\\\",\\n 164| plan.video_path,\\n 165| \\\"-i\\\",\\n 166| plan.audio_path,\\n 167| \\\"-vf\\\",\\n 168| f\\\"ass='{_ass_filter_path(plan.subtitle_file_path)}'\\\",\\n 169| \\\"-map\\\",\\n 170| \\\"0:v:0\\\",\\n 171| \\\"-map\\\",\\n 172| \\\"1:a:0\\\",\\n 173| \\\"-c:v\\\",\\n 174| \\\"libx264\\\",\\n 175| \\\"-c:a\\\",\\n 176| \\\"aac\\\",\\n 177| ]\\n 178| if plan.duration_mode == \\\"trim_to_audio\\\":\\n 179| command.append(\\\"-shortest\\\")\\n 180| command.extend([\\n 181| \\\"-movflags\\\",\\n 182| \\\"+faststart\\\",\\n 183| plan.output_path,\\n 184| ])\\n 185| return command\\n 186|\\n 187|\\n 188|def render_audio_caption_preview(plan: AudioCaptionPreviewPlan, *, runner: Runner = subprocess.run) -> AudioCaptionPreviewResult:\\n 189| \\\"\\\"\\\"Write ASS subtitles and call FFmpeg to mux voiceover + burn captions into an MP4.\\\"\\\"\\\"\\n 190|\\n 191| validation = validate_audio_caption_preview_plan(plan)\\n 192| if not validation.is_valid:\\n 193| raise ValueError(\\\"; \\\".join(validation.errors))\\n 194| if not Path(plan.video_path).exists():\\n 195| raise FileNotFoundError(plan.video_path)\\n 196| if not Path(plan.audio_path).exists():\\n 197| raise FileNotFoundError(plan.audio_path)\\n 198|\\n 199| subtitle_path = Path(plan.subtitle_file_path)\\n 200| output_path = Path(plan.output_path)\\n 201| subtitle_path.parent.mkdir(parents=True, exist_ok=True)\\n 202| output_path.parent.mkdir(parents=True, exist_ok=True)\\n 203| subtitle_path.write_text(plan.subtitle_file_content)\\n 204|\\n 205| completed = runner(_command(plan), capture_output=True, text=True, check=False)\\n 206| if completed.returncode != 0:\\n 207| raise RuntimeError(completed.stderr or \\\"ffmpeg audio/caption preview failed\\\")\\n 208| if not output_path.exists():\\n 209| raise RuntimeError(\\\"ffmpeg completed but did not create output video\\\")\\n 210|\\n 211| return AudioCaptionPreviewResult(\\n 212| output_path=str(output_path),\\n 213| subtitle_file_path=str(subtitle_path),\\n 214| returncode=completed.returncode,\\n 215| stdout=completed.stdout,\\n 216| stderr=completed.stderr,\\n 217| duration_mode=plan.duration_mode,\\n 218| side_effects=(\\\"write_subtitles\\\", \\\"call_ffmpeg\\\", \\\"write_mp4\\\"),\\n 219| external_calls=(\\\"ffmpeg\\\",),\\n 220| )\\n 221|\", \"total_lines\": 220, \"file_size\": 7883, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_e3PXpqCeLCdiplFS4yRofQdn", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_jal7MrWtgXhCUk1zIi0I2UtX", "call_id": "call_jal7MrWtgXhCUk1zIi0I2UtX", "response_item_id": "fc_0dc9f371a6d55e3f016a13794fd2308191b3e14fbd41148b89", "type": "function", "function": {"name": "write_file", "arguments": "{\"content\":\"from pathlib import Path\\n\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover\\nfrom autoshorts.rendering.final_video_plan import build_truetrace_weird_email_final_video_plan\\nfrom autoshorts.rendering.scene_backgrounds import (\\n SceneBackgroundPlan,\\n build_chatgpt_image_scene_background_plan,\\n validate_scene_background_plan,\\n)\\n\\n\\ndef test_build_chatgpt_image_scene_background_plan_is_text_free_and_scene_specific(tmp_path):\\n voiceover = build_truetrace_final_voiceover(\\\"truetrace-ai-automation-quiet-rot-38s\\\")\\n final_plan = build_truetrace_weird_email_final_video_plan(voiceover)\\n\\n plan = build_chatgpt_image_scene_background_plan(final_plan, output_dir=tmp_path)\\n\\n assert isinstance(plan, SceneBackgroundPlan)\\n assert plan.candidate_id == final_plan.candidate_id\\n assert [asset.scene_id for asset in plan.assets] == [scene.scene_id for scene in final_plan.scenes]\\n assert all(asset.provider == \\\"chatgpt_image_codex\\\" for asset in plan.assets)\\n assert all(asset.output_path.endswith(\\\".png\\\") for asset in plan.assets)\\n assert all(\\\"no readable text\\\" in asset.prompt.casefold() for asset in plan.assets)\\n assert all(\\\"no logos\\\" in asset.prompt.casefold() for asset in plan.assets)\\n assert all(asset.renderer_owned_overlay_required is True for asset in plan.assets)\\n assert plan.side_effects == ()\\n assert plan.external_calls == ()\\n\\n\\ndef test_validate_scene_background_plan_rejects_text_or_side_effects(tmp_path):\\n voiceover = build_truetrace_final_voiceover(\\\"truetrace-ai-automation-quiet-rot-38s\\\")\\n final_plan = build_truetrace_weird_email_final_video_plan(voiceover)\\n valid = build_chatgpt_image_scene_background_plan(final_plan, output_dir=tmp_path)\\n broken_asset = valid.assets[0].__class__(\\n scene_id=\\\"clean-demo\\\",\\n provider=\\\"chatgpt_image_codex\\\",\\n prompt=\\\"Generate a dashboard with readable text and logos\\\",\\n output_path=str(tmp_path / \\\"bad.jpg\\\"),\\n renderer_owned_overlay_required=False,\\n )\\n broken = valid.__class__(\\n candidate_id=valid.candidate_id,\\n assets=(broken_asset,),\\n side_effects=(\\\"call_image_api\\\",),\\n external_calls=(\\\"openai\\\",),\\n )\\n\\n validation = validate_scene_background_plan(broken)\\n\\n assert validation.is_valid is False\\n assert \\\"scene background plan must not have side effects\\\" in validation.errors\\n assert \\\"scene background plan must not have external calls\\\" in validation.errors\\n assert \\\"asset 1 output_path must end with .png\\\" in validation.errors\\n assert \\\"asset 1 prompt must explicitly forbid readable text\\\" in validation.errors\\n assert \\\"asset 1 prompt must explicitly forbid logos\\\" in validation.errors\\n assert \\\"asset 1 requires renderer-owned overlays\\\" in validation.errors\\n\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_scene_backgrounds.py\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Considering style adjustments**\n\nI’m thinking about whether to add a style for the safe zone that affects the margin for subtitles. The existing safe zone has a margin of 260, which I could increase or adjust. Maybe I should consider a function to compact things better for a safer style? I wonder if the user mentioned to continue after the final motion. I’ll also check on rendering backgrounds for each scene and see if I can generate images concurrently. First, though, I need to code the tests.", "reasoning_content": "**Considering style adjustments**\n\nI’m thinking about whether to add a style for the safe zone that affects the margin for subtitles. The existing safe zone has a margin of 260, which I could increase or adjust. Maybe I should consider a function to compact things better for a safer style? I wonder if the user mentioned to continue after the final motion. I’ll also check on rendering backgrounds for each scene and see if I can generate images concurrently. First, though, I need to code the tests.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3lPY1b0BNNvnnaZuMDNuQJndjVuctkvO9AlPDMWXNabSmIfom3HAfmUWUvHVTRQYIGasa6ICmP2SNp-xayNKIdSrvCdgGRLA2oaXzN5GpnSlc2pSnPgs3aD3CtCWmuKjlTRZ4an0rTKHYCi6nvAwiORC9NBhHZuGzP9FrX78RAqdT3DihfmfAVpXPVD2lvmRFDXf0SxJkTuwlKkccvRrBKQp0oA0KOJZ1cS6MSOdVZoitpgQ3R8ug9iDFB4A9y826A_kgRVN7d4cH4b5kNRGxjkoUpyBGKvN1c1zat-A_YLGeB0FkwE64QYiW1dfgf9dfIfLscKlqthxYUoYXnVJim0Fe0mP_r-TmQLkkT4OSIGIzzl-SuE9cFP5zBCfTeTTcrQGGUn5RJMV72rEcEyRh-vmXrNy32Vk1DVmRLi9TB9dLIYAiPbEPvM4DLdou5l-FSVI26l34vWRKWiY83qT3PrOxiiyq283MsD4os8KP7SHcHnCjQk1Zc5vFX6sjqndHsgQ1IbYnTdf4LQRH0x_nffaqqtWYheTUOqiFQPfBi6Sf2KPQQNEsXCmv38P2J3nWCufDuvdss8ycdoTlvftB5kD8UR9jv9REQmt8XlgYLwH0c3GdL8a3b6egXlqRTBrwoHOgWbAptqbATqi0R7S0iXc9g-ZMOdZNDcm7hboYErxq8tTpzpxhGqwhaQhypl27dC4MyUxHG-sT3MXqJnlvVrSXfiMEHzqYu5Foo9e3pXyVQTm6va5kjNuM1TNDQZn-o7Ml3l9EJVry7o9zVd9ycEPnat0t7Was09YYeGGp1iTMubuP5_6coI2BNXa_cZ_Qu6xOkmah6wGQRVjuzOrmz1bWzlD1f6GE85_YM3xmS0v5QY32xRixgD-6jztNceXJBJjgO-jy7E6enToadGbOcEdGFJEXOtcDgkbWQr_zGW7Tie0o6duDzL5VYvRJE91qJ_iNLOmRreQqpjdBIL2jX-EGUdsJHHneIsJ-lCZGEuZ2Mtv4U75kpaNmb8LXaK-a38JrRFWxaqgJ3PSLwMd7bw5u3lnFVUtHxQk5yFjWLIORT-4KNOCLbeTMlmlufX3qQnGtBG2qW4G9MjVSMCs2XJIZQjn4BGn9PcOPOGw99UOaViMfQ4KLfOXiqIp2FMVS5VpwZwp7bVvz4LpB8gQSbH-5h3X8Y7mVQPJLh0zRPDm1GcMa27DrHNECYMlwQSnZpCck1AtXAMAEK9g1xB5k3vOZJWqZs-LidYo_FtJb6-VEzeP3PbaIOMTl8GeinZUr4lVQpIsGwo_DN8b0vy5vYanMOuRis8tBXdDmrw46jU69sLeUWn1pTPk6FQBFLf0wrysfy934Cmxk0ia9vy5ReF5eWGCW_UEwSXyRUxOrPURp8=", "id": "rs_0dc9f371a6d55e3f016a13794caa7c81919994d46f55626bcf", "summary": [{"type": "summary_text", "text": "**Considering style adjustments**\n\nI’m thinking about whether to add a style for the safe zone that affects the margin for subtitles. The existing safe zone has a margin of 260, which I could increase or adjust. Maybe I should consider a function to compact things better for a safer style? I wonder if the user mentioned to continue after the final motion. I’ll also check on rendering backgrounds for each scene and see if I can generate images concurrently. First, though, I need to code the tests."}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"bytes_written\": 2773, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}, \"lsp_diagnostics\": \"LSP diagnostics introduced by this edit:\\n\\nERROR [5:6] Import \\\"autoshorts.rendering.scene_backgrounds\\\" could not be resolved [reportMissingImports] (Pyright)\\n\"}", "tool_call_id": "call_jal7MrWtgXhCUk1zIi0I2UtX", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_PUFGWHnaApKiRiwBizdR2F3K", "call_id": "call_PUFGWHnaApKiRiwBizdR2F3K", "response_item_id": "fc_0dc9f371a6d55e3f016a13795f8b44819189af846835eefb63", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" background_paths = {scene.scene_id: tmp_path / f\\\"{scene.scene_id}.png\\\" for scene in final_plan.scenes}\\n for path in background_paths.values():\\n path.write_bytes(b\\\"fake image\\\")\\n render_plan = build_motion_render_plan(\\n final_plan,\\n output_dir=tmp_path,\\n preview_scale=0.5,\\n background_paths=background_paths,\\n )\\n\\n assert render_plan.background_paths == {scene_id: str(path) for scene_id, path in background_paths.items()}\\n assert render_plan.width == 540\",\"old_string\":\" background = tmp_path / \\\"chatgpt-image-background.png\\\"\\n background.write_bytes(b\\\"fake image\\\")\\n render_plan = build_motion_render_plan(final_plan, output_dir=tmp_path, preview_scale=0.5, background_path=background)\\n\\n assert render_plan.background_path == str(background)\\n assert render_plan.width == 540\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_motion_renderer.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_motion_renderer.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_motion_renderer.py\\n@@ -15,11 +15,17 @@\\n voiceover = build_truetrace_final_voiceover(\\\"truetrace-ai-automation-quiet-rot-38s\\\")\\n final_plan = build_truetrace_weird_email_final_video_plan(voiceover)\\n \\n- background = tmp_path / \\\"chatgpt-image-background.png\\\"\\n- background.write_bytes(b\\\"fake image\\\")\\n- render_plan = build_motion_render_plan(final_plan, output_dir=tmp_path, preview_scale=0.5, background_path=background)\\n+ background_paths = {scene.scene_id: tmp_path / f\\\"{scene.scene_id}.png\\\" for scene in final_plan.scenes}\\n+ for path in background_paths.values():\\n+ path.write_bytes(b\\\"fake image\\\")\\n+ render_plan = build_motion_render_plan(\\n+ final_plan,\\n+ output_dir=tmp_path,\\n+ preview_scale=0.5,\\n+ background_paths=background_paths,\\n+ )\\n \\n- assert render_plan.background_path == str(background)\\n+ assert render_plan.background_paths == {scene_id: str(path) for scene_id, path in background_paths.items()}\\n assert render_plan.width == 540\\n assert render_plan.height == 960\\n assert render_plan.fps == 24\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_motion_renderer.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}, \"lsp_diagnostics\": \"LSP diagnostics introduced by this edit:\\n\\nERROR [25:9] No parameter named \\\"background_paths\\\" [reportCallIssue] (Pyright)\\n\"}", "tool_call_id": "call_PUFGWHnaApKiRiwBizdR2F3K", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_Epvet55xd8P8eC2sVYEkQNTJ", "call_id": "call_Epvet55xd8P8eC2sVYEkQNTJ", "response_item_id": "fc_0dc9f371a6d55e3f016a13796b25648191abbd3f37fe2921c8", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_scene_backgrounds.py tests/test_motion_renderer.py::test_build_motion_render_plan_maps_final_plan_to_frame_output -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"==================================== ERRORS ====================================\\n_______________ ERROR collecting tests/test_scene_backgrounds.py _______________\\nImportError while importing test module '/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_scene_backgrounds.py'.\\nHint: make sure your test modules/packages have valid Python names.\\nTraceback:\\n../../../.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/importlib/__init__.py:126: in import_module\\n return _bootstrap._gcd_import(name[level:], package, level)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\ntests/test_scene_backgrounds.py:5: in \\n from autoshorts.rendering.scene_backgrounds import (\\nE ModuleNotFoundError: No module named 'autoshorts.rendering.scene_backgrounds'\\n=========================== short test summary info ============================\\nERROR tests/test_scene_backgrounds.py\\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\\n1 error in 0.16s\", \"exit_code\": 2, \"error\": null}", "tool_call_id": "call_Epvet55xd8P8eC2sVYEkQNTJ", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_rmx5JxzK5Fqbwpfmxqjj9PC2", "call_id": "call_rmx5JxzK5Fqbwpfmxqjj9PC2", "response_item_id": "fc_0dc9f371a6d55e3f016a137971b77481918dcf60ed526c5f08", "type": "function", "function": {"name": "write_file", "arguments": "{\"content\":\"\\\"\\\"\\\"Scene-specific text-free background planning for final-near motion renders.\\\"\\\"\\\"\\n\\nfrom __future__ import annotations\\n\\nfrom dataclasses import dataclass\\nfrom pathlib import Path\\n\\nfrom autoshorts.ideas.candidate import ValidationResult\\nfrom autoshorts.rendering.final_video_plan import FinalVideoPlan, validate_final_video_plan\\n\\n\\n@dataclass(frozen=True)\\nclass SceneBackgroundAsset:\\n scene_id: str\\n provider: str\\n prompt: str\\n output_path: str\\n renderer_owned_overlay_required: bool = True\\n\\n\\n@dataclass(frozen=True)\\nclass SceneBackgroundPlan:\\n candidate_id: str\\n assets: tuple[SceneBackgroundAsset, ...]\\n side_effects: tuple[str, ...] = ()\\n external_calls: tuple[str, ...] = ()\\n\\n\\n_SCENE_PROMPT_NOTES = {\\n \\\"clean-demo\\\": \\\"clean modern laptop workspace, calm inbox dashboard glow, orderly automation demo mood\\\",\\n \\\"weird-email\\\": \\\"slightly messy email-workflow atmosphere, amber warning mood, desk close-up, shallow depth of field\\\",\\n \\\"wrong-routing\\\": \\\"abstract AI routing node ambience, glowing path energy, subtle red warning tension\\\",\\n \\\"three-way-split\\\": \\\"minimal dark technical background with empty space for a three-branch diagram overlay\\\",\\n \\\"final-rule\\\": \\\"premium minimal blue-green abstract technology background, calm final-rule energy\\\",\\n}\\n\\n\\ndef build_chatgpt_image_scene_background_plan(final_plan: FinalVideoPlan, *, output_dir: str | Path) -> SceneBackgroundPlan:\\n validation = validate_final_video_plan(final_plan)\\n if not validation.is_valid:\\n raise ValueError(\\\"; \\\".join(validation.errors))\\n root = Path(output_dir)\\n assets = tuple(\\n SceneBackgroundAsset(\\n scene_id=scene.scene_id,\\n provider=\\\"chatgpt_image_codex\\\",\\n prompt=(\\n \\\"Vertical 9:16 cinematic background for a TrueTrace AI automation short. \\\"\\n f\\\"Scene: {scene.scene_id}. {_SCENE_PROMPT_NOTES.get(scene.scene_id, scene.asset_prompt)}. \\\"\\n \\\"No readable text, no logos, no watermarks, no UI labels, no fake letters. \\\"\\n \\\"Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. \\\"\\n \\\"Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\\\"\\n ),\\n output_path=str(root / f\\\"{scene.scene_id}.png\\\"),\\n renderer_owned_overlay_required=True,\\n )\\n for scene in final_plan.scenes\\n )\\n plan = SceneBackgroundPlan(candidate_id=final_plan.candidate_id, assets=assets)\\n validation = validate_scene_background_plan(plan)\\n if not validation.is_valid:\\n raise ValueError(\\\"; \\\".join(validation.errors))\\n return plan\\n\\n\\ndef validate_scene_background_plan(plan: SceneBackgroundPlan) -> ValidationResult:\\n errors: list[str] = []\\n if not plan.candidate_id.strip():\\n errors.append(\\\"candidate_id is required\\\")\\n if not plan.assets:\\n errors.append(\\\"at least one scene background asset is required\\\")\\n if plan.side_effects:\\n errors.append(\\\"scene background plan must not have side effects\\\")\\n if plan.external_calls:\\n errors.append(\\\"scene background plan must not have external calls\\\")\\n seen: set[str] = set()\\n for index, asset in enumerate(plan.assets, start=1):\\n if not asset.scene_id.strip():\\n errors.append(f\\\"asset {index} scene_id is required\\\")\\n if asset.scene_id in seen:\\n errors.append(f\\\"duplicate scene background asset: {asset.scene_id}\\\")\\n seen.add(asset.scene_id)\\n if asset.provider != \\\"chatgpt_image_codex\\\":\\n errors.append(f\\\"asset {index} provider must be chatgpt_image_codex\\\")\\n if not asset.output_path.endswith(\\\".png\\\"):\\n errors.append(f\\\"asset {index} output_path must end with .png\\\")\\n prompt = asset.prompt.casefold()\\n if \\\"no readable text\\\" not in prompt:\\n errors.append(f\\\"asset {index} prompt must explicitly forbid readable text\\\")\\n if \\\"no logos\\\" not in prompt:\\n errors.append(f\\\"asset {index} prompt must explicitly forbid logos\\\")\\n if not asset.renderer_owned_overlay_required:\\n errors.append(f\\\"asset {index} requires renderer-owned overlays\\\")\\n return ValidationResult(is_valid=not errors, errors=tuple(errors))\\n\", \"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/scene_backgrounds.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"bytes_written\": 4249, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_rmx5JxzK5Fqbwpfmxqjj9PC2", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_X2vAVsyLhlg4BokiSJjE7KkX", "call_id": "call_X2vAVsyLhlg4BokiSJjE7KkX", "response_item_id": "fc_0dc9f371a6d55e3f016a13798965348191a147750ab08312aa", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" background_paths: dict[str, str] | None = None\\n side_effects: tuple[str, ...] = ()\",\"old_string\":\" background_path: str | None = None\\n side_effects: tuple[str, ...] = ()\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n@@ -26,7 +26,7 @@\\n width: int\\n height: int\\n fps: int\\n- background_path: str | None = None\\n+ background_paths: dict[str, str] | None = None\\n side_effects: tuple[str, ...] = ()\\n external_calls: tuple[str, ...] = ()\\n \\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}, \"lsp_diagnostics\": \"LSP diagnostics introduced by this edit:\\n\\nERROR [71:9] No parameter named \\\"background_path\\\" [reportCallIssue] (Pyright)\\nERROR [248:13] Cannot access attribute \\\"background_path\\\" for class \\\"MotionRenderPlan\\\"\\n  Attribute \\\"background_path\\\" is unknown [reportAttributeAccessIssue] (Pyright)\\nERROR [249:38] Cannot access attribute \\\"background_path\\\" for class \\\"MotionRenderPlan\\\"\\n  Attribute \\\"background_path\\\" is unknown [reportAttributeAccessIssue] (Pyright)\\n\"}", "tool_call_id": "call_X2vAVsyLhlg4BokiSJjE7KkX", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_LwTF7tAs4d5RP1kJMMFq8Kos", "call_id": "call_LwTF7tAs4d5RP1kJMMFq8Kos", "response_item_id": "fc_0dc9f371a6d55e3f016a137990a5b88191959b235f0f801683", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" preview_scale: float = 1.0,\\n background_paths: dict[str, str | Path] | None = None,\\n) -> MotionRenderPlan:\",\"old_string\":\" preview_scale: float = 1.0,\\n background_path: str | Path | None = None,\\n) -> MotionRenderPlan:\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n@@ -48,7 +48,7 @@\\n *,\\n output_dir: str | Path,\\n preview_scale: float = 1.0,\\n- background_path: str | Path | None = None,\\n+ background_paths: dict[str, str | Path] | None = None,\\n ) -> MotionRenderPlan:\\n validation = validate_final_video_plan(final_plan)\\n if not validation.is_valid:\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}, \"lsp_diagnostics\": \"LSP diagnostics introduced by this edit:\\n\\nERROR [71:49] \\\"background_path\\\" is not defined [reportUndefinedVariable] (Pyright)\\nERROR [71:29] \\\"background_path\\\" is not defined [reportUndefinedVariable] (Pyright)\\n\"}", "tool_call_id": "call_LwTF7tAs4d5RP1kJMMFq8Kos", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_jy66MvUrfZeimPTpqsMbfMmt", "call_id": "call_jy66MvUrfZeimPTpqsMbfMmt", "response_item_id": "fc_0dc9f371a6d55e3f016a13799795c48191bc1a829a880ab558", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" fps=fps,\\n background_paths={scene_id: str(path) for scene_id, path in (background_paths or {}).items()} or None,\\n )\",\"old_string\":\" fps=fps,\\n background_path=str(background_path) if background_path is not None else None,\\n )\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n@@ -68,7 +68,7 @@\\n width=width,\\n height=height,\\n fps=fps,\\n- background_path=str(background_path) if background_path is not None else None,\\n+ background_paths={scene_id: str(path) for scene_id, path in (background_paths or {}).items()} or None,\\n )\\n validation = validate_motion_render_plan(plan)\\n if not validation.is_valid:\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_jy66MvUrfZeimPTpqsMbfMmt", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_dZBGrfzxUwzxeLWyinBDiapx", "call_id": "call_dZBGrfzxUwzxeLWyinBDiapx", "response_item_id": "fc_0dc9f371a6d55e3f016a13799ed5d081919364ca22e2913fcf", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" background_cache: dict[str, Image.Image] = {}\\n for scene_id, path in (plan.background_paths or {}).items():\\n background_cache[scene_id] = Image.open(path).convert(\\\"RGB\\\").resize((plan.width, plan.height), Image.Resampling.LANCZOS)\\n frame_index = 0\",\"old_string\":\" background = None\\n if plan.background_path:\\n background = Image.open(plan.background_path).convert(\\\"RGB\\\").resize((plan.width, plan.height), Image.Resampling.LANCZOS)\\n frame_index = 0\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n@@ -244,9 +244,9 @@\\n frame_dir.mkdir(parents=True, exist_ok=True)\\n Path(plan.output_dir).mkdir(parents=True, exist_ok=True)\\n frame_paths: list[str] = []\\n- background = None\\n- if plan.background_path:\\n- background = Image.open(plan.background_path).convert(\\\"RGB\\\").resize((plan.width, plan.height), Image.Resampling.LANCZOS)\\n+ background_cache: dict[str, Image.Image] = {}\\n+ for scene_id, path in (plan.background_paths or {}).items():\\n+ background_cache[scene_id] = Image.open(path).convert(\\\"RGB\\\").resize((plan.width, plan.height), Image.Resampling.LANCZOS)\\n frame_index = 0\\n for scene in plan.final_plan.scenes:\\n scene_duration = (scene.end_ms - scene.start_ms) / 1000\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}, \"lsp_diagnostics\": \"LSP diagnostics introduced by this edit:\\n\\nERROR [258:69] \\\"background\\\" is not defined [reportUndefinedVariable] (Pyright)\\n\"}", "tool_call_id": "call_dZBGrfzxUwzxeLWyinBDiapx", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_SWU85D9IIAn6hxbwJRzADU3f", "call_id": "call_SWU85D9IIAn6hxbwJRzADU3f", "response_item_id": "fc_0dc9f371a6d55e3f016a1379a681308191b51fda55685f8035", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" image = _render_scene(plan, scene, progress, background=background_cache.get(scene.scene_id))\",\"old_string\":\" image = _render_scene(plan, scene, progress, background=background)\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\\n@@ -255,7 +255,7 @@\\n count = min(count, max_frames_per_scene)\\n for local_index in range(count):\\n progress = local_index / max(1, count - 1)\\n- image = _render_scene(plan, scene, progress, background=background)\\n+ image = _render_scene(plan, scene, progress, background=background_cache.get(scene.scene_id))\\n path = frame_dir / f\\\"frame_{frame_index:05d}.png\\\"\\n image.save(path, format=\\\"PNG\\\")\\n frame_paths.append(str(path))\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/rendering/motion_renderer.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_SWU85D9IIAn6hxbwJRzADU3f", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_NhmasziwTi2SFk52drNk7kXC", "call_id": "call_NhmasziwTi2SFk52drNk7kXC", "response_item_id": "fc_0dc9f371a6d55e3f016a1379afa0808191bacc21eed89dfb48", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_scene_backgrounds.py tests/test_motion_renderer.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \".... [100%]\\n4 passed in 0.26s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_NhmasziwTi2SFk52drNk7kXC", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_ILSYCtEpYgXE4RjP8XbgruZl", "call_id": "call_ILSYCtEpYgXE4RjP8XbgruZl", "response_item_id": "fc_0dc9f371a6d55e3f016a1379b6deec8191931838939625f668", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nfrom pathlib import Path\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover\\nfrom autoshorts.rendering.final_video_plan import build_truetrace_weird_email_final_video_plan\\nfrom autoshorts.rendering.scene_backgrounds import build_chatgpt_image_scene_background_plan\\nvoiceover=build_truetrace_final_voiceover('truetrace-ai-automation-quiet-rot-38s')\\nplan=build_truetrace_weird_email_final_video_plan(voiceover)\\nbg=build_chatgpt_image_scene_background_plan(plan, output_dir='data/generated_backgrounds/truetrace-weird-email-v1')\\nfor asset in bg.assets:\\n print('---', asset.scene_id)\\n print(asset.output_path)\\n print(asset.prompt)\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "reasoning": "**Generating scene images**\n\nI'm thinking I need to generate 5 scene images. I could use the image generation tool, maybe in a sequential manner or through parallel execution. Although, I'm wondering if 5 is too many to handle at once. The parallel wrapper seems flexible enough to accommodate this, so I should explore how to best combine the image generation with the multi_tool capabilities. It feels like I have a few options here!", "reasoning_content": "**Generating scene images**\n\nI'm thinking I need to generate 5 scene images. I could use the image generation tool, maybe in a sequential manner or through parallel execution. Although, I'm wondering if 5 is too many to handle at once. The parallel wrapper seems flexible enough to accommodate this, so I should explore how to best combine the image generation with the multi_tool capabilities. It feels like I have a few options here!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3m2uWcunn_DHn229z6oz8aDxuCWJLakOFM5O4VgdZMD9SGqCK0xGDYDVaqFNZOc0JwmS2f19t-zWhd2Yo91n3Y2u9tFyM3jSHAHkMY4R5ZLnZ_PlzMFQ7fR5T0bKfqhu6XrhmwS9hcV6kRnAOBngDmsS8B_4-iZEHG-lwhoDmhI_K_x6xaZ2qmcgO3SXonGM7KyA1e7IjYJeZCAfSXmF36D74IsLO9qsSM-bmvsFvLpnva-OcO4-jxWmFzIDNmRv8YfRQD0QaXXEhmue3PsCObUZnzv276xC6CsShK0FM5Nhynma605JbbjLwLEryez0ddd1SCrSWYOVN_Lom7O9j3g1S8AzJMlEK3yx2pdIdBem9RYRDMWvH0KleR9NUWzv7470qYGSMD9PXo00sdJ2ku-bkc8TTsZffJuOLh8G4LJkxNRmmUuZ7WFn8BZcIFjTjnjvdBHoJ2XXN6-3iqVIPXIAeF7EN9odq1vs06lY82EhWVPOEtKOrjOXgffgvm4Qofp8Mje--Rzl_5w9Ab-DfVk234cRrPGK0KTPncFIdOzQjbS0MzeS0MVgSmW8_nNXiJSZuxSAiWIMSIVvSg5qHOITe9wllU6R0o1TzzFOFjx-861bDTvtMZWcVHNzFGSz0iV2CYVLguw8hIARhzam93b9vFqRKvUA3NSQdPUt-RNL7ZC187EYS0DBuWBzAIpzHTLfVH7eYHQ6H1Mw4usiTNbEW9lNgECy5yZETX4Os8lROsu-xJGozls09QaZyKl1O9pIG6-5iXYJOzsMw9fl8uL6I98O3DaUvJ42rfxjaH0jOWR0u0eR0-TQl4cmKTYpFT569s33a3Gt7vy6UJJ0b2R7rVBZ8zSYtrzaxhyemKJUEb_ce0eSsnLsst42zF7IGzMPOJzbp7dNwM3ZNWgBDUfjabZwv3MG5E-QtNU6X9LhBd-8p0E8zcA9F4lwE2VprExonDJhUHCbJPb6gsHkV1BcA3XFllvNAwiib5rDz3EkN4o59syqbO5hEZ1Vpla68WoxPvF9_kcjAOYDADVieErc3n_zbQL662-TEA1hD-jQDomHyKnx9AZGCeUHVsWBIrxW4IcgsCAusR1LngkYLQqBh3iRwexcJhCkE3X7yPusKsWLP0z6_clfQAwS_A4RPjTQSUi-u_gkdiVpHNw94f_pbgyNJAsGd-Ppy8GtOH30qtfmVS4ZjBlaKISBDkqFamq", "id": "rs_0dc9f371a6d55e3f016a1379b40d38819183131a03aada207d", "summary": [{"type": "summary_text", "text": "**Generating scene images**\n\nI'm thinking I need to generate 5 scene images. I could use the image generation tool, maybe in a sequential manner or through parallel execution. Although, I'm wondering if 5 is too many to handle at once. The parallel wrapper seems flexible enough to accommodate this, so I should explore how to best combine the image generation with the multi_tool capabilities. It feels like I have a few options here!"}]}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"--- clean-demo\\ndata/generated_backgrounds/truetrace-weird-email-v1/clean-demo.png\\nVertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: clean-demo. clean modern laptop workspace, calm inbox dashboard glow, orderly automation demo mood. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\\n--- weird-email\\ndata/generated_backgrounds/truetrace-weird-email-v1/weird-email.png\\nVertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: weird-email. slightly messy email-workflow atmosphere, amber warning mood, desk close-up, shallow depth of field. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\\n--- wrong-routing\\ndata/generated_backgrounds/truetrace-weird-email-v1/wrong-routing.png\\nVertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: wrong-routing. abstract AI routing node ambience, glowing path energy, subtle red warning tension. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\\n--- three-way-split\\ndata/generated_backgrounds/truetrace-weird-email-v1/three-way-split.png\\nVertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: three-way-split. minimal dark technical background with empty space for a three-branch diagram overlay. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\\n--- final-rule\\ndata/generated_backgrounds/truetrace-weird-email-v1/final-rule.png\\nVertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: final-rule. premium minimal blue-green abstract technology background, calm final-rule energy. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_ILSYCtEpYgXE4RjP8XbgruZl", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_pFRDLqpLGJkHDry4CmkhJWca", "call_id": "call_pFRDLqpLGJkHDry4CmkhJWca", "response_item_id": "fc_0dc9f371a6d55e3f016a1379c324c0819182dbe4d399324fd2", "type": "function", "function": {"name": "image_generate", "arguments": "{\"aspect_ratio\":\"portrait\",\"prompt\":\"Vertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: clean-demo. Clean modern laptop workspace, calm inbox dashboard glow, orderly automation demo mood. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\"}"}}, {"id": "call_8UlYJR4pKs6jrdwRfaZyQMBL", "call_id": "call_8UlYJR4pKs6jrdwRfaZyQMBL", "response_item_id": "fc_0dc9f371a6d55e3f016a1379c324d48191a3587831beae6e1c", "type": "function", "function": {"name": "image_generate", "arguments": "{\"aspect_ratio\":\"portrait\",\"prompt\":\"Vertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: weird-email. Slightly messy email-workflow atmosphere, amber warning mood, desk close-up, shallow depth of field. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\"}"}}, {"id": "call_3yMJt1JgYJ5845VWr4tc8C5O", "call_id": "call_3yMJt1JgYJ5845VWr4tc8C5O", "response_item_id": "fc_0dc9f371a6d55e3f016a1379c324e48191ac61cc7cb963ae64", "type": "function", "function": {"name": "image_generate", "arguments": "{\"aspect_ratio\":\"portrait\",\"prompt\":\"Vertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: wrong-routing. Abstract AI routing node ambience, glowing path energy, subtle red warning tension. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"image\": \"/home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260525_002134_d3c821b5.png\", \"model\": \"gpt-image-2-medium\", \"prompt\": \"Vertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: clean-demo. Clean modern laptop workspace, calm inbox dashboard glow, orderly automation demo mood. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\", \"aspect_ratio\": \"portrait\", \"provider\": \"openai-codex\", \"size\": \"1024x1536\", \"quality\": \"medium\"}", "tool_call_id": "call_pFRDLqpLGJkHDry4CmkhJWca", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"image\": \"/home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260525_002219_f22bec3f.png\", \"model\": \"gpt-image-2-medium\", \"prompt\": \"Vertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: weird-email. Slightly messy email-workflow atmosphere, amber warning mood, desk close-up, shallow depth of field. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\", \"aspect_ratio\": \"portrait\", \"provider\": \"openai-codex\", \"size\": \"1024x1536\", \"quality\": \"medium\"}", "tool_call_id": "call_8UlYJR4pKs6jrdwRfaZyQMBL", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"image\": \"/home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260525_002251_1dfe8a3e.png\", \"model\": \"gpt-image-2-medium\", \"prompt\": \"Vertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: wrong-routing. Abstract AI routing node ambience, glowing path energy, subtle red warning tension. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\", \"aspect_ratio\": \"portrait\", \"provider\": \"openai-codex\", \"size\": \"1024x1536\", \"quality\": \"medium\"}", "tool_call_id": "call_3yMJt1JgYJ5845VWr4tc8C5O", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_k2yx9mRbQvfGM7ZvtkLohNL4", "call_id": "call_k2yx9mRbQvfGM7ZvtkLohNL4", "response_item_id": "fc_0dc9f371a6d55e3f016a137a43cd6c8191b8fa244e00536149", "type": "function", "function": {"name": "image_generate", "arguments": "{\"aspect_ratio\":\"portrait\",\"prompt\":\"Vertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: three-way-split. Minimal dark technical background with empty space for a three-branch diagram overlay. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\"}"}}, {"id": "call_xGLRUpsMq3RQFPTPqLvRQQ5K", "call_id": "call_xGLRUpsMq3RQFPTPqLvRQQ5K", "response_item_id": "fc_0dc9f371a6d55e3f016a137a43cd808191a6510e7a6d31754a", "type": "function", "function": {"name": "image_generate", "arguments": "{\"aspect_ratio\":\"portrait\",\"prompt\":\"Vertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: final-rule. Premium minimal blue-green abstract technology background, calm final-rule energy. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"image\": \"/home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260525_002346_15f5da53.png\", \"model\": \"gpt-image-2-medium\", \"prompt\": \"Vertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: three-way-split. Minimal dark technical background with empty space for a three-branch diagram overlay. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\", \"aspect_ratio\": \"portrait\", \"provider\": \"openai-codex\", \"size\": \"1024x1536\", \"quality\": \"medium\"}", "tool_call_id": "call_k2yx9mRbQvfGM7ZvtkLohNL4", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"image\": \"/home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260525_002425_90559d8e.png\", \"model\": \"gpt-image-2-medium\", \"prompt\": \"Vertical 9:16 cinematic background for a TrueTrace AI automation short. Scene: final-rule. Premium minimal blue-green abstract technology background, calm final-rule energy. No readable text, no logos, no watermarks, no UI labels, no fake letters. Leave clean central negative space for renderer-owned cards, labels, arrows, and captions. Modern premium tech aesthetic, dark blue/green palette, realistic but not cluttered.\", \"aspect_ratio\": \"portrait\", \"provider\": \"openai-codex\", \"size\": \"1024x1536\", \"quality\": \"medium\"}", "tool_call_id": "call_xGLRUpsMq3RQFPTPqLvRQQ5K", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "Need copy to data/generated... use terminal cp? Use terminal for cp ok.", "tool_calls": [{"id": "call_FA9gKBoxzpkCINla2SKb950b", "call_id": "call_FA9gKBoxzpkCINla2SKb950b", "response_item_id": "fc_0dc9f371a6d55e3f016a137a9d7c2481919800507a39f02a83", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"mkdir -p data/generated_backgrounds/truetrace-weird-email-v1 && cp /home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260525_002134_d3c821b5.png data/generated_backgrounds/truetrace-weird-email-v1/clean-demo.png && cp /home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260525_002219_f22bec3f.png data/generated_backgrounds/truetrace-weird-email-v1/weird-email.png && cp /home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260525_002251_1dfe8a3e.png data/generated_backgrounds/truetrace-weird-email-v1/wrong-routing.png && cp /home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260525_002346_15f5da53.png data/generated_backgrounds/truetrace-weird-email-v1/three-way-split.png && cp /home/agent/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260525_002425_90559d8e.png data/generated_backgrounds/truetrace-weird-email-v1/final-rule.png && sha256sum data/generated_backgrounds/truetrace-weird-email-v1/*.png\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Need copy to data/generated... use terminal cp? Use terminal for cp ok."}], "id": "msg_0dc9f371a6d55e3f016a137a9cead0819183c54f2377ceaed6", "phase": "commentary"}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"bf5cb0ea87177d298be147ce00c998ee4d3b04f1c102b1934b286cc2b14117e5 data/generated_backgrounds/truetrace-weird-email-v1/clean-demo.png\\n27c2135bfa512c06f57e9676b36915199ded08d112864912ee390a7a8f1a56c9 data/generated_backgrounds/truetrace-weird-email-v1/final-rule.png\\n8b0c27c2039e0d3fffca7c3bec015df3fae54f167c32933563ec039a6860e3aa data/generated_backgrounds/truetrace-weird-email-v1/three-way-split.png\\ncd11aca663e55c6ee6e24aec3d60feb0cfc2973ed73f39eb7b3bbc66870b6fb5 data/generated_backgrounds/truetrace-weird-email-v1/weird-email.png\\nd6c8864c95295bd284a0b26ae7c32880b7ee689276c7588c56c05b8e288e462d data/generated_backgrounds/truetrace-weird-email-v1/wrong-routing.png\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_FA9gKBoxzpkCINla2SKb950b", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_2DpAR7jLruZCxxwmc7i8wQaw", "call_id": "call_2DpAR7jLruZCxxwmc7i8wQaw", "response_item_id": "fc_0dc9f371a6d55e3f016a137aabffec81918d59ed6c9c04d75c", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nfrom pathlib import Path\\nfrom math import ceil\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover\\nfrom autoshorts.audio.tts_plan import build_default_truetrace_tts_plan\\nfrom autoshorts.audio.edge_tts_adapter import EdgeTTSRequest, synthesize_edge_tts\\nfrom autoshorts.audio.probe import probe_media_duration_seconds\\nfrom autoshorts.audio.subtitles import build_hormozi_subtitle_track\\nfrom autoshorts.audio.final_preview import build_audio_caption_preview_plan, render_audio_caption_preview\\nfrom autoshorts.rendering.final_video_plan import build_truetrace_weird_email_final_video_plan\\nfrom autoshorts.rendering.scene_backgrounds import build_chatgpt_image_scene_background_plan\\nfrom autoshorts.rendering.motion_renderer import build_motion_render_plan, render_motion_preview\\ncandidate_id='truetrace-ai-automation-quiet-rot-38s'\\noutput_dir=Path('data/previews/truetrace-final-motion-v5')/candidate_id\\nvoiceover=build_truetrace_final_voiceover(candidate_id)\\nfinal_plan=build_truetrace_weird_email_final_video_plan(voiceover)\\nbg_plan=build_chatgpt_image_scene_background_plan(final_plan, output_dir='data/generated_backgrounds/truetrace-weird-email-v1')\\nbackground_paths={asset.scene_id: asset.output_path for asset in bg_plan.assets}\\nmotion=render_motion_preview(build_motion_render_plan(final_plan, output_dir=output_dir, preview_scale=0.5, background_paths=background_paths))\\nif motion.returncode: raise SystemExit(motion.stderr)\\nvoice=synthesize_edge_tts(EdgeTTSRequest(text=voiceover.text, tts_plan=build_default_truetrace_tts_plan(), output_path=str(output_dir/'voice.mp3')))\\naudio_duration=probe_media_duration_seconds(voice.output_path)\\nsubtitles=build_hormozi_subtitle_track(voiceover.text, total_duration_seconds=ceil(audio_duration))\\nfinal=render_audio_caption_preview(build_audio_caption_preview_plan(video_path=motion.output_path,audio_path=voice.output_path,subtitle_track=subtitles,output_path=output_dir/'final-motion-audio-caption-preview.mp4',duration_mode='trim_to_audio'))\\nif final.returncode: raise SystemExit(final.stderr)\\nprint('final', final.output_path)\\nprint('frames', len(motion.frame_paths))\\nprint('backgrounds', len(background_paths))\\nprint('audio_duration', f'{audio_duration:.3f}')\\nPY\\nrm -rf /tmp/truetrace_review_v5 && mkdir -p /tmp/truetrace_review_v5 && ffmpeg -y -i data/previews/truetrace-final-motion-v5/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4 -vf \\\"select='eq(n,0)+eq(n,120)+eq(n,300)+eq(n,520)+eq(n,760)'\\\" -vsync 0 /tmp/truetrace_review_v5/frame_%02d.png >/dev/null 2>&1\\nffprobe -v error -show_entries stream=codec_type,codec_name,width,height,duration -of default=noprint_wrappers=1 data/previews/truetrace-final-motion-v5/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\nsha256sum data/previews/truetrace-final-motion-v5/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": 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autoshorts/rendering/scene_backgrounds.py\\n?? tests/test_scene_backgrounds.py\\n.gitignore:27:*.png\\tdata/generated_backgrounds/truetrace-weird-email-v1/clean-demo.png\\n.gitignore:20:data/previews/\\tdata/previews/truetrace-final-motion-v5/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_geqO6YqiedLHVXiwxJkyMCns", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_WUb3Lscm9fEi6779Ex5lY6AV", "call_id": "call_WUb3Lscm9fEi6779Ex5lY6AV", "response_item_id": "fc_0dc9f371a6d55e3f016a137b34fd9c8191bdfbf2ca3df3373e", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"- `autoshorts.rendering.scene_backgrounds` — scene-specific ChatGPT Image/Codex background prompt plans that explicitly forbid readable text/logos and require renderer-owned overlays.\\n- `autoshorts.rendering.motion_renderer` — procedural motion preview renderer for inbox cards, warning routes, and three-path mechanism diagrams before heavier AI-video work.\",\"old_string\":\"- `autoshorts.rendering.motion_renderer` — procedural motion preview renderer for inbox cards, warning routes, and three-path mechanism diagrams before heavier AI-video work.\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"}"}}], "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3s0PuMKSLqobwkYCcVFQxPgdd2yzl7gdsJmHTo8SDoB0pTk4ntll0_sicutjUudrgRsV4ErpwpZCi78lu4GxWaEp6eD4GEVRR80ttB1-XjpfQEYO4qD4L1JmYLpV7Ao10kYbg2S6qrl_6LLbwkEM8aAMPnbpPkFoFyJWCnNBBc0dkMwkUL3zOOlZIN1eG-X_SJAr_6Be7DKQnkRDgO50QknVV6V_G0RWVx9V5p9kxRzmWXVvfMfcsbFS9RF7xqD2I9wLg5r7GKSlUPobuWoa8LdYC-IeC_zkmmQlE44I86N1Sz0Ytf0QfyMekexbMnxJoiXGnRjTaZF3KgKBqgKspeatvG_6LtonhlDKO3kDah9K2wPoXzdM-Ytb1KygQxhM3KsTYo6wRoKyar0P8qK_529MOC_JQD_W10xhTWFa13n1qBXUWRhHbiJx1wgTYreVrDXt9ez7EPshJZThvZtuSs_X-prMbTn_qSikpnU7ZbwK29J0Q1aa0TmwtQP2KLL2GFAvELYvvCZ7-zQG2jlmfpBjflPuBL_v00qzg0n8HtShDtg-mYjDC9y5weu51EUFVTVXdz4TkQ2iYzU2R1ETFrvNzLazzsE7XL3UUjITuQVCRvSIlugVhOeRqStOAQlmCfc6vBzy7s-A4QX3aNtXZArgDWn8moF3TKZ_LDOjGq_a5wOOFqj0aUyolrJ7TS7WRUvi9HDRS5mrIwJAqLBlrUKcU9y7MKfNtL36R7q0syZ9u7w6zqwgSvP0-szkeKBUvr_uryLJGvm3sw9ANK3u_znh_CkCgzvzgOTKLZ_JAtZxZNjmSXFJEp9pL-cd7_Fhbcasncpu2kk-XSAh5traHEkxwn_PvTAdu0H1bE9m_pMLnU2qZUhOdhqv1BhRAJEF2fF2um8TA4zlNnme1o9AcoVmvNaNbntQU5VNngYgDmI5h0=", "id": "rs_0dc9f371a6d55e3f016a137b3441cc819185419833c8c5aceb", "summary": []}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\\n@@ -36,6 +36,7 @@\\n - `autoshorts.strategy.score` — follower-conversion strategy scoring for hook, curiosity, identity, emotion, trust, follow reason, originality, and variety.\\n - `autoshorts.strategy.series` — public-safe series registry and hard no-go validation before public content advances.\\n - `autoshorts.rendering.final_video_plan` — final-near 1080x1920 production plans that keep AI visuals text-free and renderer-owned.\\n+- `autoshorts.rendering.scene_backgrounds` — scene-specific ChatGPT Image/Codex background prompt plans that explicitly forbid readable text/logos and require renderer-owned overlays.\\n - `autoshorts.rendering.motion_renderer` — procedural motion preview renderer for inbox cards, warning routes, and three-path mechanism diagrams before heavier AI-video work.\\n - `autoshorts.rendering.ffmpeg_plan` — side-effect-free FFmpeg concat planning for local preview frames.\\n - `autoshorts.rendering.ffmpeg_renderer` — explicit FFmpeg boundary that writes concat files and MP4 timing previews.\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .md files\"}}", "tool_call_id": "call_WUb3Lscm9fEi6779Ex5lY6AV", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_oq42p9H6FCkYGKZM4HX0vSeW", "call_id": "call_oq42p9H6FCkYGKZM4HX0vSeW", "response_item_id": "fc_0dc9f371a6d55e3f016a137b3ccad881919538a5e587d75975", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"- Next polish should improve subtitle phrasing/timing around the three-way split and optionally replace the single static background with per-scene generated backgrounds or short I2V texture clips.\\n\\n## V5 update\\n\\n`autoshorts.rendering.scene_backgrounds.build_chatgpt_image_scene_background_plan()` now creates one text-free ChatGPT Image/Codex prompt per production scene. The motion renderer accepts a `background_paths` mapping so each scene can use its own background while keeping all text, arrows, cards, labels, and captions deterministic.\\n\\nCurrent v5 review artifact:\\n\\n```text\\ndata/previews/truetrace-final-motion-v5/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\n```\\n\\nV5 uses five generated backgrounds under:\\n\\n```text\\ndata/generated_backgrounds/truetrace-weird-email-v1/\\n```\\n\\nThese media files remain ignored by Git.\",\"old_string\":\"- Next polish should improve subtitle phrasing/timing around the three-way split and optionally replace the single static background with per-scene generated backgrounds or short I2V texture clips.\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\\n@@ -65,3 +65,21 @@\\n - The three-way split scene has been visually checked so arrows sit behind labels and subtitles do not critically overlap the mechanism.\\n - The prototype is still a review prototype, not a final public export.\\n - Next polish should improve subtitle phrasing/timing around the three-way split and optionally replace the single static background with per-scene generated backgrounds or short I2V texture clips.\\n+\\n+## V5 update\\n+\\n+`autoshorts.rendering.scene_backgrounds.build_chatgpt_image_scene_background_plan()` now creates one text-free ChatGPT Image/Codex prompt per production scene. The motion renderer accepts a `background_paths` mapping so each scene can use its own background while keeping all text, arrows, cards, labels, and captions deterministic.\\n+\\n+Current v5 review artifact:\\n+\\n+```text\\n+data/previews/truetrace-final-motion-v5/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\n+```\\n+\\n+V5 uses five generated backgrounds under:\\n+\\n+```text\\n+data/generated_backgrounds/truetrace-weird-email-v1/\\n+```\\n+\\n+These media files remain ignored by Git.\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .md files\"}}", "tool_call_id": "call_oq42p9H6FCkYGKZM4HX0vSeW", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_OAX84oquAYyLxLEnDzzDv0mY", "call_id": "call_OAX84oquAYyLxLEnDzzDv0mY", "response_item_id": "fc_0dc9f371a6d55e3f016a137b47f8d48191b5257cd921c65f16", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/ -q\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"........................................................................ [ 42%]\\n........................................................................ [ 85%]\\n........................ [100%]\\n168 passed in 33.05s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_OAX84oquAYyLxLEnDzzDv0mY", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "tool_calls": [{"id": "call_dqUZuukPEO5ZeunD33jS2FNf", "call_id": "call_dqUZuukPEO5ZeunD33jS2FNf", "response_item_id": "fc_0dc9f371a6d55e3f016a137b6eb5688191a04af12da465a047", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"git status --short && git add autoshorts/rendering/scene_backgrounds.py autoshorts/rendering/motion_renderer.py tests/test_scene_backgrounds.py tests/test_motion_renderer.py README.md docs/final_motion_prototype.md && git commit -m \\\"feat: add scene-specific motion backgrounds\\\" && git status --short && git log --oneline -5\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "finish_reason": "tool_calls", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "content": "{\"output\": \"M README.md\\n M autoshorts/rendering/motion_renderer.py\\n M docs/final_motion_prototype.md\\n M tests/test_motion_renderer.py\\n?? autoshorts/rendering/scene_backgrounds.py\\n?? tests/test_scene_backgrounds.py\\n[feat/core-approval-quality-gates db200ae] feat: add scene-specific motion backgrounds\\n 6 files changed, 187 insertions(+), 12 deletions(-)\\n create mode 100644 autoshorts/rendering/scene_backgrounds.py\\n create mode 100644 tests/test_scene_backgrounds.py\\ndb200ae feat: add scene-specific motion backgrounds\\n14310f9 feat: add TrueTrace final motion prototype\\n7375311 feat: make TrueTrace pilot beginner friendly\\nb9b6423 feat: align TrueTrace voiceover previews\\n3f68001 feat: add EdgeTTS audio caption preview\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_dqUZuukPEO5ZeunD33jS2FNf", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "Erledigt, Sir.\n\n## Weitergebaut: Scene-specific ChatGPT Image Backgrounds\n\nIch habe den Motion-Prototypen von **einem generischen Hintergrund** auf **5 szenenspezifische ChatGPT Image/Codex Backgrounds** erweitert.\n\nNeuer Commit:\n\n```text\ndb200ae feat: add scene-specific motion backgrounds\n```\n\n## Neu gebaut\n\n### Neues Modul\n\n```text\nautoshorts/rendering/scene_backgrounds.py\n```\n\n### Neue Tests\n\n```text\ntests/test_scene_backgrounds.py\n```\n\n### Erweitert\n\n```text\nautoshorts/rendering/motion_renderer.py\n```\n\nDer Renderer kann jetzt pro Szene ein eigenes Hintergrundbild verwenden:\n\n```python\nbackground_paths = {\n \"clean-demo\": \".../clean-demo.png\",\n \"weird-email\": \".../weird-email.png\",\n \"wrong-routing\": \".../wrong-routing.png\",\n \"three-way-split\": \".../three-way-split.png\",\n \"final-rule\": \".../final-rule.png\",\n}\n```\n\n## Was generiert wurde\n\nIch habe über ChatGPT Image/Codex 5 textfreie Backgrounds erzeugt:\n\n```text\ndata/generated_backgrounds/truetrace-weird-email-v1/clean-demo.png\ndata/generated_backgrounds/truetrace-weird-email-v1/weird-email.png\ndata/generated_backgrounds/truetrace-weird-email-v1/wrong-routing.png\ndata/generated_backgrounds/truetrace-weird-email-v1/three-way-split.png\ndata/generated_backgrounds/truetrace-weird-email-v1/final-rule.png\n```\n\nAlle Prompts erzwingen:\n\n```text\nno readable text\nno logos\nno watermarks\nno UI labels\nrenderer-owned overlays\n```\n\nAlso: AI macht Atmosphäre, Renderer macht Wahrheit. So wie es sein sollte.\n\n## Neuer V5 Review Clip\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-final-motion-v5/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\n\n## Technische Verifikation\n\n```text\nVideo: h264\nSize: 540x960\nDuration: 36.833s\nAudio: aac\nAudio duration: 36.864s\nFrames: 887\nBackgrounds: 5\n```\n\nSHA256:\n\n```text\nac8432ef5285abaa8bdb662610184cea491d3b1951dc9b2f2b6dd5a9f4ea9143\n```\n\n## Visuelle QA\n\nIch habe zwei kritische Szenen geprüft:\n\n### Weird Email Scene\n\nStatus:\n\n```text\nReadable: yes\nRenderer text clear: yes\nNo critical clipping: yes\nAI background has no problematic readable fake text/logos\n```\n\n### Three-way Split Scene\n\nStatus:\n\n```text\nNormal → Go through\nUnclear → Review\nWeird/Risky → Stop\n```\n\nIst lesbar, die Pfeile liegen hinter den Labels, und das wirkt jetzt deutlich mehr wie ein Mechanism Reveal statt nur Karten-Slideshow.\n\n## Tests\n\nFull Suite:\n\n```text\n168 passed in 33.05s\n```\n\n## Aktueller Verlauf\n\n```text\ndb200ae feat: add scene-specific motion backgrounds\n14310f9 feat: add TrueTrace final motion prototype\n7375311 feat: make TrueTrace pilot beginner friendly\nb9b6423 feat: align TrueTrace voiceover previews\n3f68001 feat: add EdgeTTS audio caption preview\n```\n\n## Nächster sinnvoller Schritt\n\nJetzt würde ich als nächstes **Caption/Subtitle Timing und Layout polieren**, weil der Clip visuell langsam brauchbar wird.\n\nKonkret:\n\n```text\n1. Subtitle chunks bei der 3-way-split Szene kürzer machen\n2. Subtitles etwas höher/kompakter setzen\n3. Key scene text nicht mit subtitles konkurrieren lassen\n4. Danach 1080x1920 Export erzeugen\n```\n\nDann hätten wir einen ernsthaften First-Public-Candidate statt nur einen technischen Prototypen mit Hut.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3t2F-_Er3cVzFodpMfwbhBEL9eMW-gFrvOeD43SESsWfTcmzRy3PU_adsfqz3vU0Rwu4KAmC5_G58g7OnbesrKVT82RZJ33iPqamCUs-G_e08x--IQcegEOFa2Hlt2LEN42NH1OTjLYOQ9QuoGP05WoJRcrJTh1a_PkB-cdGPbj_KmQ0lVLi9lCcwFcg7yd19RcApx550E6CLRppHtj-317hzyWVMpxuNmzsXBdDxOY10V6yuabJuVTaKHA-kTsic9MUk_PtNiaoxBOp9y9VemZWgg6bvDQo0pMTdgleDr_Fk8M_X4LHREmDDnrdKkuGEgpk6rnHXEJwcjVEy0Ut9x5O-ICDFiAhU7CtKptrue4FYvL_4II1iK0iS7obLgFOLiD5PwPX8zoQFHCcPL6ZqFBAKTXV_o00ag_FjBzVroXlPvuAOlnDyQjMnWVLYTOPi9fZu7PsBJ8tKGA-H3LajSkKzAsweNGMsG2ZkjgWYFCtCdtJpoho0hZs7pu0A-G_mNK6LNOtzQ7HrgLK0L14eharhngTl--Yz-s9CGDS0NHOQd-54PrjTJc3JwVARYbFTnCmQI7zRL9pjFAsN-_h8Df5h-0Yjyt-yy9-0AsQZbjR1ti010kcC_EyfFSYSqv47AcAA0aKccBueEOak2l1kKztR1iN5FdtLzi1woygoImAREBLN1R5Y3dzz3gwk5FA3ewHdW3PFJQc4v1-Kc30oFJtVV1HdGQN7WSy7C4tsKBq4_vvgGqUD98LYoOnM7LG7-Ou75jjFBQT1XIcxFAzxXiulwwv4zL5Z87-LqwSqHNncFuOzgnAONWVVeslevY4evU0OhV2KgKMQSs38XFc3jt5xI_bVezLghdUFwN8BkaZTpnyHz1iae6u3VyjH1W3XvkDV6CTN1-dwKauP-AeAhzBhKtVT5A51TBbGndmViBS6TOVbgPaOfmLZLjadR0p1j54AnUnO2qGberiA596WQi981eaPTP9Ut_swPXDmjHyTqdTkWvRPRkbCdjXrd3PH9Qcm_-kizkcZKY0pT9aXYfKQ==", "id": "rs_0dc9f371a6d55e3f016a137b7575248191928fa3c78d37f97b", "summary": []}], "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Erledigt, Sir.\n\n## Weitergebaut: Scene-specific ChatGPT Image Backgrounds\n\nIch habe den Motion-Prototypen von **einem generischen Hintergrund** auf **5 szenenspezifische ChatGPT Image/Codex Backgrounds** erweitert.\n\nNeuer Commit:\n\n```text\ndb200ae feat: add scene-specific motion backgrounds\n```\n\n## Neu gebaut\n\n### Neues Modul\n\n```text\nautoshorts/rendering/scene_backgrounds.py\n```\n\n### Neue Tests\n\n```text\ntests/test_scene_backgrounds.py\n```\n\n### Erweitert\n\n```text\nautoshorts/rendering/motion_renderer.py\n```\n\nDer Renderer kann jetzt pro Szene ein eigenes Hintergrundbild verwenden:\n\n```python\nbackground_paths = {\n \"clean-demo\": \".../clean-demo.png\",\n \"weird-email\": \".../weird-email.png\",\n \"wrong-routing\": \".../wrong-routing.png\",\n \"three-way-split\": \".../three-way-split.png\",\n \"final-rule\": \".../final-rule.png\",\n}\n```\n\n## Was generiert wurde\n\nIch habe über ChatGPT Image/Codex 5 textfreie Backgrounds erzeugt:\n\n```text\ndata/generated_backgrounds/truetrace-weird-email-v1/clean-demo.png\ndata/generated_backgrounds/truetrace-weird-email-v1/weird-email.png\ndata/generated_backgrounds/truetrace-weird-email-v1/wrong-routing.png\ndata/generated_backgrounds/truetrace-weird-email-v1/three-way-split.png\ndata/generated_backgrounds/truetrace-weird-email-v1/final-rule.png\n```\n\nAlle Prompts erzwingen:\n\n```text\nno readable text\nno logos\nno watermarks\nno UI labels\nrenderer-owned overlays\n```\n\nAlso: AI macht Atmosphäre, Renderer macht Wahrheit. So wie es sein sollte.\n\n## Neuer V5 Review Clip\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-final-motion-v5/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\n\n## Technische Verifikation\n\n```text\nVideo: h264\nSize: 540x960\nDuration: 36.833s\nAudio: aac\nAudio duration: 36.864s\nFrames: 887\nBackgrounds: 5\n```\n\nSHA256:\n\n```text\nac8432ef5285abaa8bdb662610184cea491d3b1951dc9b2f2b6dd5a9f4ea9143\n```\n\n## Visuelle QA\n\nIch habe zwei kritische Szenen geprüft:\n\n### Weird Email Scene\n\nStatus:\n\n```text\nReadable: yes\nRenderer text clear: yes\nNo critical clipping: yes\nAI background has no problematic readable fake text/logos\n```\n\n### Three-way Split Scene\n\nStatus:\n\n```text\nNormal → Go through\nUnclear → Review\nWeird/Risky → Stop\n```\n\nIst lesbar, die Pfeile liegen hinter den Labels, und das wirkt jetzt deutlich mehr wie ein Mechanism Reveal statt nur Karten-Slideshow.\n\n## Tests\n\nFull Suite:\n\n```text\n168 passed in 33.05s\n```\n\n## Aktueller Verlauf\n\n```text\ndb200ae feat: add scene-specific motion backgrounds\n14310f9 feat: add TrueTrace final motion prototype\n7375311 feat: make TrueTrace pilot beginner friendly\nb9b6423 feat: align TrueTrace voiceover previews\n3f68001 feat: add EdgeTTS audio caption preview\n```\n\n## Nächster sinnvoller Schritt\n\nJetzt würde ich als nächstes **Caption/Subtitle Timing und Layout polieren**, weil der Clip visuell langsam brauchbar wird.\n\nKonkret:\n\n```text\n1. Subtitle chunks bei der 3-way-split Szene kürzer machen\n2. Subtitles etwas höher/kompakter setzen\n3. Key scene text nicht mit subtitles konkurrieren lassen\n4. Danach 1080x1920 Export erzeugen\n```\n\nDann hätten wir einen ernsthaften First-Public-Candidate statt nur einen technischen Prototypen mit Hut."}], "id": "msg_0dc9f371a6d55e3f016a137b7620ac8191baba54b46da38aac", "phase": "final_answer"}], "finish_reason": "stop", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "user", "content": "[M G] Ok, mach das.", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": "**Inspecting tests for audio subtitles**\n\nI need to check the audio subtitles and the final preview to ensure everything is functioning correctly. This might involve looking closely at how well the subtitles align with the audio and if there are any discrepancies. It's important to make sure that viewers can follow along without confusion. I'll go through each segment carefully to make sure everything matches up as intended. Let's ensure quality control here!", "finish_reason": "tool_calls", "reasoning_content": "**Inspecting tests for audio subtitles**\n\nI need to check the audio subtitles and the final preview to ensure everything is functioning correctly. This might involve looking closely at how well the subtitles align with the audio and if there are any discrepancies. It's important to make sure that viewers can follow along without confusion. I'll go through each segment carefully to make sure everything matches up as intended. 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Let's ensure quality control here!"}]}], "tool_calls": [{"id": "call_Nx9dYLECsOdfzGZvPg4CNE9h", "call_id": "call_Nx9dYLECsOdfzGZvPg4CNE9h", "response_item_id": "fc_0dc9f371a6d55e3f016a137c120b78819186242767d590c2b2", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"test-driven-development\"}"}}, {"id": "call_ELqWNWsNoccFmdb112u3GoJV", "call_id": "call_ELqWNWsNoccFmdb112u3GoJV", "response_item_id": "fc_0dc9f371a6d55e3f016a137c120b9081919f294286cc3d8a6a", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"social-media-shorts-automation\"}"}}, {"id": "call_om5VNap6L0g2cWrmOx3EwNNh", "call_id": "call_om5VNap6L0g2cWrmOx3EwNNh", "response_item_id": "fc_0dc9f371a6d55e3f016a137c120b988191a6242dadf27f3139", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_subtitles.py\",\"limit\":220}"}}, {"id": "call_uxa0GyUflPzLV3iP1n5FJeqN", "call_id": "call_uxa0GyUflPzLV3iP1n5FJeqN", "response_item_id": "fc_0dc9f371a6d55e3f016a137c120bb481918fe3b08e61e97b3d", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\",\"limit\":240}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "skill_view", "content": "{\"success\": true, \"name\": \"test-driven-development\", \"description\": \"TDD: enforce RED-GREEN-REFACTOR, tests before code.\", \"tags\": [\"testing\", \"tdd\", \"development\", \"quality\", \"red-green-refactor\"], \"related_skills\": [\"systematic-debugging\", \"writing-plans\", \"subagent-driven-development\"], \"content\": \"---\\nname: test-driven-development\\ndescription: \\\"TDD: enforce RED-GREEN-REFACTOR, tests before code.\\\"\\nversion: 1.1.0\\nauthor: Hermes Agent (adapted from obra/superpowers)\\nlicense: MIT\\nplatforms: [linux, macos, windows]\\nmetadata:\\n hermes:\\n tags: [testing, tdd, development, quality, red-green-refactor]\\n related_skills: [systematic-debugging, writing-plans, subagent-driven-development]\\n---\\n\\n# Test-Driven Development (TDD)\\n\\n## Overview\\n\\nWrite the test first. Watch it fail. Write minimal code to pass.\\n\\n**Core principle:** If you didn't watch the test fail, you don't know if it tests the right thing.\\n\\n**Violating the letter of the rules is violating the spirit of the rules.**\\n\\n## When to Use\\n\\n**Always:**\\n- New features\\n- Bug fixes\\n- Refactoring\\n- Behavior changes\\n\\n**Exceptions (ask the user first):**\\n- Throwaway prototypes\\n- Generated code\\n- Configuration files\\n\\nThinking \\\"skip TDD just this once\\\"? Stop. That's rationalization.\\n\\n## The Iron Law\\n\\n```\\nNO PRODUCTION CODE WITHOUT A FAILING TEST FIRST\\n```\\n\\nWrite code before the test? Delete it. Start over.\\n\\n**No exceptions:**\\n- Don't keep it as \\\"reference\\\"\\n- Don't \\\"adapt\\\" it while writing tests\\n- Don't look at it\\n- Delete means delete\\n\\nImplement fresh from tests. Period.\\n\\n## Red-Green-Refactor Cycle\\n\\n### RED — Write Failing Test\\n\\nWrite one minimal test showing what should happen.\\n\\n**Good test:**\\n```python\\ndef test_retries_failed_operations_3_times():\\n attempts = 0\\n def operation():\\n nonlocal attempts\\n attempts += 1\\n if attempts < 3:\\n raise Exception('fail')\\n return 'success'\\n\\n result = retry_operation(operation)\\n\\n assert result == 'success'\\n assert attempts == 3\\n```\\nClear name, tests real behavior, one thing.\\n\\n**Bad test:**\\n```python\\ndef test_retry_works():\\n mock = MagicMock()\\n mock.side_effect = [Exception(), Exception(), 'success']\\n result = retry_operation(mock)\\n assert result == 'success' # What about retry count? Timing?\\n```\\nVague name, tests mock not real code.\\n\\n**Requirements:**\\n- One behavior per test\\n- Clear descriptive name (\\\"and\\\" in name? Split it)\\n- Real code, not mocks (unless truly unavoidable)\\n- Name describes behavior, not implementation\\n\\n### Verify RED — Watch It Fail\\n\\n**MANDATORY. Never skip.**\\n\\n```bash\\n# Use terminal tool to run the specific test\\npytest tests/test_feature.py::test_specific_behavior -v\\n```\\n\\nConfirm:\\n- Test fails (not errors from typos)\\n- Failure message is expected\\n- Fails because the feature is missing\\n\\n**Test passes immediately?** You're testing existing behavior. Fix the test.\\n\\n**Test errors?** Fix the error, re-run until it fails correctly.\\n\\n### GREEN — Minimal Code\\n\\nWrite the simplest code to pass the test. Nothing more.\\n\\n**Good:**\\n```python\\ndef add(a, b):\\n return a + b # Nothing extra\\n```\\n\\n**Bad:**\\n```python\\ndef add(a, b):\\n result = a + b\\n logging.info(f\\\"Adding {a} + {b} = {result}\\\") # Extra!\\n return result\\n```\\n\\nDon't add features, refactor other code, or \\\"improve\\\" beyond the test.\\n\\n**Cheating is OK in GREEN:**\\n- Hardcode return values\\n- Copy-paste\\n- Duplicate code\\n- Skip edge cases\\n\\nWe'll fix it in REFACTOR.\\n\\n### Verify GREEN — Watch It Pass\\n\\n**MANDATORY.**\\n\\n```bash\\n# Run the specific test\\npytest tests/test_feature.py::test_specific_behavior -v\\n\\n# Then run ALL tests to check for regressions\\npytest tests/ -q\\n```\\n\\nConfirm:\\n- Test passes\\n- Other tests still pass\\n- Output pristine (no errors, warnings)\\n\\n**Test fails?** Fix the code, not the test.\\n\\n**Other tests fail?** Fix regressions now.\\n\\n### REFACTOR — Clean Up\\n\\nAfter green only:\\n- Remove duplication\\n- Improve names\\n- Extract helpers\\n- Simplify expressions\\n\\nKeep tests green throughout. Don't add behavior.\\n\\n**If tests fail during refactor:** Undo immediately. Take smaller steps.\\n\\n### Repeat\\n\\nNext failing test for next behavior. One cycle at a time.\\n\\n## Why Order Matters\\n\\n**\\\"I'll write tests after to verify it works\\\"**\\n\\nTests written after code pass immediately. Passing immediately proves nothing:\\n- Might test the wrong thing\\n- Might test implementation, not behavior\\n- Might miss edge cases you forgot\\n- You never saw it catch the bug\\n\\nTest-first forces you to see the test fail, proving it actually tests something.\\n\\n**\\\"I already manually tested all the edge cases\\\"**\\n\\nManual testing is ad-hoc. You think you tested everything but:\\n- No record of what you tested\\n- Can't re-run when code changes\\n- Easy to forget cases under pressure\\n- \\\"It worked when I tried it\\\" ≠ comprehensive\\n\\nAutomated tests are systematic. They run the same way every time.\\n\\n**\\\"Deleting X hours of work is wasteful\\\"**\\n\\nSunk cost fallacy. The time is already gone. Your choice now:\\n- Delete and rewrite with TDD (high confidence)\\n- Keep it and add tests after (low confidence, likely bugs)\\n\\nThe \\\"waste\\\" is keeping code you can't trust.\\n\\n**\\\"TDD is dogmatic, being pragmatic means adapting\\\"**\\n\\nTDD IS pragmatic:\\n- Finds bugs before commit (faster than debugging after)\\n- Prevents regressions (tests catch breaks immediately)\\n- Documents behavior (tests show how to use code)\\n- Enables refactoring (change freely, tests catch breaks)\\n\\n\\\"Pragmatic\\\" shortcuts = debugging in production = slower.\\n\\n**\\\"Tests after achieve the same goals — it's spirit not ritual\\\"**\\n\\nNo. Tests-after answer \\\"What does this do?\\\" Tests-first answer \\\"What should this do?\\\"\\n\\nTests-after are biased by your implementation. You test what you built, not what's required. Tests-first force edge case discovery before implementing.\\n\\n## Common Rationalizations\\n\\n| Excuse | Reality |\\n|--------|---------|\\n| \\\"Too simple to test\\\" | Simple code breaks. Test takes 30 seconds. |\\n| \\\"I'll test after\\\" | Tests passing immediately prove nothing. |\\n| \\\"Tests after achieve same goals\\\" | Tests-after = \\\"what does this do?\\\" Tests-first = \\\"what should this do?\\\" |\\n| \\\"Already manually tested\\\" | Ad-hoc ≠ systematic. No record, can't re-run. |\\n| \\\"Deleting X hours is wasteful\\\" | Sunk cost fallacy. Keeping unverified code is technical debt. |\\n| \\\"Keep as reference, write tests first\\\" | You'll adapt it. That's testing after. Delete means delete. |\\n| \\\"Need to explore first\\\" | Fine. Throw away exploration, start with TDD. |\\n| \\\"Test hard = design unclear\\\" | Listen to the test. Hard to test = hard to use. |\\n| \\\"TDD will slow me down\\\" | TDD faster than debugging. Pragmatic = test-first. |\\n| \\\"Manual test faster\\\" | Manual doesn't prove edge cases. You'll re-test every change. |\\n| \\\"Existing code has no tests\\\" | You're improving it. Add tests for the code you touch. |\\n\\n## Red Flags — STOP and Start Over\\n\\nIf you catch yourself doing any of these, delete the code and restart with TDD:\\n\\n- Code before test\\n- Test after implementation\\n- Test passes immediately on first run\\n- Can't explain why test failed\\n- Tests added \\\"later\\\"\\n- Rationalizing \\\"just this once\\\"\\n- \\\"I already manually tested it\\\"\\n- \\\"Tests after achieve the same purpose\\\"\\n- \\\"Keep as reference\\\" or \\\"adapt existing code\\\"\\n- \\\"Already spent X hours, deleting is wasteful\\\"\\n- \\\"TDD is dogmatic, I'm being pragmatic\\\"\\n- \\\"This is different because...\\\"\\n\\n**All of these mean: Delete code. Start over with TDD.**\\n\\n## Verification Checklist\\n\\nBefore marking work complete:\\n\\n- [ ] Every new function/method has a test\\n- [ ] Watched each test fail before implementing\\n- [ ] Each test failed for expected reason (feature missing, not typo)\\n- [ ] Wrote minimal code to pass each test\\n- [ ] All tests pass\\n- [ ] Output pristine (no errors, warnings)\\n- [ ] Tests use real code (mocks only if unavoidable)\\n- [ ] Edge cases and errors covered\\n\\nCan't check all boxes? You skipped TDD. Start over.\\n\\n## When Stuck\\n\\n| Problem | Solution |\\n|---------|----------|\\n| Don't know how to test | Write the wished-for API. Write the assertion first. Ask the user. |\\n| Test too complicated | Design too complicated. Simplify the interface. |\\n| Must mock everything | Code too coupled. Use dependency injection. |\\n| Test setup huge | Extract helpers. Still complex? Simplify the design. |\\n\\n## Hermes Agent Integration\\n\\n### Running Tests\\n\\nUse the `terminal` tool to run tests at each step:\\n\\n```python\\n# RED — verify failure\\nterminal(\\\"pytest tests/test_feature.py::test_name -v\\\")\\n\\n# GREEN — verify pass\\nterminal(\\\"pytest tests/test_feature.py::test_name -v\\\")\\n\\n# Full suite — verify no regressions\\nterminal(\\\"pytest tests/ -q\\\")\\n```\\n\\n### CLI Entry Points\\n\\nFor new `python -m package.cli.command` style entry points, keep the TDD loop boring and side-effect free:\\n\\n1. Write a test that imports `main` from the missing CLI module and calls `main([])`.\\n2. Capture stdout/stderr with the project test framework (`capsys` in pytest) or inject a `stdout` file-like object if supported.\\n3. RED should usually be an import failure for the missing CLI module/package, not a vague end-to-end shell failure.\\n4. Implement `main(argv: Sequence[str] | None = None, *, stdout: TextIO | None = None) -> int` so tests can call it without spawning a subprocess.\\n5. Add the `if __name__ == \\\"__main__\\\": raise SystemExit(main())` guard only after the callable path is green.\\n6. Verify both the unit test and the real module invocation, e.g. `python -m package.cli.command`, before committing.\\n\\nThis catches command wiring while avoiding accidental network calls, publishing actions, or other theatrical nonsense masquerading as a CLI test.\\n\\n### With delegate_task\\n\\nWhen dispatching subagents for implementation, enforce TDD in the goal:\\n\\n```python\\ndelegate_task(\\n goal=\\\"Implement [feature] using strict TDD\\\",\\n context=\\\"\\\"\\\"\\n Follow test-driven-development skill:\\n 1. Write failing test FIRST\\n 2. Run test to verify it fails\\n 3. Write minimal code to pass\\n 4. Run test to verify it passes\\n 5. Refactor if needed\\n 6. Commit\\n\\n Project test command: pytest tests/ -q\\n Project structure: [describe relevant files]\\n \\\"\\\"\\\",\\n toolsets=['terminal', 'file']\\n)\\n```\\n\\n### With systematic-debugging\\n\\nBug found? Write failing test reproducing it. Follow TDD cycle. The test proves the fix and prevents regression.\\n\\nNever fix bugs without a test.\\n\\n## Demo / Fixture Features\\n\\nWhen adding a deterministic demo fixture for later integration wiring, still use RED-GREEN-REFACTOR. Write the wished-for import/API in the test first, verify the missing module/API failure, then implement the smallest fixture that proves the real workflow path. Assert stable IDs/order, bucket counts/classifications, and safety invariants such as review text not implying publication. See `references/deterministic-demo-fixtures.md` for the concise pattern.\\n\\n## Side-Effect-Free Integration Boundaries\\n\\nWhen building toward an external integration (Telegram, email, publishing APIs, render farms, payment flows, etc.), add a tested preparation boundary before any real I/O:\\n\\n1. Write the wished-for pure function in the test first, e.g. `prepare_review_delivery(text) -> DeliveryPlan`.\\n2. RED should be a missing module/API or missing validation failure, not a real network/send failure.\\n3. The GREEN implementation should return a typed/dataclass plan object with explicit metadata: destination/topic, delivery type, human-approval requirement, and `side_effects=()`.\\n4. Validate safety constraints at the boundary: non-empty content, platform size limits, no forbidden action language, no implicit approval, no credentials or generated media unless explicitly expected.\\n5. Add a demo CLI only after the pure boundary is green. The CLI should print metadata first, then payload, and still perform no external I/O.\\n6. Verify both the unit tests and a real `python -m package.cli.demo_*` invocation before committing.\\n\\nThis pattern lets later sending/rendering/publishing adapters consume a boring, audited object instead of smuggling side effects into formatting code. Boring is how we avoid building a content catapult with a moustache.\\n\\n### Media / Rendering Pipeline Boundaries\\n\\nWhen building toward image/video generation or renderer integration, add deterministic planning artifacts before any GPU/API work:\\n\\n1. Write tests for the wished-for pure API first, e.g. `create_shot_plan(script)`, `build_render_manifest(plan)`, `build_local_preview_plan(manifest)`, or `build_ffmpeg_concat_plan(plan, frames, output_path)`.\\n2. RED should be a missing module/API or missing validation behavior — never a failed ComfyUI/Wan/Qwen/API invocation.\\n3. Keep each stage inspectable and side-effect-free until the explicit adapter layer: `ScriptDraft -> ShotPlan -> RenderManifest -> PreviewPlan/PreviewArtifact -> renderer adapter`.\\n4. Assert stable IDs/order, scene counts, timing continuity, vertical settings (`1080x1920`, `30fps` when building Shorts/Reels/TikTok), reduced preview settings (`540x960`, `24fps` when building fast local timing previews), and placeholder/runtime paths before generating media.\\n5. Add guardrail tests that reject static slideshows, baked-in/generated text inside assets, non-renderer-owned captions/labels, unsafe render settings, missing fields, bad timings, non-PNG frame paths, non-MP4 output paths, and mismatched frame counts.\\n6. Split artifact-writing/rendering into explicit boundaries after the pure plans are green: frame writer returns `side_effects=(\\\"write_png\\\",)`, concat planning remains side-effect-free, and the FFmpeg renderer returns `side_effects=(\\\"write_concat\\\", \\\"call_ffmpeg\\\", \\\"write_mp4\\\")` plus `external_calls=(\\\"ffmpeg\\\",)`.\\n7. Only after the manifest/preview boundary is green should a later adapter call local GPU tools or external services. Planning first; GPU roulette later.\\n\\nThis prevents wasting render time on unclear direction and keeps expensive media generation behind a small, audited boundary.\\n\\n### Approval-First Media/Social Pipelines\\n\\nWhen a feature crosses from content planning toward media/social delivery, prefer many small RED-GREEN-README-COMMIT slices instead of one large integration jump:\\n\\n1. typed artifact/model (`SocialMediaDraft`, `RenderManifest`, etc.)\\n2. renderer/formatter for human review text\\n3. side-effect-free delivery/preparation boundary\\n4. demo CLI that prints metadata first, then payload\\n\\nFor each slice, write the missing import/API test first, verify the expected import/API failure, implement only that slice, run the focused test, run the full suite, update docs, and commit. Keep invariant tests explicit: `requires_human_approval=True`, `side_effects=()`, no external calls, no credential access, no file writes unless that adapter is the explicit feature, and no accidental action language such as `publish`/`post` in review/delivery text.\\n\\nThis staged approach keeps approval semantics auditable and prevents a later renderer, Telegram sender, or platform adapter from being smuggled into formatting code.\\n\\n## Testing Anti-Patterns\\n\\n- **Testing mock behavior instead of real behavior** — mocks should verify interactions, not replace the system under test\\n- **Testing implementation details** — test behavior/results, not internal method calls\\n- **Happy path only** — always test edge cases, errors, and boundaries\\n- **Brittle tests** — tests should verify behavior, not structure; refactoring shouldn't break them\\n- **Substring sentinels that collide with generated IDs** — when asserting that amounts or fixture values are excluded from a result, assert the full formatted token (e.g. `999.00`) or a typed field, not a short substring like `999` that can appear inside UUIDs/hash-like IDs.\\n- **Domain classes named `Test*` trigger pytest collection warnings** — if a production dataclass/model must be named like `TestBatch`, set `__test__ = False` on the class or choose a non-`Test` prefix. Keep the fix in production code when the name is part of the domain language, and verify the warning is gone before committing.\\n- **Defaulting with `x or default` hides invalid explicit inputs** — when a factory/test helper accepts optional overrides, use `x if x is not None else default` so tests can pass intentionally blank strings (`\\\"\\\"`) or zero values and watch validation reject them. Otherwise invalid-input tests may silently receive defaults and give false confidence.\\n\\n## Final Rule\\n\\n```\\nProduction code → test exists and failed first\\nOtherwise → not TDD\\n```\\n\\nNo exceptions without the user's explicit permission.\\n\", \"path\": \"software-development/test-driven-development/SKILL.md\", \"skill_dir\": \"/home/agent/.hermes/skills/software-development/test-driven-development\", \"linked_files\": {\"references\": [\"references/deterministic-demo-fixtures.md\", \"references/side-effect-free-delivery-boundaries.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"hermes\": {\"tags\": [\"testing\", \"tdd\", \"development\", \"quality\", \"red-green-refactor\"], \"related_skills\": [\"systematic-debugging\", \"writing-plans\", \"subagent-driven-development\"]}}}", "tool_call_id": "call_Nx9dYLECsOdfzGZvPg4CNE9h", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "skill_view", "content": "{\"success\": true, \"name\": \"social-media-shorts-automation\", \"description\": \"Design, generate, review, publish, and optimize automated short-form social videos across YouTube Shorts, TikTok, Instagram Reels, and related channels.\", \"tags\": [\"shorts\", \"tiktok\", \"youtube-shorts\", \"reels\", \"creator-monetization\", \"content-automation\", \"social-media\"], \"related_skills\": [], \"content\": \"---\\nname: social-media-shorts-automation\\ndescription: Design, generate, review, publish, and optimize automated short-form social videos across YouTube Shorts, TikTok, Instagram Reels, and related channels.\\nversion: 1.0.0\\ntags: [shorts, tiktok, youtube-shorts, reels, creator-monetization, content-automation, social-media]\\n---\\n\\n# Social-Media Shorts Automation\\n\\nUse this skill when building or operating systems that generate short-form social videos, especially faceless or semi-automated pipelines for YouTube Shorts, TikTok, Instagram Reels, Facebook Reels, Pinterest video pins, X video, or LinkedIn video.\\n\\n## Core principle\\n\\nTreat the system as a **Shorts Growth Engine** / **semi-automatic Retention Studio**, not merely a renderer. A working video generator can still fail if it produces generic, low-retention, AI-slop content. Optimize for audience identity, hook quality, retention mechanics, visual mechanism reveals, platform fit, and analytics feedback. For the user's strongest strategic direction, see `references/retention-studio-strategy.md`.\\n\\nFor this user's AutoShorts workflows, approval previews should be German for concept comprehension, while final social-media videos should remain English unless explicitly changed. Treat preview legibility as a quality gate: readable font sizes, pixel-width-aware line wrapping, no clipped words, and no overcrowded cards.\\n\\n## Retention-Studio / Mechanism-Reveal Pipeline\\n\\nFor quality-first automated Shorts, especially Hidden Money & AI Systems concepts, prefer the pipeline documented in `references/retention-studio-pipeline-pattern.md`:\\n\\n```text\\nstrategy → scored ideas → mechanism explainer → shot plan → keyframe/I2V prompt plan → seeded clip jobs → clip review → deterministic final renderer\\n```\\n\\nWhen implementing a new repo or core pipeline, first scaffold the approval-first typed artifact chain in `references/approval-first-retention-studio-core.md`:\\n\\n```text\\nContentPillar → ContentBrief → ScriptDraft → VideoCandidate → TestBatch → ReviewBatch → Telegram ReviewDelivery → ShotPlan\\n```\\n\\nHard rule for this class: AI-video clips provide photorealistic texture and motion only. Captions, numbers, labels, arrows, UI text, price/risk/margin layers, and factual claims are renderer-owned. Final content should keep `static_card_limit = 0`, use visual changes every 1–2 seconds, and reject technically successful clips that do not serve the retention beat.\\n\\nBefore video generation, build an inspectable content-to-review spine: `ContentBrief → ScriptDraft → CandidateDraft → VideoCandidate → TestBatch → ReviewBatch → Telegram ReviewDelivery`. Keep it deterministic, side-effect free, and human-approval-first so hooks, retention beats, visual concepts, policy notes, and review copy can be optimized before spending GPU/API time. See `references/content-to-review-pipeline.md` for the implementation pattern and guardrails.\\n\\nHard rule for this class: AI-video clips provide photorealistic texture and motion only. Captions, numbers, labels, arrows, UI text, price/risk/margin layers, and factual claims are renderer-owned. Final content should keep `static_card_limit = 0`, use visual changes every 1–2 seconds, and reject technically successful clips that do not serve the retention beat.\\n\\n## Recommended workflow\\n\\n1. **Define channel position**\\n - Niche(s): e.g. life optimization, AI life systems, Christian faith/FaithTok.\\n - Target audience and emotional problem.\\n - Language and tone.\\n - Whether the brand is faceless, AI-persona-led, or creator-led.\\n - No-go topics and theological/ethical boundaries if faith-related.\\n\\n2. **Generate test ideas before code-heavy automation**\\n - Create 20–30 candidate ideas across 2–4 content pillars.\\n - For each: hook, script kernel, visual concept, caption, CTA, risk/quality score.\\n - Select a small first batch (e.g. 3 per pillar) for real testing.\\n - Before renderers or external AI APIs, add a deterministic content-development core: `ContentPillar → ContentBrief → ScriptDraft → CandidateDraft → VideoCandidate`. See `references/content-development-core.md`.\\n\\n3. **Use hook-first, retention-led scripting**\\n - First 1–2 seconds must contain a clear tension, identity statement, pain point, contrarian line, or immediate self-recognition.\\n - Prefer one idea per video over generic “4 tips” unless the list format is the explicit series.\\n - Avoid generic advice viewers have already heard unless framed with a new angle, concrete payoff, or strong story.\\n - Reward hooks with direct address, specificity, open loops, tension, and a visible payoff; reject slow intros such as “In this video...”.\\n - See `references/retention-led-shorts.md` for scoring signals, penalties, and voiceover finalization rules.\\n\\n4. **Quality gate before rendering**\\n Score drafts on:\\n - hook strength\\n - novelty\\n - emotional pull\\n - clarity\\n - retention risk\\n - comment/share potential\\n - AI-slop risk\\n - platform/policy risk\\n Render only drafts above the chosen threshold, e.g. 8/10.\\n\\n5. **Visual strategy**\\n - Avoid obvious AI artifacts, fake UI text, illegible generated lettering, generic charts, and soulless stock visuals.\\n - Prefer high-contrast kinetic captions, visible hook text in first seconds, relatable B-roll, screen recordings for AI/tutorial content, phone/screen close-ups, before/after transformations, cards, and timer visuals.\\n - Use pattern interrupts every 2–3 seconds for retention.\\n - Before rendering, generate a shot plan from the finalized voiceover: first-frame hook, pattern interrupt, core explanation, screen/card visual, CTA, caption beats, and asset type.\\n - Before writing a renderer, convert shot plans into deterministic render manifests: machine-readable timeline items, asset placeholders, caption tracks, style constraints, and approval constraints. See `references/render-manifest-pipeline.md`.\\n - Treat this as a deterministic intermediate artifact, not optional prose. See `references/retention-render-planning.md` for the five-scene shot-plan pattern and renderer-facing fields.\\n - For the first video output, build a manifest-driven preview renderer before any AI-video or polished asset pipeline: first create a side-effect-free local preview plan, then write deterministic PNG scene cards, then build a side-effect-free FFmpeg concat plan, and only then call FFmpeg from an explicit renderer boundary. The boundary should report side effects such as `write_png`, `write_concat`, `call_ffmpeg`, and `write_mp4`; keep generated PNG/MP4 artifacts out of Git. See `references/manifest-preview-renderer.md`.\\n - When the user rejects static/slideshow output, add an `asset_plan.v2` layer that maps each scene to motion-led local asset modes such as `cinematic_ai_video`, `screen_recording_simulation`, `mechanism_animation`, or `kinetic_text_overlay` with no baked text. If the user requires a free workflow, do not depend on paid video-credit tools; use local procedural motion and optional free NVIDIA LLM text refinement. See `references/ai-video-asset-planning.md`.\\n - For hybrid workflows, add an imported-clip assembly layer: provider handoff prompts create short manual AI-video clips, humans drop them into deterministic `data/imported_ai_clips//scene_XX.mp4` paths, and the final renderer combines imported clips with local mechanism animations/captions. See `references/imported-ai-clip-assembly.md`.\\n - For local Wan2.2 quality workflows, prefer keyframe/image-to-video over raw text-to-video: generate/select a clean keyframe, run native Wan2.2 I2V variants, review clips bluntly for subject clarity/motion/artifacts, then add all labels/numbers/captions via deterministic renderer. See `references/wan-i2v-retention-studio.md`.\\n - When using NVIDIA Build/API Catalog for keyframes, prefer hosted `ai.api.nvidia.com` calls before considering self-hosted NIM deployment; implement a configurable model fallback chain, store the key as a runtime secret, and inspect/clean logos, emblems, license plates, and fake text before I2V. See `references/nvidia-keyframe-generation.md`.\\n\\n6. **Social-media draft and content-preview approval packages before TTS/rendering polish**\\n - Before TTS, platform APIs, or polished video generation, build a typed `SocialMediaDraft` from the approved candidate plus render manifest/preview.\\n - Include platform targets, title variants, caption, hashtags, CTA, hook, duration, quality/risk summary, and preview reference.\\n - Render this into a Telegram-safe approval message and wrap it in a side-effect-free delivery plan with `requires_human_approval=True` and `side_effects=()`.\\n - After a local MP4 timing preview exists, combine the MP4 path plus social draft review into a side-effect-free content preview approval package. This package should carry `approval_language=de`, `final_video_language=en`, explicit approval commands, no external calls, and no side effects.\\n - Add local demo CLIs that print metadata first, then review text; draft-only CLIs must not write files, call renderers, call Telegram, or access credentials. MP4 preview CLIs may write local artifacts and call FFmpeg only at explicit renderer boundaries that report side effects.\\n - See `references/social-draft-approval-package.md` and `references/content-automation-patterns.md` for concrete artifact sequence, user-specific language rules, and external workflow patterns.\\n\\n7. **Human approval loop before posting**\\n - Send preview to the user through the requested channel, usually Telegram.\\n - Include: video or preview reference, title, caption, hashtags, platform recommendation, duration, quality/risk score.\\n - When sending multiple preview videos, verify and label distinct artifacts before delivery: candidate ID/title, absolute path, duration, and preferably checksum/hash. If several previews are visually similar timing cards, do not spam them as separate unlabeled media; send a concise indexed list first or bundle with clear labels so the user can tell them apart.\\n - Wait for explicit approval such as `Freigabe alle`, `Freigabe YouTube`, `Freigabe TikTok`, `Ablehnen`, or `Ändern: ...`.\\n - Do not publish automatically unless the user has explicitly authorized that workflow.\\n\\n8. **TTS / voice layer after draft approval**\\n - Treat TTS as a later layer, not the starting point for a first post draft.\\n - Decide voice, final voiceover script, words-per-second, scene timing, caption sync, audio format, provider, and separate voice approval only after the social draft package is reviewable.\\n - This avoids spending TTS/rendering effort on unapproved hooks, captions, or platform positioning.\\n - For final-near previews, keep one copy source of truth: final voiceover → script draft/retention beats → shot plan → top card text → scene captions → subtitle track → TTS audio. Do not mix old approval-card text with new spoken/subtitle text.\\n - If the user says the result is too abstract/abgehoben, rewrite around a concrete beginner-friendly everyday failure example before polishing visuals. Prefer “one weird email arrives” / missing field / unclear request / wrong confident action over jargon such as `exception path`, `input boundary`, or `output standard`. See `references/beginner-friendly-audio-caption-alignment.md`.\\n\\n9. **Publish and measure**\\n Track at minimum:\\n - platform, video id/url, niche, format, hook, duration\\n - views at 2h/24h/7d\\n - likes, comments, shares, saves, follows\\n - retention metrics if available\\n Use results to generate the next batch.\\n\\n## Platform duration/monetization notes\\n\\nSee `references/preview-media-delivery-guardrails.md` for avoiding duplicate-looking/unlabeled preview-video spam in Telegram review workflows.\\n\\nSee `references/audio-caption-preview-pipeline.md` for the approval-first EdgeTTS + ASS subtitles + FFmpeg review-MP4 pipeline, including actual-audio-duration probing and the explicit `preserve_video` vs `trim_to_audio` duration-mode guardrail.\\n\\nSee `references/final-motion-hybrid-rendering.md` for the final-near hybrid renderer pattern: ChatGPT Image/Codex or other AI tools provide text-free background/keyframe texture while deterministic renderer overlays own text, arrows, labels, captions, and final assembly.\\n\\nSee `references/monetization-and-approval-notes.md` for current working notes captured from official YouTube/TikTok docs and the recommended approval/posting setup. See `references/retention-led-shorts.md` for retention scoring signals, no-faith/adjacent-pillar handling, and voiceover finalization rules. See `references/render-manifest-pipeline.md` for the script → shot plan → render manifest → renderer sequence that prevents generic AI slideshow output. See `references/manifest-preview-renderer.md` for the first deterministic Pillow/FFmpeg preview-renderer pattern. See `references/local-preview-frame-writer.md` for the staged `LocalPreviewPlan → PNG scene cards → FFmpeg concat plan` boundary before MP4 rendering. See `references/social-draft-approval-package.md` for the typed first-post approval package to build before TTS or platform APIs. See `references/content-automation-patterns.md` for public workflow patterns, queue/status/cost tracking, versioned approval, synthetic-content disclosure, originality gates, and the user's German-preview/English-final rule. See `references/ai-video-asset-planning.md` for motion-led final-render asset planning with Kling/Hailuo/Runway-style clips and screen simulations. See `references/imported-ai-clip-assembly.md` for hybrid assembly where manually generated provider clips are imported into a deterministic local renderer. See `references/nvidia-keyframe-generation.md` for NVIDIA-hosted keyframe generation, model fallback, secret handling, and pre-I2V logo/plate cleanup. Re-check official docs before making business-critical decisions because platform programs change often.\\n\\n## Project/repo hygiene for automated video bots\\n\\n- Keep source code in Git; keep generated videos, assets, `.env`, OAuth tokens, API keys, and downloaded secrets out of Git.\\n- Use `.gitignore` aggressively for outputs, media caches, local credentials, and temp files.\\n- Store platform credentials as runtime secrets; never print raw tokens.\\n- Build the repo as modular components: idea generation, scripting, rendering, review, publishing, analytics.\\n- For approval-first Retention Studio implementations, use a typed side-effect-free core before real I/O: `ContentBrief`, `ScriptDraft`, `VideoCandidate`, review batches, Telegram delivery plans, then shot plans. See `references/approval-first-retention-studio-core.md`.\\n\\n## Sensitive-content positioning\\n\\nWhen AI/productivity automation is the primary brand, be cautious about mixing in religious/FaithTok, health, finance, or other high-trust themes. If the user flags the combination as sensitive, pause that pillar rather than forcing it into the same testbatch. Replace it with a safer adjacent pillar (for example `attention_design`) and document the paused pillar in config so it can be revisited only with explicit approval and a separate brand strategy.\\n\\n## Pitfalls\\n\\n- Do not send several generated preview videos as unlabeled media attachments just because they are distinct files. Telegram/mobile previews can make timing-card MP4s look identical. Verify uniqueness (path + title + hash/duration) and provide labels or an indexed summary; if the user complains about duplicate-looking media, stop resending, verify artifacts, and continue the pipeline.\\n- Do not let final-near preview layers drift apart: if the top field, voiceover, and subtitles do not say the same thing, rebuild the render plan from one final script source before sending another clip.\\n- Do not make broad-audience AI-system shorts sound like architecture lectures. For early-AI users, convert abstract workflow concepts into concrete everyday failures first, then reveal the principle.\\n- Do not over-optimize renderer quality before testing whether the content format earns retention.\\n- Do not let German approval previews become unreadable technical cards: use pixel-width-aware wrapping, readable fonts, limited line counts, and visual checks for clipped/overcrowded text.\\n- Do not confuse approval language with final audience language. For this user, approval previews are German by default; final social videos remain English unless explicitly changed.\\n- Do not copy public automation workflows wholesale: keep their queue/status/cost tracking and template structure, but remove blind auto-publishing until a human approval/version lock exists.\\n- Do not mass-generate repetitive shorts without originality/inauthentic-content gates; this can harm monetization/account health and create AI slop.\\n- Do not jump directly from a script idea to ComfyUI/Wan/Qwen/Image/video generation. First build and inspect the content-to-review spine so weak hooks, generic scripts, policy issues, and static visual concepts are killed before render time.\\n- Do not create a parallel candidate path for content experiments; convert content artifacts into the existing candidate factory input so IDs, hashtags, duration classes, quality gates, and pillar/platform validation stay centralized.\\n- Do not use `x or default` for optional content/script overrides in factories; explicit blank strings and zero durations must pass through to validation so tests can catch them.\\n- Do not assume TikTok monetization rules match YouTube: TikTok Creator Rewards emphasizes 1min+ eligible videos, while shorter videos may still be better for growth.\\n- Do not publish religious or health-adjacent content with overconfident claims; preserve humility, nuance, and platform safety.\\n- Do not rely on platform payout as the only monetization path; plan indirect monetization such as newsletter, templates, affiliates, digital products, or services.\", \"path\": \"social-media/social-media-shorts-automation/SKILL.md\", \"skill_dir\": \"/home/agent/.hermes/skills/social-media/social-media-shorts-automation\", \"linked_files\": {\"references\": [\"references/wan-i2v-retention-studio.md\", \"references/render-manifest-pipeline.md\", \"references/retention-studio-strategy.md\", \"references/social-draft-approval-package.md\", \"references/approval-first-retention-studio-core.md\", \"references/local-preview-frame-writer.md\", \"references/preview-media-delivery-guardrails.md\", \"references/manifest-preview-renderer.md\", \"references/content-development-core.md\", \"references/ai-video-asset-planning.md\", \"references/approval-first-content-pipeline.md\", \"references/beginner-friendly-audio-caption-alignment.md\", \"references/audio-caption-preview-pipeline.md\", \"references/retention-studio-pipeline-pattern.md\", \"references/monetization-and-approval-notes.md\", \"references/content-to-review-pipeline.md\", \"references/retention-led-shorts.md\", \"references/final-motion-hybrid-rendering.md\", \"references/imported-ai-clip-assembly.md\", \"references/content-automation-patterns.md\", \"references/retention-render-planning.md\", \"references/nvidia-keyframe-generation.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\"}", "tool_call_id": "call_ELqWNWsNoccFmdb112u3GoJV", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "read_file", "content": "{\"content\": \"\", \"total_lines\": 0, \"file_size\": 0, \"truncated\": false, \"is_binary\": false, \"is_image\": false, \"error\": \"File not found: /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_subtitles.py\", \"similar_files\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_probe.py\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_brand_profile.py\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_content_brief.py\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_demo_review_batch_cli.py\"]}", "tool_call_id": "call_om5VNap6L0g2cWrmOx3EwNNh", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "read_file", "content": "{\"content\": \" 1|from pathlib import Path\\n 2|import subprocess\\n 3|\\n 4|from autoshorts.audio.final_preview import (\\n 5| AudioCaptionPreviewPlan,\\n 6| build_audio_caption_preview_plan,\\n 7| render_audio_caption_preview,\\n 8| validate_audio_caption_preview_plan,\\n 9|)\\n 10|from autoshorts.audio.subtitles import build_hormozi_subtitle_track\\n 11|\\n 12|\\n 13|def test_build_audio_caption_preview_plan_is_side_effect_free_and_writes_ass_content(tmp_path):\\n 14| video_path = tmp_path / \\\"timing.mp4\\\"\\n 15| audio_path = tmp_path / \\\"voice.mp3\\\"\\n 16| track = build_hormozi_subtitle_track(\\\"Most AI automations quietly rot when workflows lack boundaries\\\", total_duration_seconds=5)\\n 17|\\n 18| plan = build_audio_caption_preview_plan(\\n 19| video_path=video_path,\\n 20| audio_path=audio_path,\\n 21| subtitle_track=track,\\n 22| output_path=tmp_path / \\\"final-preview.mp4\\\",\\n 23| )\\n 24|\\n 25| assert plan.video_path == str(video_path)\\n 26| assert plan.audio_path == str(audio_path)\\n 27| assert plan.output_path.endswith(\\\"final-preview.mp4\\\")\\n 28| assert plan.subtitle_file_path.endswith(\\\"final-preview.ass\\\")\\n 29| assert plan.duration_mode == \\\"preserve_video\\\"\\n 30| assert \\\"[Script Info]\\\" in plan.subtitle_file_content\\n 31| assert \\\"Dialogue:\\\" in plan.subtitle_file_content\\n 32| assert \\\"MOST AI AUTOMATIONS\\\" in plan.subtitle_file_content\\n 33| assert plan.side_effects == ()\\n 34| assert plan.external_calls == ()\\n 35|\\n 36|\\n 37|def test_validate_audio_caption_preview_plan_rejects_bad_paths_and_unsafe_side_effects(tmp_path):\\n 38| track = build_hormozi_subtitle_track(\\\"valid subtitle text\\\", total_duration_seconds=2)\\n 39| plan = AudioCaptionPreviewPlan(\\n 40| video_path=\\\"video.mov\\\",\\n 41| audio_path=\\\"voice.wav\\\",\\n 42| output_path=\\\"out.avi\\\",\\n 43| subtitle_file_path=\\\"out.srt\\\",\\n 44| subtitle_file_content=\\\"\\\",\\n 45| subtitle_track=track,\\n 46| duration_mode=\\\"shortest\\\",\\n 47| side_effects=(\\\"write_file\\\",),\\n 48| external_calls=(\\\"ffmpeg\\\",),\\n 49| )\\n 50|\\n 51| validation = validate_audio_caption_preview_plan(plan)\\n 52|\\n 53| assert validation.is_valid is False\\n 54| assert \\\"video_path must end with .mp4\\\" in validation.errors\\n 55| assert \\\"audio_path must end with .mp3\\\" in validation.errors\\n 56| assert \\\"output_path must end with .mp4\\\" in validation.errors\\n 57| assert \\\"subtitle_file_path must end with .ass\\\" in validation.errors\\n 58| assert \\\"duration_mode must be preserve_video or trim_to_audio\\\" in validation.errors\\n 59| assert \\\"audio caption preview plans must not have side effects\\\" in validation.errors\\n 60|\\n 61|\\n 62|def test_build_audio_caption_preview_plan_can_explicitly_trim_to_audio(tmp_path):\\n 63| track = build_hormozi_subtitle_track(\\\"Prompt is not system workflow boundaries matter\\\", total_duration_seconds=4)\\n 64|\\n 65| plan = build_audio_caption_preview_plan(\\n 66| video_path=tmp_path / \\\"timing.mp4\\\",\\n 67| audio_path=tmp_path / \\\"voice.mp3\\\",\\n 68| subtitle_track=track,\\n 69| output_path=tmp_path / \\\"final.mp4\\\",\\n 70| duration_mode=\\\"trim_to_audio\\\",\\n 71| )\\n 72|\\n 73| assert plan.duration_mode == \\\"trim_to_audio\\\"\\n 74| assert plan.side_effects == ()\\n 75| assert plan.external_calls == ()\\n 76|\\n 77|\\n 78|def test_render_audio_caption_preview_preserves_video_duration_by_default(tmp_path):\\n 79| input_video = tmp_path / \\\"timing.mp4\\\"\\n 80| audio = tmp_path / \\\"voice.mp3\\\"\\n 81| output = tmp_path / \\\"final.mp4\\\"\\n 82| input_video.write_bytes(b\\\"fake video\\\")\\n 83| audio.write_bytes(b\\\"fake audio\\\")\\n 84| track = build_hormozi_subtitle_track(\\\"Prompt is not system workflow boundaries matter\\\", total_duration_seconds=4)\\n 85| plan = build_audio_caption_preview_plan(\\n 86| video_path=input_video,\\n 87| audio_path=audio,\\n 88| subtitle_track=track,\\n 89| output_path=output,\\n 90| )\\n 91| calls = []\\n 92|\\n 93| def fake_runner(command, *, capture_output, text, check):\\n 94| calls.append(command)\\n 95| output.write_bytes(b\\\"fake final video\\\")\\n 96| return subprocess.CompletedProcess(command, 0, stdout=\\\"ok\\\", stderr=\\\"\\\")\\n 97|\\n 98| result = render_audio_caption_preview(plan, runner=fake_runner)\\n 99|\\n 100| assert Path(plan.subtitle_file_path).exists()\\n 101| assert output.exists()\\n 102| assert calls[0][:5] == [\\\"ffmpeg\\\", \\\"-y\\\", \\\"-i\\\", str(input_video), \\\"-i\\\"]\\n 103| assert \\\"ass=\\\" in \\\" \\\".join(calls[0])\\n 104| assert \\\"-shortest\\\" not in calls[0]\\n 105| assert result.output_path == str(output)\\n 106| assert result.duration_mode == \\\"preserve_video\\\"\\n 107| assert result.side_effects == (\\\"write_subtitles\\\", \\\"call_ffmpeg\\\", \\\"write_mp4\\\")\\n 108| assert result.external_calls == (\\\"ffmpeg\\\",)\\n 109|\\n 110|\\n 111|def test_render_audio_caption_preview_trims_only_when_explicit(tmp_path):\\n 112| input_video = tmp_path / \\\"timing.mp4\\\"\\n 113| audio = tmp_path / \\\"voice.mp3\\\"\\n 114| output = tmp_path / \\\"final.mp4\\\"\\n 115| input_video.write_bytes(b\\\"fake video\\\")\\n 116| audio.write_bytes(b\\\"fake audio\\\")\\n 117| track = build_hormozi_subtitle_track(\\\"Prompt is not system workflow boundaries matter\\\", total_duration_seconds=4)\\n 118| plan = build_audio_caption_preview_plan(\\n 119| video_path=input_video,\\n 120| audio_path=audio,\\n 121| subtitle_track=track,\\n 122| output_path=output,\\n 123| duration_mode=\\\"trim_to_audio\\\",\\n 124| )\\n 125| calls = []\\n 126|\\n 127| def fake_runner(command, *, capture_output, text, check):\\n 128| calls.append(command)\\n 129| output.write_bytes(b\\\"fake final video\\\")\\n 130| return subprocess.CompletedProcess(command, 0, stdout=\\\"ok\\\", stderr=\\\"\\\")\\n 131|\\n 132| result = render_audio_caption_preview(plan, runner=fake_runner)\\n 133|\\n 134| assert \\\"-shortest\\\" in calls[0]\\n 135| assert result.duration_mode == \\\"trim_to_audio\\\"\\n 136|\", \"total_lines\": 135, \"file_size\": 5287, \"truncated\": false, \"is_binary\": false, 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It sounds like a good place to start. I'll have to make sure I'm searching in the right locations to find this file quickly. If I can locate it, that should help me with whatever I'm working on. Let's see if I can track it down!", "finish_reason": "tool_calls", "reasoning_content": "**Searching for subtitle tests**\n\nI need to look for a subtitle tests file, possibly named \"test_subtitle_tts.\" I wonder if that's the right filename. It sounds like a good place to start. I'll have to make sure I'm searching in the right locations to find this file quickly. If I can locate it, that should help me with whatever I'm working on. Let's see if I can track it down!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3wXMrudMQqy6zDnZ4OSyVS--L9Rvdxk3QVhtcy4fl42RtNTHvz_swHyoy_dsA8qDJieIgk3ss3tj4C6he-fqpNrUCrAHcE0I83QW0LkcRpSstBKkzv4V2FCOSNYkuZeGH3ZyU-oKpSXzpt5I7LstSXs4Uk4JQFii-NMwyT0nK1yATEQSrEckSvV3tQ4gJ_SB9B7QqMOpDVxzcy--akfcMcxFmWk1nOdPPkPOSaFs9VkhlUGvkxt--XX1gF-TtLKgX_MobuZigIHDPa0gze_PJxvM5VYlLWU6rhZeQWvk7xAd24y8AfAhvZFbGrD7izr95BgzfFgRczIsF3vAlP5Wbjri-dieYhc9UhHVLeAgmsoETdbo_TrOrd2DYnWIfnD9TKZT9G-BDI9TRVK0JRwcHlsDH3N-To4wO8fXN5EwyP_FY-w5Mx3fw-LAITDt5EthFmUdrDzC1-wzsTUNdP1dtMOq40OdtvaXnvFer26KwRai73lg1ctRaA8NM5iarH-Xy6YgJCz1NRBqhR-ESHh1KqPwz-S6gIPRoaVihR9yAfyav0lGH6ZiIpwt2YnGa--mKGsbp42uTUiZLJl0XDSS36RO2KAJGmwvoAhdU6xHNzfzg9Q3YP3HwMd5ymoLUmAy5crorvGzzhOVB9hK9y_hpT6l5KZtvgM5mgQNuCdWq1brxVIbKvzQsXxrfVpkqtLp45tQElXryZ1EbnZJ5ep9J-GU14gRQ6nhht6PBTIWSVfWD06rwmzeO8p_a0PIZFfRJ3d2aqKCB8Fkn8G7h4-3UdbV6yJX47EJejtFrNrQySjqqxaFVqT1fDg7mKNH_4PlIqUaGO4-adceSEPCOz95msZfc44HhGwxectoS9Y-XacPIwxBCHjFGhwOy9XK15Jnz5p6etnVbQ3Gat79zlUtqTLmA_RsFwvM5vkBZMSVUp9d0hZi4VUMT_Cizq5bBuH48oqaRFgqrVyqZx0fDOzUlbymGf7XSVCJlZpYqviIfMz6uk=", "id": "rs_0dc9f371a6d55e3f016a137c15aad4819184c4444aedf15d3a", "summary": [{"type": "summary_text", "text": "**Searching for subtitle tests**\n\nI need to look for a subtitle tests file, possibly named \"test_subtitle_tts.\" I wonder if that's the right filename. It sounds like a good place to start. I'll have to make sure I'm searching in the right locations to find this file quickly. If I can locate it, that should help me with whatever I'm working on. Let's see if I can track it down!"}]}], "tool_calls": [{"id": "call_XqTVu3rBWyImQqLPPsIFmF1C", "call_id": "call_XqTVu3rBWyImQqLPPsIFmF1C", "response_item_id": "fc_0dc9f371a6d55e3f016a137c17eb7c81918bd5dcc312f14bad", "type": "function", "function": {"name": "search_files", "arguments": "{\"pattern\":\"build_hormozi_subtitle_track|SubtitleStyle\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests\",\"target\":\"content\",\"limit\":50}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "search_files", "content": "{\"total_count\": 0}", "tool_call_id": "call_XqTVu3rBWyImQqLPPsIFmF1C", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3wgRZXt4OGY4cZ2jgQ5XOgWL7n9SZCNtgBeFsU4b0WMhdAyZre_4PI2F4Cp_vHWQu0Z-l-l3hobnM9AGMLEh2tq15-zE_A79YAcoXa6eq1BewXp_2js9pdN9P_P_5FuWRGWL3OhUK0vKUM8NJ4lgn2_e0YLxgULAAKntIc-dswApOsqDWIn_egbRmtimkDIAbqIlwO7hYJuaTsGweJy4dL2-Z1nVWVVuu0QAe8acmegVmWzH-2Voc2Mth9Bwsa37ajJCF5ARtEbyI8SlNYCpZI9IwyD8Rz41cQYGc-NSFGtNKbqVzMYMKFWl9LndhcTa24y_jjolv7EOf2G9MiKEcBw3JKhNyS1JfEmaNivl2YsF4ufFfqNdMwr-0UaR40g1CSemI1sJh_VCrze9Vjp0nmDA8samEBoMEgbjI6aI9zsCRIICaCt6UX1u4ZKsNkyivgE8st7iX7Zn91z_mOT285jTZyVYQHJQfbM-LoyigzSWiFjnIJQDqv7RQGK1zzGvfX0rae6piDqL2IICYGA_j_7JOjv2aLd9qFR5FiPW_SfsLcSIadbHIFpW-ju_xIXJ50kEOO_AJz9uxDXaY6jVm6-jbUt0AMfjpeNmXQPuAGES4Q_w8iH8GbrQMDB-NZ0L94BOh9ibJhjqUcIor5FJ3VBObfY0IAyhFawYSANgdbT-ZzPKM89P01ZRGbyUUqNPvidUKjfxKQIRj4ZwOlF6TlFCOTnGGwf9NAkVDJM_ayKhfuj04b-OYcXxfO7p3x-rqCWzj5BmBlGBJni_n4lzk77PHMLFmJKj7JpyJ0UBOfWoMNH3BwW1lSmGqTpcFldVeWPPZUJ9XtH_a_jhyAn-rW899pg3Qjf7lXZvez2j2tW20rfvR9J2_13P9zwKdtUiSDKd6E-85eXK6F7VdbAzhUHwRO77rAA_58EXHGNnRrbUKNM4283_EdGLoNqc7zWqJyPMpWzK4TIXnENaIsl5IJpwHnm49pEevle4cuzHU7bx20Sjsm1JzzK217qCFmLY7Xp7EUOeFBqxSht3AkVI8Ptimx4Kzz986gMMnHi_jG3ZUPSk7U2VChTxWrCrXUfNQDeGTDVsOG9q5XbikUVPEIDaNhXTwPR5J8hu405wKu5shBdA0RtxJ6FxKGCoTe1ixP4jzPhBtHCaeYbazOgINjewiYIMhyMuqfHhTsXp6r4CjbrAgMNnB7-8GSr0QEXxdNFvzSFaEdM4BeOMRFHSO9J4EvmxkZUtA-go_ZkrnQzf28KTAV1to755f9O21tcF34Z_6fLdEIdjGfaSMO-oDL0SLP8CLqjp3KFofElKnRv9Y5L8JyCpsUyqX95AdLe4vMyj9XIwTOz4Nxhg87NS1f-JIsQaKQ6QjGXpnA7LJLtNuhzVyJjbeyXbPVyIbG4D0d3-i1yDCZh71fbGssw_nEhA7mCielrf_xrBPcwjXogaHVBO7GI-1rcdKcx0FQP8eY0GST2AutxbPfrFKECJODwDPp-OLhIRoWfyJ441iKIZF9cosjLXMHGoz8mhmtL5aJ_1V_FjvRBMPqpZA_m_lNwSsSu1r-qT_3FGlPUKsvjzGoV8udX_HaHw5UIYh9KqLtmjC2CUVEid2KhiwMgOfKePPCV9DsAL6UjTOdrpSj3MYinUbFDES5xc0Io8avVyIV7sd3lsHD2eEZs8JkexIwPrBvGGY6LfiyvKmErSfX2b15Xoq5K8caZt3VCBgNl-dOax77MmHwoXdgrf5kRNxlZtJZsEqzpJVx17zAuWLs3BeiBeST-GRtT5j7ZVoaW00oEfn57ZLWastIz8YL_6Mj0D-7-HlifhmPnbkOlg5zJt9QFtzdPCjWdBaWuIEy17b8vLRpyJvAoYHdUK73xduYB_ubf1Kqk0qFk-fba41V42uwPrpyNQ3aYfHpYD5YIJd3YcFKSPd5e96eujij1uSLufnC26v9bbFfMLS1MllLz3qLMYtKilUZupDaxN8Gf1iKa5brPEQRK1g-Emlqm50uCCMCqdSszB5zrxgwkBNkfqdcaJdsdr_zNnAquAX33lhF1r408CYAChTYW32Jf3ykKWRbU8X8micNIWoWodN4zGgBd9vWJZKyy0ZxLlv4249BHUv2_vwXQJALJOiQDT3cWDOc-gVhp9tzvVlQVtcu1DSxFGUzN2OeCAwF6N8-R2SNdhwNwumPslwf1pJ3gzQy7hxLB_KATm7oqYBOfBC_7fXrfarpYw6XUBe7N3c-57-VvAhQ6oG63Fak6iqZqRMh6aA==", "id": "rs_0dc9f371a6d55e3f016a137c1ba9088191ace22743e46feca9", "summary": []}], "tool_calls": [{"id": "call_2tgMIVewyEyvEL15t20jiEXw", "call_id": "call_2tgMIVewyEyvEL15t20jiEXw", "response_item_id": "fc_0dc9f371a6d55e3f016a137c208778819194504cb1338a9e32", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\",\"old_string\":\"from autoshorts.audio.subtitles import build_hormozi_subtitle_track\\n\",\"new_string\":\"from autoshorts.audio.subtitles import build_final_motion_subtitle_track, build_hormozi_subtitle_track\\n\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\\n@@ -7,7 +7,7 @@\\n render_audio_caption_preview,\\n validate_audio_caption_preview_plan,\\n )\\n-from autoshorts.audio.subtitles import build_hormozi_subtitle_track\\n+from autoshorts.audio.subtitles import build_final_motion_subtitle_track, build_hormozi_subtitle_track\\n \\n \\n def test_build_audio_caption_preview_plan_is_side_effect_free_and_writes_ass_content(tmp_path):\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}, \"lsp_diagnostics\": \"LSP diagnostics introduced by this edit:\\n\\nERROR [10:40] \\\"build_final_motion_subtitle_track\\\" is unknown import symbol [reportAttributeAccessIssue] (Pyright)\\n\"}", "tool_call_id": "call_2tgMIVewyEyvEL15t20jiEXw", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_QSSaNaC4UCE6Ow529i243Fst", "call_id": "call_QSSaNaC4UCE6Ow529i243Fst", "response_item_id": "fc_0dc9f371a6d55e3f016a137c28cad48191bdd02d61a33df507", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"def test_render_ass_subtitle_file_uses_compact_final_motion_style():\\n track = build_final_motion_subtitle_track(\\n \\\"Your AI automation works perfectly in the demo then one weird email arrives\\\",\\n total_duration_seconds=6,\\n )\\n plan = build_audio_caption_preview_plan(\\n video_path=\\\"timing.mp4\\\",\\n audio_path=\\\"voice.mp3\\\",\\n subtitle_track=track,\\n output_path=\\\"final-preview.mp4\\\",\\n )\\n\\n assert track.style.name == \\\"truetrace_final_motion_compact\\\"\\n assert all(1 <= len(cue.text.split()) <= 3 for cue in track.cues)\\n assert \\\"Style: TrueTraceCaption,Arial,72,\\\" in plan.subtitle_file_content\\n assert \\\",80,80,320,1\\\" in plan.subtitle_file_content\\n\\n\\ndef test_validate_audio_caption_preview_plan_rejects_bad_paths_and_unsafe_side_effects(tmp_path):\",\"old_string\":\"def test_validate_audio_caption_preview_plan_rejects_bad_paths_and_unsafe_side_effects(tmp_path):\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\\n@@ -32,6 +32,24 @@\\n assert \\\"MOST AI AUTOMATIONS\\\" in plan.subtitle_file_content\\n assert plan.side_effects == ()\\n assert plan.external_calls == ()\\n+\\n+\\n+def test_render_ass_subtitle_file_uses_compact_final_motion_style():\\n+ track = build_final_motion_subtitle_track(\\n+ \\\"Your AI automation works perfectly in the demo then one weird email arrives\\\",\\n+ total_duration_seconds=6,\\n+ )\\n+ plan = build_audio_caption_preview_plan(\\n+ video_path=\\\"timing.mp4\\\",\\n+ audio_path=\\\"voice.mp3\\\",\\n+ subtitle_track=track,\\n+ output_path=\\\"final-preview.mp4\\\",\\n+ )\\n+\\n+ assert track.style.name == \\\"truetrace_final_motion_compact\\\"\\n+ assert all(1 <= len(cue.text.split()) <= 3 for cue in track.cues)\\n+ assert \\\"Style: TrueTraceCaption,Arial,72,\\\" in plan.subtitle_file_content\\n+ assert \\\",80,80,320,1\\\" in plan.subtitle_file_content\\n \\n \\n def test_validate_audio_caption_preview_plan_rejects_bad_paths_and_unsafe_side_effects(tmp_path):\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_QSSaNaC4UCE6Ow529i243Fst", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_Er0JMdvxMVDKV7GtfpTCszIu", "call_id": "call_Er0JMdvxMVDKV7GtfpTCszIu", "response_item_id": "fc_0dc9f371a6d55e3f016a137c3c88808191945db3a76d2679ff", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_audio_caption_preview.py::test_render_ass_subtitle_file_uses_compact_final_motion_style -q\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"ERROR: found no collectors for /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py::test_render_ass_subtitle_file_uses_compact_final_motion_style\\n\\n\\n==================================== ERRORS ====================================\\n_____________ ERROR collecting tests/test_audio_caption_preview.py _____________\\nImportError while importing test module '/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py'.\\nHint: make sure your test modules/packages have valid Python names.\\nTraceback:\\n../../../.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/importlib/__init__.py:126: in import_module\\n return _bootstrap._gcd_import(name[level:], package, level)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\ntests/test_audio_caption_preview.py:10: in \\n from autoshorts.audio.subtitles import build_final_motion_subtitle_track, build_hormozi_subtitle_track\\nE ImportError: cannot import name 'build_final_motion_subtitle_track' from 'autoshorts.audio.subtitles' (/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py)\\n=========================== short test summary info ============================\\nERROR tests/test_audio_caption_preview.py\\n1 error in 0.07s\", \"exit_code\": 4, \"error\": null}", "tool_call_id": "call_Er0JMdvxMVDKV7GtfpTCszIu", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3xHo881MvIIyod9yfa6dARUMlDeRIwVBajVfRvj__GufcLr4WQ85E5UQr3l8skklAnaPSHeEW-xHrUadqa-1NvXukkJCbtDtNaV2NM6HKfBvbydpxtiswNlWxJnUOptc_I6h7EWWbmMklX8AumJcldwLPWE9Rrjs6grpQNamJGMvy7oAcHuvpuXR4YcKFQGK5W33Ybgj7u6RN_6R9R423V0rYNR3qk1kKDEwJKmzSVWYwbpmNRJRHswik0gjf0weKrU0XTxvyUtqRPw5lQ92jfqtBICJFhtj3vGiv_VuYyHHLR5gayoz4G9tl5jSE8m3s1pFmpRVCZNynTbW5ktIZuLYUgh6cVbAXYeWtnHLt0vIke1tCAKxKOa6WgNkg-7JJBcdma-GpNduK0bfZOSUlpy6alBeUrjUikurb4tBb897iECW15rBFmmdo5F-y7F6fPjMb1gcWTlYZ4JZpXUrB6jtGamgSaKCYDFoloe3y1yueZKVc0kvaPA2jGbojZYmEGMuys_8P2r8p9m30Wif-UY-LEECohWvk8xvB4SkqTJa9Sb-M_vZ2kZpqWUq6NEwfeywXT3lGy-_-sMyQAqNr0KVpepLjpr-0_2YOpUEtxPZoc5pt5iNJ_XzuremS8jFJ6Uofbb6xVOpCuONq2ASoyemLIe4cy8bCz5AZNEjssdKA9jfhQbpsg0GpoPRbNAFxVipgrVDCxE6-_7EZB0zzLHRPHS8q6Fh-4ZzGUgKnWc8gLaTG1mdveNO-joUwa_YoSzl0Cuy2SHSJOdxDeN3DvUGGFDlpA-gE6X_HMMtfP3WREiVacWxgxTjWtXzS_iv_6sEYpXJBz4_2Y8eunF8AfZzeENY8RbmG7QFBfgLWwkgQr58D-qIyK_skyU-XluQxUqqcz2kCrnctvx1MvcVGeBeatZm9QFalfk9yXHOB0iMp1T-moMDiUBXjbm0NjRDfuTkRMbF_zFulQLUE5Dj0MKF5Rmme-d4y1L1bsHd5o3gdhojr8HY671_-1m3TXHb7L1HFBtHUngHQQP87v2VMfGzYGF1x3qy1_-9R0FMSQLrWC3yrOsO1sl5TtD2iUQ7chuyLy27AqMf01o5AWnKxoXXg==", "id": "rs_0dc9f371a6d55e3f016a137c456f588191a2fad8df8a26e0ee", "summary": []}], "tool_calls": [{"id": "call_ftxMHpRoiCnz5CGk4oa9jzC8", "call_id": "call_ftxMHpRoiCnz5CGk4oa9jzC8", "response_item_id": "fc_0dc9f371a6d55e3f016a137c47b25c81918163cd27268b485c", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" safe_zone_bottom_percent: int\\n font_weight: str\\n font_size: int = 86\\n margin_v: int = 260\",\"old_string\":\" safe_zone_bottom_percent: int\\n font_weight: str\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n@@ -24,6 +24,8 @@\\n max_words_per_cue: int\\n safe_zone_bottom_percent: int\\n font_weight: str\\n+ font_size: int = 86\\n+ margin_v: int = 260\\n \\n @classmethod\\n def hormozi_inspired(cls) -> \\\"SubtitleStyle\\\":\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_ftxMHpRoiCnz5CGk4oa9jzC8", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_ScWGNeSvwTdSNcJn20Nu7DwG", "call_id": "call_ScWGNeSvwTdSNcJn20Nu7DwG", "response_item_id": "fc_0dc9f371a6d55e3f016a137c4c1e308191b062177260c3b045", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" )\\n\\n @classmethod\\n def final_motion_compact(cls) -> \\\"SubtitleStyle\\\":\\n \\\"\\\"\\\"Return a compact final-motion style that leaves mechanism diagrams breathing room.\\\"\\\"\\\"\\n\\n return cls(\\n name=\\\"truetrace_final_motion_compact\\\",\\n primary_color=\\\"#FFFFFF\\\",\\n accent_color=\\\"#22D3EE\\\",\\n stroke_color=\\\"#050816\\\",\\n shadow_color=\\\"#000000\\\",\\n placement=\\\"lower_middle_above_ui_safe_zone\\\",\\n max_lines=2,\\n min_words_per_cue=1,\\n max_words_per_cue=3,\\n safe_zone_bottom_percent=17,\\n font_weight=\\\"800\\\",\\n font_size=72,\\n margin_v=320,\\n )\\n\\n\\n@dataclass(frozen=True)\",\"old_string\":\" )\\n\\n\\n@dataclass(frozen=True)\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n@@ -43,6 +43,26 @@\\n max_words_per_cue=5,\\n safe_zone_bottom_percent=14,\\n font_weight=\\\"800\\\",\\n+ )\\n+\\n+ @classmethod\\n+ def final_motion_compact(cls) -> \\\"SubtitleStyle\\\":\\n+ \\\"\\\"\\\"Return a compact final-motion style that leaves mechanism diagrams breathing room.\\\"\\\"\\\"\\n+\\n+ return cls(\\n+ name=\\\"truetrace_final_motion_compact\\\",\\n+ primary_color=\\\"#FFFFFF\\\",\\n+ accent_color=\\\"#22D3EE\\\",\\n+ stroke_color=\\\"#050816\\\",\\n+ shadow_color=\\\"#000000\\\",\\n+ placement=\\\"lower_middle_above_ui_safe_zone\\\",\\n+ max_lines=2,\\n+ min_words_per_cue=1,\\n+ max_words_per_cue=3,\\n+ safe_zone_bottom_percent=17,\\n+ font_weight=\\\"800\\\",\\n+ font_size=72,\\n+ margin_v=320,\\n )\\n \\n \\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_ScWGNeSvwTdSNcJn20Nu7DwG", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_em20LGCjPbTf2Qdn5oPoLLyS", "call_id": "call_em20LGCjPbTf2Qdn5oPoLLyS", "response_item_id": "fc_0dc9f371a6d55e3f016a137c579e7c8191ab1e026c06d85b5d", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"def _build_subtitle_track(text: str, *, total_duration_seconds: int, style: SubtitleStyle) -> SubtitleTrack:\\n if not text.strip():\\n raise ValueError(\\\"subtitle text is required\\\")\\n if total_duration_seconds <= 0:\\n raise ValueError(\\\"total_duration_seconds must be positive\\\")\\n\\n words = _words(text)\\n if len(words) < style.min_words_per_cue:\\n raise ValueError(\\\"subtitle text must contain at least two words\\\")\\n\\n chunks = _chunk_words(words, min_words=style.min_words_per_cue, max_words=style.max_words_per_cue)\\n total_ms = total_duration_seconds * 1000\\n cues: list[SubtitleCue] = []\\n for index, chunk in enumerate(chunks):\\n start_ms = round(index * total_ms / len(chunks))\\n end_ms = round((index + 1) * total_ms / len(chunks))\\n cues.append(\\n SubtitleCue(\\n text=\\\" \\\".join(word.upper() for word in chunk),\\n start_ms=start_ms,\\n end_ms=end_ms,\\n active_word=_active_word(chunk),\\n renderer_owned=True,\\n max_lines=style.max_lines,\\n emphasis_color=style.accent_color,\\n )\\n )\\n\\n track = SubtitleTrack(cues=tuple(cues), style=style)\\n validation = validate_subtitle_track(track)\\n if not validation.is_valid:\\n raise ValueError(\\\"; \\\".join(validation.errors))\\n return track\\n\\n\\ndef build_hormozi_subtitle_track(text: str, *, total_duration_seconds: int) -> SubtitleTrack:\\n \\\"\\\"\\\"Create continuous 2..5-word renderer-owned subtitle cues for final burn-in.\\\"\\\"\\\"\\n\\n return _build_subtitle_track(\\n text,\\n total_duration_seconds=total_duration_seconds,\\n style=SubtitleStyle.hormozi_inspired(),\\n )\\n\\n\\ndef build_final_motion_subtitle_track(text: str, *, total_duration_seconds: int) -> SubtitleTrack:\\n \\\"\\\"\\\"Create compact 1..3-word cues for final-near mechanism videos.\\\"\\\"\\\"\\n\\n return _build_subtitle_track(\\n text,\\n total_duration_seconds=total_duration_seconds,\\n style=SubtitleStyle.final_motion_compact(),\\n )\\n\\n\\ndef validate_subtitle_track(track: SubtitleTrack) -> ValidationResult:\",\"old_string\":\"def build_hormozi_subtitle_track(text: str, *, total_duration_seconds: int) -> SubtitleTrack:\\n \\\"\\\"\\\"Create continuous 2..5-word renderer-owned subtitle cues for final burn-in.\\\"\\\"\\\"\\n\\n if not text.strip():\\n raise ValueError(\\\"subtitle text is required\\\")\\n if total_duration_seconds <= 0:\\n raise ValueError(\\\"total_duration_seconds must be positive\\\")\\n\\n style = SubtitleStyle.hormozi_inspired()\\n words = _words(text)\\n if len(words) < style.min_words_per_cue:\\n raise ValueError(\\\"subtitle text must contain at least two words\\\")\\n\\n chunks = _chunk_words(words, min_words=style.min_words_per_cue, max_words=style.max_words_per_cue)\\n total_ms = total_duration_seconds * 1000\\n cues: list[SubtitleCue] = []\\n for index, chunk in enumerate(chunks):\\n start_ms = round(index * total_ms / len(chunks))\\n end_ms = round((index + 1) * total_ms / len(chunks))\\n cues.append(\\n SubtitleCue(\\n text=\\\" \\\".join(word.upper() for word in chunk),\\n start_ms=start_ms,\\n end_ms=end_ms,\\n active_word=_active_word(chunk),\\n renderer_owned=True,\\n max_lines=style.max_lines,\\n emphasis_color=style.accent_color,\\n )\\n )\\n\\n track = SubtitleTrack(cues=tuple(cues), style=style)\\n validation = validate_subtitle_track(track)\\n if not validation.is_valid:\\n raise ValueError(\\\"; \\\".join(validation.errors))\\n return track\\n\\n\\ndef validate_subtitle_track(track: SubtitleTrack) -> ValidationResult:\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n@@ -114,15 +114,12 @@\\n return max((word.upper() for word in chunk), key=lambda word: (len(word), word))\\n \\n \\n-def build_hormozi_subtitle_track(text: str, *, total_duration_seconds: int) -> SubtitleTrack:\\n- \\\"\\\"\\\"Create continuous 2..5-word renderer-owned subtitle cues for final burn-in.\\\"\\\"\\\"\\n-\\n+def _build_subtitle_track(text: str, *, total_duration_seconds: int, style: SubtitleStyle) -> SubtitleTrack:\\n if not text.strip():\\n raise ValueError(\\\"subtitle text is required\\\")\\n if total_duration_seconds <= 0:\\n raise ValueError(\\\"total_duration_seconds must be positive\\\")\\n \\n- style = SubtitleStyle.hormozi_inspired()\\n words = _words(text)\\n if len(words) < style.min_words_per_cue:\\n raise ValueError(\\\"subtitle text must contain at least two words\\\")\\n@@ -150,6 +147,26 @@\\n if not validation.is_valid:\\n raise ValueError(\\\"; \\\".join(validation.errors))\\n return track\\n+\\n+\\n+def build_hormozi_subtitle_track(text: str, *, total_duration_seconds: int) -> SubtitleTrack:\\n+ \\\"\\\"\\\"Create continuous 2..5-word renderer-owned subtitle cues for final burn-in.\\\"\\\"\\\"\\n+\\n+ return _build_subtitle_track(\\n+ text,\\n+ total_duration_seconds=total_duration_seconds,\\n+ style=SubtitleStyle.hormozi_inspired(),\\n+ )\\n+\\n+\\n+def build_final_motion_subtitle_track(text: str, *, total_duration_seconds: int) -> SubtitleTrack:\\n+ \\\"\\\"\\\"Create compact 1..3-word cues for final-near mechanism videos.\\\"\\\"\\\"\\n+\\n+ return _build_subtitle_track(\\n+ text,\\n+ total_duration_seconds=total_duration_seconds,\\n+ style=SubtitleStyle.final_motion_compact(),\\n+ )\\n \\n \\n def validate_subtitle_track(track: SubtitleTrack) -> ValidationResult:\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_em20LGCjPbTf2Qdn5oPoLLyS", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_r5VFDd6WWGX17qRjTHehQH7H", "call_id": "call_r5VFDd6WWGX17qRjTHehQH7H", "response_item_id": "fc_0dc9f371a6d55e3f016a137c6db07881919658c3476c3bcb21", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" f\\\"Style: TrueTraceCaption,Arial,{style.font_size},{primary},{accent},{outline},&H80000000,-1,0,0,0,100,100,0,0,1,5,2,2,80,80,{style.margin_v},1\\\",\",\"old_string\":\" f\\\"Style: TrueTraceCaption,Arial,86,{primary},{accent},{outline},&H80000000,-1,0,0,0,100,100,0,0,1,5,2,2,80,80,260,1\\\",\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py\\n@@ -81,7 +81,7 @@\\n \\\"\\\",\\n \\\"[V4+ Styles]\\\",\\n \\\"Format: Name, Fontname, Fontsize, PrimaryColour, SecondaryColour, OutlineColour, BackColour, Bold, Italic, Underline, StrikeOut, ScaleX, ScaleY, Spacing, Angle, BorderStyle, Outline, Shadow, Alignment, MarginL, MarginR, MarginV, Encoding\\\",\\n- f\\\"Style: TrueTraceCaption,Arial,86,{primary},{accent},{outline},&H80000000,-1,0,0,0,100,100,0,0,1,5,2,2,80,80,260,1\\\",\\n+ f\\\"Style: TrueTraceCaption,Arial,{style.font_size},{primary},{accent},{outline},&H80000000,-1,0,0,0,100,100,0,0,1,5,2,2,80,80,{style.margin_v},1\\\",\\n \\\"\\\",\\n \\\"[Events]\\\",\\n \\\"Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text\\\",\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/final_preview.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_r5VFDd6WWGX17qRjTHehQH7H", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_U7a84CBrwpvReIl4uLNcwoAy", "call_id": "call_U7a84CBrwpvReIl4uLNcwoAy", "response_item_id": "fc_0dc9f371a6d55e3f016a137c751f2881919a835b0bc0729f97", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_audio_caption_preview.py::test_render_ass_subtitle_file_uses_compact_final_motion_style -q\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \". [100%]\\n1 passed in 0.05s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_U7a84CBrwpvReIl4uLNcwoAy", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": "**Planning video rendering**\n\nI think I need to test for expected failures, so I'll proceed with rendering the v6 preview using compact subtitles and try 1080p, though maybe starting with 540p for QA. I'll use the existing generated backgrounds and make sure to incorporate the build_final_motion_subtitle_track first. I should also consider rendering the final export in 1080p, but checking performance is crucial. Adding targeted and full tests afterward might help too, since the render isn't production code yet. Let's aim to generate that v6 preview!", "finish_reason": "tool_calls", "reasoning_content": "**Planning video rendering**\n\nI think I need to test for expected failures, so I'll proceed with rendering the v6 preview using compact subtitles and try 1080p, though maybe starting with 540p for QA. I'll use the existing generated backgrounds and make sure to incorporate the build_final_motion_subtitle_track first. I should also consider rendering the final export in 1080p, but checking performance is crucial. Adding targeted and full tests afterward might help too, since the render isn't production code yet. Let's aim to generate that v6 preview!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3x9gz0li9f0yffY4Uj5qMH6sDuZIedIbBj2JMWNcNfqI3xKcUnm4bnFbu53JGWYqo7QiOGmqpv_3SfoEinYgPLPokgJ2xgVWlVfycJIvXfQw00yl5E7gRflr2I0E-WGN9oZYwhyrzqPxysQjxVqKjbxG4vSaVsX63c-Dt8kDPXpZFynPDTRBV1ZeFGKJGP67rAEUUFjLqJwirx8KeqNyGwQWIW3cdKKuow_0V5q0HIM5TBSr-KWvH2_Cvr6kde2zXkqMFG52SLdclqF7sLK0QwkEjcrB75uNWQb_tTfuQMX3ps9YnkcdLqWXuzsjV32nGQ0qPCwx9l3ojC5GMBvlsvMTQnJOh6Xr7ggtDxVlhs-4HeRutB0YIH47jXrhu_u19cdE1MgUiOhHP9rCCFT8IBMYyhPcamQKMx4L1eRfND_pp7PsMAEaL55Vz2xGjz81pUqcUbS4stWzvGE0efwTkdbqUTgFZaxSsbrjVivDcqEA0fyvLoLnOfPRVta3jSnnvNMOd9ppDiKkMUfnxvaSuGcjmQ5RqGqcRsUJtaZqws4MPi9HG596KyX44aP4jEPMDZJ3OGIrEV5wss4sMoO9eGn5VmtBTv1fFYPRMHBjRd2z8_6jtOIGxW56vZoyz3-MJZtAJy2NGcXGi2W5KqGW1PUPMevvSycm2EGPIg86_RcBNyJUOkaGbdavy9RszfQWCLU7xYL6cNpNpi8v5l4IpAIcvboxiopiPDr_-M8wbkehoE7g5eMkRM5B1JTOEbcuYvg4u3aGjoxsc_HVb-iGu97Vdti5SH3ao0JJHlxRLZG8cRAd9jO2ozFumCnvEzRu5B4j52saHzTtFyrZzVWaDxltFmqm-arn5s0h8b0fXMf4NMNgLN8ti-JD8TK9BXikaXL6uXvfckQS9jM7i8Ao2pJHqJMmacviq-4TGGKJ_K3RrSBm1Rit93xnrA4ap7bk7AvHDORD1l5oOFTAm7xYHjtGXus3_ECL_3D6pEzksZV0ppyxyRNRSRNub19BEk2eMXLkNXVn311vu17S_TlP041pHqrspLbEc5kI-n7rp_AaAxxBqbRuihCZgESpkn_kL0l5kzODfycUuSo4WjLvp4P8_GWoEoE4PpWIixhuPDMAApp9hcMMmwkxIhNCpSUvUbzRrnpBbB_xn-DEX18Ng7VsWVHy74T85XUO-EjIcCuc903-RwK6YkMrzbkf1hYocBIdrO7f3ojxfSJ1EHnxmqtXaxDkbwnBAcxGm7BKqBZRdAqB12D5UxeAdyhXMHmoVR5aoq8VPS_gdRZTBTMWt7dpc3yxcXjXDGeQ8LRfnHYzgeVm7TsEqKY5SVBYTPjIXpwXcTbQ1Dts1mamxsPtfkhbpwXeHsp632yNiWJ16oMovto7wKugHPXxRKCbcdn7Ka15dFD4QFSD5oD-MhDQgsTIjvA_BBvXT81pv7R0uRNkaE=", "id": "rs_0dc9f371a6d55e3f016a137c7ac00081919efe6d5f252e82c3", "summary": [{"type": "summary_text", "text": "**Planning video rendering**\n\nI think I need to test for expected failures, so I'll proceed with rendering the v6 preview using compact subtitles and try 1080p, though maybe starting with 540p for QA. I'll use the existing generated backgrounds and make sure to incorporate the build_final_motion_subtitle_track first. I should also consider rendering the final export in 1080p, but checking performance is crucial. Adding targeted and full tests afterward might help too, since the render isn't production code yet. Let's aim to generate that v6 preview!"}]}], "tool_calls": [{"id": "call_ohZSMy2w8IisjjHocyz2GU2D", "call_id": "call_ohZSMy2w8IisjjHocyz2GU2D", "response_item_id": "fc_0dc9f371a6d55e3f016a137c7db4508191a89baff832b38593", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nfrom pathlib import Path\\nfrom math import ceil\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover\\nfrom autoshorts.audio.tts_plan import build_default_truetrace_tts_plan\\nfrom autoshorts.audio.edge_tts_adapter import EdgeTTSRequest, synthesize_edge_tts\\nfrom autoshorts.audio.probe import probe_media_duration_seconds\\nfrom autoshorts.audio.subtitles import build_final_motion_subtitle_track\\nfrom autoshorts.audio.final_preview import build_audio_caption_preview_plan, render_audio_caption_preview\\nfrom autoshorts.rendering.final_video_plan import build_truetrace_weird_email_final_video_plan\\nfrom autoshorts.rendering.scene_backgrounds import build_chatgpt_image_scene_background_plan\\nfrom autoshorts.rendering.motion_renderer import build_motion_render_plan, render_motion_preview\\ncandidate_id='truetrace-ai-automation-quiet-rot-38s'\\noutput_dir=Path('data/previews/truetrace-final-motion-v6')/candidate_id\\nvoiceover=build_truetrace_final_voiceover(candidate_id)\\nfinal_plan=build_truetrace_weird_email_final_video_plan(voiceover)\\nbg_plan=build_chatgpt_image_scene_background_plan(final_plan, output_dir='data/generated_backgrounds/truetrace-weird-email-v1')\\nbackground_paths={asset.scene_id: asset.output_path for asset in bg_plan.assets}\\nmotion=render_motion_preview(build_motion_render_plan(final_plan, output_dir=output_dir, preview_scale=0.5, background_paths=background_paths))\\nif motion.returncode: raise SystemExit(motion.stderr)\\nvoice=synthesize_edge_tts(EdgeTTSRequest(text=voiceover.text, tts_plan=build_default_truetrace_tts_plan(), output_path=str(output_dir/'voice.mp3')))\\naudio_duration=probe_media_duration_seconds(voice.output_path)\\nsubtitles=build_final_motion_subtitle_track(voiceover.text, total_duration_seconds=ceil(audio_duration))\\nfinal=render_audio_caption_preview(build_audio_caption_preview_plan(video_path=motion.output_path,audio_path=voice.output_path,subtitle_track=subtitles,output_path=output_dir/'final-motion-audio-caption-preview.mp4',duration_mode='trim_to_audio'))\\nif final.returncode: raise SystemExit(final.stderr)\\nprint('final', final.output_path)\\nprint('frames', len(motion.frame_paths))\\nprint('cues', len(subtitles.cues))\\nprint('max_words', max(len(c.text.split()) for c in subtitles.cues))\\nprint('style', subtitles.style.name, subtitles.style.font_size, subtitles.style.margin_v)\\nprint('audio_duration', f'{audio_duration:.3f}')\\nPY\\nrm -rf /tmp/truetrace_review_v6 && mkdir -p /tmp/truetrace_review_v6 && ffmpeg -y -i data/previews/truetrace-final-motion-v6/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4 -vf \\\"select='eq(n,0)+eq(n,120)+eq(n,300)+eq(n,520)+eq(n,760)'\\\" -vsync 0 /tmp/truetrace_review_v6/frame_%02d.png >/dev/null 2>&1\\nffprobe -v error -show_entries stream=codec_type,codec_name,width,height,duration -of default=noprint_wrappers=1 data/previews/truetrace-final-motion-v6/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\nsha256sum data/previews/truetrace-final-motion-v6/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"final data/previews/truetrace-final-motion-v6/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\nframes 887\\ncues 29\\nmax_words 3\\nstyle truetrace_final_motion_compact 72 320\\naudio_duration 36.864\\ncodec_name=h264\\ncodec_type=video\\nwidth=540\\nheight=960\\nduration=36.833333\\ncodec_name=aac\\ncodec_type=audio\\nduration=36.864000\\n757669ceef2f2548eb74eca395570f62102d1e6cf44e1f74d137ca8ec34d3406 data/previews/truetrace-final-motion-v6/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_ohZSMy2w8IisjjHocyz2GU2D", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_oJ3ieDZv35vYDxsFNZXWw0wD", "call_id": "call_oJ3ieDZv35vYDxsFNZXWw0wD", "response_item_id": "fc_0dc9f371a6d55e3f016a137cf3e210819197ddc52393775e51", "type": "function", "function": {"name": "vision_analyze", "arguments": "{\"image_url\":\"/tmp/truetrace_review_v6/frame_04.png\",\"question\":\"Check v6 three-way split frame after compact subtitle style: mobile readability, subtitle/diagram competition, clipping, and whether it is good enough to proceed to 1080 export.\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "vision_analyze", "content": [{"type": "text", "text": "Image loaded into your context — you can see it natively now. Use your built-in vision to answer the user.\n\nQuestion: Check v6 three-way split frame after compact subtitle style: mobile readability, subtitle/diagram competition, clipping, and whether it is good enough to proceed to 1080 export."}, {"type": "image_url", "image_url": {"url": 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"}}], "tool_call_id": "call_oJ3ieDZv35vYDxsFNZXWw0wD", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": "**Evaluating subtitle structure**\n\nI’m noticing the subtitle \"ANYTHING DECIDE THREE\" feels awkward and might not sync well. It seems like there’s a problem with how the subtitles correspond. Building subtitles with phrase rules could help, targeting compact phrases that maintain sentence boundaries—maximum of three chunks. It needs to be punctuation-aware to preserve meaning without crossing clauses. I think allowing four chunks might be okay for clarity, especially for the phrase \"Before you automate anything.\"\n**Designing a phrase chunker**\n\nI need to create a phrase chunker that focuses on punctuation and commas, ensuring segments don't cross boundaries. Ideally, I want to maximize at three chunks but could allow up to four to keep meaningful phrases intact. The tests currently expect three, though. I’ll implement a punctuation segmenter, using regex to split the original text. For phrases with four words, like \"Before you automate anything,\" I’ll keep the segments concise but meaningful. So, shorter chunks of up to four words may work for the user’s request!\n**Creating a chunker for phrases**\n\nI need to develop a chunker that splits text based on punctuation and commas, allowing for up to four words per chunk. I want to use `_phrase_chunks` for the final output. It's important to set a style limit of max four words, ensuring that no chunk exceeds this limit. I’ll also need to test that the maximum remains at four and that phrases are well-formed to preserve clarity. Keeping it concise is key here!", "finish_reason": "tool_calls", "reasoning_content": "**Evaluating subtitle structure**\n\nI’m noticing the subtitle \"ANYTHING DECIDE THREE\" feels awkward and might not sync well. It seems like there’s a problem with how the subtitles correspond. Building subtitles with phrase rules could help, targeting compact phrases that maintain sentence boundaries—maximum of three chunks. It needs to be punctuation-aware to preserve meaning without crossing clauses. I think allowing four chunks might be okay for clarity, especially for the phrase \"Before you automate anything.\"\n**Designing a phrase chunker**\n\nI need to create a phrase chunker that focuses on punctuation and commas, ensuring segments don't cross boundaries. Ideally, I want to maximize at three chunks but could allow up to four to keep meaningful phrases intact. The tests currently expect three, though. I’ll implement a punctuation segmenter, using regex to split the original text. For phrases with four words, like \"Before you automate anything,\" I’ll keep the segments concise but meaningful. So, shorter chunks of up to four words may work for the user’s request!\n**Creating a chunker for phrases**\n\nI need to develop a chunker that splits text based on punctuation and commas, allowing for up to four words per chunk. I want to use `_phrase_chunks` for the final output. It's important to set a style limit of max four words, ensuring that no chunk exceeds this limit. I’ll also need to test that the maximum remains at four and that phrases are well-formed to preserve clarity. Keeping it concise is key here!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE30Ebo8mlyYsRUIqn4yf4jPtCHyeUnmu3zG_3GyQZIMeKilSXnjh-APMZZFb6pw123wI_e4Gm7s4v01CDTpZ3UYXt7LCi87OrROKQhj770aBKGsb1XzPvtqw08yo2fgkZ9u7uO1P6a1iy851QjJPs1-lXkRvwRE7AHz-z1zL8eeoyIyMzehE5mXJkJwumKQc7oxmPBki5bAg6rEWDnnioGsQL7ZD7X2Ws4cCcHTxupmdRctjE4RF9Ed3CMWsko2b0S89Tacci1UBGFLmc6e3pyl6cG7jwUhI-DlNiMHfFIfM7AsL54o6WkPtJQlucWExOos3qREDd4LXGL4hZYGhnFzz88FdGPkALVd99hgKOm7IX1uBOnNVV-24ca-_zQC7ffFGeuuV-vaDZvIhVlU1coEpYjBHB_U-M7HHrGvXTrXMYAIN8GVhKKVIrOPegAZcY641N90z4E2cZp5qFo5PTwbnNAXUJmTH1FVWT-IghxRuSkcGnh0pTLHjy5ehq66pEuaM17r2ov0Av_Iuc3EBfPjqw-yAiMR_AvwLW3ArvEgOyIpHIinyFEjcWjpoWKfzCLEF3NtArCB6gfsPFjz8I2rorZ4buGLsV6u1ER08UkMlOBBhDvlVYY7fxfNSntC1KpINwAgVKMSzWqAijZjzeVvbhgegKqcCfIp04ysNfqBqIYmcinCBh0x18268qRNsXNlGXSJbyqQCn1EUJvBcuFKcdXvwOqeELA3X1eNpHnHxRI26UWGbs2tX3mX0IOI7-DUNmVLbZbD1nsKGQtuWNovGSOqgQ2y80GeJjPhUDitsQRrY2aAkqcqjfwlMzzBxLpEDH_wEK6xGRWf7BRqoTK87_bD_BWU4oCW7kWR9TnA4dS7pugto9JcGtrG-_qq_rO-ujVUiHhSz2hLjIyj-vmJoQe8rjR4xapqXMUHrYMKVVFY1rHnnm2d2nNOjYWfGUhvTTSnefkhe9fvrTWDdop1jH8OJKQB3KxyOh5ganZJf9gJXo8abwwxUF2NMIIqsCIuBWPZy9fWlvQQRAF30K0h-GbHDXuOiaYlymboP6tBYCljyNvFVIaQPqXa9o_hF4MJqLLCGlctibDyzX0qW9BzIkEYNOcKR9Y7qFVikcRcS5O9t4MSXwj8JdqbfDE_Jtz6omR8p28u4xQmQg3_1M9C3vdBhSuOUnKAqx1PO0DKQ2RMdrf_0sruO9QYPL-D0v35cTxL0IwayfV4TwLm58SPXQHECs6g_3NVGLJi69rrvabih_7TmqPjE83fu5gdSIVvG5wJ_d99hH0fNe401tJDN70xFMRkbc16UKb2C08qrV4zMHjMmkoFLgw-r_io30JNCQNMWU3Jyawk9XU1y__MRk2Hl8OobJSm2GiauYxe9QC7EideYYCwVhlUvGE53niZgpYMe08mOxcdcNlAI__4Rksi1u9Lwu6zUf5lAmXXCbFiUMZSgCIW_L3ODo84h06cyBkNl-RX-0dUmL9Gbesw5cmzND8KIv-vDFZ5C5HehjcNTVcyFFaYDOoQQ-_OmczK96R9seBM4FN8BrgxPvFgQujfakSKALuVqbdgjF0E1RKjV3peGE5fwoXlsQcEID2HgKfS8SmGZXEYeFBSU8qrFX7l-Ono-8SoAtqmENqFLlxy1V6l18GTro9nVEBhRDxN0LFTsULgCauxu07LIqbHhVAko6zesIa6pnPwomYw2QewskXJjoKEt6yUvSPTqKuqcbjzj65USelr_fBI2sNZc8wP9bGCYCQHVLwwUeGjG7J4f8tyErpyNrPYasK9rSFliBh76aYCDD_UvHlqEY7YMRg5V_EsjbeoRfgl_fI2MZLCIhh-pnSWzuAKw6HN1jhQxbX-FnuW359ih2c5yotg--_QPCC6nT00G44wvLAbuw6uEFbkc8qgnLD5LH3G-IFCu-44PsKLVL8Wm3R7VaZ4TVFckJBRkihUwWHPgYY9JYOaW-KMP0zAHJXrJc3dMNOTJRw8FiRpQTKl_WuN3OVgTJY0w6m3z5uGUBjffvNOy1IOwCq_MZjHPnfNkFx0ctuebtf4Y-OjQB8a1NVKgsYg52a7X6E7mDuvnsPKFXevqn39O5c-Ae7Y90myKjLERShL9d5Cma_UWSJIVKfaYKeD_Vv6vuvB48R6JPawl8pVouAGGEJE4wNyw2E4fG6frc22Ggt8_1zOQdVNB0dDc3NiEUtbHn36_HByia9YnGtDHir0NdOYRPJlt7HIllvYstSTU7HD6-Q1OXrEY8fMhlfZ6p3nTlWRYf6wsIvIbKZ9Q-AGsIFdblMYHZrD0e5FKOUzMHIoF2i3XL5JCsOHYwn5giAVsl3rPaULM2SW_25j3xRC9BLD6eGP-KfNsXURIfUFr8elOFE7lmyJsZuEWZz-R7mD7UPl-_D6iSzzPL0keXEFKb9iLUtFP0Ijqxyjwy9YWnPkpMyzN8yx3NxQTjXyiCoGxl-acXME-J0VHNGdHmNmMpaSdUopYuVadkUYvsbRPfk7SVMkVdjoD9N8KxTTkJR1LYXzOEY_p23pxhAtC9xS6lcZT4RYkmhFw7-cJJ5MxoduHG1mujQzA7qelicMXBP_pIjlyKQll9QoplGdtjDclkVL6J1-ic5ceQVE0QrPhqklG-OhZzLtNDNGcL3cD4wCOLfWu9Hu38Mbeu2oHFY5hs8C9THoIwvuJH5adMb9ybLYK-KodJmQ32FkbCU_pgQWrUcqW-9tEqptCj8_t0lyEduXxFYj5h45zs08dcMtEpdO3AKSjxP12Ksq_5sZh0G1F5SIycAbC5Yp7852DIEQTBZI_TsofRnKreVQwLpDNcIRhXx8mim0S0nQXvpFpmYCK97QKB8bF7KA9P6437TSb6BHsFSPYi91znXXZ5Yj2FAB1RfYLN2_6Zc8hVfAh_H7spIDbAGVRnvaqOA8hbn1MeZ9FvTloEKOWKM2b77ab_4qppjZ_gGOjsAjuHk4KoGSJ2QP89qXG06mcMMRT1QglLraDUkYJSvziIgm3qsH--Hadf1sTgorBRUpeMRVCObIBetJXKJLuAUqHtPCuGG3NwPjgJRmL18kK_SpS-yBzOzQoGDdQ2U5i43LfO1csJhfKFiIxVS3xPlXF0BDJNrTFJoPMGiyUm70JJzHc-IpuvPpg1sY2wjnVqMCxKcJRQ6HNKC-Whn0W9PZw_UO3AvPf5okc6gNG72BCOgILyXUQhy6UIorIpLC5UjKk2oPYVBIg4RcPMJUsv-dICpN7UApyEYq2b3tO1JWwNgtCLqX-5b2a1Pq5C_1guhfmUkFQtEDL5iT3hF6Z91xmslBfpYnQETft2xgwQqG6ezlo1tMaFN9M7lEtaO2xz2UYZr5vqiq-AEBFwS3pOFD3jI6mFrPR6FbwNxgaBU0EW-LlB_un2c4-axKlNFv4ML_U1pz7hpFRFHpw9aDbZcRv52ePSmYaIcg1MWyYHgObgMQ2VyExo1GU3SDwkQg8gXlXEWgitvNOiNact4BZ-w9zyv7qwwNWiqt10Tld8PD_-fpKdT1f5ZCjjqwWhflHtmHiEM94umpVa_LEySxWVHsZf44psTibX9lnc6OGjE1t7NIjYkvstRcMBhNqfpbcTtyU1PgVt37aCtF0dpdnMzhPYn_Ki0Lu8ruw_gAT-8FF5G2Z9hW211zEtP37eaIHeVWRnEqumg==", "id": "rs_0dc9f371a6d55e3f016a137cf81c208191af98f33395877932", "summary": [{"type": "summary_text", "text": "**Evaluating subtitle structure**\n\nI’m noticing the subtitle \"ANYTHING DECIDE THREE\" feels awkward and might not sync well. It seems like there’s a problem with how the subtitles correspond. Building subtitles with phrase rules could help, targeting compact phrases that maintain sentence boundaries—maximum of three chunks. It needs to be punctuation-aware to preserve meaning without crossing clauses. I think allowing four chunks might be okay for clarity, especially for the phrase \"Before you automate anything.\""}, {"type": "summary_text", "text": "**Designing a phrase chunker**\n\nI need to create a phrase chunker that focuses on punctuation and commas, ensuring segments don't cross boundaries. Ideally, I want to maximize at three chunks but could allow up to four to keep meaningful phrases intact. The tests currently expect three, though. I’ll implement a punctuation segmenter, using regex to split the original text. For phrases with four words, like \"Before you automate anything,\" I’ll keep the segments concise but meaningful. So, shorter chunks of up to four words may work for the user’s request!"}, {"type": "summary_text", "text": "**Creating a chunker for phrases**\n\nI need to develop a chunker that splits text based on punctuation and commas, allowing for up to four words per chunk. I want to use `_phrase_chunks` for the final output. It's important to set a style limit of max four words, ensuring that no chunk exceeds this limit. I’ll also need to test that the maximum remains at four and that phrases are well-formed to preserve clarity. Keeping it concise is key here!"}]}], "tool_calls": [{"id": "call_dLyWsuRB5eS8f5jwYl5wQzwn", "call_id": "call_dLyWsuRB5eS8f5jwYl5wQzwn", "response_item_id": "fc_0dc9f371a6d55e3f016a137d04babc8191b28dfbb1df3b93d3", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" assert all(1 <= len(cue.text.split()) <= 4 for cue in track.cues)\\n assert \\\"ANYTHING DECIDE THREE\\\" not in plan.subtitle_file_content\\n assert \\\"Style: TrueTraceCaption,Arial,72,\\\" in plan.subtitle_file_content\",\"old_string\":\" assert all(1 <= len(cue.text.split()) <= 3 for cue in track.cues)\\n assert \\\"Style: TrueTraceCaption,Arial,72,\\\" in plan.subtitle_file_content\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\\n@@ -47,7 +47,8 @@\\n )\\n \\n assert track.style.name == \\\"truetrace_final_motion_compact\\\"\\n- assert all(1 <= len(cue.text.split()) <= 3 for cue in track.cues)\\n+ assert all(1 <= len(cue.text.split()) <= 4 for cue in track.cues)\\n+ assert \\\"ANYTHING DECIDE THREE\\\" not in plan.subtitle_file_content\\n assert \\\"Style: TrueTraceCaption,Arial,72,\\\" in plan.subtitle_file_content\\n assert \\\",80,80,320,1\\\" in plan.subtitle_file_content\\n \\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_dLyWsuRB5eS8f5jwYl5wQzwn", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_vWzciQYYCjeyJ5PyKxyDMuvq", "call_id": "call_vWzciQYYCjeyJ5PyKxyDMuvq", "response_item_id": "fc_0dc9f371a6d55e3f016a137d0b5fbc8191bb97e626249c749c", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" \\\"Before you automate anything, decide three things: what should go through, what should be reviewed, and what should stop.\\\",\",\"old_string\":\" \\\"Your AI automation works perfectly in the demo then one weird email arrives\\\",\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\\n@@ -36,7 +36,7 @@\\n \\n def test_render_ass_subtitle_file_uses_compact_final_motion_style():\\n track = build_final_motion_subtitle_track(\\n- \\\"Your AI automation works perfectly in the demo then one weird email arrives\\\",\\n+ \\\"Before you automate anything, decide three things: what should go through, what should be reviewed, and what should stop.\\\",\\n total_duration_seconds=6,\\n )\\n plan = build_audio_caption_preview_plan(\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_audio_caption_preview.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_vWzciQYYCjeyJ5PyKxyDMuvq", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_6xm5Wndrz0SwHJ8cokPICtis", "call_id": "call_6xm5Wndrz0SwHJ8cokPICtis", "response_item_id": "fc_0dc9f371a6d55e3f016a137d11b8288191bfa20e158fdb4771", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_audio_caption_preview.py::test_render_ass_subtitle_file_uses_compact_final_motion_style -q\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"F [100%]\\n=================================== FAILURES ===================================\\n________ test_render_ass_subtitle_file_uses_compact_final_motion_style _________\\n\\n def test_render_ass_subtitle_file_uses_compact_final_motion_style():\\n track = build_final_motion_subtitle_track(\\n \\\"Before you automate anything, decide three things: what should go through, what should be reviewed, and what should stop.\\\",\\n total_duration_seconds=6,\\n )\\n plan = build_audio_caption_preview_plan(\\n video_path=\\\"timing.mp4\\\",\\n audio_path=\\\"voice.mp3\\\",\\n subtitle_track=track,\\n output_path=\\\"final-preview.mp4\\\",\\n )\\n \\n assert track.style.name == \\\"truetrace_final_motion_compact\\\"\\n assert all(1 <= len(cue.text.split()) <= 4 for cue in track.cues)\\n> assert \\\"ANYTHING DECIDE THREE\\\" not in plan.subtitle_file_content\\nE AssertionError: assert 'ANYTHING DECIDE THREE' not in '[Script Inf...,0,0,,STOP\\\\n'\\nE \\nE 'ANYTHING DECIDE THREE' is contained here:\\nE n,,0,0,0,,ANYTHING DECIDE THREE\\nE Dialogue: 0,0:00:01.71,0:00:02.57,TrueTraceCaption,,0,0,0,,THINGS WHAT SHOULD\\nE Dialogue: 0,0:00:02.57,0:00:03.43,TrueTraceCaption,,0,0,0,,GO THROUGH WHAT\\nE Dialogue: 0,0:00:03.43,0:00:04.29,TrueTraceCaption,,0,0,0,,SHOULD BE REVIEWED\\nE Dialogue: 0,0:00:04.29,0:00:05.14,TrueTraceCaption,,0,0,0,,AND WHAT SHOULD\\nE Dialogue: 0,0:00:05.14,0:00:06.00,TrueTraceCaption,,0,0,0,,STOP\\n\\ntests/test_audio_caption_preview.py:51: AssertionError\\n=========================== short test summary info ============================\\nFAILED tests/test_audio_caption_preview.py::test_render_ass_subtitle_file_uses_compact_final_motion_style\\n1 failed in 0.10s\", \"exit_code\": 1, \"error\": null}", "tool_call_id": "call_6xm5Wndrz0SwHJ8cokPICtis", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE30X0eG1ruNB5rhE8F-N_f1hZWGnIaOdrXNCg66H4AunVKy-DEGheAMLRAczGQmSRDNHUkZssI0uYX5FU0a3aUzyuV4O_NunD9AvGlOB40MZx2BimG1wxab-MibzuediufId0S19SiFAWJYqdnuJif52zAWNzplhhDddzsD_D1t2Z_vwI-1OYdKOCAT6bpRwM4llr-c-ucIzmZ1FpHuaX4ozE6LE49gXLNbWjq4fYvVdR4ATn2W1STSQ40jJfzCExk3GQzAvCqqbFnbSiMwEr47I5CwwLJR2KiYEBUViD9eXlU4n5obf8qGq4hitIOaVzzBSofD7vjZarZKnNh2iWfNR5vm1Uf_be8gTnfQXUv33KfTXc0CWo1TqSLRP1KfVT9I3FK9YYg_wX21HW-vDP9lrWViDzpkm2lntuCz5KEW82_erd3IF6tsCixiWy9dWxJsFilkARKBC5bRPVF8ni2YIxNu4UYyjdy-y1OyaUOFmT8APfuYCNWNIKeuHvsYnsELTINxxSHc0TXTId-5kPjOnSH38IeelKk_HDQtmErxNu95kldC_grV5_pytxUwFjWGn4KPziEclRoEm08eGwWoR5EmSXqK0TnvBSJwj6OWidrUNlXDX6QNS4OoCQFRJA4DUUy51ew5H8meJ4iFfXEQzIt3glAfKbryH7_cXEAksZseEKsO-DulR67F5luJdq8l07WmkTANfnjG3KutjeshoW7T_LjYxsyKPZ7-AdzfysJeLgsY61V8sjMR5MkGhICa4gagTYKhOmkUclScKOq639NhdFTLfwdz7pjOuJ4_Wh7EoODMNrNvTSEMSrvNC-K_HdLKGAez6YwYvARRYCIYBbEMckd1_nU1nEZ88DFaA5x9vjqpLqF89qi3_gzUTgyKwf8BRlo3ctrdE9CL3YBi0R0YvamfkaYxOCtCr-VwYlgifYy9aW44uC06P5ZdSOCau", "id": "rs_0dc9f371a6d55e3f016a137d1644c88191b5ff82c05c764e75", "summary": []}], "tool_calls": [{"id": "call_AIj1S6Nl7rXA7Gx6f0S445Tx", "call_id": "call_AIj1S6Nl7rXA7Gx6f0S445Tx", "response_item_id": "fc_0dc9f371a6d55e3f016a137d175ee88191b10ac56d1078072e", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" max_words_per_cue=4,\",\"old_string\":\" max_words_per_cue=3,\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n@@ -58,7 +58,7 @@\\n placement=\\\"lower_middle_above_ui_safe_zone\\\",\\n max_lines=2,\\n min_words_per_cue=1,\\n- max_words_per_cue=3,\\n+ max_words_per_cue=4,\\n safe_zone_bottom_percent=17,\\n font_weight=\\\"800\\\",\\n font_size=72,\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_AIj1S6Nl7rXA7Gx6f0S445Tx", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_jIuUZsphRHllwPdd3ruPEUCH", "call_id": "call_jIuUZsphRHllwPdd3ruPEUCH", "response_item_id": "fc_0dc9f371a6d55e3f016a137d1c7e34819180f72338aa4c36e7", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"def _chunk_words(words: list[str], *, min_words: int, max_words: int) -> list[list[str]]:\\n chunks: list[list[str]] = []\\n index = 0\\n while index < len(words):\\n remaining = len(words) - index\\n take = min(max_words, remaining)\\n if 0 < remaining < min_words and chunks:\\n chunks[-1].extend(words[index:])\\n break\\n if remaining == min_words + 1:\\n take = min_words\\n chunks.append(words[index : index + take])\\n index += take\\n return chunks\\n\\n\\ndef _semantic_word_chunks(text: str, *, min_words: int, max_words: int) -> list[list[str]]:\\n chunks: list[list[str]] = []\\n for segment in re.split(r\\\"[.,:;!?]+\\\", text):\\n words = _words(segment)\\n if not words:\\n continue\\n chunks.extend(_chunk_words(words, min_words=min_words, max_words=max_words))\\n return chunks\\n\\n\\ndef _active_word\",\"old_string\":\"def _chunk_words(words: list[str], *, min_words: int, max_words: int) -> list[list[str]]:\\n chunks: list[list[str]] = []\\n index = 0\\n while index < len(words):\\n remaining = len(words) - index\\n take = min(max_words, remaining)\\n if 0 < remaining < min_words and chunks:\\n chunks[-1].extend(words[index:])\\n break\\n if remaining == min_words + 1:\\n take = min_words\\n chunks.append(words[index : index + take])\\n index += take\\n return chunks\\n\\n\\ndef _active_word\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n@@ -106,6 +106,16 @@\\n take = min_words\\n chunks.append(words[index : index + take])\\n index += take\\n+ return chunks\\n+\\n+\\n+def _semantic_word_chunks(text: str, *, min_words: int, max_words: int) -> list[list[str]]:\\n+ chunks: list[list[str]] = []\\n+ for segment in re.split(r\\\"[.,:;!?]+\\\", text):\\n+ words = _words(segment)\\n+ if not words:\\n+ continue\\n+ chunks.extend(_chunk_words(words, min_words=min_words, max_words=max_words))\\n return chunks\\n \\n \\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_jIuUZsphRHllwPdd3ruPEUCH", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_A7klIFumfzvBJTJIZAISzYn5", "call_id": "call_A7klIFumfzvBJTJIZAISzYn5", "response_item_id": "fc_0dc9f371a6d55e3f016a137d28a2cc8191b528014d83508dbe", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"def _build_subtitle_track(\\n text: str,\\n *,\\n total_duration_seconds: int,\\n style: SubtitleStyle,\\n preserve_phrase_boundaries: bool = False,\\n) -> SubtitleTrack:\",\"old_string\":\"def _build_subtitle_track(text: str, *, total_duration_seconds: int, style: SubtitleStyle) -> SubtitleTrack:\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n@@ -124,7 +124,13 @@\\n return max((word.upper() for word in chunk), key=lambda word: (len(word), word))\\n \\n \\n-def _build_subtitle_track(text: str, *, total_duration_seconds: int, style: SubtitleStyle) -> SubtitleTrack:\\n+def _build_subtitle_track(\\n+ text: str,\\n+ *,\\n+ total_duration_seconds: int,\\n+ style: SubtitleStyle,\\n+ preserve_phrase_boundaries: bool = False,\\n+) -> SubtitleTrack:\\n if not text.strip():\\n raise ValueError(\\\"subtitle text is required\\\")\\n if total_duration_seconds <= 0:\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_A7klIFumfzvBJTJIZAISzYn5", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_7qkC1JWWX01kxbmHujPPtE9I", "call_id": "call_7qkC1JWWX01kxbmHujPPtE9I", "response_item_id": "fc_0dc9f371a6d55e3f016a137d301cc88191bbdb53ff1b81c4be", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" if preserve_phrase_boundaries:\\n chunks = _semantic_word_chunks(text, min_words=style.min_words_per_cue, max_words=style.max_words_per_cue)\\n else:\\n chunks = _chunk_words(words, min_words=style.min_words_per_cue, max_words=style.max_words_per_cue)\",\"old_string\":\" chunks = _chunk_words(words, min_words=style.min_words_per_cue, max_words=style.max_words_per_cue)\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\\n@@ -140,7 +140,10 @@\\n if len(words) < style.min_words_per_cue:\\n raise ValueError(\\\"subtitle text must contain at least two words\\\")\\n \\n- chunks = _chunk_words(words, min_words=style.min_words_per_cue, max_words=style.max_words_per_cue)\\n+ if preserve_phrase_boundaries:\\n+ chunks = _semantic_word_chunks(text, min_words=style.min_words_per_cue, max_words=style.max_words_per_cue)\\n+ else:\\n+ chunks = _chunk_words(words, min_words=style.min_words_per_cue, max_words=style.max_words_per_cue)\\n total_ms = total_duration_seconds * 1000\\n cues: list[SubtitleCue] = []\\n for index, chunk in enumerate(chunks):\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_7qkC1JWWX01kxbmHujPPtE9I", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_2o5xgVDzGM18lUcezohSAVVq", "call_id": "call_2o5xgVDzGM18lUcezohSAVVq", "response_item_id": "fc_0dc9f371a6d55e3f016a137d3761ac8191afbb6d4af05f5047", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" style=SubtitleStyle.final_motion_compact(),\\n preserve_phrase_boundaries=True,\\n )\",\"old_string\":\" style=SubtitleStyle.final_motion_compact(),\\n )\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/audio/subtitles.py\"}"}}], "timestamp": 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<<'PY'\\nfrom pathlib import Path\\nfrom math import ceil\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover\\nfrom autoshorts.audio.tts_plan import build_default_truetrace_tts_plan\\nfrom autoshorts.audio.edge_tts_adapter import EdgeTTSRequest, synthesize_edge_tts\\nfrom autoshorts.audio.probe import probe_media_duration_seconds\\nfrom autoshorts.audio.subtitles import build_final_motion_subtitle_track\\nfrom autoshorts.audio.final_preview import build_audio_caption_preview_plan, render_audio_caption_preview\\nfrom autoshorts.rendering.final_video_plan import build_truetrace_weird_email_final_video_plan\\nfrom autoshorts.rendering.scene_backgrounds import build_chatgpt_image_scene_background_plan\\nfrom autoshorts.rendering.motion_renderer import build_motion_render_plan, render_motion_preview\\ncandidate_id='truetrace-ai-automation-quiet-rot-38s'\\noutput_dir=Path('data/previews/truetrace-final-motion-v7')/candidate_id\\nvoiceover=build_truetrace_final_voiceover(candidate_id)\\nfinal_plan=build_truetrace_weird_email_final_video_plan(voiceover)\\nbg_plan=build_chatgpt_image_scene_background_plan(final_plan, output_dir='data/generated_backgrounds/truetrace-weird-email-v1')\\nbackground_paths={asset.scene_id: asset.output_path for asset in bg_plan.assets}\\nmotion=render_motion_preview(build_motion_render_plan(final_plan, output_dir=output_dir, preview_scale=0.5, background_paths=background_paths))\\nif motion.returncode: raise SystemExit(motion.stderr)\\nvoice=synthesize_edge_tts(EdgeTTSRequest(text=voiceover.text, tts_plan=build_default_truetrace_tts_plan(), output_path=str(output_dir/'voice.mp3')))\\naudio_duration=probe_media_duration_seconds(voice.output_path)\\nsubtitles=build_final_motion_subtitle_track(voiceover.text, total_duration_seconds=ceil(audio_duration))\\nfinal=render_audio_caption_preview(build_audio_caption_preview_plan(video_path=motion.output_path,audio_path=voice.output_path,subtitle_track=subtitles,output_path=output_dir/'final-motion-audio-caption-preview.mp4',duration_mode='trim_to_audio'))\\nif final.returncode: raise SystemExit(final.stderr)\\nprint('final', final.output_path)\\nprint('frames', len(motion.frame_paths))\\nprint('cues', len(subtitles.cues))\\nprint('max_words', max(len(c.text.split()) for c in subtitles.cues))\\nprint('bad_phrase', any('ANYTHING DECIDE THREE' in c.text for c in subtitles.cues))\\nprint('style', subtitles.style.name, subtitles.style.font_size, subtitles.style.margin_v)\\nprint('audio_duration', f'{audio_duration:.3f}')\\nPY\\nrm -rf /tmp/truetrace_review_v7 && mkdir -p /tmp/truetrace_review_v7 && ffmpeg -y -i data/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4 -vf \\\"select='eq(n,0)+eq(n,120)+eq(n,300)+eq(n,520)+eq(n,760)'\\\" -vsync 0 /tmp/truetrace_review_v7/frame_%02d.png >/dev/null 2>&1\\nffprobe -v error -show_entries stream=codec_type,codec_name,width,height,duration -of default=noprint_wrappers=1 data/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\nsha256sum data/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"final data/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\nframes 887\\ncues 26\\nmax_words 4\\nbad_phrase False\\nstyle truetrace_final_motion_compact 72 320\\naudio_duration 36.864\\ncodec_name=h264\\ncodec_type=video\\nwidth=540\\nheight=960\\nduration=36.833333\\ncodec_name=aac\\ncodec_type=audio\\nduration=36.864000\\n0a3cc3129cd09d4b2594f23ef2d35faf5b7d04e1e1f94c55a35b50d1f8034616 data/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_Dq132v1y3KC6Rexro03J8aiu", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_YPL167UBBYnDfNjebMDWuAKk", "call_id": "call_YPL167UBBYnDfNjebMDWuAKk", "response_item_id": "fc_0dc9f371a6d55e3f016a137dba66a48191a4bfb13048451e44", "type": "function", "function": {"name": "vision_analyze", "arguments": "{\"image_url\":\"/tmp/truetrace_review_v7/frame_04.png\",\"question\":\"Check v7 three-way split frame after phrase-boundary subtitles: does the subtitle read naturally, avoid competing with the diagram, and is it good enough to proceed to 1080 export?\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "vision_analyze", "content": [{"type": "text", "text": "Image loaded into your context — you can see it natively now. Use your built-in vision to answer the user.\n\nQuestion: Check v7 three-way split frame after phrase-boundary subtitles: does the subtitle read naturally, avoid competing with the diagram, and is it good enough to proceed to 1080 export?"}, {"type": "image_url", "image_url": {"url": 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5zRDmuwxSIzrmj5K7MBKgOwkj2lN5et/+rXz5ETxUC8YPZGHMEkBceobxiHCrksCldyzHPyJqFZDhWzPTwZqBx27GkjJTUoRMZle4SKxSlDOlQmDBVUJgAVYTyEDpUdFiqQusUjm+SoMZGyZhhRzC1FQEVKpWh+RjZFo0CU6YKKPTTPGVngii5UNN8emgNZAu21TfdlrkweKqwFvgyVrVVQ6QVCNteTgpb+zaXNg6q2AC3dpT/e+2i6MM8pJx2BhN2XdgbAlaJTbnEFW/k4fO6vsJEu/habrwiZ3TmTK6soDZmdSabmKWJxJ2YbVA4+8oQVazet7xuGp7JhYETxVEbe+XDdLIQKTGTzUGEezM/Ov4RZ27LlxZuzw0DljWUfTBQqI1zdW0a2DVRwzU1BpWp0YfMZXyZIkQavsymLP6HGD9+4Mrr9XJKG6H8tTkUeGTJ6ZZMvKMWipkzanM+achlLLmvOZqRYTAoGWfp6nF3Bjwgn8VwV16CWkq9KBod3XEm24FxwBURxxxYBKpAzAszMoybuelyZXqhs6hsLKlyoiQ9sKW3cxKzwF73rMgAAEABJREFUE8+83DJvV7M7TFChEfiEFmUQPiOKJ9qJpYORpt0RaLWzWb/yk4EKb2KxepKzDSqLjzv15bfeB1GUJocRatCehVCBrK6gDpUqqLz57ocDW0tqHQtSXoxGoFJ+hbYpVCSbtymoVLXx7EhQMcFdKGvbQwVEsQTCtkLems8BKtYiW5EiYcnrlcJhxhK7l02Lsg2gIrkLZn8bvBOFKMxfgeMCiRP6Gt05iODBk9WL+eoVwGj0EKvMuTIGVNjKIGtS/vYPzic8yPH2aGbewp0POPX0//zzfX9bt3ErvJNNvUzdPQwtmxVzPFgqPf3iG8Fki0vOQTbhpARC4MQbm0Neiz82L5hcCK5A8FcAFaMzZXZnJFPI6k6DEEYHDHdM7IRWJc4P2hOXCuGHkjWELRY3tiRJ4ArBwxlIYwV/Yt0TyrHOr8qICsYewVxKRrfNHZHMAUHBKuGwkuSUrD7J7MEHafWyYxLDDMpwDcnkO+KETxNL4KyIUCn3LQ4pGu1qDK6wS5LcOAJW8GhwHBoIMnpkyU0EYqeArPKEoYLblMy4U6z73YH4G8tW4gmKUNnQO3jI4cdKkhX7kNEkWZwhyeyVjE7J4tGCiiSZJJMLlhdAwm44giTZgS6c1+6J4ucmezWocNha4XTsOi0+cQUihLCHhadgcPGDGMstujCazQoPUXmgLmb7rO5lKz6Cp1IFlYMOO9rmZneEQrN7wqwQzLgqD66BIc3q51Ah4VPiUFGTq5cb/NlDV94T1hXb4OF9zesOZqIrZONdDCh2L27QKSft/jg11TAK2vBEHFhaPCFI3d/owh0RiniZWDwRWo6+ut4o/sSStS2bPTTgxlhuLadBNjXyjsrsojlusay4HisO5VUyG6KI3LRDo1BxRhuX0RXTkvav6ofXjK4Il7hdEiWErSRvTML7TG0keByhtDlZsGVaLalWa7rNmW63J1vNckbyxA2+pCmQ5uGvKmldfyN5DrUGFEvACfwSEMUd40EwJj7rophuq+7kjCRYbS7YbhLsOItBwWNQXIdGoLK+dxQqECDh9mdDsfZ4es6+Bxx93wPPdG0cgY/CWln6Fbr0lwaGS29/sP7aW+4MJjr80Va3clIe/iKW+OJzQ5lFWI9kdvJF58JfMbtzWHGHOij/sT/SDgVibTgI2OAO5rGCpZZAEVybw5/xhArYE+u4ZhQ0mOGLFPzRohxvhQKxFmyB3EHcSwZ0wQoUSrZjNyzlaJ4LVi8YKwTCBa+cLStfpWCiDUUnJ4quYApfI5Y4TpW0oIIfKsooSonCr3BVIBa7JOWy6VBYoVugy4Zwa7A12IIrwZ++YK4pOX3xWLo9lm6NZ9pg9+Vo9t0P1q3fNFgFlc+c+YVwohBJFiPJVuyPJRSKF32hDDgUjOW0oBKK552+KJbYB0scBMK58HP8NpxoQQmjqLHuDaaxhAKRXK08cgpL/C9+mMh24ie0hf4Ld5EuzIN/gAPSkd2h9ISFh4ilL5rxhFMuf+Tt5atY4+LQiAiVI487xRuM4168waQvlEK5YSUQyeAacD3uQPKyJTdpQcURiAWThVCqFa8NHh8eKx4f3kYStvDnyzdypVsX4IegCL1yIApqb4F4wR/LQk45DgvuCiawLifyuAXcCHaOZjt80Zx4j6zOF0zhhzhCpm2hJ5zxx/JYOgKJSKYdB4/lOrEbNuKHJPxvPaVI7lASS5wxlCri7PiTb8GfuF9cD//T7o8CKrRPWRqPI1xoXN5oi5a0f1JfvliRS9zuFuSJFbmcsQJE6454ATLGc+CKOdliiOVtiRZzNG8JZm3hvD1SgNxRDWlcJ8xaXcHAcmntI0meFJOSL8sit9pC7dR074nMJ7nD85zBOfZAh9XXZnIXRe9Ey1OhPF3UU5lPfDJu+Iugsra39K0fXlAeS898DoevIFlibl/e7krLkdZrrr9zY2+pb0upf7DU3ceaoHmL9G77HA7LruTDT5PUsSnepD2Yw9IZLiTy8086/d8uXXLLvQ8/+/aKDWu6t0JYeX7pWxdc+qtDDj+RPlHYd5srBmmFv4AHckpMykj4Axef9ONzL7/1zgdefuuD19/7aMXa3lUbNr/05oqnXnj9mhvv/M6PLjj4iFPwMWNn3Dj5MZLkwEeLE4mSTB5Uill1WKOmj2tbuMu+Z//o/Meffun9Vd2r1vW/9Nryvzz01L/+239TpRv27qjjP82aavtHNvZtBVSou+0Y4S+qS6IqimojLMgJn/ncFdfdev9jz+FG1vYMQ1iBL/iLi5fsf9hxMBmsXomataJmPRVW8bf44IW4/DFABYRYtmLt6vV9IlS6erYsPvpEOBxKfCzMpXpyFo/B6q2FCn4IqCgxIq9kcsxdtNtlS65/8NGnVq3rhScEf+j2O+8941//y+VPsGtAOZu95HnU7QjAPCrJgp1POf0LV/7qN3fd88gby1ajtLt6tr734YZHnnzh6utvP+LYT7P3xK3kehmz46mWqOZeFv4M4pyvvvleqVRat6lPhMq+Bx4mmZ2S0W52+NgNWpg3hnLAXeAC8Nzx9mpBhUzqLnsffN6l1yx94328nBBWrr/1rn/54ldhvnF2raAcavoU47J6w1Tll0xwklyS2SFZnIF45rBjT7rxjj888fzSD9b1rFi76cEnnoMpVz0GxV0gz4AcJvDj1DP//aobbr/n4adeeO29ZSs3QG8sX/PoMy9h46FHnwLw4KSoLWk7dkEuHDCWaz/5jM//4uIrn1n6+guvLcNLjmt47d2VT7/42s8uvPyEz3wWQMXtkx9T4eXUd4P8EhzcunKEaqXZqg/vod7+7CcaDfhaDf6SKDHtikuWvGEpkpBiKUO+YCq2WIutkDvRYgtnKUZCpkltn9do8K/jM2lMitF4kFwyeNMKVzJKyqyswZsntIAlEHHFH1/kjS4AWmz+dhEklaEwzTYVu7/AMkI2DxU4ECCE01+EABVvoOgLFuC4vPjK8p4B1gcMXIHJw8cDC94/Urryut+Bn9wxYr5RIA8Z3HHJFgrn5n/lOz9/54ONG/rZ0JCuvlL/VjY0BMIK/g2VShv7SrDRJ5z6WdRMYQGd3qQ69FIJfGEF0CqvxwEVVOo//6Vvv/zmytUbhnBYpgF15MT6vpGREuvU272ZHX/TltKPfnEZuIIfkvDzs8+5CJ4WF4Xyzr/4apgJQlqt8L+r1w+AGdQAg1/1D5WGS2z59vK1x59yFirgHCqQCJXy2xBVNBrxACeAh0Rh7nd+fP47H3bxDmN0FzTeBTcCrevd+vwr7xx76lmwRPgJi104ow2KWonIZP/Pt3/4UVc/XMzyXYyIUMF2cIWMI+6La8l1tykxKK/VFSSoMAelEiqSwSZH09fddDt+u7FvCE5P3yDzZfFwsURxvf7Oql33PAgOB490AVd8hQsvwC8vuWbZivU4zuat7Oy86YuKHQfEyitvrDjtjH8DWibUkWm0XeG/vvH91RsH8A6vXt+Dy6Y7grPCpLS64XQfdfWuWrdpXfcAazJh/tzwXx56ElCh6wdUxPY5ESrtC3e7/tY7+ZgeEr2o2AfVhdb5u4kJXUThCOTyrusdwjGVTupbb/7d3WZ3YM8DDn3k6b9ji9ITZJheEizhJbBZnip7BCUKnd895zzwAztvKakvGBf+3KJ8LM+9/Daog/dKm8SjYztwbf9Y9iHe8M0ldoW4MOrzRpaEBsa++s4HZ/37V4V+1bwLk0bLllavrfFiVlUatxfZZKECxstxcypnyxbNLa2ACo2WNwWSkjdGDbr0dZdDZ4H6qsVes61udaAi5MXiIwRNnrQj2ApRyIuCY574QixtwU5LoN3kazV4imZ/G1ZU+Ytc5kALRG0w5d5WeYErjULFrjg61K7u9Lc6fC0ef8HlzR1wyInwUbo2lTYPq11myVMBHqKZefBsXIEWd6jFH+uwBzKuUN4ZzBx05Clvvr+WWcn+zWt7+2Hwe4aHoa6BAQgrsDj0TeKTxgd8zQ2/CcXzMF70YHgjisOfUSPOrhCqfk/+/RV8bOKgM5yCPKfNykcCM4G3HCu4SNT04aBwqODBw7kRa5cQLgP1Yqp7MimGGHgDTjyBzJ1/ekTtMKoAA44IloMKUWDmsH1d99BXv/GDE049UzGpW8lY46Zght79YI1aDbeHlY4ArP0fjirACcP0yYOOeu/D9Tg7DCgOMqhYTBwWB4GwQpc3qJhmaMl1v4FLhCu0u+MQLo9jo1Z0RlUCVMQusI2oFiowvt0Dg+t7+mnl2pt+M3+nf0JNn7OEGq5xU1RipLeXf5RtmWf3hG3uEHUHIOGwktEJ5+nATx3zyhvLsecIa+wZoXun14Mbbth0lAZqI+u6t/zx3r/6Qpmqpnvu8Ywr7Pa1b/5QPTh1S9mylat/cGRUeEMGS7SEfn3zbyWT2+YMWh3yhZdcLe6J13jNhr6rr781met4fukbuAu6bJSJ8p5swZ9ESgh/tnTujCvBAxUujHUHuODSq9i9D430D5cIcl29A9fdfOse+x703odrURXDWfCOoZBxNOXgI7F0EY4UZHH64Vd55MTBi4977e0PUGJ4EPBK6XXCe0XFOKwUI66QjtDVM/Tgo894g0n1iZjdYvoQ+KBOX3i/gw9/6bV3cI+8bwKeBR46r3/QdmzBE1y/afPv/viXQCSFi8FvcVXk59XVuH2Cx+hS3Jga6jw22qXYo/QSViAKVLNOw64ASyqcSBgyGWMhbyoW3C1t1kyOzQHsD4mdBSoP1Wg36Ma7hmt6tyJURLRQB2Ia8yG2uyhNL6znsVXuAFRGuSJAhUTejE3V+L2/6kJFoREjE4gCwV8BVOCvPPjIC+u7Rzb0qNUc1aD3lU46/T9MjpTZmTY6E65gEUSxeJOnnPmfK9YNwKdhI417+3uGRwCSDZs3Q92Dg5uGhnq3buWvI74xekHvvPtB2BdyIam7F7XMU3v43gcdCc8dRAE2RKh0lyuJqHnhjGAMcaUKKnBTmoKKy5f6zR1/gX9WMRZBMZH0CfFaP67/2hvvwAo+1zGgYncnARWDBW+A9/BjTuPeT5msW/FzCCvidqIOneXOux9m4SNbCAeBcEytkNd0QwWVepi8DX2bH3j0iZdfX4arhaVDzYAQSMa0Csa/+e3dSuu9n5r0yaDgT8nigQWke8eeRFDcMjSoHBArdEwqGXphsOdDjz1PUVPJ4qsKo00YKhU4aQYqcOLpOm/7/T0gCu6FKgR0R/Q0cf10RrqFP977KGoJuP66UEHxDqAQRtgSULnvr4+9/s4KKmE6GrmYWIGLCfPN+hQY7S4/HFPf4qNPBrRoZ+VVVK+NXEAOaXou5Jvif+GEufwxPA7+dMrPyHvEsSfDYwMq6IOl7oIQHZ9/RwQbWuJzfuixpyNJVBMDdg9A5dTqJTiboUIRP5MvbA8lzPm8vbXV3FIEV4yJlBSNs6m3ti1UtLhSBypqOwQ1S5TR4gx1UN5G4gqhBV7LKFemEirn2wPYdi8AABAASURBVPxpOBkqVHxtkMOryFeA7L701797Ll7T7s0Vngr+vHTJrRZXxu5Vz+KNFhb+04EfdPWu6R1kB+/ZjLcN7x/VufCp8PpX/+DwwNBWWtLK2q6+Sy67Bv6B258mqFDgC1fesXCvpW+8B7+7e8uI4vKP0MUTTng2KoozkGu/aUvpFxddIxIFOue8K+pB5WalBj0qGJ0zP/+VQVYp5lWzEmEDSyUw0s9tBNVDye4rZrQ+VFgyAngqJv/CnffDz9dsGMBXTfzgCOGU5d8nr6rjOtdvGvzpeZeSv4LjTAYq/I646deCChm7KqgQV2DvNvZvIVWN8xBiawwqVF/edc8DaKCMqN32OnAl3pKtFSiqin3RBSvmbATVapQ8BdYuvfLX8FfELmFTCZUtJVKDngpZWDyj4ZKKECpwGH0qCv7K0a1hudPun4SjJlhYL3TB/16hBOKGoY39A90Dm3Hkrt4+chABcnw7WFJR00o4mTE53Fa3z+bx7/RPe8H6UyhS6es8GvCkouMXUFW8eATnXngFc00MDmI/CR4SbgFHI/eIiAJmkOhQ2IKngz+HS6N9rPEn3hlwDkRR2qW2D6hQ65E6viQQlCIxKZOSCjkQxVosWlMZUzwp+YJMfuywraFSlyvjQMXgSkvOFGNDgDW0gCtEFE98IY+GEVco5EWaQqgw1YPK3gceu6GfUYTHT7uVXGH3PPScL9wRjM+jBJQOOX3rXQ92D5U2ls09vW34Eh57+rnDjj4uXWyDsPLIE3/r2zJERMEK/PGhEfZ577rHIeAKoMK6ypllh5/14Lrh1rvZocqhLYIKXQPckRM+87l8507+WD6a7dht30O/+f2fP/vSWwQV4GQCUEEV+O8vvb2xj1kuTg4IO8OdOvBTx6A2l8p3HnncaX/480P4360lNVSlhH3qQ8VkgwPEAlN3/ukRMuJUuUMdn07x5LMv7r3/oXI0DWHl3gcfYzAeVJtw8GETWnbb62CPnCJyTBgqolmhSmvjUIGoEk3+Cp7s6q7uL3/9Wx0LPhFKpA887Ii77nmQW1I6Mm4B3P3ej89DOVfWgv33Pfw3clWpkMljw20+9Nizhx11kjeYdPqie+9/2B/v/SuF1GAZsedwSa1073vgkXhYk4cKqDB5qFBJgiuvvvn+1775/WzLPI+c2Gu/Q37/p/tg6Mko8zJHreLHP78IL9IYUIH6h9l6z5ZBkBtcufehR076zBmJXFGOJTsX7rT4mOOffO7/ABWz02NxeaEHH3sSXoUSRx2FCgrt3gefgAcTz7ThUe5zwOJ7Hnicorjk9kG4HhQ7vEb4KyJUHnvq70REzkKq+vzhzw/AgwnFs95g/ODFx9zxh3uwGx2Q2KNE+Qb+aZ8DaWwHf+LbE1SibEp5QzFvbClYCgVjNmuAgyKHGFG8suRj2vZQqeWKJM7rXiHKtKhOzctESRvFIBhHiz00hzelcK5MH1Rg2efutF8fjOBQhacCzDz/8nKnvwhPhXLmH3L0ab1bSz2KyIHAi4haKgw3Xla7J4x3GtUWvGTRZPY3d9y5qX8ziKJK+bzv+vNjXjlLnYwlSxCnPvSo09b1MJxQUEvpsMu67b781vu77H0gDUNRBqxUjG456fR/+5cv/LfREQZRCCpY/uT8KxuByvGnnPVR12YKxfBwAchx2ZJfByIZZTCHl+wjljfc8nvCw9aSGpeoggoZepsrYbCEDj38lM3Do/4HfjWkAOOKa36txJ19XB45dt1Nt9PRxMbzu+55hHWUMvkpTNfU4EcaSvL6Ox/WQuWAQ48uN3VUO20UsBIb6slZocbtVes37rX/QZLVIVnsktGCKnMy1/bXJ54lqHDPAybsiWeW4uwiVI47+QzYO97kgCuBRcby0iuvRzlLkhVfC7tmyYKLv/bGO6ihggqkxIJLLCQoSc5moSKWiWRyvvH2CgKDyhWFJQcecrTZ5rfYgySzTSZJJq/NGa6FCr0DuB1oj30PcQfieNshVNXdgShMM1U4OFdw1089/woNHqqFSu/gEOEEKyRABeQmeMApIYRwYTt0/Kmf+WjDJvIbiARABc6L9zacKLDRNmY3YQy0vv7m31FDCxeK9657HmY93JTHBJfl0//yxZVru7nTzH1QvK7iu4p7tLoC1998RxVUsHLn3fc3CJVJw6O+tIx+1cBJvoPkV5gRDBsTKXNL0ZDPSfksuGKLpUyhmMkXJt4w5HiZtPk0PlSmKt1OE1ChOa+scgcQApB4E4sg4gpTYr493CFyZVqh0jJ3D1QPeyozHItQoTTGl193exVU8PG8sWwlqkjUAKg0BsIWyy5fsLVzfnffQP/gsAiV7r7Swp33cwaykfRceEguOXfpklsGS6M4gbr6h3Dk4047k3VbNPmUCaOq+yJHM3MS+fl8zKNJmT2lQahcff3tr7+zSmzYGCmVVq7tSWTbgUa1a6nBgS8T621zd/5wzSZ8kFtLFEbXbKiHLrvqliqoQG+++2EkmZcMNtaHtSzYl3ShgweyueA/5dsWlb2fCUKFt6ySYFCaggoMHFbgrEDf+t4PYeMMNqcnGIFdA1RgQb753R+JUMGdwrQt/ceyqvDX/151AxUCDDEBA+/YshVrQ/E8u1STi/aninMs3UqNzNQ3jHi/ftNwrnXhbIAKFSnu4rs//AWIgotH/Ql3gVcdj/JbZ/+Y4kLEFfIhXnz1HS1PBRQhT4VD5fY//AmuCUGFEIKirtKlV13DAmKbR+gNHFDiBK+9/QG8alwSnQtXRakB4EihPCmoSA4NVuDOFtoX4lPFbtB1N/2WGud5zQb/Xn3zvVi6KEJFksyoEqEyAQKJUIFWrO5q6Vxo9wTHDX/NIFTEHaRAGPCgXF6mYsHa1go3RcplsBG8qRger7S+zAqoqOlJakXJSGrRonT6sgU74akQVwgt3uQCyBWbaw22WeRW6v2lARVKKJnZ9+Djy1AZYqoDFZqza7ShnqACE09Q2STEYXuU+UgIKmxoiznkDrW88f76gVIFVPBiff+cC+yeKCW3YJ133SG8r3a33+EJ3PXne6lBhUn5mGEyvvilb8JNAU7gcPgiLS+/9cHmErlHakUJL/fDjz8DQ0MN+zQWpCorPuvbp4xFF6HyswuWjAEV3tX11Tffh5mj5mLeYeaWO/6ET9HpY2PyJQPsnR83hT9xL7/57d1vL/+IWmW1oCKZg25/9o131rBBP0K/Jpzi7B/9HKA1WN1qEghFFIn+3R//UgUVVM9PO+Pfxg5/jQuVgeGKaxgDKorkKqhAFP5as7EnXWyTJCMsGtwUWDq7N4ArP+LYk7np7C33VIY7UtVQD37wphQKwlCUjFhCtg9uCg1rx7P+3R/vxw48FEOdwc78/FcmDxWlu3w9qNjCJLM1RDKYfVZHCFC54OIlIlSoJPHa5Frnk0de7uEWgE4/64u1UFm+squSssxAl6Gi9m/m4/x322t/8IlGBYnCFq633lvJG2+4S3T2j87FWdSeXSYXFSYrWJPrwUefUd7YEao5UUfqz37xK4QfXBI+BLG1j3z3b3/vHJEoNI6HVuCX8BZB+hWYdNoZn0OFabuAitkbkpIJKZcFSEytRXDFls3bIkmTHLV6w6NhMcVHqRfy2k6gIrnykrsAgS4VaEkugLOCpS+1EC4LuEJdiqcDKlZPksJfdaFC+xgc8Xj+E10DOHgFVFau7Tt48QkufwIfvEIUBhUIUIGzcv5Fl1RBBWbiqmtvDcTa5Hh7KNmZyC9c2zNMXYRZ33y1/jvyH1/5hmqe1Kxf1SkNABU4Z0pkTE2A0QhUiCuwXAAJDAS8E6rB4Qv56je+x2IyBodovKhn1Je+9v94G7sWVAyWUCTR2TPAhpGKBn1d98DBi4+h3jvUMZREjDn3wsuqoIJihyNld8dnECrUSg+ivPneCvgoAAkErrgCIfwJE3PAoUdWQYXwWQUVpR17iOJj6zex/qn48/BjTgGqIXJW2FLxceEj/uTcS6jFhdCi+FisuX5bQsVo8QMqNmewFipdPVue+b9/0OstQgUPd58DPtUr5FujkoFbUBkPrA8VWqJU8T6wdm9moL0iXbCOH2JJ7SgcKnSW/Q4+kuGEvbcB3pmb+RYm10/Pu7R/SG2dom6N0MWXX0tlHk4UxB5rBBVc/GFHnYCbEqHC+ncpHZp/ecmVIlSoef+yJdfL0fRshoramuIN2eUYeSeW9lZrR5slnWW9vBSEUE8wNrE8wONjwv7QrICKpTwtPDVCiNKMjCmiWX5h9F3Boi/azpyVxCJf8hMQVtyxBVa5A+wRE4LRCgW1YPf3Pehk6v6h+tTKy7euh9K0JEcTivhyipTAl7IOi3z4cf+sNlzDTAyoAlTufuApqzttciTApNYFe3X1s4Z0tTVlWG2or69h0laKHXOt7xv+/T0PeUIFOCvgSvuCvSnOTqH8Tf1MG3uGTzzlTIs96PYlygP9YlWqml+Ltal4Ij+7UDP8RYYAkqNZXqPku4EQhx9zEtmsqmZwmN1jT/rM6vU9ylhONowOVgDLdz9cLc5Q4vKlOubt0dWzlXfrnJhwMX++/4nmPRWZRkVIFt/r76waEyq1Yp7Tz355keKjDEIU8cef1/z6ZrJoYo0VO++13yHqGEnBwOGhK3VkPw3OKLR/grZTawRv3al6QGNI6QMy8rs/PihCpemBYxb768uWU48D1ZQrZVIXKkazDFntEZsz/MuLrib8sHZ+9k2x3157422iuwmNA5XKQSEQdSnmoVfql3XXPQ/Sy1lOaumlWQx4OAtvb0vnJ3h/dKG3xUiNKvpi0M60pCE18Mip/jFn4e7ie6L5IVeKB3X71I7Lw3ff91eUQy1O1FaWmil+SU2lKB5DddwRpSmetZ34FTx4ZNaPSw5LiaQ1X7Dkio6WdmeuxRRP24JJo1fNxtZIg3xlC/z4KfcbSsvfQO7OsaDSFFooJSUPiPHhLJSsZWqhgv/9xtm/oKEVIlQ29Jd+fuHVgIpkCkmOyILdD6Ixw7ybb4NQEQWo/OmBx2hiY3Bl5z0/pfZNEqCCazj8qJPV6LYGVEScNAIVPBh8n1iJZ9roY6DaFg0OxwUfedwp1HGoFipHHHvyyrXdIAobU6JU5Lt6B6qggovcdY9DQOXJQ+W+h5+mEY4zAhV6ecaFipjyRIQK+YK4mEW7fpJKuHGKiCpHV0qPPbV0m0GFuFILFfZRTClU6O56ywNg7/jDPZwoVaaZmvrh2LXN3ZkjuXGoiGihUNjDjz9H44cW7rK3+JI0DpW+wVGo4Iz3PfxE3S7FMwwVr8wEoniDxkjclsxYcnlzNmcrtJoyeTZjYzAKohg84R0BKuNyhdBi8uRtATYC3xub54vPh7CiZKXs4DMWV0KlZd+DTlXHxA5tYaoDFSY2RYqCFrs3S5jxx/JPvfA6DdoQobK+t3T8aZ+3uFJuuWh0xebsvB9rma+Eitbr2LuVtLVK63q3PPTkszgpZbnvXLSv2vQ3sBloDRtCAAAQAElEQVTiUDn5tM8azD4RKmb7KFqszvg4UCmHqge2VkAFYlAZ3MqHYtA4m1XrNh11/KncU4GxVodJKpg56dNnUidaHiCqAxVXeMHO+1QNTOGfX+MiM9p8+EvtSiuZvYAK//hFqIjhkXGhovRzbQAqiqhCgJNiZ7sniqKAvzJ/p72JNBODCvUoQ3m+/Pr7k4cKHnQVVA469JgxoGJ3RepC5ZobfkMlMCVQ4S0TN9zye554vyqIh8I0KQmh2+buKhKFqmJCE85YUOE95vEmvP7Oh9TSQ55KrzCIamCMOmIlVPqE9AFPPPMCTSIw41AxCCKcSOGoIRo3FQts0sZs1pTLOZN5Uygh+cKSl6Vm4ZptUBH3mRqoQJIzY3BlWV4WuY3QUtYcT7STo0WZJqtRqDgDaSwpGbAIlUOPPmXNpqE+oV8/QWVN99a2+XsAKnBWXKF8qnWnzaUKolCX4qagsrZn82PPvkCTpth96WCiA18CM9kCVHDqL3/tOxZ70OVVE5bw6U8IKjZXolmo8AiYHM3yQeObRyihxXCpVPraN8/mUDFYZMqSgo8cG8/+0c9LzMCNsPxUlMG3Jvxlc0fimY4NvSOQyBXqHNW48PO/Pfeq05uccqjwBo9phQrKwemLSyZPMjeHY3UCgsM3rOSOW/qP9yYFFauDoELZ7zlUDv7UsXXDX1gSVC64+Jq6UKHGjymBCh/5cfX1t5Z9lIqnSZUVLEWolHEyooz7GWoQKtTNBG/Ca29/IJlcHjlRaF84XBp9USnTQVNQIT37wquSxTXroOILmYMxcyLlyObZIPlC3pzPAypSICr5I0wiVHyR7QYqtWocLUZnSp3typ2hCbK8kQ5ftBNQ8cXnQpQVn82UpXClQU/F4o65g3mWCd+fB1SwHkp2PvrMSxsGyq9LeRYvfE6X/+o2lgPYm8XODjlr86ff+bCrCird/aWO+btLFp8vlKHwC83PIdm8dn/UEYiYXH6j02d2BySryylH7f4wBJIpae1Zb+ZX3niX9fGvhMoTT73oDaTcvkQ5C5bqqZhsEYOFDQpRk7uZ/SCl2vtrTKhQ9xgyo6+98x7ZCBogRk0st/3+bso3hdPBWJOHhNtxB5K33HHXex+uVYccK0Cq66lAy1dupB5lokGfv9Oe2I06KLNJO1A+ptHmerXp3uyUJCuu0OVPsPzBJn/VaMfJQGVD7zCgonS1sk83VMrdlJleffM9bBwpiek9hlFBpnlZnL6o3ROmVn1OfeZTmtn0MJLBRf0IqkbUTwAqb7//IWoPPNcD91Rc3ij4IRn9opuCpc0RlcM5DhUS3SmlbZ4qqOBrpXaOy5b8mkOlKrszlSe9XW+++xHlhhksp/bCEfbY9yDJ5KCezXZPkI7DO4NRQjby0SmSRrPjUGDtrfdW925Rh8pT1y+sL9p1L+rS5kR13mhnr6iSy5m6LLLRRZDS6wQn9YUS1KrfLFSmNuRVHiEfVgbDy1IgJMXjhkyGZpW3Z3LWVMYaTpjkqMET5pI8IS7t081Q+Eu4hiagMh5dVKKQLB42AyPQQnOZ+BPzAsn5EAMMHBegpTGowATDU5HMssmRACrgKNz82/sp35daASnXzlav7d1z/yOxPyOKLydZZHe4cM1Nv9tcqoDK+k3DF1z6K+pbxXt/sTRQSmodNoGayy8ZbZLNHYhnjjnl9EuWXOcJJyRLkNK0+CItl155Lau1VYa/NmwaOv1f/gOeSjm7YhxQwRI48cp5LCWj1+qJs4z3Rm+zULn+ltvofzf0bR4pqU0vH3X1xtLtbOChOaAMZozh1LDR+bZFazb0UUcXNiJPgUqtpwKhhn79zXdWhbzWdW/5xQWX07AGmJiqUQv4GvFNsq/U4oILddzJZ1x02XWsK7M3OUGomDwvvba8KuYGB+vgxcfR2bclVK698TbqUESZvggtF1x6NRk7SsVPs2OhGMnwUSkp8Zng8aecdemVv67K/dUsVEwOd93w14GHHC1JDoMpAK5wqJAAlVR2zvkXLqkLFeoHNYWeSiNQIb7i7eoR8q0pGrr48mvoGeEyIHqm1GpCnfKpVCPJ4iGHH3/FNTfhf6mjPP4Xn0Z/OdMduR14TD859yKGE6rxmJ0EGByZDVgxObAF/0sMO+LYk/HxMsCYnbWtQTMAFWqcD0WNkTicEkuhYCoygSjGGCOK5A1+XKCihRZqtOe/whbWhi+3eKKdwEkwvRBiK8m5gXhnuaG+Giobeke+84NzYe+oCuyRU55AJhAuwGLutuehTzzzsmgEuUu7bMX6K665hU1PAqttDlvdaYMzag9k9jnk2HV9apdiSt5Ooz1OPO0svKk0qJ5W3AEsI3j/sBKKZ08/64uPPfX39Zs2P/bsUosnRDNCUt77fQ88nCaVYhevhN3wDW8ZLq1c3b/4iNNC8WI40YLLZhl8lck2KDZ1xAmnf+HL33KH0gaHzNrZXGyavJ9dePkYUOE67uTTn1/6Gt0pt3e4gEuuuA7fHq6ffZNmN+4Chv6WO/7EU8ZSrIwq3UqX4lGo0Ge/zwFHbOyrMOhUFT3mxNOpVk6hc6xQN00IK8FYBuXz+NMvKglln8NjwtMRc0o2CBUlaZjnb8+92lPOWUmlgcP++5e/SbXUqizCiqPgE6AyzIsOnLj6hpvKUAnwUYoqVIRyFqEiGsSDFx/TXx790Dc4arzAzmAsB5yorhubctGltMcEYaoCkczxp/zLw4//HXdx74N/o97qE4YKLp6edRXsv/6tHzrcYUDF4YpXQQWY8cnpulC56tqbYECnFiogxBhQEXXU8afj7drKcjQMUU8wxQ0dPOr4UwORlFI7MdFxeMdu/OmREyjwhx9/Dvs/8uTfiTR4ySWD49AjTkCFabg8TyiFsrt6tpz5+f/ETanJIsvZkbHuDcbJO8EO9z74GD7nvzz0uEeOKcipHk6/baBSkXZFDgMnQIgtnVU6euXtqawtmTEHY0ovYSWjlxLvIqhU9gaeXVCpmKZlwlAZAy38vxhmfHlHsBUOCkEFCqcZV5z+4n6HnEqjKESo4C3kUAlEctmWBfvsf9Rnv/A/t/3ufjYrV3/9luT7Hn4ae9L8V3BTABWLNxlItNsDqd/d8ygfp9JTDrPgLb/jD3857KiT5i76J9iLeKYNIFmw8x5f/p//d9mS6/Hirlq3ifa85+En3SE2pYrBHqHJg32h1D0PPE4TFG7qG4HgqXR1M7dg7fqhq6+//aRPfy6R7cTFB2OFPfb91Ne+8eMH/vo8ZSl2ykmamqkpqOALWfqPtyknPyVyV+JUbETFnXc/uPf+h8Ha4lPkOalw/ZSEXMkorI5nroIKJEfzBqv/r0/8n1iSPZvVPMS333kvvuE5C3cHqGLpVpRP54Jd/v3LX7/iml+vXNu9YnUXVT8BFYBzdLqUcj+0RqBC82499tRS/lh5E8WTz750wKFH46bEcqBimT6ogBAwOjBS+C+UIZUzhW7uvu/R0874QrFjEZE73zavY/7OX/zSf8NqL1/ZpaRzZjv/5aGnqgzrBKDy1PMv9QkdYUlLX3lnvwOP8PjSFPISw18WWxi+4zaGStkKaxIF8oUyeLvwrSmVRTVhF0oVJfzHex864dQzFu26F76mcKKQa53fNnfns77w5WtuuG3Vul7qtY8TPfDI0/g82ZhiZbQp0PLn+x+hBDPr8AhLo70ib7z192d94UvZljm4O+AknMjtvf+hJ336zOtuuv3Nd1nKBuyPnVFTBFQm0FA/HVAxhGPmWNKeyUGmTNaYzpiiCWykkSjbMVREQjTClbptLUZnQnMQpbIPDWfxxzrkxJxIaj7kDGT3O/REdZoHimAomVnJRmuJIl0DSv6McsVn5KXXluc7dsEHycZLBjLqHPW+rC2Qd4dzu+zzqQ+6etf1s7m81vYMqlk6hkqr1vRs7BkmP6O/ElRkVvAZYP2Bx59lk2+XJ2y3euKuYGqP/Rd/uGbTuu4t/eXJG+iwPE16rbDPeRdd6Q4k+VB5mMhfXFAXKjfysEB5vnTvGf/6n5RDibyQjf1bxETfvAMSUQRAxA68YUCp+28RoKKiBTAAuXfd86DV6wdgE6lHLGVRxPpHXb08F6w4xyI35ZSUEFajeqxMwylbJHMANPrZ+ZfzzgK95WHe4khv/l9wnggVfPBj1cyPV19/izgmnFeB99rvU2JB0SnKUBktE7AZe1KedphC3qFrjOZfLkrdCE8Fvtek2lRs7h+de2FX/xDlAaIlrwzRhKf9ygoEB1FtVhG6FM8wVCrfgd32PLSrh/XkHiqN1loqA2Kawj5/vv8xas3iLVio+a1e30MPUflIB6uSY9Z0JBkcLKkdBFgd8YFHKRQ23VChIJ4Y7CrjJGD0ylI4bGKNKCljNm3OZiy5rCOctAXjYi6vKlXN2NjgWEs+inOqoFIHMwI4jUqPhvGhUoUQrQZ8LaiI7gvQ4g61BKIdwfgcLajAyo8BFdKW4VJ3L147mnfhKdS44aPA4ldBBXLIaXDlqFP++cMNferMdMoZARWIEr6qvWUEo1MqfwB4ax97dqnVGwZLWLxbGQZPM8Mfcvjx+AjBNp6htu47zTUxqNCHShPo3nLHXdTFqFeZNImwwfvPsEkey5XBK6+9YWCrOpsIN6O1UFGugXHlsKNOWbNhi5JIaTRJRhmWI7VQYeUzpA4ShJ8BM1o9E9d4UKEpWGyuGJaLdv0kzi72vKIz8sfBy1DJSVMfKiwDWN+Q0i49cajQmHn4r+AKCFH1BCksRqrFDCVbY1CZXJuKZLLvsvf+8KpXb+wjnIwBFZcvNZuhQkHRQw4/ccXqTWKvwn4hyYqWsBv+wVPBWaj1vtwtwnn4MSfx+CT3VOqSnqpZ5NnQT/76xLPwBd2B6HSHv8aAilWOmBMJayplzmdNuYwxnZKSCUsgavSqubzGJcq4UKlKCjCFnsoYUDGW+8g1BBWRIhODitjo4vBnPKGCS87s/6kTqBoofvDjEgWCkwEkvL+q+7s/PA/HgZzBnEPOMqL40yJULPhTzsJz3POQo15/f836AfV9reh8qQ5zGSEpW0a6e4fgx8B8PvjocyABddxSuwIr6evd/vQnDzzm1TdWrukaGhhicxv3CjmjxMlxefwXUKGJ2cup/QSo1Ax+FD0VpTXeG4wV7nngSQpPiymVSPBF8NsP12z8j69845gTP/3ci/8o71Ci7CPvfrCuCiqcK1ge+Knj3vtwA42FHCzPwFGZgn6kR5hShWbow84oH5pMDG5Hs1DBT9jS4rvz7ofXdQ8NVfpeVTYIotYjwoYKFUG44CXX/YY6VZfDWbJyj5pQUVryK1Lfs4mhTC7sv/Qfy/j19A1WG8G6w+tQXM/83+tiy/8EoGL3RyWL+44/3U8z444NFbyE40OlpqHe7gluG6hIkgdXiCey38FHv/rmB6XyFC9V73yt+KN/+PHnyE3h3SJw8U5f+NAjjsMbDh+FngUFeHs2V393NNUKTdNA80I+ALn/pAAAEABJREFU8Mjfys340wuVOi0oFM5KxQ35DCTl0pZ02pxKWSIxKRAkojTiozTlqQhcmS6c0DorLnWeZn+jUOEgmQxUSDTZ+2Sg8vwLr3/rO+ckc3NYNN/DxhVavEnVTVGgwriiQMXkTYIrJl/UEoj7E4Xv/+LiZSvW4kXc1DfCh0xWQQUaGoEnNPTgX5/+9nd/km1ZAMcCnpBkCVCqFcruZXVGURELRlu++4NfvvzaB12bKnJC1JUIFeox2QhUcHanLw5hxRfKXHDp1bDmSvSvwqSu6x5YvnLdaWd8DhWxU07/rDIr8MDmsmeGcq4LFcHyhsKJlnMvvOr9VRvoVzVDBypOh0vFB/+9H5+Xa10I4ClpjyPNhr+oMzQeYihevOMP94MrfYOjZ6w1MaixTi1UeOsLSZKsvHtrujDn/IuvWr6yi/deFVlSWyl+4pmlX/zS11s6d5aM7slAhaaMjeXa//zQE9MEFRjlMaBiqZxpcWJQoQY23s0dDyKWbv/lJdfgJeTzBYytvz338pe+9v9yrfMlg4N/L4pYk4lHjsUzLXgHXn9nhThhV63AEqVFZ3DpP97+r//+9txFu9GMwnSb2x4q1rYiZCxkpWxKisUgYzAs+et4J2MQZQyoGGqmu982UFFHq4AoNm8FVLQkcmXyUKHtLjnHUp70sTr+hk1MG3uYuvpYthXSmu7S8tX9S19f+cyLy669+a5zzrviqBPPXLjbAdHMHHcwq9p3TwJEoQSUjCiVUGFEAVcCccjuZwIejj7prB//5NKH/vr3199cveqjgS1DpY2bSu++v/75F9687bf3Xn7VTZ86/KSW9p0kk9do8at9mZyRquRd9MGQfMHcoYef8tNzr/jjPY+/sWz18pUb8e29vXzta2+vfOr5f1x30+/hUe1zwOJ82wLqHFmuc4W/dfZPNvaVKIkZjw+cd9ESipKJOSW5JJNnzsI9fvSzi1Epfv2dVV09W1EHvPu+xz//H1+PZzqo9fvI4z4DA01TzYtB6rpQqTUKRx77zz845+L7Hnr2rXfXQRt62DNas2HL80vfWnLdbWf/6PzFR59aaP8EzDd4MH53r8YEQu930LEXXHLdi68sX7dxK7S+ewSoJs+JgvI0cwxB5byLLl+xuosasVAVpUnOr7vpt1VQUS4y1LlgN0rKSe1SVI/5qKu3CiqiiaEkhr5Q6sTTzvrlJUvuvu/RV998/6XX3kWBo2BXrx9A+V974+++f84FBx12PCymR06x0qgZDNh0l2KXTNU96IDFx151w61PPP/qu6s2Un0FOEHJEFc29pY8gYzFxrqE2V2RH55zoVjx6h5gbQnnX3yFOE4FFpl6Oe538OGo5otIxvFRn6C8mWKZ4Ag0oyIKuVcZ44mSvPHWPzTiqaipS5UngloRVgKRzCmnf+6iy3512+/vgS+IGh7NOopTP/nsS9feeAeqKfseeDhYQu3zQh7MYBktMhccTTmaPu7k0/EyPPz4M8AGPHVc59vLV731Hj69l37/p/u+84OfLj76ROyGuwaNIOonVvvESbzlmT0IwXSO2wJft9Mw/A+TL8wSeUGplL211dCWh8zZjJSIm7DRJxu9IEpgqqCijZb6tzAxkNT+tqLRvhGoiFyxwVJPBVQkS9DsilscMbs76Q0UIZ/cwhRRRTkcaTi93Zem2d25cacYFDaqIBFVCRUmBSpWLxvEDg7hCH45t2in/SQjG6Lc2r5rONrqDaQc7igoIhk9wInZJivTVKiDCvkweC7aTqNDXL4UuIJ19qcnKhlc+bZFgUgOVXgIJEB1nj4S8fMAVJSZBONcLn8C+9MEvWLH3wqoWHw0ws4bTMOKdczfnQ0IZ9NGyXQujiL8HPjxyAmIes6Ue0+NAxXcTr51J7WaafTJkSJqxLg2QAungPXEPdL8hsx6To4lIlQMFnY0OH+iSQK9lGExHmrzIE+F9TaWTNSvl8ayKX1JPcp/yaKbgiLiWdRojAuNafAG42RnTcKsgrzGyh8TjUGhns1kcIOxgiRJWMKxYwc3eeCalFNE+0mTgQqPIUCOQIxlhTJ73KE0HjfzWb1JSXLMWbCXJLmVOaHTHl/a4YobzD68tJLRwRVOZgw21poiQgVlBUNMU8ejHMjIkp2lvvV8pCH32Cjc1DF/52zLHCo9ihBqvkW1XTbsQhRXGeVDI37UKSeUqbrimTas4EVl/qIy1JSn6zeXsyqUP5yACBWW3liSlDZIdndwRHB3gUgq3zaPPJJC+/xEtlVpRPGJafm3DVQIAIZwzJ7KWotFcz4vteakQhpEkaIRQMXgZ60skts/tVCpp9kHFc4VmmJL5MrEoAKigCt2V9rpyTrdrZDL0+bxdeAF9kc6/ZH2QLQD8oXbaCw9PzVXOTE+U+V/CVAhkafiS0JwcVjk2p10etMQVqzOOBul6GDDlUlYtztjJEKFiJMqqDDLa/KzgYcmP9DilfNufzYQbgEv5UirwVIeD6hmsFBbj5XPBj/0aA0YrAuV2o+WonD0E1wMxaBABTLQbAdXmIbLKG0n8lhQUQ7o8mVQGjwjAMoHK55Ajk5EZ6QTSeYAjbucvJRTs9NJBr9kklUpx2fdjhlUWKaAygFrXhqSrYzKZoOoxa4NBJVyJCpAPySTRAnbabg1dS0dAyrEMGrAlyS7ghCfevuSk1bUJiKrHxc5tVBRvk8XoIJKA6tJSDY6I5YoGawAKpLkQcUIFSBJchktbi6zE5dqkUyOqoSSVGJAMpZiung2kZdkF0uYygTbhV4PPmVoYZA7EI1ARXwiVJ48jElnIbTwyhbVADhRxoAKsEFJaMj5UAfVK+E+3Li4p4hP2lPsyiE+/amCijKSOmQMRk2hGOHEmM1iaUumTNGYOciIYpUjJl9QCsjQdIS/KpvrpxcqopqACnGFQ4XHwZqFismRYGJTjERN1pjLmwNOSASVQHSOHOsMxudAocRcAAZocQTy9HOnXCCK8OW4UDH5oqxZRZnHV41f2WAUfDBk4IrNlYAZJYSg0ufyJKGmoEL+Cu0JywiQUBJJ0AWnkAxe/C/8CcW4s7iwL5QiqLDgjPIrMZjGdvYmWXORKyxyRe0JZvLjgDBtzOYqK/g51fTJ0JB7AXPDTI/koMQB5Rja+FChuevBEuIKboHWyXqy80ImNSqI9SkiSphOJxnxRgbpGtQdFANNZVX2RZR5R5TZjqkGWu7gxCrCPPzFkxviZnkLP2wQmyrG4mIj79RRctXhL3UyLnWQo0fI7s6OTENZvXIWUGFoQWlIHvYsLL4ph4pkcrIItWR3BBIAJEOaxDra4bmblA7Z7OVxRCGXNw4/2+FGLQ0edsDq8DOoWOxsSDnLczWa/ouG99LITTGUhLPgnYQXQmPXuShZDv2XQiOrZHDwybXqDH7UhgreQDwI8tfJBST3iFxA6rpCF0CeUBVUylwJ8DHz5KB45BjdC1Ykgw01BlbJMNhwm5SvRZw6jGcb4imWpwkq+LnVG3YkMp4Mm08eXKFZ5Y2RqCQH4aAwrviCDCqhMDSt4a8xx7U0B5hpgcoY/1s/fYs7XlcqcggwimiLxZN1BIreSIc/NgcKxOfKiXn+clZKW6BodGfEyb4sdcSmMWYdwOrKmzR7WE8Bkt2XxpJNI+9K1ZXm/bri4hT0/ICjP3QmK46jTHqGPfkPKTkmjdKnI2BJM3phHxBXQyyHmGiGKKBHovCgKDVwpwy3FNuEqnYTVHG68gxjWhcTbRYhFQZUOO841tYhMzVpoOscoVZN7i9ZZZTepK5kbKiUi0IsFrZebzYkNpBWI4xZd2eodst426dm4qZaoTCrTiquiNdQKZlav2mWKq6qPwVpHafOjTM1GT7iU2aRa4IzSi5lJGAsbkxnCCfeljZnrmCLJNn8jPCuyjJ6Q1xacJpMZ4FK1bkpkydc1d5ejQf4fE4/xwkL6zUAnqmESn20aEBFxEmFlARihBZ3qM0X7YT8SjLK0YTHgeJUQUUlQfNQEYlSFypV4rQQaYT9OVo43saz49UmWCRELS1UitCH2jxUiCvTBBXxerYjqIyPwG0FFWj7hYqWGoRKFTwmDJXqEpgEVEgghC0YV6ZCKYIokC2dlcJRZZB8SAsqZkHTA5j6UBnXQZmANzP1UKlGixZU6qc6ThidKUp4XIUWd3wORGghl4Um/lIRUisBJDzNpXLMCSakGbtYBNWHGS8T3OPoJDTlsTsUUeSNVdjH4IzWVS1UtPFQLdGIq9+SChhNZoyrbQSVj42ahcoOqyaNe1PGVCtkNOYswhohIzFUJYelUFRKJC25PIgCOdI5Szxl8IdZLi8lfaQIEvG3Y0XSmoGK9m8rWGIqJ30ZI7QlHq1xokwjVEbRog0VDQ6liSuQwYF9WLDLKbfYw23OaIfor4ArsxAqYmiuUll+mwo7E1XZ0qo6QehQ+XhKh8r2CxVDOGZLZqz5gqOllbkp+YI5lgRmWAZ7cCUQHgMqWp5Ks/c7NlQIJyJUGjzOrPBURlGhARWDK0kywoCW1yXF2tYKx4FfAoo4Q23ACaDiUXwXV6zTLrdZ/S0mTx7SgkqVx6DhYTR7ayKoxFPk60oN1pUJx2cK4J4Zd85UCPlZTkwUlNEVg6YEKhWAEaCiRuSUdqCmjzMJqMwKNRsWm2VQqUwaOKqZp8L2BpXxVN/gMgcFZtQbYNkhszmAhHwU0MUYiZOPQgip8lSqGuQb8VSqrDxfNgah8aFS0XutzLZqiM5mqIAlXBwqhnItvlYGmF1PltBCXAFRIHdkjiPYTmhpFiqT40pdomhCReNiMtwzEyek4W0/kFpcZbToUNGhokNl9kAFRLEEovBIWKQrlwdUTJmslEiyUFggRC0utVCp7eXVLFTG4Mq4nkrd+6raX4SKGBmb1VCp6pc8ur9GAz6ZXRUtwRbIFmp1RjsAFRLQUsGVxqAyLle0w2V1oKI4GcW6qtktX4ZKUisgJhb46G7TARW1o1rG7Ex/7KAyy7Sjhr8abzBXm823F6j4Q9YoS1/vzLHJtcyJFJtcy6cGspRpUcbxUabWU9FWeOz7EnFS66Y02Joyw1CpHT5ZMYqlHlQgyQm3Ji15MgZv1iIXwRWwxBnqqMOVhqFSlxwNQqXq4AoqxvJUOE6EOJjYSWEULXWHmrLddKjs0Pq4QUXzJ9sJVGyxlCPBWAKuYClF2PxaBn/Y4mPCCouAjemjbBtPpVmoiNs5V3j34m0KlYmFkqq6IFOop0YRLt4xl/XElQuQLdgJmUIdttg8V7DIBkUqQ+VxQLs/B+fGpASUIIOnCKltMHSpynatNhKjO8NFx9HS2PsYcZseuFlpI5u4jA3JtPpzUJ0SIMa4Ymw0jxIBoyukgBgFqRhl7XGDPcKl3Uu4etBJucuyBiQ0uh1r2sHy0H2TTV2fWaiMdanbgzT5vW0BQCs8GDh5nGgZ6+Y9ldEwTr1gzmQhpD3YkIkGo9BIFGqWB0ts6aw9lbXEU1Y5ZvKF2UwZ3jsdUosAABAASURBVIp+w1og0Wq0b0QiMMbeU+uOKMc+LauuRBqvlNSEm5REkkCiNUnXZKAy4f5Udce1jA0VccyHaqMD7YCKPT7fHO6ks9NQedDFKRe2AVQa2EclCq3w0f51iUJQIVWhhU1qWR5cSSNICCrazsS0Q4WnJZ4NUNlRNeOuhg4VJhpp7wnaQwmAxJHOkYNijiXBGKKICJWxgTGzUKl7JXz/RqAi5nKeFFQaV4N+jNZgyWqoUGhIMYhWO5PdFoHwJxsw6Mlb/S1ScL4UWmBP7OJK7y6FF0neTsmVk7xFOqOKFkW0bvCOSrM3V/3xlaMa233hYtliKrmiqqYdhYcNRa5wtAAqJIYWZXx+eXBiWKOeOwoVwrAK4zEHV9ZKy9iZynlWODbGTn0/49Z5lms2eCoiDMYJUn1soKJKCWQxiiRY1MuZzKoTAAdYj2ECCQW+xLGN0wGV2t9qAWZsolSRrxqiY5eSh2nWQWXstC6NQIWsqsGVhayJXfwt+zqSuzpTu8mdB9kye5gCbZKnMBmoWP0FrslApQIkZboYeea0WgeuphDUtijFTVHRQrkAVLTUGUu/zaBSRY7ZAJXtNA42G6BC8S5YdrM7TAl+xO2zASrG+h2ZphMqLpad3hiMmsNxgoo1msS6mtZegY0IlUaAMVNQEQ8ixujqeGZjl5LSt03tsCCeoilOiF22JgwVanzWhIqm0lxGe5wnrJQcGfgijsQCubh7ILnQLreZ/R2WQKcpNMeX201u2w+kkXztEB/LgqXByyT5RlXZeD7au3dsotRyRauDQN0snFWN8w3lTBMSvYheC8FVTdOpkVhFDH81ZMg0wmJVUGkw8KV7KpOCzTb3VEizFioNa3yQaIWSCCSqtQUzQjHGkhRzUEAUakGh/l2iiZ8wJJran59XjLPVneJeCye17SjiPprF5Q0ppRG0JTOmYkHKZihBTkXq+20PFUu9SVk0o2H1oMJSaTkSBlsMMkXm+gq7+3K7mEIdRncO/orJ124LzpVceYPcYQgv9OT3Crd/0p7YCf8lOdLUN8zkL9aFithHizQuUaqlyZWKkqlN2VLbYWEMqKhoEbwWcbsImOmAiri9KvClQ2UHg8rsDH9NLVRE1VpkmFFLIAqK2GIpWzoLWSIJAEYdfTIJqHAkjNv6UgcVSiYxzhLmIQWifKL7ulAZ20OqIIpXu9wUqBjCMWcmb24pgis068/MQ0VrhzG4Qn6JQRmqInmzkj0uhVp8rbsGi3ubQ/MluCyosFNme3/WIudpwi6cRbLHzHKnnNs92H6gLbm75G5l8rSYAh3kr1D4SwSJ3V/g0iKKVlhM7DRc0ZW53NhO4xnpTybtXnDjQkXN60w5KysTXPK2Fi2vRew51kj4SwswHCQ0iawOlcnCQyv8OLkuWDOobQMVsZWlssWlvkfSiKdC5hUeiSPMxjayvl6hBP60esMWD+t3WxXmmgxUJsAVjgfqxGwOxqBaZ2VsH0Wr3V6zHzO5NZGYLZuX2opS62yCShP9wepBxZVe4G/bzZ5ZIHnbGSRcKREq1mBBcrCJ6+lEki0jOfNScKEruxcg5EruAqJI7mIjUNHySCYAFd4tmDWNKFMgTytUOFrqcmUKocKmqFL6gOlQmUbNEFRmZ5fiqYWKlqcCU4u6P4jijKTsqaw5lsSf2A6iMK7UtJ00CxXRmk+GKzQaxiRHAZVaZ6XaBRkz6sWlOd5FgZYkh8ypDIgi5euFvxpuZ95Gkjw5JneWyZOD0Tf5i+ZAC4tWOdNY9yTmh/K7YImNbB9nhoua62mwodrergzoI5lcWcgemuNNLJJzu3qSi4z+VrPcbgq0YQVHrpLV3wLxdJC1807WbmTbvXkuV6BFGU4Y5X2grZ64M5B2BVNOOYkV/FkLAzV+pREGLO9QPWkYTUFWJWUylXEmRKmGjTPMpJHwQ50ozOCye6K+UAbLqinZ2f+yCQT9bEYps1ey+KpSstt9SZhI7DNNDelND8ZUh2L4G9C2SN8yGxrqJ6UpC1tNr7RgZvDAaMK4RyBzMAFZQkl7lPkodVsstqUagVZFY3sDwJO8gbrSOr5W4suKwY8zTpGxoOLKMDnTTNa4NdgWyHzCm1xAOwAz2CJChbjCocK4UgMVyZU3+9ts4TmASqxtL0d0nuQp1IUKtb7AWakLFS1VQUWyxCRryCXnRD/A4om4Q2l/tAgLO91QGcNZmTBUOEhEorB5f00emoqcJkAk/LApCyvklUw+ycomJtGhokNl1kLFKjOcWMMpyCTHOVEm0Ai/o0KlwsObzVBhHglBhYjizsIjsYXawRIQhVHEGleRo4g1v2tDhRNFgUpayR6m/MSTI0cHh40Ud3PH5+EUFrkVG6EqqFDfLT7lSZWqNvIeWZDTn5csEYIK/BImOChyMtu+QAnLRozKxFkKErYnqDh9cXJWWjp3pomK1TnhTR53INk+bzc5mmduitlLMxmLopkop6+/rw4VHSqTgQr5KJZA3B5KcaJInpBo1j/OUNEKIc52qIxyxZ2FoZezO8Xb9vAk5sPQw2VR/7e8A0FCVENQUX4LkAAhABWgAjmjc7AFfxJaCCpwU5Q5XbJVbUuNQMXhy0VS839y/pJVXcP9W0tMI0xDpdLl195s98cdgQScFTEINh1Q4VxpBC2NQAVeCIhy3MlnXrbkptfeXrlsxfo1G7Z095egns2l4RJbHnDosUcc++l13UP9QyVRH6wdYM6K2a+Hv3SozEKowEGxBZOqImlGFG9Y8kUMlcPOdahUhbxmI1SM7gxrgXckQRGGDVcGCAnmdoZ3ApzA1ouBqVGueHLUjZgLf5oVqWNNnNUqo2VUlFsFFLGHO4AWLHF2XIY70gFRr197IOMM5hxylgt/ukKojwdG+3HRiPfKiYrho5x78a82wOBuqdBVN9wKqFi9URBl+4KKL5QBMF5984MNvSMb+0rEklrtc8ARi48+tXdLqW+whCXXyvVbuPWcbVBhE4ybnDQ3LUtqpGykFcnmlaw+aMog0axmnBbbP1TEBnzJHRJl8IThnRBILKEkpIS8ohQNUzRxAEyHpupckk+uq7pnrBoUOduhYiqnz5JsCTAD3kmyYy9faiG8BzEkNR1QUXuUubOscT7YBqjAMcJ5JWeKXY8lbHangJCnly7bNFTiWttbWrFuy/6LTwZI8L8kwGZ00ntlCvoxoMKIsl1BxexmrSa77nnQW++t6erZCnJUeSGixoXKNGkyUJEkq90fXfrGe+v7hjcMjHCt7Rnc84DDJIsXhaBDZceAiqFSFPKCm2INp0AUczABqFTuo0Nlu4EKjXIfFdn0cGFXIgdr2wi0m/1qSIrlgvS1UlJInhoSIBFVhgprljc6MxBfgcp0SXKJA9pBF1wDWOKNzQkm5zsCRdhZhz8Du79iTf+mLSWulRsGuwdLi4//Z7MnZvMnSRZvGQ/lYYmuQOH8i6+muJCoq6+/1e6JQhwqhKIqqNROVlbGA02uFeUrFYMiRUQp9zg6g4A9rmpsqAji9oJV1c3uBx99ZrCkomLzVk3tc8DixUef3BhUqGezuF5HklXzf8Ue0iabKrM9ytc1pHBF7WvghySLx+YOvfrm+6vX94kPa133loMOOxa7ydG8DpUdDyrACRdwYvBHJV9ECXntmFARB8eIIDH4g1x1B9DMFqiMnd2EkqZI5gjcAnekI5CcDweFeQmenC3UTu0rgArjijZUqmSu4UrjUBEzDYMo/ticaGaeO5iH4X7upWUiVDZuYf4KoOKNFhhLuKYUKgZHnEvlijqeURnNPlGosPWKjMVjQYXnP5ds/l322H9j39aBYeaLgBZVwBA1BlTU0XwNQ4WYQVCpGmFTFyqEE4sjpoUT7KDsUw0Vi1P2yIk3lq1cv2mQ7o6Emz3yuNMko9sjp3So7BhQoQZ5ki2YZH29AizexXDiDTN5Qh83qJjkMBeNz+ej9JuDimYOq8YTk0wwiS/LK8za3t1ZW3SRXNgr0vZJV3IXQ2AOJPk7mbztWDeHO6VAqyUyzxSaI/lytvgcY6gVMgdbTTKOkGeqF0xjcS0H7HLShstgGcOSEOwpJY3neeMrPZUkn+SYxipKZtkZyEbSnas3DBFOujcz9QwyHX7cP7vkjBhxsrmYrI40ZHelPf66UBm5+vpb7J4wRPvb3UnK1e+V84FwiyeQA2Mko792xKJoYiyeiEmZaKsc6YqWU7BE+OAYuy/Nh9ZrSRwOKTlIIS7VPjpQkXd/5etnd/UMEVEIEsSYs77w5WAs5/LHuGCgDz3iBFjn4VIJO3C9t6qHbkGyBOr5KzUOilIIbMUShJSZY9gNonzE2wQ+JYMPsrvjRIuqkZiS0UeDNLFCW8pDZwKKfJDF6Xf6wstXrtvYN1QFlQMOPRJ+DG6q6eZ6YYpiLUNcsc9UQUhD4sBVLU3m+E1NEajMU1sfAJrTJE+aK2ZvxFzGCShCUS8s8SfgIbkiTcngjs64jJ4YVyP7W/xJLikQNYUSUrFg7OyQUhkpljCHk9iidcwKb098NEI1VBJHhm/jwJcEyxtsC+Z2Tsw50BHfySjPZWPdg/O4GFdcLQa5TfIWJHfBHl8IqBiCLZI/DxkDRQhEMQcK4l3we5HsCckaU+chBl1sCYjq6co4RLXxQ2yxEKHCR7BjH4c/9dqyNaKnQlBZfOzpdaFic2agcaHi9EXd/rQnkAFF3P4sluCK1RkHYGAxAbN6FXPVVJE9Yqlkyw0qor9Crg9ZXj66vtaVoX3YXGdlUXobHtCDFEdKzcTwg5/8kmJfHCprNgzc++ATIApMM9X3ea2fbtDmDmEdUse41NivsaGCSyLmwVNh5LCGgHnJFFClIB9QYdsV6kjmAGW3BFT4LC+0ha9oQUUyO7F8672Vazb01YWK1VVOCN+AaVatcw02xlaDR56walvjavVxgApwQkQhYf3jAxWTN85lDMY9mRb/7ruF9tozsGCRlEwDKpAIHvH4FZ0d7P5RCdVQyRlq4/JEO7eZbIFWf2JBKLOTOzLHFux0xxZ4E4uckXmu6HwubMfSEmjHduoDRh20gCLIEWyHXMFWd6itVoH4XPyXU27xRjr8SgNJJDU/GJ8TjLbBFfAFc6OKFPzRoj/aCvlirf54W1ktvljRHUqnWxdEMq3LP9q4abDE1TPEtPi4U13BhFOOcwESTL4iZHdlPf6WMaCCGr0vlJGj+VCsNRxvww/lSDEYZZcXSnY6/Bl2SZGWShUgTziDC6NRL3T9/C7+P3vvASbJVd19V+dQnaqqY3XOPT05z87mJGl3pd2VkEAk4wDG9gvGHwYDNmBjsIUROUoIhEUSWRgEmBcwGIHBgLEFBoSIQqC0eXZm826//1un+s7tNDuzQeH5Vs//qed2dXV1Vc/q/Orcc+45Srwiij7lDxdgfLlkNUfyaXm8RcfwX6BNxmmLoXjWF06+7k3vwMWL01mwuTff+sFoMh/Rc+FEFluSGkvLoahfjSdzFbz+UffHAAAQAElEQVRrqBjRC6pehHBCwFiJlwRVukpNVHGRQAsGuFRs8ctoeg1v4SXG2OIAOhLCzwjh91QiBRL9pBAG+GEDahZiIFdThnTIp8RwtXBTsP3Ng/voHjlUzjQa23ddh78XOzKcZtKyZ5U/nDNU6PgLLiXz175oav3Nu2t5pyp3Ff6XWZECsUJX9Tpe+N9zWQoI8sfLUNvLNvlipRWp60keZXXe40qOL0JSsSSVypZcScoUaI94j95Igav332jRYrRMf521d8gFVHFwYzQ3QV3lQRRgwx2uY4uxPzFM2rTz2W9572e/efeDv9rTeOBw47v37HnLrf+y4/r/wxcn2vwtJetFwTvxKMXNO5754le86SOf/vpXvvmTX/524aH9jQOHGw88cvwHP77/W9+958Y3vWf3tX8AL0Syh9ijLuQSpcKVs/sibDVJKHbvbx7uBRVRhtuRkQMFaAmovOe222n6Cw/LY9Mb3/z22/7t6//9698e2j/X+MnPHvr0nf/+p3/xShj9ttrDi3lfQqOL1Zt2vvjlr/3Cv33nru/8+Ke/3v/bPcf3LzR++bvDX/nGDz5559d//7kvHlt1edu6fZ7xTN4J6MXlVtqF3wfCL+AMRN78jlvaYicH5k/c9N4POGXzYd/mDlicPi7aT2M86TM5g+KTvvCQ2z1xALcMfwXWduuVT7v9U1++6zv33P/IMdzj1771I4CEpr9wAN1X/9iG17/5vbd//F/x973vd3N7D55+cM+xn/963z0/f/gt73j/H/7xXxYq4yC36U36oobChlSILvjn9z24b+6YCBX8vdZt3iZZvRZnwJyzWsHDe/d6a71qr13U1LhlxniW5/T0mEoVOrQuR11ieJQe0uP4XjXxeskiyOrXbQE8eqchp5LBFi8h7OeytH7krBI/+1iJ7qLzXpYjt5aJ5gcia9dBydl1rkrdqaTgzUhynKvlfnv+KRd7X7UE6i9UfIU+QnCS3LpLKcINwtgip91qKVWZydRmo7mRN970kblTjUfmWdD7YDNW8b4PfFoOpkanNnzhy//x0L6jMMEnaFL+5KK+9NXvVerTbl8CpsGMSBtrRFyhNG7JHUzufsofvecDd9z/yJED82doLV4vwXbcv2f+1Te+PZyssv+dfAkKKrB/jt7IC176ajEPWIQKcaVtD9t5rPH+2//F68/KgVxz+uvmQ0fOwDCJgqcS0BKJTOmOO7+8b+7Ew/uPHDvNLoZf2MKpxt33/HZgfCNMf+u0FZvpcocSeF7evOPa//v1786fauw/spSOnGn84nf733zTbX2js/ig1YjwN+fr2ifB8BsCJM1JMNZruTwws2fuzN75k/sWTh1cOGlc5Jk2f2X5emD/UYbDDiP1urfecuBoY+E0+533LZzBGD/mzbd9DBCaWnf5d37wM9wm3uU61mhoyZLkCsFpwwm3Xf20b/33PYdPNsRpK1H07fipf/fI3Gv+6S314WmHl7Wok+xehzf0wpe8AiDB3UGHjpwS767tPPQwQZOft33kTvySVG+m53TQsie+Hj8xlWWpZyHIlZWaX6lsfmVFshiyBlRbUIMcSsSpRiFL861zEM52VtHXnb9Wes6VXpukac5UyjnWr6ydCowMSIWMFIlIKjuM36/kC3H1DtQHuXpC5fzFnR7Jk5S8KQzS1VXFwfUhfSCY6O8FlVvff8eaDVfd84sH8f8zWLKYpXpqUXicx0P91Ozl3kBShIpHzQIqa7fspqA6aHTkpGGgu1kZWk5x1LDI9/z64f/5yf3p0ghwgvOcP1SAE3ClF1TONBrvft+HBsdmfnjPLw/MnzrZYEmrGHDOQUdON2DK8UgOrogREaefNXmM5/qufcZz9hw+hYuHCRatrSgYYlwSrhxjDIBPWUvhDDAuIlRErhBUuPCyMrhq72H8SqcPHD13lnA9eOAYQaXN2IlQ4Zf9rvd9ZNXG7bhscJH2cOHHJ6g4A7Gn/9Hz7nt47pG5k3O9s9Hoj35w4TS40mg0fvPgAbhNLI24B1T4nV6CyhMdKqIZBVRIl6BCssRi1nhcyiWkWp4RJRkDZgAVOtXjCCriBJrkSUlyJpgazg1uSNZWU60tts2NvfGmj82fbuxdaDoNR5k+94Vv/uq+A3h5cKFBC7aPnjB03JAxPt1oLBxr3P/AoZhepqkMbhkt7ujO6/7gkFEshK3Oa34EOnaSScxEgq2HgcEzL0wzLPh37v5FKFFhE18mVGIveOk/nBtUXN4UiEJQecNb301TXsxOHT2zwO70zGc+9+X//cmvcb+0/ty0WccaxrtsSzgEQeGWqdGyN5B2ehMQwSBdHgIIYYVxDbj+tpWVndo7fxrbhw4ehwmWbGxZOIeKGNXnUOFVA6C+kTW0eHMJk71SqLRYOmNCiaCCpwfcNf47YYD2i//2HyAKLh6YoV/btOknGwBqLFuT7P7SwOT9e+YM/+YUW7Q43y6ABH9oLvJXHtw775Q15qk4ZKestEFFdFaWCZVeSVNLrLzpMRX2BIFKD610+ut80oKXI7bcJBRjy+MNYUzLUCwd6x+Xnzq80rTd89FKz7nSa2PdkSMJSYtIEZY9zJKMFabebYZ7JVP0WKdyoeIr/FM4JxACliQqqwASvz6oZscw0HLjvaCyQDrB7AuthwAYmLWl/YbZPTRvDj7+qS+KUCHtfsofPbjfzGTFkfiPc+XoiZZV3zBbMF6wZWyyxXCVnv9Xr2ZpxBcZKsfxJA4LePA4vx4KutAvQFCB+8J8Nby10Lh8x9Oiep/DEwdU6H/dv3rlDbgemF9yVjDuNfdFD/7HDfDAoHsUvXXJvdCc2OAK91SIKHI43z+2bq557xcEKux5dkmowPTjNyEkwA+DwBUQkf5S5t/rRENJFPDBv/yb18CF4r9/r+/FOcGS/YdPki/4wJ7DDq/KuHI2qLSh5RJUnlhQIYqIUKGVKJegYq5TCYWtWswSS1jjOr1LUCHA0AlXDBVqUUUy13x0yK4UuJzBCuQIlCEak6jKr1OtOZQqa4EVKMvJieL4ldHq2lhtnZKfxUtfahIKJJnCuanX3/Sp+TONvUdOzR9fYDLs6YnTDAP33nfgmc9+Yal/VTBaWrX2ype+/MaD88zOHjc4AYsMzR87tXD89NZtT5bsikPOOH1ZVmfeFt3xpGc8sB9AaXzj2z96+d+9AQf0Dc7qmX5vMOH2x/CQP71my6tf+8Z7fnH/gfkTJxrmxM4hY7rsu//7K8nJynnBX7F6Ys953l/vPXh6/1xj/2F2Wa1G6hQM3wkWsDljUuoE095DJ2/78KdzxWktWne4U3Kg8Ma3vZd95NgpEq6ZfCboN787+JK/eW19aLVfyYxMbPzCF+6an2/s3XvkaBMt5Ljc9O6P1Admne4oRJmyd37xrlONRTrC2D1y4Ojf3/Cm0al1wXDKpyTUWHZwbHbT5bte+eob7/r2/1C05uH9RyxOVjmYtTkxQv1iiRdahsmDK7LKMpeg4alNcOPmjzG84Wdl93Li9KKM3w0XwP0/mq7EH4vM9CMHFrpARVilQam9NEmIvy8n69zCGQh+BnTHnV/efMXuRKaCu6sPr9r5pGd+5I4vRdN9klX+4r9/R8QJ/Wive8PbR8Zng2rC49Mi8Wy1Pnr1tU9/xd/d8NWv/+dDe+ZwwMHDJxzuoFtW8YMALX/1N6/GDwiG4cfExfMZsMPHT+Eesd13+Aju5VTrv4FbP/DJgJamgH+vnrsrDqSvcLFhy9RTj2Mop4Nln/u6LKKkfwkWoxyWabh7NMtqbX51odYk9prm6tF5cMnjRaPPm1Y51bhLS0D80fscFjBS2+AuUiJdhW/noiZatF9sqCUFNHqXHRbsLurnSOLHt6nlq1VBwjcuLZzWEU6YZ+vWIJn7Kz2bm50/VDha+Fjy51h931DFFix7YkO5oa3lyZ3x2kYQRSvNBjLTwAlxZWmogBm/vO/w9Loryaj5tLwvlJWDmWf8/vPZY/t848Dc6QNzx2EU5o4wfeijn3d6Y1Z30hsq+tSyrJQu33X9O2+9vVidCKhZi0OFH4OBN5Ck//lpXYIWz6zddMX+w+SpsPpOFNA+dKKRr08yoshxyaEp8QqdQYsXfnjPb0SDctqw6dt3XWdx+swVD27WsN3iDAXDGX+opKdH1UhfJD7QCRX4XjBP+w+dWr/pKnZhcpw+63aHv/WtH5450zgqEAX6zJ1fd3lidmdYsgRxvNuX+Nb3fgzbJ3pdN9/6YbCELXxREnIojoHbH8EYz+PhRD5bGnjZK//xS1/7tuTws2X8cqQTKk20MKjw2TBA3RNKhWLFSKIS1av4ljaonDbiQ1488kg2SgAj+ZTYZTuuxm2ebDXEy4eK+e/hyJkXvuRv/aquRDMAgLHkJYwf2auwRp+SK/TdH/68DSo33fJ+q8NndwVIgAdkscsur+LHnVQGX/jil4MutJ+W1IArtKoGMP75fQ+CHyJUDh09sX33k+DTSHavEdv3gcoQtY2hdjKPZ6j0OoYti2nChp7TiRbLgcqF48qFgQp1+OA8YE/ZhkFn3X/VOD13r4goFwkq4n5wgu33KaAF/f5tZS6Z5BAdgO+iU1Hz4AsLFeLKElDpuqL+gkGFleHqJodWk3x5d2JQKUzlxq9IDGyM9W1MDm6N1jaECrNyetqfXYUt5EsxqbnpG2/+NKCy7+jJI8cWmGDWjQjKc//s5aFo1acWZaWAbVAtKWG2huPDH/sCnu5PnmGTQsDJgcMLhxaOPrz/GJ4W4aAAJ4AK/BVZS6l6EX4JaxLlCFK3D+CEyqJQCimMYDCs/+jeX7O8oFONR+aO0rTG/mONXU/9A8mhSi6zKAiIxbCkpe/91cOmZTSM6TFc+eEjsJtG1ixBhRX/oDF8FJc3E1QrgMob3voeAyonDDGo0GP4X7/itR4fTq6DmthKds3rjd5ww9uOzJ86duTMEUPzR5nu+dkDbjkq+5NtUKF0A5qWecs73+P24zbDBBLYRwgDGE1aloi3YDrZmnBniP0mAlRa0bI4kYhfAFCH+VbiJfhSWqx003s/xKaPBKjgq99z2+1ACGXlcsH+griUj0vb3lBhmBegckbUhz/+WdwIpfMaFx+g3i3GzFLYF07/59330jwkh8q73/tBuCAQmAGoADAkjIEW7IT7grGL9T31monOkNVLgPnJz38jeirQwSPHr7zmOvyhHV5zaSfHCW952XO1/OMAKvywzp1828KMblDp0az3YkFladh0MWqtMKD6IoSTzg67jxpU6Ntd2AbN9sNSJMYCGAogoUgh1ZXO2hJJb66gDA1pIyPR8fHYxISoyORYaGTQ01dxVorWQlbSY1IuLUVUKRDCx61axI4TqhqXOLW1TJy0I6oHVOg37PmnEdsJXyioOMN94cJ0dmRLceKKaN+6WH09cBKurFNLa/xZRhSuQIapF1R+99CJdG4MOPFrpWCkwrZqKZ4chGW/fMf1D+9d2H/oBLPLx04dOXFqQz1O2gAAEABJREFU7sixo6caW7Y9iaa/gpGaEqs7/FGPouP/83xl5E///KXvePcH7/r2D+Bn3P/QHEQZX8bcPcs2xoP23vnj9Ki7/8jpuVONpz37eRRQMZdwWwKSXcGj/f/+9H7TbJ08Ax05xQZbt++WQ1HYaCYj5kHo8vrzTk+apr9EqODKyVOB7SvXxgEVv5KD4Iq5fUmPJ/KsZ/2fhcMn26By/wOHXN6IGi64DMh1Tn9BeLh+w1tv2rr9mkr/OCxjQEvioRuAIYjCauP5OhhOsTxaR1AO6Z1QaWpx+T2IYrxcrBTwnts+2gaVvYeOAiqAtGFwA6Lw4+CqTjYoaHTq3KAyNr0ebgrcCGb3mYvgZ8z2hiVbkNbrfPhTXxA9FbiwePJ4583/vGHz9nypP6gmwA9QRLJ6wBWQRpJc2IOBLxhlUJEcOC0Ri36ln/36gcVUPQMqBxaObbpiB5htPECQNHpSkWz+xz9U+Fttx5i9Do3qDHyxeleotLGErUi/YFw5hwSwLqaNN1rnRKEpL46TzjbsjwlULLEEQKLW6vGhkeKq1bmpmdLsGig+OQmEhEdHgRZR6tgwuJJYNZVeO1vcvKG8dVNuw9ro1LhaLHv0FLjC4PRoQYVpOVBZFkhaoFITZQtWsdWy07mRbVBq6LJ4fVOsf2ukb3O4tkWrblaKa0OFNYHcLEmEyutuumOhAefglAiVr931I3+o4JBTarwPUIGnElCK2ANjGo6XD8ydhOCmMNNsQAV4ePaf/qVfq3iCBVbZ3pOKZqpT6y6//ROf+c2D+/bNsVwiqrpxwsgpohl/SgEwAwANM12VhdlPN57/kr9tgYpdgRGH30NZzuSpACc01Q67CVvDocI9FZtTt7uS2LrlbJunAuEWvnbX98AJX1CHjwKiEFRcLm3r1qvhqUDzJMOw7j90yukJw1Ox2lW6nj97wctw/UsEpX/y899+6GOfufHNN13zlGclMhVmlO2+5sqMQNv0F5eNlfHorJPPArxsZs+hvvt9t7dBhdbcwDUBVEiwvND5QGVu4RTYAJ/1xz/9dUQvAIow+mT6IXIO2NyXPYRTPeu5f4E/3AKP4hw+AWDjWeGRffM41Z79C9/77x9/7l+/+qrX3Lhj53UhTYenAroYOHGanopxZgNX3aHC/tA7duIecVPEnmaJF40Id55Q6UxbeHQkokgs/NPpi3RC5cJx5YLkGZvMgCUlB4XrQhV87GmC1VaFY8a8U9gWjrOsqpDGXmoRZyqjVPsSw6PJDWv19Wsis9PazKR/bNg10GerlS2Vor0ERyQPSbmslM1AzkrZW+/zDdWtpZxUyLj6yp7+Kl4q48PhqbHYhlkounoqvGrCUypKibikAjBBmigz2YaLaaoTG12EzzYl/latgfruU17nBRWLv+xQ+tzhAadaB0588ZF038bi8OX50e0QoAIHxSDKJhBFrWwiqATzq9ugomSnukLlIx//isub8obyNPfFoeL2JbRYCW7KofnTZmTCgArs1Ate9EqwBG6KTy17Q8Xd1//Bz3+778D8CSIHLSrEAzVl9YgZPtjPHvPPmMs4zgEqW7btAlTE6S+z6q0Alde/5RZmiAWowOp9+KOfAVT8oSRYQgJXOFTaPBVABQcTVPxKBh6Dnu37rx/8HDdCLpdwX2eMNTFsQYaYVvsvn/+3Hbuvh3U2CrwH26a/WhN4OqsXP9pQgSdHN/7v3/iuSRSH38BJiENFcigs88riVRKFb3zvbribeG44aWT6URz+0PxJwIkSuA/MHSfMPLz38Ec/8dld1zw1Es9a7DKDihkj8S8BFdwmQcWInyltUDl/T+WxgorIlU6ocHJcZK6cl5tCs2H2ZlKTSJSlZ70uBlTs8aQjkbJGEzyegZeRvoHCzGxlzTpsU2MT8sige7DuqFftfRXCiVQusG02Y8nnCCdAC4jiqlbctSpYwqCST1uKWUe1aCvn8ZLtKWche1/JPVhLTU9lZ1elxsaC5TLF26UQo5olEn9iQEWODbu0fuAEUNEr6ypj2yFApTBxZXJwa6S6EYKPApyEShuglULllls/w2aNlBIJnCCowJgGtdzDexd4WhQEq3H4aONFL/0HyR4LRfuAosHxLTBbbDLEMHm0Gh8W9uH9sGzm4nyxbDvFVNqgYpXjgIpZBNcoTShChaawyNwAKsYDrCGqrG5CJU5yy+kmVE5xwfB98PZPp3P9QTXtDaQZVIzFkg5XZPPWJx1pEoVDZd/cKfgW3kASZh3GXQ6mcD39I7Pf/+FPKQzOjSBBhTKm+PqMRw4cxS3vP3zyI5/8nBLN4FQsYaEDKk271lkrpQMqgldEUKF4w4WCCnkb+ON+8PZPiUThYlEiY95GsvuxzVYHwBVzJvC4KXF9EoiCLc55xljhtP/QMaAlqCYkq2c5UGHznDt24tYkh9yESrvw/5JNbmlL/MSFiljH92JzpVdAvldMXtxPOKFpJcqPEuMoeMu2vKmtCwUVEyfwTpQwPI/o1GRm3drY9JQ6PAy5y2V7Pu/pq9mKBbgjQAgGOIzkqZScxby7XITkWsVbLVuzaSmlS/mkrZSxl7OWQgpbjK3FNGTPpRz5tC2fklIxqZy29eU94/XAzHB2zRp8ly2TlcIRKRpnisSgiw2VlkB9z2kupeBQixANaA9gA09F8pWU9CRAMrjq6trElaWRK7L9mxOG4vUt0aaPAqIEi+sBFc4VQkswy8ShcvDEmVZP5at4uofDQUQhqDCuGDW1Htl3hC0MPN4ClT9/4d/avWm/VnHIqXf/87+Yq+SMB0w4KHBZ8Kj+xrfdsvmKnVocJlUzxAzfv37lLr7ywJyXP9MOFRAFnkEnVPj0l2FAVwyVd7/3wyBKJI77yoErciAH/4ygcvRog9QVKr4QIJSgQHE0mX/pK179vbt/YtwjyXRNYKApwZcISis9sf8fb3yb2x/DZ88ZKm1TbRcDKg/tmaMbv+XWD9G6dwIJF17SZ1l/X5bCFPIo0ec+74X/9YN74JTg52UBp+PmeiCc55SRjA5WEa6AFvgxr7nhjXZXYDFQfzaoNMsY94SK3aexrsOuQCdUKK3A2qOD8mMIFZErPBOsDSqcK52B+vPnyhJQ6YqWtj0EFRa0CCcAFTHR69GHCk18BQrl7PgUcBKZnJD766CIp1JxFou2XA4D7AFC2ohCUPHXa+nZGXV40J7PgiiWTAqSMnF3X9E/VHPVCt7+sqdeclbzoIuzkAFU7IW0o5gBVKRSSqqkpVpWrtVCg4Op6ZnExKQjneVceVShwlqSdFMbVFzhMgaSP+PRR1KDm2urdlVndpYmd+THrsiNXp4duSzWvzla3wSFaxu06nq1si5UWhc0iLIiqHzz2/f6gnlPMEdzXzT9BcGo5ctjcwuLRDGgwhZPPPWZz5NsYbgp4WTfA/tONqFyYv6EmRj6opfeUKhMWmwZ2V8jc+xXdcnq/ckvfg02zJ001AoVLkqL8ij6j37xgJnma0y+GelnR+GpGFUUCSpin1qzHxS8EJhLvviRBCP7rvd82OFhbVTghAXVki9YlAMFpzs+u+ZKDpWjzbTafYfOOL0xgooc0uFneIOxgJZ0+yN4hNfiueGJNU971nNf9LJXffjjn/3qN7734N55uClwTU43y9QbUDm1b+7YfQ/sjSaLRjl6igOZC1/OLo+G3+3d7/voowAVPnMFqFDWFqX/NrOEQw43AzkL1xvl6OVQnOIigM3A8NSTn/r7f/v3//Thj376G9/6/n2/3QO/hHLQIQyMxbMnCV0xPb8cqBw8cnzL9qssLi/UTEMItUFFssm4kk6/irpJ4gCaexQ+0j6BtvQ02sUWBertTYp0Va/UL/7ynLiyVJaXiBbaSn4mDAASUMQVTdrjSUvE9E5oBqxlKTiOD4YX83ebubm91gkuvbTQDMKH41JQc2kJfJf50iCKp1SOj0/EZ6aV0RFfqeLJF925gjOTI2GMPVJSZ/GPeIxtIT0BWdMpyJHLQhjYMmkuwAPylPP+vjJ5J4wluZSzlHVX8iRfveytFbEHgMHBeBfHhwZqqZmJ2PgwjpfCIXtAdRiVVxy4hZC6KLGLcEDh6sz7ElOKm20Luv/tJLtW7ioiCsmplSRv0h2pZAfWlqeurK++GipObCeckBKDWwkqkb6N5wOVBx85lcyMEE4oskJQgVXdec2z+Fr65vq4xsH5xsTM5e5AFqoNr2XtszqgomcG4RA4XLDaRZr8gRkKJ/IP7D2Ah9DDp84AKoeOn+mEitFPhTVnFKFCnsrB+WPHWOLZLsPEnCNUXLIOVwZuSkApB9WKFilvuezJx48vBRXYnWA44/CqSjTjUxIQ0EINS2DUYLmo+HG+MvTc573o5/c9LEIFJh5fvfNJTzf6TT2RoNKqEERQYakHNpnJ6KCF25dsXo9Pw6fkQIQlDVvcerp0zXXPeHjvYTozHkpwcmz3HTy68+rrlwOVE43Gmk1bGVE8vuZCnHZPRZLs+NkZRWyyOE0HNWP7yuMZKtZmrxFHMLYctHTzOc7NWVkqfELehsgVkwp+zQ2nJJxgIYRI3BpN9PIwOEUAFWzpkRx0EVeMrxQqVi0mBcwu7gQYTzqXm5iGc6AODjkrZRYRyebtqQx8BQywteopKa4zp8EACVGEoSWpswFIY9DFFPGGlGKyZnQItGAvkzGmVMyaS3K0ACpyXwlyFbOBesVXK9HBQFF8YkQb7vdFdasvBKg41ehjAxVHuAI5I1US9kRKU/VVO4bW7upffW11end+dHt2+ApR+tAVsX5wZQtF6dXKhnODyoHDjRe/7LXURMsTysiq2QBDi5U+8/m7ABWaHGfW9khjbr6x90Ajmuinxr2Ta644zAtpCEY8VxpXIiWqncVivBYZT/oveflrKDO4F1SodDYrCRxMilA5euw0dGjhOMzl7uuebnH6ukElTP2g3L5EEyoNjhYOFVxPs6BLXg6U1Eh182XXU6hZhMreww26DIs77A0mjDU3kWA4ZVTON80WWS4KZbPqI1Yv7vFPnv9iMuVk1vHVD++f/7MXvIS3zOLMWGxdtWKosNbIjy5UmOg2+e2Tv8KW5lByl8UNumAArmDrC0Zf+arX4rTHmkEXDPAVL3jhy9qh4vB3QuXo6ca2Xdc45AAkLvAUhVv+2je/24xsneJneOYf/hmxhKPl8QkVQgKI4lISZ+VK1wmxCxtT4a4JcYXTxXypxWU9683kgRMTGD3qlBBCWLjFmB9bXOtnHNyJlrP4KM2D4aaYMfB0MjQ2klw9GxwechaL1mzWloG3kZGScDjYGAMpnmBKgBxJFiZJ6TS1BTkKOX+95i7Dg0ksSo8vKsX4IaXjQIgZQUmEJT1i0WPWJKgTxcCe1h2ZpCuXhkAUb6UAfwV0gY8CFNmySTAmOTqq1mrWaEzyBwghVFzyfKDS2mxtGZ6KLzkoBfMQBrXpbcDJ4JqdlcnLy5M7i+NXAiq5kW0iVJLD2xKDlwMqkFbdeI0pvv0AABAASURBVM5Q2T/X+NX9c5XB1dRXyqflCSrXXv+cR/bD1rAiLhSrB1Ggj33yq1q0BqjYvcnBiQ175s7sP3LyWKMFKn/8Zy9LZoe8gXQ81a9Ecz4lOTm76YE9h2mtSSdUeDMGu18XoWIGgY+eOnb8DPkrz/zDP5Gs7pVCBX6DCBVDOcjh1let2WlavWOCpzLfAhVc//Nf+Ndvfsd7B8dmqccUjBQAY1Sy8uNJmT2wO/ywsK/4+9fx0lWwdFRP5UUvexW8nCcKVGjuqxMq1LEYd/3H/+cvb3j920en1tG80yJ17LIkuRhgJBfO8NeveA2rtCbE8PFFf/WyvyOcULJyL6jsnVt4xh8+Z2moSHYvoIK/bFuPA/iLPcIwjy+okIknT2WZXFl6Tux8oCLGTjhLRLq4oslAuhAqVdnclwEJWp7SyRURKsQVHtLnx4tAWg5UKFNZUiNqpS+1bk14asJb72MR+FxOSiaJKExACIEEajIGFOECVKLjo4X1awkq1myaBecBFQM8ppJREIWxBAM9YjIGg3gERMEWUKExGAO0SImIpEfJm2GR/GySfB1XOh2qVNKjY1q1dqGgInlDXEtBBX6JN9HvitYkpRzIjhcnrhha/6TBddcMrL26vnpXbdVVpamdhYkrc2Pbs6PbMiNXcJGnAjcFOh+oHFxgScD3/mbP7/3xC8ZXb0nk66s3bH/Ry179wJ4F7AdUqEQxnjThqRyca0zObFfCFRDFHciqifID+47vWzhlFHZcNAoP7Tv86te+cWLVRgo//N0/vOHBvfMwcHgChTpjKhwqjkDSq7A2f8PTGz5x51conAM3BWADUY6fbvzgJ7/YtvNaWHkmo+ejGi2Sab6AUNm/0HD6E7gSmzcKKMoh/R9e91aYYNjrn/36obe+632//5znj02v7xuaiiaLPiUBJ2b9livxvQAnr+JOj8+Ayo7d19O6dLaephWETwio0PJ4iluAo39/w5sOLpzee+j4j+79zW0f/tRTn/FHV+y4pm9gXE+XJMkeUOIj47M3vO4tFPnn0ThK99h1zVO5m8JTlu/84lcbjZZ/P3j4+J8f//SyK3fJSlhc3SlCBS8BFYK3CJU/+pO/oIX6HWGYCw+VJcqx8EGvkvViv14RLcucDbuAUGmLycN4iVzhUAlmisFixZ3KOiM6nBUyfHzbMv0VMCfNABUcTHQRq5Isc0kg+TfusC4FNW8yq09OpaZn4KD4Bwfc5TJ8FCmuhweGUmMT1rjuSmedqQxk11OQLZGEMJBiMSkaJVl13Z6CHxNnLUyw7SrDFyG/BKIB804SMWssAmFgi0cdetydTmLMSCMITowzm8KWZtgcuWxkZBheixPfq6hSGLemcahgzNWVKJJQ0WCJFtFSG1GwtSpFcCU/dhko0r9mN7aEk8r0DuhiQ8UoT3tmz+FT1Fpj7sTiKsUTjcWSULA+R483Pvu5u0AUrz9LMRg8y3/kji/hU9T5Y3FFtFE4Ev/DU8VA6quBMYhy6OgJgkovT0VyqvASZC31in94Iy16AFTmF1jZsflji403Fk6YBSUf3ncCIOHP/hcEKgeONDyhlD+cww3CU3HKkde96V10R1QBDIwUS/pDeIsq8grZxiym8vD++USmItm7T9k9QaGCa8Bfk+6XdTc4QROkZ771nbux/fX9j7St0qelMA/vPaxGUiJUaAYMzx+0+of9aEdPQPSvCIMH9h4QEu1OPJ6hwhuDcqJ0HtMLKmJ8BWghEWBE9ZoTOx+odM31EufB6CXsuzuWAlG8mbysZyFeL7JLTIVnNAnzYBRiWdFScwCJXJl432Bt1Vp/rc9TKttLRZYfnMk4CgV/uVqYXaPW6u5MjnBCLGEFgA1ZYgkGFcgAhiOdtiQS/GVXwfkAEggkzCOJhckpIZyAJSAKcAJZomGMRaKw+TEcH4/gJM58DlCxZdL2bCZcrxdmZpRyRQqGTKj4Q/BOloAKz/5aMVRI2aENw+sYS4AQbKszV2JQntpemtzGtj2gkhq6ItG/Nda3GWJLVSob1NI6ZblQOcZEKcWf+OJPf/HIoWNGm5BjzJ7uP3LakNGayTDNh4ykr+//4L7+4XV2b9qnlt2BvFGlWJvduGvfwpl5YRaCVpgfPmYuhKQ+K+DW9+7+2Q9/+vN9h48cPnXm0IlTVE19/jSrfm+T00wGV6xe3aPkI5n+6shaOgmFeU+eYQPqz7FgiKCyf67hV3IWRxjbZqC+vZ3w0ZONd93yEbM/ipwylIPgb61av5sQ1QaVRG6g0DcZihWpscpr33SLMcVnQkXsOUYlA04YlRyFPiLmws9/vPEtkuQ2bNwFhMrHqKoYzxeAYEO3br8G8G5CZbH2V5spJGP6hre+57DRFMAoKsrKo+FHvuXW2ynXi4LzJKsDXAlQ6S2HN/z3N7xl8ZmDlWk5RR8ndxYv5/DvQegpwBeyvPxvXysHYpQNSJJsfpwTPt/D+4+Y/9KM341+OlpFK5bGaeLBhMrXv/VfxvPKyccJVHhxYrFMy3KgIo6JH73QIu4xE5HPAyq9csDEZDCWzRVghdbtRpovXBZPOgf5E1lPJNk5AyZCReSKLRyHWMi9R52VNrnVOLOYkXhmbDI5Ne3I5T35olVPORIpBrZsAYQDSwKlCigCeIiSonGztjy4kkhwMWzAZYGbsgRXDDZQ1ARbhhZwIha2ZnQ2zQWl4iy/i6a8EhErju8mdybjyWbhG0FSSrfns5HJMWV0yKZGJF8QFMGgF1TElOIVQyVWmalNbxtZf3V91Y7hDdcOrrsGFClOXEE4IV1sqNz2oc9su+ppv/jtwT1zZ5jdNGalFgyTAagcNJqvHDjcuP/B+bUbd7OVg4G8rJSwDeuDnlDG4dNffePbH5k7KYZMYdHwGEtoIZP9/R/+Yu2mK7/6zW/vnz964NiJI41mE6rTjT9/yWvMRvdGN0mbnLT7UmweTMt97v9+/TDF6puz89T2g9XGb2rfoUZQK0g2FeoFFbBnpVCxeaPBaCGcrCqRkhzMvPp17zxwZLFL7nwTtzCvJ5qwwS0LLaqYZfzop+40loUHjMUfFwYqUC+obNl29TlAxUj5XRlUqJkbkZWveWS+7AlWuBNnY5OlQuVj7PzXL31Di2Y9vogIFcYVi6zGsnfc+WXRs6T0OVz8yUaLOyhCBQJUcAw8mMcDVOilwx91BmK84r2ImeVABRL9Fbeqk2jc6bVgcM5Q6bXOsTP7i0VQYOC8IZrUYqlf0YQvnvFGU+6w3saVFqj4FzOMgZMVcQUMU5L5/ORMrH/ImS9AUizhyjKcuJIZCANyTbhTIop2Mt6IUNE0RhRwBYMeUGEUMWbAOF1oHgwUSU6P59bMuIpZM3DCUsLivaDiTKXsxmwboMKWv6R0KZvyD9YLoxPeRIq4csGg4lRrLq3PHa7XJrYPrto1NLsbGl59dd/0lVy1qR3Vye2k/ORVXOnRbSngxJAYqDdqtJgzYJ1QUTJMambixnd9klWb53WxjP/h3/meTwYjlYGJLf/+nz89eIwtd9+30MDgMMzNmcb+o0xfuuuHg5NbXcEsLL47VPAoRVcwjy3GkKwVn/ei1/zqwYNwPsz+Wkaj4j1zjXkwYKHxic/cla/OyErhP//7N3hJ3XYPwgCdahw62fiLv369VS4xeSuQ5M8ZylgCWS1V/fidX91z+NRh40F1vumdzLPFK43DR5kAPFrPyBpquaIuWX/jW2/DTnqXhINvfu/HzGw0A2AWOQvBPVq18UmgxVyTE0fnGkcOsT5mzmBN8hd8g5sqG3c588O42Wc8+68++7m75o8w5OC+jp5u0BQNLyEzf3xx8eP//vS+P//Lv2mmuqqLMijSkl/QY9U3qOb0J95168eYQ3ByUbjU93zgjk5rJdl8m7Y/iRoKiI2tHjpwsm25H53/9W9731wrq3DxYJhZWN642hYACMsGn/6Hf37H57/+4P4T883Onkdam9Xzl2DPj+797Qtf8iqXL0pYwv8AJH42uv5Pff6reDQxGyKIbYyFh4MmCUxOfOM/7wZF9h46Knozf/CnfyE5/Q4/ztlSdO984LFMwDCWaAl7JGkL61Iouriz2/GSV+0qEU4OJeFUdZI1EKWGH9hJMscGYIhMIjzEcu5iU6xeC1N6qdcCRmdEh9fC5sQMsexhAyTiEsjO1GFLs+o7l1gu3hxH4lJQVWv1wsxsuD7gL5Zd6Sz4AU8FssRitkTClU5jy+x10wXBflHWeBzCMfZ4whaLe40V75ZIdFHGeazGB63kwUSj7GU8QmIOSljBwJ6MO9O6K5PMTU+svmZXZKAPe2x6jA6zRmN0wrbz05lxnd5cjr4ImMHA3VcMTw7jbFLILykhSVXYIKy0BPD9oUVxwAAeXN5Qq6cSqsRLs5t2PhsgqYxdMbr2SVAnVLhEqGTGtneFihhWWSlU3nHLJ9R4nzuUi2aGrrruue947x13//Th3+07DZbcfe+DN7//jmue/ieR9GAgWvEoefgQBBXCCQZWbwpQ8YVLyeLAy171ui/d9b17f7MHZheuzze/d++7bv3E7IarKVXMHch++/v3HTLA88hcYy+s83GGlv/vb95g85WZ5CpkCeQ5VByBhEdNb9x2zVtufv/37v7ZT3/50N6Dpw8ttABj78EGnAngBMCAswKo/OPrboYHIx4DvfWdH2ABFVlvg8rspmv3zTNLfWAe7kXj1NHGGTzdH2wEYiPhye2ASqh/lTq4WnLrjKNyIhqvbN7+5L+74W13fO5fv/nd79/34CMP7ju4d27hd3v2/8+Pfva1b373DW9999bt11ApSREqYvbXMqECy/vmd32AtRY+tihw4q03f4gm7tuelPFD7Vs4A5yY7RoN/t17374loAKfgwJFgAq2y4EKtqyypDfq07Jbr7z+hte/89YPfPK7/3PvfQ8c3Dd36uH9xzD45f37vvDl//inN960fddT1VieWqE45Qg7Z8fKdhOKVhlQfOett3/nBz/DYwQXzsnVBpWvfP07cAcf3j/PJ82gJ//ec6h8SytRLjpU6M8BqIAo4IqE5/cmUdpmw2jc2sVvUS1uUHCRKxwkXOIKfEKLGGJZGirLJMoSK+SpgRWF4gEVCsiz2InQZ2WlUGEVIfEyqKZGxtPjk+AKoOLO5CBvrmBJJOGseLJZWGoy2YuTWh1Q4VyRVE3O5lhqr6q1QYUfQwOTMXE2o0Ug8eYzsP54KUU1SQ1iECgXPLk0hP02Y2YMZ+Zc6Tw/QOXOZPzFIojCYvVAV45VgokN9cuFrOT3ScEAo5caXBlUOj2V3MAmeCczW57GWDK5A+P+6avqM1edFSq5iSu5syJCRXRWlg8Vevq7+bbPasnBQHzArVacoRK2Xq0eSoxgALPrCBZdSlnyJF1K0SKn3WoJx2APtjSw+fNWXwb7JWcUrozkiQZiJbeScYXS4JDVq4M6MOIOfzYY6yODDhqpOv6tDLnSg5ZonxSpSeEhyKqNWdTCr+9HAAAQAElEQVRRSalKwTK8BMjqS0GSS7X5Yp5QhlVdNODh8MS5bB4dxMLW6k5ADjklOaLYUjF53rsXA+NidNwFJPmyTF6cP+NVC5AjNAxJcabA8GXhySvTxc0WV9WeGvKVpiRPWvJmnO44ZHGz0sJ+JQM8SHYN1yMHM7gSKhTGmjwahk+onXWuULEGOmuNEGzscozGi21lPRHsdweTbWVgRPPdWa3E4YszSAjegyi+v8tbDsUsMdn0OYyKyzH6XvM6HUrLeRwKfK8liqaAVbz/Lt/ZOWHF57WMxY8sJYwnLLB2ALJKPkoHVy4uUeBkMCrAasPEKwmrYeJpeorPcYmexNJQoTGdgbjS5qBwrrT5LtjT2XtKhMrycXIWqBhmDgOHEvNEkr54BsLArcbtzWhzz0WOHQ21zN4nobA3mU3OzMQmJuR8Uan2ebJ5ZyojsdAIIwpbKp9KEQnshpuyOG3VAyqedMaVTMGNgL8iGn3umoAlkBSJ4CM4OWw9mAGi2CnqDpzAjcBWC2EnQAK0ADwYkPuC00KdXOHnxxbOCrlWuGacygpHJ5/SRgc85bwU8kkRzRINtyyQDIQWJUyFiVBpSSl2KFWLv2gLlqOFmbF1105seDK4Uhq5bDmeiuistEGFOysiUZYDlXfe+mkOFWzBCUegHIwPK8lhX7SOnVZfDswAVJoyiQKBOgxC4YovWgNR4LJ41CwRBXL409gJhBBUIA4VPPU7kv3WeA1Qscbq1ugIZI9MQLZwnXEFUPHlLXJS8iQkT9gqs2q+DBLuGF88TwJIQBQ4Q94QKzaDAbYsatJkCe9WYvEkcEktUHHGwRVcJKAiyXWXOuqqrQdR4qt2WwqrvKERu7cuBXKe/Dh+BOBT9qc9chJXAsKxxpG+hDeQNivwswszOGHyY7Fq1kqhwnubw+J3kgD7+WFtUOno1t5+2s499EFCVKd6QQUX1lnETLwG8mbY1uBiVyy13a95pMEq8WA+c9gJFSN5LMhTjSntWHIFOnyURwMqhAHJECy7ZCR0tTkQYq5Xz5gHpZDJi1wRsUGAsTYLhVmMdzunxegCLjhURANn7jGmYpxq3B3WKcTiDevgylnKsfSCSkAtT83GJyfd5TLlB8NHscZ1yYi9m+vkjaAIuRctsZAOqBBX4KY4EjrUbvSb54GtB0vgTATLZTZV1ZzXMmfAYmFzHNUIM3QA7QdgOFTauGLmMRvfQl8haRoLtKR1lipmLIVRBvtCAzVARVJDy4JKj5pgbPpLkvNs6864tL784Ga4LJMbnwJ+VCa2VSe3E1QwhjCAd8LVOgO2nbKK2xKLKVwPrnC09IIKBerf9v47/akhb3zQodWc4T5sXZEBOTHijY36EuPYOtQBm1KBgEPIFWIS2xu7lRrkVStu+C7BosOfb1WWQ4XEiOLPSlpRipQZUQSo2MLj1vCIRRuWAn2SryrJOSZvUoL/4UkCAEwYGLIYsrqZbJ4UZPemHXIGjgvUDMin6CXzZmQmmvgiqFiVouTLSG6dbbObfIO7E6O75eIme3jYqg5aQ1VI8uf8uXG7L4d7YS1YZN3iS1j9OjXRIm+pDSqGQm2eSq9A/RJ2dgk2tPGjjStdT0jGvZdlXxFUOgHWecFL3ELXKxG/S/zGll+v9bc1ls2H2lax9CDKowSVlskrWkpiWHzyHvjW0hsqhAEOIR5lEafC3OEUoYUdHIAthl2GdY5JwSi2dk2H2lyWC+WpLEKl+bBMC/HgnQAngXgG8kVTcFnaco57QYW4QmH8ypp18aERShoGUby5AiOKUfTXDsZkcgZdootTW5QuTGouRuHIgeR83h5PwFMhqLhTaQgvsZNOAgfCk82CJexIXRdjKhwqJPglzF+JahiY0RQjIE+hFHAF5xS5YjXaTdojuK8oBthC2OmIRFyxmDub8pfyoEuorxIsFSQl2JzsCrYtiuwFFTHVwoCKr5Aor4a80QHJkwVaahPbp7Y8dXjtNeSpEE4ILcuHChVrAVQ4V5YJFV9y0BMb4FBxhvvBFU90BFDx6xPgiitSx/6loeJRyiuDipJnUss0/WWJDIMoTJFRcAU2nXHFmASTfHAsTA9DFCUiAyRcIIqhVJt6QUXCZfgyrmgtXJxUxq4DVJyZtVJoWAr1W5QBu9onBcpdoWIzGt07vTGBKNELCBXRKC8BlaU9lbNOf10kqHRibzln7oSK+a6zpZcw/bZCTlewbVHk4wQq1mbJSOayCCEQ7kMsEyp0TtZ0AHuak10uLUl0wUuAhLgC2dQERFChKbhOrlxAqHCu8AwleBtyJAmoUG6YyJUlPBXKDStOzET6Bz3ZPOtxkkq64JcY6VvkozSJEudEWRoqcBHACRYmafoQZP1piz2U8kvhGfYpVSWXQszgEgFjzobFwhiIUOFRepph41wBQpyxBIEEUKE+xEzhMLgCMsmFrNpfc+czsYF6pF4zWdJGFAEqbX8IMYWPxVTgo8RLs0p6HFzBlu2R8/7kCCgyvfVp5KnUZ1iUZZmeCk1/kbMSrmwINyfBTK4YKcXRzMib3vVRCsma69EMqLz9nz/viw8BGyBKU/0mV2JDPn2UKTHtjU261SmXMunS+h1KnzNY48JL1kYsWHEF2NSZzVcU1cGYPIHH5k8byjrAmABA1ecODXiUQTO+AkdBHbQpNWbWfQWLv2gCRpSPyerLQWZScjcZ7CGiMAiZUJHzTN6snBiKldaF86tdiVFJ6bOF6sw5M6YoLQFQJyMFs/78KBELRHF6ExZfzOqP2/1Bmy9glf0Wr8+UJwA9mlBZjh7/UFla3aDSPsHYVhL/MYFKL7EJsSZXOFrO6qmYaBHPw3caZyCvBXRhmWZKTApFpSDMVpJyz2ws03cx7sLR0hUqS4fuu0dThAzXtnRkcMWtxuGpeFv9lSWgYtfi2dnV4eERVsgrl/Mmsx6drWSUtIglkYSPwooN0yQYyxWOnxUqIArNaGEAQ88svhGlJ6LAa/Fm4Aml2AQaWKJpLKbSnArrBRX+kgaL61EM1wfnJE+Fc8URjQMqYAkJdAFRsEfSFCmiuRJxT1LHx735jL2QVobr8WpdcstwVtjqyA6odPYR4H84M1APqOiVNXJsED4KoIJxJD/N4tKhspafgr9COCG0LB8q8FQgatulCmlgoRzjSiw7ujRUuAgqnCtyAi7LNOSPrZYjq9zhASAEDOgKlTaidIUKiUOFyQePp+YK9kMEFZs2ZA8PO7Q63AX4drZgWQoU28Tsvr9oY6fKizGb5UMlXlkdK8/CJ5M8RYvWL8lFDOxKP2OYj/Ud4FCxeVIiVKBHDSoXUI8aVM56ARcQKp19Vh5fUPGqkhHAFwPstt7rS84KFSbjhOSycIoALc5Y2hFN0Utya8inEblywaHS5q9QwxUq2AWocK4sAZXq1Or4+IQzXwBU7HAvwjDH5npGUMSdK1j1FAvUx3UAZllQUZRguUzZXGymy8AJbD1Y4klnAAAjGUw116wYOIHLQtNfNj3G1QYYkTR8P87PRUShLaACB4V8FJEr1liERVBUBVxhREnGqX4loKLmS5Ic6Dr91ZnYbRe4wgL1kiebrK6FKfdGB9zhOhTQR2DgfPowRREyAxsnN18/uv7awsjWwtTO4vSu3Nj2wsSVpYmreLni5PA2CFxJDF5OEftmU+GNEJVsgQLNLpDRzNCbb/rIgaNUUdhYvWysA3jDLZ8BNgAPIKSJEzYJRsJLvOWND+MYf3IMXgtMsFMbhAkmSWodVhgP+Cy6rlRtwXY5DPfFAe+kVQQDEoXB6Uh7sO4I9TvUIac27FIHncY0FFyW5gnLlOawKOE8beeEzLC8EYyhPZIj4VLKAHnf5A784AC5FMjZ1JKV5RmzVf1mBX6/bjUkhTJOvWbxJMEnlycBSXIU4jU5OkSNCNv391rweLFB8kSHSpcLMNKp29KLBag8NvDoJf4PwCouQPFH2bRV0LT1hBNak9+WuCW1Toi1TIvR8vtw0hVNQ+5YBnJGUiy4Eojw2TaghSclG5NvRhJRx8PvOYjnI7XsNGp2Ub166hvviOqABAaLyx6Npo22mI5BZmwyNzHNlsensq50lua72BaGOK67Mzm2ktE4mEqwULIWHvkdxlQYo0IiJulx8kgYP1QNroOczVGtLRzmiuu+dNabBHHjFOSAiccZeijJhSuHcNm4eBIt3qT7olvjJxT5QZNd+DoeUOFcYZVd4KxoCgZUQ8ybTbvTSdxFaLA/VCrj+m1BjXVh8QZYAUrjL2UVEurol29PKRahQmJcSY3iqTlcmIZNh9fiiQ1UJ7dPb31afd2T4ZcwokztPE+o3Pi2Dzyw/+jcCbOaCK1meOcHvwSHAMAAPAgqnCiG6hB5LUALBKh4Y6O2yKA1PACBKwQVC+7r/KBiOjeBPqbQgF1hRIHoGuAM2UM1gkoLV5aECqHC5IonLblTvmg9VZmNl2ZN78dfYMWhOXgMotDWYoigIrl1eDkgitMdf/xAZaWfvQSVxxAqbWghqJhpwVTWntbrLBsqZqZyyOQKcAJhbEbsKR2gOVfGg/xivcLz50rneWjVPUGFxNFChpihhZo2BhR9aDQ/ORMolBlRkhlAhS+GB1qIMV2hAnvtaMZXqGQ9vBDyEtypNNwRmGa8ZHRJZSA6nht3Hjnn8XNBMfHKyW3iOCEuivclnrPNNeFxlJYvgqcS0SAqTwmu2BMxQMWWy+AutGotUCgCJzajwZfF3wJssTJYT6i4tD4uUMSuVvHsnKiuUXOT5LL4kyMTG58+tfmZ1endIApBhcq0LB8q/vxqX25WTdZe+5ZbHzhw6tCJxr4jTHsWmN703s/gq92JYUd0wB7ph2zhOpdV7Yds2gBkDw86IkPO+IhbH3MlGFcILXgLxxBUKGOK1AKVDnUBgFyALH5go0yfBUVobs2p1vG7ORi0ym1ydAZyWqBiCkSBg6KlR9OVtThesiXMOS5PVnLpkpwxU8u8OsnCQvpMUihl1yuSExRJgigOV8zijTDJ3RdFd8PMJahcUKgYF/C4K2W/ErEyLU2LbxOqeFlkbUVQ4StjbB3LWcQQvbicRWwAzJFwoQDDoWKWx2810BwtrLd8SAsWKyCKUq55M3m7nqKKkMAJtgAJlWCRwuCETqSxx1nTSZrUIkhQFIRK1jvzOeq+5SkVbZm0FI3YsxmIouXcuHNzzxnQhgHxmiFcsCue4jgR1TymO06IW5QARjwjcZyIXMHWXB0Zj0cGB9nCGlVzBDWbX2nzUbiDuCyowEGhFCw8Pocy41p+Ci/Z5IynGCutG934tLFNTz8fqESzA5AczsfzQ5FMP6SlByElO+GNDwIqrvgQcWWRKFofQUVEC4cKZI8OgSuADXShoCL5ShChhdPFQEuVuALZQxWulnP6iuQVtUHFo1VD+lA0NxHOjEk2XXJnyd0xYvU5RpRWqHCiMKgoaQ4VEOUSVC5B5YKIwuadq+JXChWK2dDZKB+MYi1iiF4EGKBCYUh7iQAAEABJREFUXCG0tIRJLhRUAouTYG0uC6FFUsJwTUAUrVoHURyJlCebN8nRLOfF1jxqrGQL6+AiQIWiKabnYXgt1H0LUImMDIeHh+RKGVDBlhWf11SadDKnnnp6Jz2h4tGBpeQSNcraQMLV5hUtzoY1J74wsETDbNmjsfiRysa4czkoNzHJPC0f60nctR7+cj0VIfmqDy4LtnBTQBevOiQ5C45Qf2Hwiuktvze0+rriyPbc4OWZsSsJKrH+rYCKGK5vg0ogN+PPTvtzk970mDc57NGH3IlBbD36CESEACogQII4IcxuDUqqsQ32SUq/M84O9iTH6SN0PNwXSIKNhuug1KDlQEWcAWtxKXwFLnIm+GSXyBUBLTVjWow8mwodiY+w2JURjcfOdN/6aGHGGSpJUtjiSbP8YCP5mBKRrd6UseSFrY5ka2LYshh9UR1QkTxhph61m3pBpVfhyHM20Jeg8oSGCl8LaRMsvrgqvm1hfK/AfstqfKM1i1nh2AjR0xKZxRotbCqM4YRzBTq3CbHO/h88prKo1ud63nAeqChOz4IonnSOprlovgs4cRu95SHmoESMXvRGw0eqYsnGETzjN424qjKu5DLwVHKj45c95akbr7k2NTgspzLMfAdCLDAuxMl58KPDO+kOFbgpcipHLOzNlS4+SufORW8pzpwVhx63J1iPFoIKPBVXXA/li5STFiiVogMDLGjvC7bXwzfiYSvwVETBZSG0RNKroplZpzIgecve2Gh9+urJTc8oGMvpyU0hqLQ5K12hImfG5dQIcaUNKiIkCCrEFRBFCtQkX8UWGfampiAcTx/hR4IortgIfB1jJXxpmZ7KcqDC0SLGUThamJvCtjUuyZEk0mAgOVMYhHNTemWNPzHMIijulJF8zFacEE5ovSSgYkg/K1Tszih0CSqXoHL+Equ28CmsJbiyHKjwc9qbOcd8OQs/IVkoThQOGHE2bKVQaev82BUq3GWRfKHM2GSsf0jOFsAJaoVCOIGbEqrUQBQWpY8m4Je4khnmx6Rz2NLAm2PyZ5jcmYycz8u1irdaHt20ZeuTrwdUCuOTgWweXIEFl0KqCJKVeirwUXrNfbVBpSuoumZ/ASc068VmwAyvxZXSQRdAxcUSEzKUjaZUq5QM1tlhxcyzOAeocLRYfFUQJZJbraZnLB5WdRGYGZt9cnnVkwgkqZHtLc6KkFLchMqsP7sKXJHTk97UBARXAyI8OPUJR2IcssfHIGt0xBIZhqTwCJM2LKlDnvSqQGEdtvb4hFufcOFggT2MKPFRV3zImxz1xIYYTgxn5Ryh4m+XJZBnakWLOfcFqKh9lB6GLYX0Jbkg2ZO4klh5DVw9yZWS7AnJl6d+aE5f1iAKKxdGpV+oJpi5Vt+ESmpRStau15aGSsv/2K1RWa5LULkEFVFmZUkxjdhYwNhWxYtzZZmV7RfR0sz7gssCCedc5AGHiktLrJQr5wYVKaAGskVAhXMiUKo4WaIwC877SpWhy66Qi2W2NiWdo5QwBpJMHnTx6BlfOs+zv5ws59jI/koyZyU1MTF7zTVDl10WqFScmQzkymbtqRTlibWBRPRgloAKWy5jhOiXrNKvtakTLSJXaMpLqZSKM1MADHX9YnQxstfcMd0ZMXMK4KywKEsz6NWmc4cK5NaGKCEKUMlWN4fiE5KrCLoAIQMbnlZb82RyUxadlRVChYgiQoWtFGHzXf2QNYoDJoPF9XJ2tTs148utAVGcONKACovSC1CBaLHkRYUKfBeRK4QTmnZjRPHk8DJeWRvKTEq+IsOJv0CRKpbiJZveCYcKdAkql6DymECFcYWC8yQfE0/WauPKMqGyiJZmaUvOFUKLGPi1BcGwGIhCWhFXetX16gmVUFjyK3j2r86sIWCAKEq5BqJQyAReRbDaB7G6LHGdpXvFdPgrbBIspLEZMDApqInTX7RoEVBxFvOhWi0yOBgeGHAZrbHYYZrG5sfCbB0iHBdfOstzfHsTpQUqcFNYZxeqnbxsqCw9vQaKACpyLpOfmoCPIgX9UijA8sGMlTQ2NSLrLPWZJT2nUmwSjNeRXAIqrlBVcmWSpdXB+DCrbqL2QV6tLgKmq2BAvdGBSH46UV4txwYlu47n9Pzg5rF111bGrsBOgCrdtz5S3hCrbgJUABJaVE+Bek96GpINeZKTEHwOw+0YFdWc9aoDMGplg1bdCFeG5EpOskF8zIDKCMkWGaatmDPmTgx79BF7pJ/VG5bzPA9YVO8k4EWJ77Z/vMkVWiBJa+8xUHPTieo65jC58jZ3wR2syGpfE1dsMaONVbw31Zz4ShlhlQQXrzNmkdPWSN2lD0v2CCBkGkQDKudjZJdTXuWx0krB81hpxbf2WFOkXUtSgYdGeElKZk8DKrW9MpcZ+pjMBouGoW/Z31zfwLHhjaYgTg6RBNxfIbTw3LDFwHsz/N6p9t7yvQLawIYaLq5aHRscpjKR/mIZA5ADdJHUCNwRwAYIoWgKTX+xtSzhGONK2ExExpiL9uCYUKkK50aKJUKVGks7NoBEGczitbmiSVnP+lOsI7I7lhI7HAs1YyJUfB4eA8Z2LQqxna3MoAAJGxsFWkhi0y2chD5O1ewxcIRj7JwdJY0dCZ0W/NN+bO0GFFk1zHzeU6lIipkDZjY9MwtKLs58njtUOFrc4Xq8NKtlJ404AatKOTS7e2LDkwGYaGFGK64DVKK1TbxSSy+okESiwHFh2VzRoUBuJjWyHR8ESODuEE7gzbhTUyJLekGFRBNitNiTMLA0VJZWFyxRVrHhqcAx8ifHgBNsJW+eTX8Fat5gn8NXtHpyFxsqK4XEJahcgspyHA7eBRJb9qQfNNspLgcq3OHgzgTlffHsL/Et4gpHi5h2vDRUOhvL93yiV8PRgaHCzKycL1ICMbXeMhOFY7qcLRA8yEEx16YYgFmkiAEYLha6V8KgEWNPNC4ZiyVZhKYHVCSfQm0ogRNAxZfMEV2cEZ0AY3Q+jhEV3DiJGuFaKVToPBwteEl8EmuFsYX9xgrNtgrKBBVa4e/r65OSSckdYF5gK1Q4V84LKrRMknKfMFbS48HkKEuK9eYwoL4smaFtib4tQIta6AIVEiCxKAEqcFDAlWhtQ6S63vRL4M2kpvBxObsKAzZLtmyoWNSaVeuDU+WLD1Fc/cJCxZwNc6S88eF4Za2Wn2ElIO1JyZOD++IKD7F1/kaCslgf7GJDZTnAuASVS1BZ5kQWfBRCi7nyQ0i1EhFC6lqsviUP1Wh/IqYUt01hcbRw9jB49IBKJ1GWgAoQUlmzTq3VCSqebJ5DBQDw5YrklEBwXAgYHC2mp2JIhApE0Xv4K6xWWCRGBfP51JlBncVr4M2MWZgkFBZXonj0DLbGTJfGgy7iRBacCVFUp5KNjek4U22TYEaaAK8Axmrat0GI6KKo7VUvI/i50ubSzmRKGRhkjxRNP1WEijl9ej5QYUWCjVbE2FIelD8xHM5Nsdkwd0ZyprL9G8c2PTM/eiWgAq0UKmppTbiyDm6KJzkOnOBIAoklMowtXuI8jB+GloCKpFSJKFbDtXKqNVwn0HIxoBIurEr2bfDpo2AJfljJXwJaXJEByV8FVGjt5GMFlV5G8BJULkFlRTESY/qLGXGzf+KyodKeNWRMzQMV7rDOsbE0WlhzRs6VsxFlCahkJ6dTYxP+YtmbK4Ar1H2LLXiMJwEGdyrLU4f59Jc4CWYGVzqgEipV4ayw/VQrTIvgzGeFCmw0jcX6KzSA3aeyLhwD5wYViuWwEA5OElTMRimtUAFO7PEE91rYCWl/001hEaN4wlMqq8Wq5Fe6QoUlerDl3K5MLDet6KPOYIVDBZaXqxdUxGNEqZkJs9qxN+eJDZXHtw+vvRam1qOPeJOjcmY8VJyBq0E4oVks8jzYpFZq2pqYkAtr48PbA+UNGLgyqyC8y0VhfOJKAHxiKBo3csBGLNogMQYUgUAUe6SfcGJCReknObVBOT4GB8Ia7JN8FV6vpS120lPN8AzLM5bzkicLlKZq63DjzF+x6+2L7aP94AFdj1NldLH5yla5ZLAk01RKkM5FZV1oi/PYYwMWV5x1lqSuJB1QIa5Q3yquJ6in8kSB0P/foEKFGsnc0wwVxQBMi0kRF8Pcd1k70pk7ZLgsQAupa416+i6aFzK5skKo8AWPgWyxNLsmWK6CKHBQMIDpD5QqYAysf7BYWZzOMrDRNgPGicKhwo5UI/BvKB7DuNIMtxir7tl6SWrE0pkQ3La8sU3AAKDigd9j4GSRE4QTmrMyqtw7EjpL2dK0xcKUPRZCtkrlbgqdytwKn2UzYEaFSiPWwn4NtT7AGpTJIfzy+JcgeUNmtx5DFwUqsKp4N5KfhoVlIWtPTk6M1Kauqq++WinMeFKjwcI0uR1gCdGF5rWw9ebXhPsvU/u2ONMzhBNPbnUbVAhFxBW3PgGuQN7UFLaUYQy0cIqYS/E7oAIBJ57oiImWjlD80jLXQnqyEFy0RHk1K+0MutgS2NKPJkLFEu4DVOgajCovdbdSd4X67PjSRa70hAqvGNYGFahroJ4I0dkP8RJULkHl/KFibVYXJqNvRtSNnvAtDsGyoUIid4S4wijVo/cJ50ovkPSCSnP9fCQ3OhkbHCbvBCDhboo1rtOKes4DwoYrmelKFBI7zFiTD6iYbwlQwfFsNT6rDJY4N6iwAvXG5BWf/iIPg5px8X5f1PPRnKQyOrKYdYjJxRHVBhVVW5z7avooLUAKR3B+BhVGIBZkcqSz/nKV/EXmjLLK0OGLCxWaEIPNZbNhhelAapTa8cZqa/rX7M6NbnVE68QGbFm43uAKxqHSutjQNjgooAjoQjjp9FREroAi8FRAFJcBGAxChTUYUH0XWHA+8WVKKPTCSoQprJ6YJzEW0oeoIfFyuUI+iq8Qzk3lBjbhTtmMnzvjClXxA+KXlNxZsQKYJZC1hfI2pcJK3VBRAGPljStYFLjSHSpiGcplQkVExVkN3CWoXILKiqEiqzTBhQdVWHkmmq5JJaRizpLPSYk4s63KCqDCs4p5fL5zKowyo8REqeVDhTwVrVSrTK9Wqn0URZfzRTgrtODRrqcAFR6cB13IQQFUehGFHxwqVfm7NM1Fa/XxktKUJWOV/kqhQitg2IRVm4dhJGiBKK5kispW+nJ5bKnFJK2eWSRKTzdlkVV8jb2ZHi0mBYRUXIM/kzNyi1nUR4on/LU+XzxDa+mNovdhzpWLAhV6l2L4VJWSSodJsJtaVe9fD7SEa5tY7lZ8DESBg+LPr6bFknJhLdRGlE6ocK4QTqzhIcothrEmulAO8dJQoephhBa3WgnEB4AWj1ZdZkwFIEnV1qmZCYYTbw43i1vGT2fx5uGc4cek6mHNGmJplu4VKDKoKP2sNIA6JGnDHqUscOVcoGLxRnp5Kss0cJegcgkqK4WK2RWG+jJRCqwxs+QdHYqvX5Nas1rur9Mz+4qgIuaGca6IaOEZt8SVtv3yZPsAABAASURBVN7yZ4+pBLXqzBq9fxhQAUsIJ7SFmwKXhcAAilBwhVhCg65EoYwvEAVuCs82JqjA/lKeMRGL5YOxIPnKoOJNpsXqk23TVtQ2OFgshUrlwY2byqtm3ZmMXddZCbJYbFnTX4IDxDMC2Ne1QgVyxXW1WKYayZKelJKpSL4qGf2b2YOFUYHUjLexmRxHIpwZ09KASs2Dx3a136sNnBUqvYjSJl7fBWhRc5N4VJdcKVekXpy+vL5up1qehYlM1LcVxq+JlLcFMpt4xUmaGeOypKds2RknCJRdZU2M2PRRV4qJV3PhNV3MbaSf6r6wQH2gxIpL0vSX2ktVuk5vfBCXijFcKzDAG6w6vAXWRNJXNPHgybL6XdXV8cIUCCQ5dcmTBpN80TrjjczrrKRszR7DrM2w0KeLehhD7lDBFhqwBvstvipTIM8WV5qTXax5F32Wzub0sTWSrtgIQGhx6TZPyuKNcVk9KxMttDSXW7a89diD4fENoWhX9f6pL/ItXCCoiP+WWv5dydHuajYkh1xKjFwWOZJ0rptMXH1Ffte2wJopZkZVM6jexhUBMD2q6xuzW0ZOLZtYW4yj0LpFYysa38VYS+u0mOlMGODBRyKVemH9+tDgINyUYLkKNwXmXs4WcIw7lQ0UyhK+LgGipCFXMmeLpSwRHaIi+bQVJWmaK50OVSrkIlCfR9YJuFmansqreJNZgm7LZwWoiO+yGzTujmWCRRN8bUqLqMawETuxp1KpiYn1u6/Zct1TokNDrEWYEainI10KU1t6sayncWYpoIj7+TqYzq+jd72JlD+VxccdCqgfDRSKrOeYJ2CTQ+K/h3OEyjKJQlAhkdVWshNAC3ta96f9+dHyzFXV2V2Z4Z3e5GwotyWY3dyVKJCruMaeW2VLTUGuzKQjNW7FAzse2wWiiFDhSV+u+JA7wZLB2MpHpUrrSHpBhaPFnxxhPcoCRRCFyVe0ywW4IBBcE72yxhuusYYo3owzVPLH+l1KmdZLcoq0QaUNLdQaElwhqFCRArtSsoWKNn8WronR0esSVC5B5QkAFQc8CZ8KqHjDOqCi7diU3LbZhIoWIRhY/N250hMqfpVXF6ZojYkNw+CaXBEe89scF642qFSmV4dHR+35PJwSQIVmwPhyesMdSQIkEKGFoALSEE5EKhAGAJJguWyNmx26TK5omggJ5sB1g0onTsQ99CmYflYopbmsZNHoC1CBQrXa7I6rwBWtv99OnYkVpRdUsBPnxJnFnW1caWdYkyv0QRAFciR0Xw6P0SG7TzlfqCyfKCJUILgpEFwBcCWQmLL4WPOrWGlDedXVmbHt9vS4Mzvpya9z59Z2ypGZsaennekZT261IzFqj4+49GFIrGcsQsUaWizDRc0iXZEBqp5CWgIqJLhTcmLIqcOLLxndfItybDhZXa8kh1kDYEcCRAFayEEhBlCicCdLlkDLYp/jQJnXOWYVZZrntDSnxdjBcvoSVB5jqPQo0NnTXj/eoNLrd2gtBLlYEbInVEJc1GnDHlA9eCqvFGPTE8mpSW+5RHlEtObO6O+kNBs9LarXVJjkD5sK4AxAAvyVpDOSsms6xtjDhZdMRtNiyB5JWrUElxQxFGYKVOrV9Zu91T4plcHYnStZ9YwjnZeieqBUcxkDKmVv13W24s+AhMV48G+DBJcvV/Zmiow6BoE4h9poQSXr2XoUIwesRUBvNE4Da1yn0A7kSme9rDry4qL3ljRioV0xKOJIp+NDQ8nRUdbEJRa1JBJSPG4G3imDS1xd7w8RJNjixx5c6YQKfYQywczr0TSlWmUej8cn/ntYMVRWRJQ2qFBJSnAFJltNz6aqW5zasOQsWCKDkb6NlfXXRYe3diUKU341RAnHTlYibNSZGLLHBnp5KkbLSLNNJA2ovz3QgnE3riziBI4UXSQu2BKBR1yyR/oD2cl4aY1D6YODAkMPlgTiA45gEWhhMrwW7lssR8QVtpzFk4MDZJULzQJirMIxHKBFVl2CyiWoPL6hAqJAeCKWIqqkx1iUPqyZLXUNU8VxYmU9ORbVq5YXK2cpcIV1pVThr+jUTZIaSopcAT+IKBAHDCRCpbZhS2x43F2uWrN5rX/YnsqRrPGUnC/jMLtuFuV1plKskJemmc5HxMwcayMKFCzWcGZybiA4Oowo0SRv9Mu7toArbGpLwAn1jiSEUE8w6t1CmDEbTVJSlsqCKOIqdxEqzkzGYkTmXek0g4qqsCtfAioBBVzpxInIlV4inLA0MwMq+EazerEIFdbVw5MGUcAVR6DqVliqK7jStsjxrBIbVYki74RE9hqCs5IY3R0e2KFWNsnZ1azSoivjjQ7UJrYXp69WKxsoMYxPhbFKX0a43qlPQWZ5fKNkpDfG2tSTHOoAV6/YCTUhBlrEncAMXRgX4AdPxZimKwTyU/H6ak9ygPVk9KRsvnIgNuJWKy7FLENpcsVQa7D97GJ1JD26Ofbm7XIBfwWoWT/fqJxvpJmx7AA5y1rFhPqs7uR5QmU50zUXKoDfazHm40EXyohTQUazLOOjCZXz+PsuByoWOdhV4nSHEac1xRavNGXrodZCwtHuEs5vZKw2i8FocVc0SaJYi1gsi2RmoxmikIakhtX6QGHtOrlS9eSLoVo9UKpwI26mAhtluxyJDDwP7nBw2bSUM5qVQgmrmsTAEclgoOTrjijQFae+99RDntRW1l5SNHMpu0EsdyaDrSebFePqXIQK2GvGBqOBfBeFmWyRsDMes0cjkDURtekxqjpMsoY1Llcs5ohEpFBICgSkYHBRoZBFUSD2liCbpnWVmXxsZCFTxeVgtcpILE5/sSJUTh1EgURPxR2ucy2zDlj3eL5Q4ZiV5g0UI8WZysQ2tb7NmVnrSk77cmti5TVsCTpMpzsDioAr+cldgcIaqsgCwGDrTM/ATXEkJgEV6rZCUHGFTTm1QVG9oCIFAIw6uIJvhBPT1VMhdwo48cQGon3rABWWuAXrHyp6Y3X8OFa5RK4JDD2tl+QSA/LLkUNOQTS2enI25rKUwC0RKtTsC19EULEodRAFsspxLtHzOB9dDMN3obKqLsbxyylCvFJPRQTMxYfiSj3UHufpmegV6ipbcwm9kU66aFDE/aLncT5QEU8uBTSwBERxx1LEFZCDQvpcFNs3I/xGU3d3rpCZmomPT3jLFWcmFzRSv/gsEy/zZY8n3am8J13gUfpFF0RN2sNpwoknUcDAlyrLydL/Y+89mBNXtvXvBkQGgYiSEBI5g7FxGNuTdz77pHtu/le93/9rvM/qJZomeXCYPTP7TtVTKiGECJ7pn1ZW5S87FkzYAxgGhxxMgvU36/m032wySDa+NYmQLaiUy6GpVA0HyB9QvQKKEEvW2MCRiL19PkyWtXQwMEUUSw5C5Zg2vVsqVXwjfEHYSel2ey+mkvGtxlk1WGEtSxbHEIyVLRfWCZbKUQtGW6xN77yz/CmYf7QCKi6RDfBvZR/JVWXwFjJqC5FoiExQ799NXv3Nm7yDTZN1Fjg/5b2SOMHJNyn7HGKbAwbKQa4cgwp3EQZaosVheIX6QtJl8zlFjgpKKp0bfIxCZRZJ+Fjrc+VJvjY364tsfQ7QMkI45qHrdPfXWps2LbG0DxmZAMInVFITJEW2DahES1Mj04wk3c9hqegLjb6Y/qHWwBEwfO7zT4GNSFQO6njQ/muzVA7rWKD+eABfu6HJOUrCdKFonmRoihebSjGzoRTNeQelXxMv3zw0GwnLT5Vb6Uo7U+2w8BAHlZKlQClX7+HZbGc6+fCXwvQi0RkXevN8Zxq3O0m3B2Waw4zbj5VheTSNSoDL4lX8Fvo1QRSIcYItVO0vcCRmNYySt69kvYPL5psjbLGfqLWxTTs9YTqiCD4BTi0WnoJwRAkn4Ezs4FMdvDiEjwHjKVVopIu0hfAQnydleVBCKl5sKOEl+KiRAv5AtsjXt4Qjewdx5kHFy036APjiZa9gdzNlP1JrFvsz/d8DrjbjaHPBmeMe3KwvoYJ9nnfOlHI2raQPC+ccFJCgxNm6EM1lcS+5P7FRWwIqGQ8Pr2jCiqQITij6K34Jp/mCKDBTAJWUe61DJWtfsDL185yzUso6y4OCgaLvK+EtlGCg8FtjW7aXULG+KOH86gxc4d8Ev5sSfjoly5k+UvON6jNWsTbVP7PpkgoN+qNk3FXauShUR/nyoGD3lYr1l1JXybJ7Svrxx0q/zmNVcvpKn+P8x3/mwUGVnKHS9lNP/+6n6fDneayKzuNkuUMl/d9hzh1ApkPSzzc15e2+kmmPDmr/vbCD6+PlDBK+DpjB2rqm9l4Fd4gjqWAERf2+0RpmglHS66e9QarRh8CVbGMAYWXHUo7z+VU7gl3Cpkmy3sKW96GM3WFlnW7O7W3kEav4ytjBlSEcBGb4Kf1Zta8rvILTPaiMS8I/1EKtw/9i+VMVnR5kSuXtrhJ/Knqh/Ki61FP7Bw8q38AHprcz6x28V6rZywRbf2sRL/VFppl355X2ZcRsJ8oDVrIyVFIHT1S2PMyUBrnSMFPsi0K/3LvrXP2lufwp376HVHkjVTgGb5LN+0zrbbb9LuHdiSq18yp036S8axobnGgl3Mvm+e/+xV9xPAr8OJdQsn6Rslc8UkXNHlZz7FkwPjhEv2upcEtHrRxS5Ho4wqEL0LE5focVnHxxhsuz5dlW03uu0LNmF+xJOXNhwYBo0eitTCeaDAw5IXhtxzSVYtnGI7WxZpKFdtrq5ioDCr04S1GbR0tnEWsRM6eRHKyuQOR9I9mAEkkX4lCqMEn6HcTW3aWM5ezrpe6g942Vp7m8HmttHDOMHvsZPvkJ9f2HW6sd1gulAj9WW665E/T49i3Vw8qWlPSm91x1rzfMPzA35YiMsp2ouuwH45BGWJ9Yd5SMRgdyP/5g3d6lJ/PCcpXtT2PNbsbvRmuNYm/MJSlKB1N+qWV9nbqtcIswqDKZRW2XSyZjToOdaRx1DyPt9QYUkcIbUYJytZH1OjG7HakFBmwdn/CWbY2xj4PxxjhqD0StA2X9gVEnPxvMEe4/ppdV8kjjsJ5RVcsXS1wgyc3t45W6nrJFM1RM66CiZiluVUWuGCuUsVWZFJSwJyP2qvd+GOTnfpSyJSUX4ePdKbLSH2KHE8dDqOScGaASK3Z1ljwZKrnKCFCJZ1tZa9C7+r198Wtt/LbQudGhwp0iARJwBYo5N4b7CmjJte4gPpPQkh+CLtngtvfqX42z3zLulVHB3fpV2gnb4Bu1BcVXnN0qyBOhIsxeqjLDEW4HaffuiBmRusi2U5UJDiqccGxDDWIJQ/rlYdKeUbgoT0T5TFDhipZMqSdSbsw9F9WZKM4BlYS1iGOn3BOlLkPFiNtQJCPL7POko+6LlHNY3zhUTjnnOe97MOLylJ/oK4DKKbD5HFDRJ3GFvX6Lsu3xI6Ei8iWuYqG4ve1RsTfP0dKgIkqO2Z/5P/9iXt+kxjNAJdEaGH6PA/LdlZjoAAAQAElEQVTZgHZ0bcdF6hyEJ1zJAcP5bn/y/uPFr38pjSbcN4xH2eMpbkvMp8mmLB4UZUmoxGteptFONHpACEMFO7CZCr05HhruCFCJ2j3DHWSafUCF4zc7nfa5YYwobToWq0SAsCmLhEE4K0VSIYQKa58rEidgCdCCHZWkx3WRVOe4wycArGDhjZK2W+kPeXIloELZzw7NWSGogAEi7WXtabVzBaikqiPomVAxakOsdJXRq+H979WLfyR7H9K9j8Xpb8wSBkbYKbJ5H2/cRu1r0AX2Cuii+kvGnZXZeQ3A0EThwlik+/Xe+9bNP0vjj5n2ndG4TNcucs7VUajIyAqlgWkdJKFIZQxx6IjyEawJHpb6d+7gNSgiEp6INwCSnL3I1GbczV7HyZaxkutQepjZ5QYtKWtEPW/k8XDw8AtBhcP44IpI2Fn7gtoq51u4G+CE6Wj1EhKliSgMRbYr0u1oqkHixfSRUHnuWvk5ofJM8OgXOUga/fzPMW75zwWVA4H0nUD9lravFpPThWOFusrR2lSSH5k2f1BMIOJT1WV7BXThVF2WqHrtV+9gqaSW54BKZrqIeh1AJdlowUxRRY4HLRUua4eZQtlcTgNmSnB1c/9v/w41zldsl4Tth0sVWm3XhSb0vhIqLBgrMadpuD6UbI9jzX7U6xn+AFtIOO3cYBHzJ8IdxPxRqjuPOi0o0ehE674aC8Y2iho3uTMhmO0GtlSYK7sWhuKKLs1S4R1whdGiD4jUy1bUe6Vdr3W+YsOFOru4XrbdDUtWFVRq3WvD6jFUdrjyaEvFP+td/9K9+QVcSfU/ZoY/Zvo/QDpUQBRK6GqQsaIExnBnSW5gzD3Bir232MaKM3BF1Jf22a+Ni9+T/k2ifJaXmWCH3V8nQCWW65e9K3v6PuuvqN9wwgM8OIDEsXEebalwok94DEfTc7a0DKEDKvna/DNBhZ1gsFQAFbLesj5+53DKZPXSqF/zLxADV3I9zg0LV/M/kfvrpYB3io5BRX2dZyYgfA1QeZ7761lQia4r58NhX0+FikJLmPQlU3s5rYuVCgb91z+U7u5j01l6Mk8MJ4BKrEk2CnvAQJcHoMIz4XFNrJhQc3X1/r/+ByoORso6Ia7I6kVVdLIDFbZXks020JLpzeLBkKGSaI14B0p1z8AVQCXdW4i6D6ikmr1IrclE4f5j7Nzjh/tdvNj9FZaaSmOFRxEfhsraUmEbhbcsrpZX7q+dQsjQ5ybtJOp0WSxlPZ/6UToNytIu28QVgERkmpn6xBncngIVukFe6xhUQJTrX//X7FwUuqv85BdwJdUlYyXfe5frvuXSk5h7lWm/Lg5+ZAMFOGGu6C0j1Th6KNu5j3tXIj8WiQ4MlO7yr5Xpj7BXIuUpoKIqH5X0mhVKBlvPUImbQ0oILvZTjSVwYvVucUTEPJHyeTRyojRS2VbK68VE4S03vcdpeJgoDGCdhMcL3Wh5iMsmnIXIt4UJugTQU6GyEXW/TzvJQiBSds5eRvL9aLYWy9VFxhF5L1pZJuxLo3YXr98n7Lfx+ptYeSGKU5F2RKKmZ848Fir62v2cbK4nRCz+MB37DLHkRvuWyo658w1B5SBgjFz1c0BlK81UImS7zzGJ+0hyYi57nPZdYTo/jtW+hONV+DoyyIE1Duu+e/6qd//Rur0Tg2F8MIZgpkDl4Yxxgq3qyEKSERTAicsVlaibi9+COq/u7MUSO8rZpVxe+n7EaSoJWBgNP9psQYn+1OiORdCPdUbR9lAp0p4mBsvk8EyANH5X4LP5MGICjqOkm62dScY7zSI5fZmhonNFGS5bONHowkRhS0XXpoS+WE5U7RBRprVpT1ksSW+bBbSQhVSxkn4j2/REPrcFlVNiKqdAJVYduLM3i4//ap5/SHTf58Y/Zwc/gis6VECU0vjHXOc9jBUQhWwUiZZjUIGNAqiYjZtMfSVyI5EZWKMPwfU/KoO34ApME6DlGFSAE96JFSeRTDdRGFWGr0v9u2h1QhnMMQ9H8s4ZT4LZcXPplSLqWR7MRYMvi0NAhV1kkdKAWJJrFzo39viNyAafHSpZF1AR5kQUpqJ0Ha28AlSSzru0cxmvLhNFmEoNlf35BKjsL6Avu3D/wVDZd3w9cPIxS+X0K3xDUPlMlsqJUKEIirQJ9C5eeqOwU6ASto/k68gQeqbVwbZ79wEyr28AlWh3EOvBSuhk+9Ncq7+Jo0icgCsUaGkEIUVkO16lqBw4DzGrqJ+xhAeXT7LY8RVyZU2UqBviJOa3IRAFXIm0BjpRGCrRziw/v4p2JgwVIooTGHaD5hPvjZj8JFTYeaUAsxVQOQEqylJhYwVc4QvqUFEmi5xEWTAattkKhFXcgsop2V+nQCVZ6FJBpXt2efeP2Zt/tzqvMs0LLOKF7huz81q1tWdLBVzhWD2j5RhUjMoZFHdWHMkX5blItCPWrDH/xZn+lG5cqZmPrB1LhYkCFVrXwfLnQmMl0m2RamGBTjln8dqMxyGz/bEDlZ195gqfmTT7GWvE+6LQEaV+oXufb9/i+4pCj6Gy9mI9kiVanj4YADYki02RrqXdhaDeMC6AETcdQkvKhlESyQaJYi9avY7btxH3IxSt34nSFb/2aVA5Zd08xYL5GqDy2M/w2T/hlybKs6Hy6UD9trNr09dLD9qHR2ST47A0knOuZI3kPleOQYVr6UO3Vc1mN1S23T3/9R/j979kLlbRyZSI0h3Eg35uMONoChsrjBbsp7w292LZb0oP04cTwAAVUaqEcel1EIVBonxf1F5lTRRqAwMCBe0YXtLqRLuj1HgR641FG4QbK4lglJlfxwZzY7iIdQYi6ArHB10yPk0j1qdMngoVGWk/nP11GlT08AygwnTZgoqMpgizSA/LxZhbL/a7Mbv2WaCSKQ2MXEvE3Wiq6Uzez9/+R3DxC9ZZHSohWpr3gAqUbb9jtByDCm69U/aKB3NB+fa96d8KcyxSnaSzap79Bh2DClgSLYzz7qU7/FAdvKZO+IYXKwwztYXpXlAD41yHwbBjpuzEUXTDhY/Hc93k2v2VdOdW70ZUZiLfT3vn1Dn/M0MlTB2mIfYOdyQT5pkoX4raW+F8IKhUX+WqnZTlU1VasvLkmMpDAW1tYvG3CJXnA+nbhcoDXq8/DCo8XiVsx8IJqTylcV17/xSoyPAGVvlCf7j85e/Tj78BKmJEvi9wJdObpLtjUMTsDKFs0GPfV7TW4J5dB8V2CVgCYwXXVyNS2OvFb8f9u1iKKPtQyUyXieEMUMFWSXRnyckKRBGdcXIwAVdAlBh9tgYPCsPOYy0V3Vh5MlRI+eLw+rbc6VMPt22ocDKYTFIoR+xqtuUnPVdCJe2BBO7wTofKA9jQuXIQMOAQRaqzPjl/Uu1sadpb/rq4+xdu4ZONVbZ3l+68MlrUzR6KBa+wTfff5vrv0p3QiEk0X3FfFqNxHXOvoLizJcMGaa6zwb1RW4oMuNgzW3f+8i/FzmsaqmhNk6WzhLUQ1bmoLYR3kZu8L43fi9pcZNoi24mXJ/nGBbdpiRaHwtyNoGyUb8MCgKhLyjqsgi1PtqeYeX4YrcyobNNdCXPIs7+obX7mBRxfugcsVWxF0k7WWdCkL9lX38g6EJ8QyTkQjQLLNWPWgDp4VhfJ+lIE74X/zqjdkX8s3cGfw0hV4+kwgC+yHinjQmuDwz5SdH14cTxWgf81gOTJVHvKh3/smv6FYLPLjE9ZLY+HyuFA/SmtXLa03c4rDLRsD+Dab3EfCkaD50ebfuv+de8f/3B/+ik2GYt+z+j1i8vz1d//kR0Mc61+utlR7i9uBCkqzk6FiihWQveXTAMzgy51EpPYy/udBJWhOLrvix8yVChK3/CNoBPxiSvxTi/R7YvuJDKYm4vrxGAhJqTIiBSfXRjTczxljJfRzgTPJnpz0RzQOCzIdsW60WSo7VlhPPxYDgej5T40UMyw+z2oIHIFHSr8LJkyMp94v4H0FlRyhebszBlNORkspNFOdpmcGJZseIVu7xNQOYaW06ESz/UN6pTVLjRWo9f/4S1/jTbOjeaKJm517oETbAEYCEQBV7KdN4or1OxrzZUdqCi0gCWwVGiQIpZ4a1of/9C6+Gs+uDUKs3hxDqgkghtz9lE0V9S2Mu4BIdyumLvi4yFrqwmmBhXyKa3rTmgEfa4TNnmkFKw+YJauLc3WK3CFifI1QIWKMc0uPgZBxX8HJezX8fo96J4qjECUSLzEPrHnQ+Wl1u5vhSgvBoOvACoPwOaLQ0UhRB/yeApU6C6e1vSGEbQGHz52/va32ocPxnQCqEQ73dLFavHbX2J+wDhh3xfbKPtQUXUqqmYl12yrhxx90aHCBSu8H2+2YakIl6L0O1ARvWl+fpWZXIjZEopNSNmLV4AKPxvrTuP9eSQYRVtjoFE06OucCBVO+VXdiNkDxm2JQxtFgwqlCEuWrDtGH4GKbJXPY114aJjyjG2gUipHa3XDdsxO94lQ2efKMagY6XYiS/NCqMe72Q/mP07e/KvYfZX0r7Kd20z7LunfZLr3WPrj/qvUujSSucJQYa5wf2KlDVdqSx5Nn+Bc29wAD4Pz3wuXv4rWZXX4weq+EamBMDp4FueY3goGCpkm2mwVys09AhWauyUn0lN+V7Ytyx7x7XpACFbtQvs23VjBaoE4HeBLQSX0OeTqUCTbkJxoADDx0jJZuUg4d5DhvI7W72KVK1E8j2b8SLoZT9sQ40TkbOhQM/xvGCqfxSj5DpXPDxXueRz6u3gcFpeUa7N4t9J/tfm+MFNEnYaoz3751f/tt8LdXWI+E71ucjjKzxf26lI4LkfmwzTiI1DRicIPs15L94nBcNGJwmUrHL0Pk4mbrXiry74vQAUS46mYzpNnF9nVdWS1gmJSucub6GQueqPIcJoczUWrb3THkdYAaARXGJOnQsXaTSAOjRUNKhsqaPMIjkIFSueUgcI2yk7zfIZKpFrLtdpPh8oD0qECooArRJRUQGtxpp10zwa3f29c/Gb2X4Moue7rFJbmzh0slYTMClNcUcYKlGxsSaEFnAiH0jeuss2bWPWMXVKif1u9+3ux85qcY8l+vrrCs9HKAkjg8SonQiVe6LLjKyxMKcgOj6UxNR9zV2SglCbcy5IjN18DVKI5j7hCJgjoMooW5pHKlVF/FbPvobR7n3LukgVcxDdS9T8xVF6cKN+h8sdDhSTX9LBEQ83cPQQVruHg+/ry4mz+62/eL7/kbm5SZwtApXC2jHV7SdxKN7ytDsRHoMKOL1GskB9MJivDOuH3ZYeYDhXl/mKoGF6LPGBuk/K+ZDTFaHcJKpNZdH4Wmy5AkdjVFRRnzZdiNAVRYuN5tDuK9cacIRZvtcEVYPJEqIQF9tsJxGRb6NGU9Q55ybQJN0ehkjX1ehfmyr6lwq2LM34g27SkPaDFG7/WU4ofsEI+WRSpQwVrXyTd4EUw9CPJSe/B+H5+85s7epNvLPPBLVZ8OuwSAwAAEABJREFUmCMAiYrhgyjYUfYKQMKmiSIKKym7TLKM2oXZem227oQ1FfGW6d8CNpHyHHZMSuaPiaLe6368xZXt+PzG/VUacQIxcUX2DE5WZ/nGRbK+jFgTqmMvEUtComxDRU4F9o2cBz2HKPzytNUGWvBzUUsYOX9lCyoSJywOmyeyVYinvMTAcnxy+ybt3kb99yTnnai9pkyHTJ+vE83WIpnqkcldz+q2e8oC/eKAeT481PbPBJVTQPIcqJxUCHkCVPSX8+R5tdDrbVR2h/LKmLaQ1Yj+7R0sFfuHHzJXV+nlGYyVaKcLYZmGGCS6Drq/dIEouWZbZT+zHZMO2pwVFlbXr0P3ejIxcMJEIffXdCJm09jqPHlzBdolLy4Sq4vkpUxOm87i07noh6nPlAAWdBVUDNlnTDWD2QragyWyOhJbBZXNPC6JgdAJptWshLlhGlRUuJ56t+j9XWDlrO0SvogqilSk4feN12zqBvYHQEXVhOtQEelGutwf3/wVAlRgbeS6b5koKlDPmOEj3PqeKHIcKikcsS9xKVwQ/IhXl2BVoX0PosCgAVQi1uyxUFE5YFRyb/ZNbwWRB6w4JmlQYX1tUAkHEqdbUXI/zqPlC+G+Ft7bmPse4u6ckVRNJCpc+/LngMpLGSX7XPkOlT8GKuFILmmvMFS43v5YdlYYTpdQ4Zv6wYePw48/VN+/T5yf5y9X8dlUtNqwVITb0KHCgxo/CRX2fSVtT3e+4WDKb+2YKWy7UHcWp8lQAU7YUkn1h8b5UgBvF8vE9aV5ewuolN69TV9fmdc32dUliAKu6FAhokioRLc7jO2Wrcj0MN1SCaMp6xwwFQjRAyrs/toUPMqekmE3MD2LbB2SUVBRJSzqtNDtZpWpEPIYVB7r8joGFZFx44UgUewIrIPhIkstF9OFVjzrxfLt5vD+7N3/BGe/cg8rtlEgHvUIG4VNFkAF2iGKHlzh+V3qiMgMY+UlDJdoZRmtLDjPGDuPhUrcGsq2K710fQEDhWaxpLuGNeUgStj6pTwFWmh2Vnn2paAS0cTHE5k6ZGSaNHwlV4dE3oHwmyetftR+Zbh3seZ7yKhfgzf4XiLVOT6/6+ldSU5ZlF8QKi/o6foOlS8FlYOVjxRi2QPJFk64aYrbSLQ7MFNa96+t16/ZUhGDPqBi9PqiVo/5wWOhgreAmcJ20hZXnAbMFE5iVmYKQ4Wzv9j9xWYKttHFNH6+SNxcpO+uWu8/DPEhf/rRfvO6/PouvpiBfJHRMNrrxfr0aYU0U+jTgijHobLx+5F7kDo87iz6XBWvF9uHvq9tqHB6Mbds2U0+XhsrKjajimBCn1jNfjpUTip+1KGSdhLFVtLCnX5DhwqNOySPP811x3Lcu/zb8O5/C50POlHYG8ZoAVHSTbJXFDz2oQLkRGsXEE4TuXGyfllov4lVz5koojTD9rFQEdl2sjzm/GPKH8v3VDKx4oqwxtTM0RzupBR/dVAxXeIKTz4uXYjqlXDfRL13Wf9N3L7BFyFj6zhUnjxxS1+UjxVLvhRUPitRvkPlj3N/HWnzdRJU6nZxOpv89HNwd19++7by7h0Rpd0KLZW6LRqbOMrplgqgooY8Kq6IcpWgInGid2oJoSKzv3T3V2Q+AVeSr1alH97e/Pf/QOf/9Z+N9++SywVkTCc7UCGirAP1R6ECi0RmKGCroKJ6dvG6z30h9dAIO8R0qDBXIPKAqcD+trFCqcnY2YOKKJZK3T62RBeKGaSDSL7rjd5yC8WtYcDa/MedQZBGccA74cHyRpnKAIspTBOxM49dusKwE0k32CGGbarYwUMRr5fc2fnt7+35T6ZLE7fy7mW2cZ3zbmjUo3stB0ReZbxriPdT7iVFStaFLFIrqXPqD58ZJktn2eAmUp0bFRLH5/VP/oC/i8sbQZScvYSM4ogaAGcHMXNsFCaR3JAzzUQRCFlU+++T9QuBg8VptHQGC4mLH3lBD2sYHz0RcrehZNqi+DzPeuGWkYkMyOGAzdD6XSSEQqjIZ7OHxS1ejHI/WRslnFdQzH4jKrcw5igihRuCDP5SriZP/uEc0gkTJ48txGr0yImL9RMw8yh4HJvw+ESqPYyNPxAYx7Qz+VjRJQyzPwsnIVQiWUufKv98qGz1+Fr7nXbQEqvjVt0O6zkct3F94/36U/722nv7Nn92tl6gSaLqiJqb8FqRegP7MafJXAln0ctrbpixVrzm5v2Oenf9KTxMuz7PXNlAhetLPC/i+xHiWRDrdpLDgZj1klfz3NVZ72+//Pd//n//9o///vk//+fiw4/J1Sy6GEanfTHuxvrtaK9ltINYy2eohCnF9TBcFF2XrXBgiVsXU3/+cggVthg2hYpUnFiLOI46TqWLtZoohcF57kzM3SQpSp8tcEUkR1lU62KSHCbNL9nhisLYJ6ByEC0KKqxwcvAJUMHimCn1IBW9V7ARKRdcwQnN8Yez+393hx/StSVDJQMbpXHDONGhwlwBVDSunAQVbhm5Xzy/FUHJtHCa1VwlSpNIHkf6ItcjlmQHItUFV0RW1j+a44g1w+fEDugSLc2/GahkpPBnMlvCWkarl4CK4bxNOiujtoQZGjHbO1DBn+z5UDnWtPh0Qvwx9sqfFSoH6fKyUGGufD6o7HOFtA2V9us3tY/vAJXK9XV6Oo20O8ILGzsyVJLNdlQ2pcf+KVBJ1Bsq9Wv/hKTtYU2nHvgqO8t2SK4rGg0dKpGzYep6wVABUaAf/vWflz/8nHt1nrqcJ5eT2GwQH3Yj3SAaNCEYVYBThPq+bEogY/yQOjk+AirCttVBOl7FUyFRsAVOuAe+SgDTYy0KKjEcX8OGcbIV0pehmheASqjS8JNQwaoEu4QXx/Ui1VDrJmNGGI1EYdBb/jq6/GuxdZt2LkCRbPNmx0bBvunfFlv3KoAvPWArJZEdJspn6daNqIUtJnlmF3ez32nqte/yytkLLN9yvwuckKWS64lMn6Ai7RVqD1NZME7oSHkBATDfClR4fWdg4DuCmoY1T9cu4vV7VrTyivIRsp0QKrq1kaorPRYqj0XFsRM+CYPvUPmkthKLXxQqL+v+2ofKAa7oUGl44x9/Mu9uMtcra7WKD4cRvyVcqhohqEiQGK4PG0X3gD0MFRCFa+l3T5DpAzzHZQsqbFU4ZLIkut14h4iSmYzBjPTFDFxxfnn3/n/+5+1//dfl//6H8/Y2djaKzAewVCKTHqACYyXeaSW67WTQTvhhSrFqWMkdxsgVxvO7ToAKj/MiYwV0qdcBGO6wooiiovQqvZhxooasMFcMaawwe5QzbWOvcDD/paASszZcOQaVsLpCjpzKVQbYioTNkw159SR7JRVEMtTqsdBYtc//Uh++100T3UZJ2atk/YIDLesQi9bV+AhUGCf8+Y9BBQYKxeczLWnN4MxROKcEdok0VpKled69hKUCikiX15zyymTLy28FKiAKeaJkBYzIdEi5UbQwBUu4iz410q9Mqd3Ai0JF9zt9JvfXi3DlO1S+cqioOpV9qBhBa/LTzzBTUpfnhfNz0emIRhNQId8XoILVH1YFc0XWqZwClbTrky2yTj/bgookjd6yRaYUS2Oi4ZHzyvfZCWb0usAGFF9NKx/vZj/++Oqf/2z99N66PmeoiHFXDNui44t2M+J7wnPjzSDMJ3a9ZDOAuAl/WL3Pw4ZPgEp4HCyRUInChOKOkGaJicKZxHrLFjW5Sx/eZUhjhfGjIvabIA1HXxgquDdvjt/pUDkYTTlIF+X+SlTGULI60aGiL45snUhyuDx3HcKKybDBEXkaAENcIeX73uj96Ppvlc5tsr6Eso1LKOOuYMGk7HM6uFUUuTFWRKYHSyLTuRa1SbRKYuDpRAkDJ7Kqkb1heecsNFAkUeTg+h4PseeYSgLwKEwgXFyGVSiOQsaK9IOBLiCKUTmnLsX5TjzrQ0beJUmU7uuxUCk0zvHZng+VZNZOZOrsjNJIYxu5VrLQJR7XLjgfL1JZCWsp0rb0mLki7TA2HobKscX9+WB4wmufAJg/K1R0kOwj5PlQOQUkLwuVdWlkjYrvJFSK0xksFRAFxkp+MosGbeF4kBF0KHIup8eDIimvrXASdpOse8q7pZfuM1R2Diqk8ZYnTnJdvVatwm4rh8otWy3YK5G2n52OzLsVEJK+OcvenicuyXAx5kPYKJFRV/RbOEe0mjG/GW16HKJXNgpdlmtx5MWBHBnAt6G4AyjW9EaTPAtSoSVes1OtFgdXcr0ej7VPUkPo8n5RvdrHDs4J61eyhXihbGyPHN4YKCpf+WWhAqJg+0CgnhxcEioQh+uxVrKlsl5hN1Ch2+dsN9+4GFz+3lr+Zvo3oMgWUbahsmlpfBwquo2i7wAnMoIyogZfLDmMiwyUwpAslVQrb6/s7tt4cUrur9wgVpyI/Ag4gcG09n19M1AJc8PCBsOaBSN/f7ZagBMeK4mdRLlDsf2UHcFbyCqWLwKVT1oh+y9/msnyHSrfFlREpUqSrqf6xar//kNytcy9ukr1pe/LCXs76lBJNlqKJdwHjOjySKgI3L/LhGOeOCnK1XDAsHKCEecovgKoCNc1em3rfCGmPTHrAyfgilhQoCU2k2bKoC16AYgCgSiiEWIppqd+SagANnxx6kkDTtTrgIphOyCHEs+CVKKeYI5jDgbl6TTh+1mPtInA79XVq30Ot7Ap89mhsuUiW5spn3R/qWgKowUPc5UBmykiYYdLJHvDMrKHYxrre682eDe4/ke5+zpeXehQids3JJlSHK0tgRPYK+nmjUj1MqWF2b6WOCHxZ9a9XuTjkrO2gBNAhbvZK4Voka4h9oDBTInTRMUetnJQ/JCzv9zJT+wEMypn3wpUohlXlkzSq/hIPGdDRt7e1FFK11+kdB4tX1CJT20ZYejKBpSRTBX6Y6DytCX+CRB6rr56qESPDHx8KahwueIXg0qV+t4Hd/et+9exs1n66oLqHGVPRijht2iNJj9VCBLl++Lu95xS/Cio8IzIqJw9nGwGvPpzwGMrviLzwYygVZhNEt12bNSNT/oUXDmfpseD1KhPNgoTpetziN7wYKaELWc2AyXXUEn5PkCSHfTHP/6QbHhkptTx3as6RRJ1h0WA8WDxOMV29+bXv7z757+C5QXFV8pbNsoxrgA8yqD5o6HCZkq02Nehwvxg7XCFjRUVrs+UeqliR4cK+6ak36kr0h1RHDfnP7fP/7IxU7ahEo7zkgNXjkFlJ3wCljBOaKXeSQCT3VnAM6t5lSxPw+yvTD+MrMiUYmmaLOLVJQVXzDF2vhWohC3FZAP8HaiwaPwXcI5f3pyDKyAKVflUp9HymBtWcluXr9n9xTqYbPZ/FioHi1FAlz8TVNyra4YKjBVuyBjzgwegApZsClYeCRUmSviqmg2uwFjhrN/N+PqaTWxwXHM8MdpBZthPzUcRIGTYhoESafuxbis6lr6vri86RJSIz0RhQ+cAVBKARL3u375yr6vd8+4AABAASURBVC5jdTtaq8ccJyrzu5SUB4zMlFoNFyx1+2/+/s8f/uO/Fu8+ULi+Xt8nyj5XoHTVeQRUwAN579kCVHAXz6g40fHFJ2dqMyhVHXFppGH18u6cih/THsSjcCGRsqMphydBYRFklxejhRmDI2SycOGkHG+FS8WK3YjZhsIlPtNKVSbjq9+d/j12SPaKlaxfcDSFE4tFKkiXxqZ/w9WI2CaLQxwJpzTmOmyg4JPTlVM+O7uYLirKAtzibj3vnFNyVHEkM4kp+4v6ZdkXsIeihalh0VhJmV7cw4IrCmM8Vey+oiFdeR9aFz8eBkbkBIHQ2FIB6QtC5WiR42EJawgzxSivYqWLeGkZKy7C+taUzeWZ+BPzMDFIpGsPBPCjWmKxvvR/sihSx8ATwPAAVPZ9a8+CyleDkOeD5wmBeqAiXqhCTJcwaK8N5jJyZaXHQkVvfb/TSpJSoeQK7r57Xbq5jE+GmbNZrNUiyWoPrPgc3OZmWWrylVFtxCqusHC1reLHkCKFMo8W3uk2dlAUWZGnbRUnyk9VHE2SQRtQiXdaVIDS8kEX7PORdLudDIKE78ebykZxpBqqSAUUUQJUsu12NmgZtsPxJKNa1wMqO6L4fLWKt1j9/vuH//3fxmrFlspBkOwkFrOxEk5e2ZtMHB6pliO1CrbRenULKqqS8RSoYIs1HYsyQ4gBAGGHOh9jucm3CAmME84gSjmKKyp0v+MNw0vwQvCJdjLNsCyf1Aklox3B9MPo8i/V9o1ROcu4V2nnkudCHoQKN1DBQ3CFxjVaQ9Nd5uyF7uwKk4nVu2RanGcljaQ2xVQyHU79ihenRBc5CkzkRrHijPsixyoT8g6VZoCK1bulccJ/JqjgZzfxjeZR6xxQgfA3wh+a/75EFLJdPg0VHSFPJsHzQ/cPx2mea6l841DZ0pOyv2Ja567QKDlElM8Elcb7NyZslPFgByoJ2ZMxjEnUHK2zrwucACpyZw8qskjlFKKwN4wdYvyRwkL3mp3rDUAUCqoHTeCEDJGgmep3sc9HsNwrnGhEcfSyRx0qoTg9oVLFVuV9Ke1AhQMquV7Pvbig7C/bpvfag4pYZwyfDhU6WC2LsiVKRRonvAOVE7nCVoJylNGKvMYJRK1fcBsrDY5YnjrAq8g8OcFSDSyIqkJlk0wcr4uELRKuyPiJYi+Wb4t0M+zjkg2YJWrFFwkPH6C3/Lk1/yVTJ28Y+BF3zqGw+FGDChc/giixXBcfGAYKfWtYJ9Io4fCJIgrMtYwcWS9Tvzrk9ZLFj8QVmUycsGYUqDe7NAjLHJM3DIApzURpIax5yqWOlkZ1KjuG/Xmgwk3yQY54vgl2kk1WWZLqr0T1mnpr5vocwBd8G3EEKk/u9fIAYJ55kZeByj5Ovlm0PL9Ni15Uz1bLS7m/ToFK++cfgBMdKpyYy6EOauUrzRSGCu2vEaJ8WTtcgf2h92t5mCts1iio4PrASbrdpRg+oNL0Yn5TNFzsJNotyu+SR3QbhRJ/t6WDJFqTkhlfvC9KNHhxhyi7UKlWreGQ4y7pIBAWAFCCOF14hyiPgMpm5Fex1O3n/Ra99Y7763SoYOVVmVTU8kSaKUprn1XAa6JukQAqpHXNCjvBsMMOMZHyiCtp2uEhvjQjK9/WzZSwET2QEG9UO6/7F3+lchZ3dQwq1KO+SGZKpjzJ1uf8fVU+MV+NL4gtvlrJv1SBeqqlz3YpXp2naAqgwiCJFgHODkwWCt2DKLBaKpSKRk3GzJEAoqA/EVRwKYYKmSb4cfDtANHyWaT1Id77Ke1cPBYqkSP1K8fW9BfM1PosMZU/BVSOxVqeBhXmCtsr7A3bcohJU+YzQSU1n3wSKrziK6joAZIdhIATek3MA0Rhs4YqWrT5LoAKd4Qks8N1QBTeGoFP+xIwwInyep0CFYrJO9ScRlglUbRoRlZ5lys6VPLdLr+cXuWQ0cMOMVUwz+X0O0R5FFSK7W4WtmBZVtRz8KAxfLPpubKNlp1CSN7Zyie2tlrls9USdpxc2xw0QhE2h6QFtnroXg1ckRlfvi6eD0/7kgTsVVPzfWnEb9xLFAbB9MNw9VvWW0bLw4Qzg/AWucrICq6pr7DsMWw582x5uJXfpUAlWcU/BZks6YABI+0YIHOcqS0YKlykQgUrhQHsHm53L8rzaI1C9NHSWSQ3pHO4DYzEIWw16Fig/kSoQNzpmaESz/oA8x8JFXZdhgtl1sZ7xfPtVLFndH9O9H+12nc0ClM6NsOsvxMC+M8xLJ4JBv21B02W/2tQeamGkoolOyWQcasOgQqAhMiVICbHC0KFOCG7BQc/fkhMR5FBNzkbh9lftktRehno5jN5uQ/jK9psR65nVIDhEL2K0kf3hoPtEEWN8BJWRRTLcccr9oYqLiKTgx3DdVkp3+eHCY0ou1CR4XQCQK3Gzq59UQ2jskg0qHBWMbawIYAfqmKRQApfBRpVqvtNWYgrsvfXwQC+Cs6HbfDXUgfDNi0KKjokjkFFEYUdRButfV87wZUNFVIe9ycmriTcU6BCXq+MzwN9YWFQBrB0qelQiWY7clZxYLrLYPljdXBn1CdJd453yZQGprcCVLjHMN6aZuhux1FCo0f2ZaH1mi0h2WKAfWJgSTm44Q5gbJfEZF8W2D00FSY/TFYWIApZKpmhyI3/L0CF59vjFgFcEc338d4v2calyPa+IahEn5eszNpKLvgOlT2oME5Cukg2gCvMCUWOPwYqWM0PQmVnmqQ+/kusRz3mmu2s19rBxgNQCSMxpSrexeqPwJWweYyECiVorUGSbDbx8CGoMFE+CZViabfTlxSIAplBO9NoKqKEaXLkLiOo7Ax83Mkw3nlKz/jSuaJ3ankiVFR/32NQ0dEC2wImS3N4T2iBgZINwsX9FKikm1i2sHjh/ExllLRouC+uswMV4gpHRLKtev+uNrxPOXNwK1noZp1ltDgkYyVH03NxZ71lqVByF71QzwELYzbrcAsHVNgJxl2/wBWZUjw2rDkn2lLf+2w3bg4ThVEsO0yYk9CO+RNBJZ5wICNJYuebkQni2RbnOsfzgfxTag0oPydUXiot+JlQOfAZvnqcnNLu3shVlZ7m/tqXMk2YDcpq+dxQSbQ71CvF9aj4XIOKSv2S7eI3UOFguwrRV/rjvN8BV/aTiR+ACoVn7IbZ6ScbfjiJUkGlVofRQFWKjpukDvx17EN6fF4nCvusdKhwirC+D5ZQnSN3CN62VECUrOcrwOitwIAi4tB20pfyfYXOrgctFR0qolDhPwqNU3ssVA4TZRsqnFjMkZVK+7I5eWPas1xtwiZLWDN/AlT4TEkgGWtJN3EFXGcfKiEJcm2Knxew+gciVgdCcu45DUEhk6IHPpGdpEEl75yFNJL+LuUHwzZVmVTbN/KaPdlKskN19dw7UsZUuJGJKM2ilUW2eUVDujLdKO7W/89AJZb2wZWwRULC/kxQeYAuLx8Xeb7+FFB5qXkqO1ARWSxbZLIkSjaLIPEHQMVtHIQKLBV+7Q5UOGLPGV8ib4XZXEfqY45BpTQYgysht/agAqIoqPD+c6ACgR/7UCl1+7BRuPHXhijF0g5U9qP0jBYOtzxsqWzosgWV8oAi6plmY3TP+/rY4Ex9krWnqeqIx3YpWhywS0odKez06IL5Fm7/g+mHRv8WRgbWVgq5yxxirEdYEFOFJoTVjQbZhiFc6WbZK8JniXSDhUUWyyutsOlGbN2Jcl+wVHKVkVmbAEg0E0wShRqQcBFMvoUPWe1ccQZzeDDrqwxmHOcctmixTzF5sArEkiOEY+VlvHqRsc+ESd3vKfescZUNbqmMvzTjAkkAJpbrr8eRUQmkDsI1bEgMjH2tJ24xV4LwB8y3Te8cBhk3ddbLGNdDhTcV8gyVR7u5toLq2lOcCM41RlkPSuSaNLtTcwE9rKct03rp4pdnxidx8m3qsaR5EDaHoaKHWDhunyrZ6bLDixGtRGaYgrw1Qni9VB1UrFTXlaiShVFs91vv31E/4G4HSrU6EdmSKwmo8ORdCQ9Vd6IH3hknmUYA64R7EnPgnToQm2X1RlufYd3Bl7r8yhaN2Ob9FoCR8ppclqikP8QJXGLCrTB16edvubmU50rmEKudTZhE5oBRbrFZzDUDysUqWIm6o+wYVaKoJg0rY5EDXSrcxfjnSBiHwZj0RqUSK8vs4bUiFmkzzgvSoQJy8PBHhgpYwlI4OUaUHaiItAcDpXv2E272YVuky8Ok1adJ6UyIVCOSdHn9orUv39hay45BBQbN+p4d+0mryzlRp0AFRFFQYeAxV1g4QmihIZVeKbgIn8o08ZBmijBRpLiOEkQxKucc/xc5/DIzUVkY9kXKuwZaUuUFWTO5/p8AKluAWROFxYM7qeroM0NF58qXJ8d3qLwEVFQVC6WElW1epsGPPxIqOlE4fMI4sToD1Y04dGRJ/MQrDrjCb3oUKrAD8gWs5mQfVKr7UFGrP8StuiiqsQ2bgyefDhU5oN5Kux4RRc5h1AcM70LFtB6ACh9XvsrQe1kuQ5FahYocZW3KJ6ACfgAebJfoE4X3w++HoLJRubU6f/tvnAkGosRkXESkvK3uLKkabBTyq+RccIUdMhIq7kHBKGGKCPa3SMyky/1jnU6OQQXWCb4g5TorlmR9RRp+Kqyw4WcL0p+WH/Jc+lhxYlidiBmwS42HCjNU4s4qWlvm+m8SwQ1FWfJ9ds39SaCSsZXrDH8y6h6mpQg/jJBn1qYornzV+tJg+OagEop5IF1h7OzSofIAUZ4JFd1G4cb1MEf0IkedN5TQJeFH5lTZfsBS4dWc3EpyoX8YKpQQvIaKDg91JjPjcZaKtJPMoK1mqHBbyQNQkROCPwkVFQljtIhCgSgiocIl9J+ASqY+AQawVURR/i6lU6CCl9v9V6OrX7P2FGuotFF8jqNsSiDlOiX7dtR4wWK0HINKiBP2g6VcrqnE4psstA9y5RhU+BsxVJSxwl+W+8pwIwBlk4l8G1AJZ9HnhyLbF1lP5PBh2pIrQ0opLs2AE8oBK89FZVaa/lAavBXZ7rcOFf24ThQ8xF8N+mOg8m1w5UuD4RuFCpMDC5biyh8DFR0eMFBChJilTXREGivRdZE8PgzeAvbK7mfQoMKB8TALq1I96NHah4pOhTBSIs9/GlRANSKKDJxw1ASGC7iyM/qXtvniw1DR077ZFUZ/o3LZqFTirp1qNmJ2DVwhw2UHKgAALa9pD1DJOTPFEiXdTHkAKluBetzap5tW42x08XOzfxPPB+tQPNGFQu5xh1clFodV2GpJWT6WxUimjq1q+0GdP5goaz+Y2j/qLku4IEqhPt2BCtslnETARphulyjSqO+bLM2pL4tF5fFsKoVt+dOtDVQqC4mThSiMrfnPleVvxeFbYYZ+szU8Wjvi4/FCWxlh21zxpPhNN1DJuWciHXai/BxQYWnMCHmPPw0bKHvWzIEV9msHwP9hqOyy4dA5qnvxA7yY1F0fAAAQAElEQVR5MUuF047lvXCq4ibLDhkEhYquU6BCZKo4IIEZdP23bxgqNBdLjreK2i61esSqqiUQAxVcg8Kerv2qRo7J8/ArNlCwVZYK+etgvsiyQQ53cz25ggov9wfiIqUyxAGVHWzsQ+UUcS6ZKFrJRuj1otAOpKcXywHybJ2QePX/lKWiiKLSJRK1WrxaXfzwYf7xPRsrDJXNRGEoVR3tQOUYTk6HSro85JJ4qDd7O1p+zFUGDBVa1rn+cRsqvIMFK1lsgitxswHciXSNSyJ2oLLxg2mD7k+Fyto6AV2qnSvYUhxW0btY8j52yGKTU7moNj6zthvCWS9tSlMujMmCKc2Ak0j1rD79KT/+KGpy4mRp/DBU1mgJlL4eqChLhZ2TCiqH/GPfofIdKs+FCq9ruBEGVMAGFbd4PlS4lD3mNBKerxKIOXwCnOz7ux6ACr8RdlJ1T+RLYQaanJwocsWi14JBwMm7tI7vmRH7UFHn7OhRRIGYKOmmn2u12S4JLZVnQGU/DS+Mr1SryXr9+vffzn78qLu/tqCSqU9oSU26zuAWK6xiyT5OPgEVLbE4TB2Wq6Qw6plitz9/Z7cuCDOymJGKHw9BRTb5IJAAKkBLiBN55GUtFWWUUEtE7ijDPXdlxT62HF6iH0EaTGHqc6YLrad4UUwFUInLHi359j2IQi33SwujdmH6t3J+F4yVPqcvH4MKY+MQWr4kVJSnS4lmD5/sxfoOlS+uU71YT33ty0JFd4WxNaAC+Ce6v45BhXxfXtifmMbuVqjnStZrcaIwtJ7Ce6D5yg5UdGOFXG2cD1Yoi2wh7zQhXtC5cET3Uz0AlYPFjI+FClhSHU+IKKWyMlB2CyGfBBV+lg+GkZVq1ahU+nevnMVsByobrgAk5PlZQ+UBnJwOlVRpIHtB0qIfxzIdt0Ws6rRXndn7XG1CZko2OAYVdnbRyph3gRblBNOhQoF6mVusuoqdDhVYY1CIlkyTXWFhnWamyZhhnNAJ+PDSYMIFKYyhQyUHK6QfK04S5Xnj7DdABcaKKM+TzhWgUmzdyxnDn4aK8nrpXJFqSnFHzj8aKgySba9X7XRgfIfKF9c3CRVTSkYvTkHLKVDh2YgpWU4fdzxSzWVjRe9mf9ADpkOFPxK/Fz4h3ovsFZOIkqm5hUZAHjBZhIhlnRKuKoe5cgpUHkUUaHB3f/nrbxShKZWVmfJMqDBF9GfDDONqNWXb0XrVcOp69tcWVCjfCffmcdvyz/PunOszTvFx7arcj1rdeHmSsc9ADuqwkq4BWdzrHlsRr+XLvcHsTdC/TuSavHKxy2sHMEp8y8yLmohXVQt9HtDCwkMj5/EcQ/04wGPak4IzJbAV2ipokSp14oVgbQeQeOQUZ5ThzKTVTVuypCbVwM8SSVKVX4iTdA+K5fqJwogK7PP9fHDrLX5N2atYeWEUZsnSWaQ8j1XPMt61yA0YKuwE27Qa25Fyx0kvnJIezA8ddPgWVjfrLEQyHHR2DCohGNKkBxxcR2yUOo3qklveYRvlW6GFkdpIP/7ZCye/NEWeyZ6j57xQ8eMxqDxQ/Ij7Yl76w/Wd17gjUAnD76U61nqGSrzToQm+jivqtn97Z83mjAdVKRn2oNwuftQVXXcdVq/iYknQhckHeyXTaOaagd4oZV+q9pB2ypSIFanXk83mTs/Hg7Pld8eiaFYIzkm7YKRd6Q/9s3McTNSdLd5wr0mzQKEdLo3UWnXRw3zx6O8v/1IhUfIlRe6EXU86drRSjtdr2IqSFYpxwtfnTiqwVKqdq8dCRbWPJAum3E/bk6yzTNcXO1BRY1QiSazRdqN9MZy/LdR6jA1OADsIFbZgQrTksYy6IlHj6R26aILhyVAhOOEEBonsp0tbXCQfACfcCVh24Le5RT/XjYdQkWMfARUR9w17WZt8LMBAsaaiSAJUYub0Aagc5ooGFZ0rfwBUdK6ofWaJjpNviCjfofKngUoYKJYLPbuqwmqJ41BhewI2xEGoVM6WbIuoinpuVEwjTw4R5QGocIgeSy3eywzaPP79RKiEKVhyytYxqBzjCoOE606wBc/4suAKjhBRCtaOhUTNvqwSBf8fCZWtv44MboUmWr0GgSIgylGoqEI/u//qOZYKiJL3FoBKsjo7CBUIROGdlBkM5vfB4HKHKPtQUWiBOQKu8ITBHR20YI5CRWKJRqyvuQJjJVFspUq9WH7TdARazzmm5AIj04SoA1i6LZKDQueD1b2PVmTH+9IMFCGW0LSu8cNQOcCVbagornxuqOwHUVTshImyE0H5JojyAFQ+u740Hv58UBGybT4XSGL5NmS8XfeG7UOFPVRbUGl4wm2ke32I8UBs4DSwuss7j4VKmJ9mls1mh1ts0YL+ICF0qEBR234YKge5omY7Ygc2CjcnDnHC2+34vLoObKnnQkUWfrKlokDyWSwVDkhwi3sQBVxJVKbHLBUWl2GLeE0Y+OPPRmdvivX+J6FCkgYKoJIsBDvuL4bKjgVzDCoxWDw5j3BCBZVN4CRptbENJ4mxjSIbkVFVTbyuQwVESZQmpf6PqcadAGCsMaDCRIEMi7jySajsomUPKmGR/2eGit7+i4myzvKydX/XN6djUHnxOv/vUPljoEI1K3JFA1TSQTtZ23DloKWyAxWaTm874ArERg+BYQ8q+0T5BFSyxawbkL2CdbxYStou0HIKVHg15+bED0OFz9+/DucC8PtuaubN4n4chQ7iHLNIr30SVNjlCJuMokfSMiMzpWDGqpWXhArn2vK4X66UxKsK3hmIQqovdqACfjBLOLLC3T5kE/W6iBaxivWmt53xTbroi3h5Pcb8IGBqDA/mCs0fXA+yPahjUOEgCoSdOK5ToJA4MQY4ide5NjOs/Je5ADxJjMZS5bvFzutS7228PBK5drQwplp66fiiIhXJFR4BGUIlP4wWWdQ9bAcqG2lxFJ0rOlS4pEaYLaPcz9hzkQ7TE14EKooo6zr5w4vmw4WNL7tAq0s9wT313VJ5DlpOD8jH8lUoSr3uy58JKpH1QOIwsbjuJJsBoKJyjg/GVHCm9/o+O50Y7Ta4QsNUQBTYKw0vRIWMpnBretVQUknU7OS69aSo1vlNebSX8puJnJWqexSoL1R4HWcfVGgrrOPkOzYHiwPmPE9lP1iyY2dw1D1MJyuWcH3o4Nhgfl9Z6rg9QWt73oleVM89hh8BFbMsy0uLJMWStbaaSz4WKmoGV7IyzDkzvMRsLLA9BhVFEeX7CrtIyVaSAAngYQfz6cV7p7Xgh0e4UlNc4QgKh1IeCxUOqIAlsE5CnHBYRXN5MVc40ywcTFmd1oZvGBUxa0Cc0KECo0S2K5ZDhZ8OFZ0reuE91/wzVMhSkVB5IPvrdPcXFzayOGPiFKjsuMU+rwXwHSpfK1QOEaWyw4xNeeMjocKxeoZKWLNCg9btB9xfCirO7avC2QJQgXSocE97nhtPY05wqy6lQwX84FH2PESSqyax5Wn2dH6xDJzATAk/1do+UOu+KmV/OlTWWApLXtbQ4tjJfg3Klo5AZWue/MlQCfPBpK+P8982RNlGy7OgwgUcIApYwum5WXsKe+UBqDBRQgNFBe11bMQs3Cb3Z3dAC0wW5opCyxZUOCKypssDaHnAUmEDhZxgHKhnGfVIMmwhs1VfWZjke++szith9kSmGSYf54JwqHBhCr2UpaJzRa+6x9tRy+RCO1EdUkpxJmD76ZmWil7YyL28TofKQWx8h8o3qielDodEYbp8JqiIYoXnMBIzeP7Kp7K/sAJWry4hHiRM7i/p+4I4+4vNlBASVoVr7DcuL9uNybYuMFN4Px20sQWE2P2FV+W9tsqG2ioKkcs92yvPhUoxTFBml1fo42JbxCrvVMvvQuUBrpibfiqnQ0W1DyC6KKK8IFRwywyKFLwzQAWAAU64Pf5R95dRhYxMI11ocUBlPUNw06ZQwaNY74MrteaUnGNGadteqe1IQeUgWo5BBQYK4YTJxIhiUfawu2mzn3KpsZjVtUY/iBqNMBHWkJu7hE1cNKjk2/eR6pmwpkZt+Xyo8Fvo3Vx40JkOlXAcyzOgcggn3I3tVKh8PnIor9cT3uI7VP4YqCiifCaohI6XNVEocWtvnsoxqJQuzu1XNwwVIwhj9cJxuf0wl0AyHnjeyQ5UIBgrDBXQJdPqUOuwhs9hGLPTp4IYbllWcXbSfJkH4MrzocLF+Zw0fDClWD8/fLZYCrHxAFTWXHkYKvyXCv8K6yh9CBUmygNQkS142yLlFVqXWW+Jh7HKKFIaJAojXXFzmLIm+dpZxj7LNy5y7jl2GCG8k3TnUMqZx2uTVHVALRdlqu5Og0K9lTrzRvePiTglEDd7F8PF62yppXKOd2pZlPlCCcdaS3blW6NLpT22olTzFazLWK+TGc9IOhGjBsUStpJIuCTZWkYkHJwJcFbal3JWcQuKZjuJwiBu9vFTQKLQE6UhxerLU1Ga0JZVWkSq59ngXuTHPH8FNIJ4ejEPN9uK2JsnKNeOWQOR7ySrE4ZKPE9iKpwOlf3OK6rZ8CeHaH09Dq4/ib40SHa5csyN+chAPWNmHzbHzokcUtSssWKFetxysFVHjg3vUoWEolTO9Xrt21tzMMh2u0bgi4bLk6+its2jrri5Fr+EG2epGScRty5synHKeA3sG003NghE2xUtVzTrqcCL2NV4qQxxTu3+hJUQeDIGwwDjgpiwLEZ61WD6UMymZm9ETY4r4Ywvs8TtLClHYB344fyCjbSBYGzPhSqUuTMmHcc1lfRz5GkhYtVpVjVsg0aTuEok/bV82s5FtM+getiQQXMiVDLlWcE+t9zVQaJAqQYpac/w2nipS618Odn3CFSYIhxoUWAgusBGiVkZKwBXGp0lPdwL4G+V4mtXUBfZgQr7rLg7y0GiEFRSHs2XlIIFVm6t+LXc6QvilsNSPQhEybeuDHsZcgWqzB6ACljCUNlNA3skVDimwpZKyAaZaX26paJlD+8T5VSofPlF+VvXl6bIVwsVhZNtlnwaKqp3b6rVAlSKo1G63T4GFe4QzL2EU14z3fSpgxaO2KSkY6cbLoiSCLzEuCO6nvDt5KiTbjVFxToFKsKqqFKYU6ASpgnItRvLPXBCiz5WdmbJDlEegIpkEnFFJ8oDUJE4Ue+7YYwOlfUJu9fRPgMbjiFUcCdO7RHjXqV5WXSWeJiyQJGBURwpZetnpntRaKygg0Qhl5e9yNRmeCGuxhPL2fI4Np8DT/EAQU4PU9ZG2AFMxvDd9llvepuvdLC/b6yEkmRSWQA8PIreWrq/8vVxJNtk91fYNj8eerp2xAOME8Weac/KzXNqUJb2CEi5sIM972ALMyWW6yfL00xtIfLDRHkeL80Maxorziil2JoYlbnp34hcnykSFocegUo8d1jHoJKuz0TS40B92Jgr39xw5UGoqDbDjJbjE38PzlP5TpQ/BVSOfJ4nxFQ+B1R2iLJjuJDytlLMdJQim/wR5AAAEABJREFURSzuTqziQlHb69+/q8/P00E35XcM1zfsZqzuxWsenjXKbqLqpavNRMmFGZQsN7CTqfmFRjdnt4TnC9cTbjPabBntbqLbT0+nsX4/MRqlJpOo6wtyxzmQqJCOQYUVrziJqqtazlD3MIkWjujosEmWnYjs2Jiz/RS+guyPkijZx66sA3UHtCJXilv1g+5EvTukepfQryh39BM28ZX18cjxMc+qbxv5Bk+BSsm/tppXeec8Zy8PEoUslcqE5r2nW7iaIVtygRa01h+DilFNmQGEHd1kYX5wQ1yYLLgTb4+ugZb92vsdqLB4KCGVwmhQUS2NqRLlEFEIKimv6C6qwYpaLEvAcHNJ7nIfN/vsB8vX5mZ9SZZKtisyHZHpxYqTtR6CyjH312OhAolEQ08pBk5UZejDUAndZXtDU75D5TtUvgao6C4vtb9rqTwIFaz1wIaoOoPX752zFYjyAFQYJ9jmnXaq4kFAS8RviYYkStAhogxGucUCRCmcn0d7PWF78Wb7RKjoHqFPQgX8SFcbWOh5BVcLPUcyIgcmTh6GCl4CooAr4cs/BRV1mrpa5NCELj7hk1BhiAoTRkZ1hrWyFlxjHzsWbJHyJO0us95FrrmCzOAK+zgCmd4KOElWZ1mHAIMtbBeo5F+aeLa+KNhnljMl1UfF2tCyB4dVH+kq2WOo7EzK7uigKo1xyRkWar1ivY+XYwfav45S0Z1ZjTnH6rGvxEewzdVGvJOpDHA8785zDp6ldgAFZ66EX4N/lrK3KjoXkOWuCvZ5qPoKytusKyjjrqCcRzt554zkzkm8vyfLPqycu1HWWbDjK99YQonKGD9voU4/CGQ5443cIYSD+MVsb+o0Z7XmlH+6o3+IU9X74io5faUv/mGeK6fzRaT/hluS/wH3Zbn9R6no9D4p/fyCVLExsLwhtgdlOj2lY+dk3Xau0cn7PTPo57tDsCTT6qltymtnA3oKKvgkq7lR0esppd1WptHG+elmB/u5ZhcngECpVi8ZdLNeB+Jf0nRJ+Ub/oExvoMQP882B6Q9zXr/YGmML4SEOZhu9jNvNOt2M3cm5PWjnOtjuHKTj659C/3H2hd8W27zdLax/aogf7h/f+UnxF8HBnb+Lfv7OGymJZHHIlgoWTfCA78rTpTEoApawFFEgdn8xTpguRmkcLQ5l494OrgYgZct9WY5e01OHH7Aw2PGliiIPKlVoBoNLWC3YUVaL9JLVDivlMlSoACXlbiTrUULF6zBiys2zensVdinOUJ/5LcloCn4TkQrIQEmHMRWeQh/LDqF4cSo1h2CmJOvLYutWFMe6pRLu7+mYpcI5Y0pUcZnvZOw5ub/SPlfShKEmPZda9nhmCyaVa2TM5pHJWk/Ql761/zpSlr91S+VY7ERFJXeVqytFs7WD0s8x8vYnpZ+vTI14saFbIboiufonJfIVYVaFRb4pUXNLo1nv7q3ZGyWbbVgqZKY4PiwVCGYKxKYJC8aKEp1Qb4Ioxd747P3PH//9f3/+1/+7ePuzOZjkeiMwhpBTdCCYU5BR8pRiVuOY6IRKE4pX/UQtgNRDIkqjFyk4LJwZLzeV8FocTFT83WuaTsLyIN1c2xF+UmzZpNN/K/5V8aza37f81JEHfn/9tclSM1fv4PNkqi0hrD7F6hNu1luawUpkg1hllHLmWX8FZZoXUKqxVAJU8o0LbhwZ4iTXpeEipX60Si9Mu4tUdRArtilzN3G87co2A1RQ5HgMpgxxzrEdzDkRmYolt91fSiJeLTemRXskjMomb5jqHJtKiWKv3Dynbvx4mHB4ngol9UqccIOWWKZtB9cpayQTwAgqkUw3ZU1ihSFJJhbzsGHDok4torIMA/WFqR6oPwaVHXgcExXS5ztstYhMEPYl45wufe5y1oY41gKiZAv+8eFaXy88jumzNIL8vwaVo9nDpcM6lBb8QJG8sa5YfED6+dwmcuPtOZ5e/LCon/x63ruw7VSr1bm7C7O/XEdUq6JWi8pYvT7ld2fWL2Q0bFLLS3aDy99/ff3v//z53/718W9/T4w70b4vPFs41bCXYk2qWFQKm8DzzPbKtnBmvULy7Kjv5sd94dbS/TbeCBcUlaIoSZUtUrWsxK1QuCWwLryFUalA+pvuKBz0Kz+YKBSU6KFpxvGbmKZ+XP8u/Cpcf+uE7XNwfaWk30gFXqLpYkcAIQSVjA+iQPHapNx7VWhdKpbsQMX0VuwBi5cnxBI5VgRoSTUWae8MUDGqY0opzjSIKBn3aDn39g2R6jh5zLLBesexZQCpN71tDa8yViCM0k5vsY0yLkNltygy44tYHRQBSyr+BQXk4w5V1ZCZ0gxbb2lQyVijHL5pusUhehAFBopZX+pQ4er6sBDSmudar/PtNydCJWYNDkonCh4mKjRHkv1g2ElbXRqpcgQqHIdnS0WZKdzv+QQduZP9CqQvyl/8wzxXp807eXEZueoRlQ/qgfEnD9ejnNqphUsatX5f+zrmx99PKQ7H9zqO4Xnd+/vCcJjstGN+U9TrpFqNs78eGF4Sc+tYFhMdH1AZvr1/91//Dqi8+uHH3NkoNe3hIJ7KNj0Iaygto7XaQUXsqhJYwjtRpybsSvV8fvnPv5YWE3CFiFIHPNYgOQKVA51R1mv6Dgn2wUA7EiRbzMvnCSr5/FGomGZ48W2o7EBLCTjB1+SUayHKZ6S0V26t7MnHjHdp+jcpG+bIEksY+/FTDmhxlnYuct4Vr2tY6US2Rdt8h++jE/YSStZJ8eoCojm72T5FyHM+ZRhnqJuWlKxfOQIDlf0VXZen7OcpgSW5cpv7HOudrLbOSdmhpbLuli/L5mG1uEmrW3RnudpIZYXJYH44C0uOF/NTpQEeEnKyvqwPbQqzJVJhzWMkpwobSZESwIyfYibMeT64hWKyFjKEjTznuKUyjFkj2HyANAsP9YuzktUZ+A0bMVUBy8Ox9uFILnYecvknjzjjsHyGuKKyh3d+xjDIv6dTFvTv+nYtmMdC6FiA/bG9v3QbJV6ospJWXSfKKZbKsZA4T15hUbZuudq8ummsrlL9PsSdV8IxKnWH9zdpvqoQBLKJSfFWABOncn42++2Xq3/9s355kW63481m1HXFtq3D/bhYmUZTKd/tpoMg5fvY6schb3729h//Zo+nquvwAzpWOb/TyOuYjHItrIXcecq06KlDTVzUNRP4ZUwr7NW/FjemZOEEtcM1nqBysuEJrqvA0mk2FoBKyr3INi4pyKxBhYP2OA6u4JaZiSIyAd0y12c592wHKqEqCyhqyRU578tyyE9DJbou0FPzu/aTvsK+YYmK01pML94DMGSybCcy6VAx1iX0WHk5Vo9FWch2LOHYeSq2bzFOoKTVL7oL2k+HoyFFPkjbk2RpzlAhWSMo7EOc78IWSdSvU86rBE0UDlvinwIVvgJfTelpUCGuyCmZ4W+YJq5sA2OrWuU7VL5GfSNQiRfqhlk7lOX1EFRYCirxtctrfzT66VAJM6z2oFKazLzL63inkx4M0kFb1OzToRJteuletzCbZEeD0tk8PxklgwDWD9e7bA3CWncLJhWsjXCbXyqRylvNJfEUIcdvJW33k0R5ACq8mn8SKhB3I/4EVNY19kpx/BRr0uxcbYcrjJawibLtWP2BiNYucq3X8VI/a09ro/cAA0OFEcI44aQj8MMoybtys4cbc+wk7QVniMGO2YdKukYi3lTGHMZfBzMILSdChRKL18OGdVcYH8Q2VWjCZGmPrjlyoLiyY6mIeDVVbOFIotjhIY9yTG9TjbuXk32DeKGrthy0J5+YrMnP1LegEvqmpMsrVl6kncsQJ4WxMEenQ4WfZRcibw9y5SBUjLxLQ5dluY+qU2H3F1sqO1DZnjn/HSpfpf6kUOFwC0wTiHGi2rTsj0Y/HSpMFJq2okGFygmr9YTf6r1+C6IY7Xam1TkRKpF6PSa9Z7lej11noEui3VJmCrnR5Dxg1jEY4DocwqELam1a8BRwwqNQdHI8ASqfJoqkQmisPAAVrRsYXxNbMlPyRX64A5KDUOGQFSyz+nwussG92XmLpTPvzku910nnPOddASc6VEzvHEShUgmzG9aHV6cgihlc4QQQBeccgwrX62VqM7orl/f+D0NFd3/xOrgPFeUc4x2o1pyOzt7kKx3FFR0qyUJQqA+z5S45waSBwm3tt+beZ/xcbcJz4LFPhovcgiU00x5cyfq6+0vkO/g1YsWZYc1T9ipamgMkEa2t5InuL6M0VghhqOAIZ0B8EipxswElck2Iq1XUjPqDlopqSAx9h8pXqm8EKo91fymopEo2c4UDMDuj0R8FFUUUKjDcg4rh+a1Xd4XZTDQayWZguN5JlkqVhp2k221I2HXRcBM06L6+MVPqdT2wvwUAzWqhjAAH70UX3IJBpcadjNWsFH2g1gtDRaPCUahoB3Uflw6YU9xf+Jr4vslmszgYEFSSjRuRdGGpVAZvAQbTvym2bil80rjkZGLCSa5Nolq8Yco+LwSvcA6og/1Q7gVEHHIu4tUFoJKpn8dLMxDFGb5ujt9l63NeqT9pqXxSO1YLAwYmi99fNTrLbKlF/jEJFbM2iOebIAq4wlPudZDIpsU+95oETtLlIcdUZDfMpkhJ80Vv9ZgbEk6yA1ImiJdHmfqKkr4qZ7BUwBXIqC3DHviF8emWyr50Vxi2BJVMu+hfJWAp5jqACrQPFbZdQoRIS2Xf5fUwVNTMxwe48h02fw6onHTOI4sf9wPyvM/WCYdV9HMe6FKsV3Sr3DCerbJfVLg1X8tpEFdkWMW9uRE0EYsGfIUDUWQ3+1jdDdtqrftLrvtrleOOW+j2KOwvR2lR50fJEnCFA/4HobLVA98q41XpIKDUgOoWJLg75E4b4xM9YOqFD0NFD7fwYK44DRbbCo3gKXJwbYOEz8Fx8GaHJZsXrjmE0/JeAG6F478qVcN28t1uptXagkp1+A6WCqACARsZdxXDfbEl78plQB7LKI5DOIGJwhTZgQoXACbKc7Nx1T77sdy+jltDrIafDypKlj2oNMYADAwUhkos28Bqq+YN61DhDi5Jqytv/Fv88YgoKS9fnyatfqLY24cKK1EZ49fgEcLx6hJQMf1bslfWg1WwfQ5UdK68FFR0tBz3g9U/yZXvUPkOlVOgorgSTgVeB+qfABVVB86V29wR5BhU2FLBtrZY+vf38Q75vgCVdLMFbHAr+wegkvEDbjEZusLWUAl9X9WqHlPZX/rZBMELU77PlsozobJjrzwMlXCJ1wMq0gPG3ZGPQUURBaex/XEMKiy+YNjnWD5kxBb6fXxx3JHfJtxrkXAy9QksFYABzICZkqxOqOAOpgmIIiMo4ASsk3xwm/GuU+5lunGltklnpUOFE8D86U+N0ceMM41XBolyT1aucAOuTwTqnwwVdpSFdZHxarU5z1V6sE6OQQWfJ13us7HCcRS2UbBfcOZxmWm9NeU3TdWOCWuWLM2TIIeKbWgAABAASURBVEduQEnVZp/QW+in7VcF/y1HVkKuPA8qOlpeECoKLapR8T5UHubKd6h8h8rplsoDRDkRKsoDRibL3szHUDpUqnUyVmw34bf6Hz/StC7Xg4GSa3VTXgAzhU44AhUs+lnPj8pZJqr1JKUdy3TkY1DRZ2eFJJBWDkGlXN5KWeZGllZpK9p/ijiKs96Jap32t9xuhwiE45xppnfL57GSO543fP3dM/emTCbqTtr1KBlBzjBWsSIctzo9Oi3lvYo7VyJup6ojZ/pDtnkFogAJ5OyS1knMGhjVaaF1bbXvso1LIATrJrZAC4hyECq4wuD6HyAKdVos9wGViBmIXPNzQwVLpIrHbKAik754zaVR9ttQ4WkrnFIcy8Nq6YdpYOvqSI7Ss9LWPFWchTGVbJ/EAXZrKLlyZpRXgC5+EA7XvwhUXtD9dbBd8TGoPMCV71D5DpVToKK7vI5VsZwIlU1zqnWvrQegAqIQOeT0xubdXWY45JgKLJXycBJO3zoCFSYKL69cTclN8tmRRcZKubwfqNfXdxWoxz17lM9/EaioNsylMrnmjkCF53fxaC8FDBzkeV8bWqyhonCipoHx/tEhYMWSGbTxK4mcycEhyjuQx3Ew77foA4ANNFEq7uWqM2/xc6Q8FWaHmuGv82LxbLH3vtB9l2+9S3v32SaMFdqmGzfbWkFx7wYCV/pXf59d/yVdHuJ+Hyt1qthKFgLV3J6C8KktcVQZOgqbY4F9WZlxYPJjvFpuzjMSKpFsg8YGS3GWF4tHYOETSseXlyh2KDeMW0/K9DDwhvCQH3LWb6I0iVvjWK4vUm2esMLRdfqtKotI9YxGdcGI8W/NyQdRmUasCUTTVkoTre/klqIq9LItvaySm1SKXK/YuePGnfickivgtKcNtfTlQ8/YFpew7Gi/Ez5rp4pFTz4+SKYvvwp/E4u+/trTrvPwuv8iUHkWPI60bOF55qoBIoVAcCR/UjlkGDWR49BF1lKhe9gocaueLDvQARtFE8/RijueYTeStQbe3V4sm6srw/MjTiMKrrS7xJtyVY1UCW//19X4Sdvjpu5G1YmWw/IX2pFONk4KONY7Un1rCbmtjC81yTH0WfECrYyPSlXd8m9IsLegq0GQ5d5AnwqsO7WOOtBkdlaEK0DxplaJvj7Ytq6yjNQq8XrNqFVj1Yps6b+V5bVxprH1I9HF+ElUbXJ/Nf3sYGjaWIssrJ9XBJWYm6/N88ENNd81O9HyUOQGkfK82HldHX4wO29zrdcgCsREwbbQfpPxXmmC7XKZaL6CYKkIc1hvX53d/q3iX1DlRyHIlDp6d68dqCiufG6owPhgioS1jSkPzINUhrHa4WWaoFKacY4WlnWRbnP7L+4JButB5Hs0TriyoG1hDKI4y9+Lsx9EYfA5oJIsj43iIFXCt2gDKpIrvqYDUFFo0emy0xJ/J9tYj77s1LV8h8ofA5UXUSRd2nn42aGybqlLczXABkkUkbNOqbTfgso6HwzWSaJkM1F2WsHrOAkTi+0GE4V2Kg7OSfmt3t3rhN9irsSbQcLzYbXsQIX2S+VkwyPvmZwgQlMgt6HCbwSoHGtLzO/IH2x3TV9DJaz8eBJU+CI4B8aBHlNRaVpcL3IYKlUynhgq3ETAsB16X4mTaL2KrSLKDlS2QjXsYVt/Ep5lSbH9oAWowDCljD4OyIu4k69PzdYd3ZUX+uTPqZ6BKFC2eZOGXQJJqGAn5b3CljDDx6WyzSsISyrdp/s3tJimm7jm9OqXYHwf1h6mvWgqDNHrOIklaxBz5XNCRXq9tN5fMFO4KgVQYdOEiiLXFZG8TCcqU6pyl3PpRToQKV+ksA2oxWSaoiwJc0ItCQpT4V4U5j+5y7///+y9+ZNr6Xnf92I5+8G+HxycBcDBvjSA3tH7XWbu3Ll3Zu4Ml6FIFilbkpWUXFmcqvi/SVXiSpWVSlwqbZRiS4xNUqJGQw43qexSLFGkKFqSY8VxOT/khzzPeQ7ePkA3+nbfO63h0lXfQp1Go9FozNz3g++zau6x1j5hSJQB6MOFCm0boyICKoDmfuVqqKygZV3qXk7VqDZsmRyldWj56E/5O6iscSSXfvmhQWVdqXGqAK5C8FvlyW2gtLVQoQlj60Jh8DxEFLilp127TtjfDSyXTDAofMg8Briy+frufrLVAa6AU0G0lCp+on4JKjTiBbvBF4sOaY3xRagAOTg81s26R3+2kucIOZVLocIjTiulxkta+AN4Np5gp8ounmm/AirnZiVUzMbnx6B8tNBgmDBUeCafPNY5+Sg2mM3Bm6k3W1rDY3ISN9vL5QnOpxINAAAghKnY2KgYG4QTMDFwC/zQ7Llc3ZeMPbgIvvTRcilUlMoUzsFg5IlSrXo73vAwWWz5RLkEKhEhT1AB3TZU4FWRTQH/BIcyTpMMJhPXuMLhL4CKP4PZwi5IgIqKq4WZZPmjwLyo2gKuML0jVLYKs8eJ/j2Wn7LCLNE9Y/gmfPhQoY4ZwsmCK2G/8hyocLSsC2eFG1muSMZwtHz0p/xPFlQuDXk9v5vkJg/+0KESTxa5gklcABI1vTS/6+ZQ4R6FiEK4WgeVWMkAqNBGLKoNoy30LFco9IeF4Rg8ChAFbqk2LAwV+uSu1Cw/8Y4sAa6sQIUDA578CrPCX9VqtvzDgEpQrEyJ9EVvIzUqBrVYV4a/uFmhhhuhVsNtmJVizMAxmmLNAKLwaWNhqPD2Sd45z6FCPAYYK24D31s1jU6FKRYOXBHLyWIn2zyJ5MYpd15onyZs4MQOCC4CU2LOdfuIELJClItOJZrt08gTPND9bna7vVN1NwXNAq6AZQlWSElFFs+RUwG0wHV4jSNfOH8+w/iGUEmWOzj4K+xUZDAiNm7iWgxlWQDG5dl7siwk6pEMKseCH3FwQIDcwHR9ps+SHblxnB8/VuxDlt2IVfai5d1U72EE3qLKtlCYUnAM3hCKhl2hYAClL0JO8K1cP45bJr1UYy7l+n4UrgJ/FPADcAJo8eniUpYllqg9Fyqoy0JbQdfkYon9FakU/lMf/Sn/0w2Vq81K+DEvD5XltsfzdIiQKsjZMoiiHy+uUNFwEM7Kra4+pD6VcPMjHPHgTqiHkZ/1hBkQ8EOq2d3Te2BWMPYFfsVP4LNUmk5D3CLsf9ZGm5LJUuAr2OwbuuZPS10y68zKeSjML6MK14MF1VZU7EsmZrmKjB6/kiRfKSzmyfaLPYlUNHwelSqUeEYHf4TYSQalClApMrfGahVmFEBRy2DlfDBH2Z9ryd3JSs9K8PIWz+bzqRS3rUy9hW8UeFMQTvECyUaq1LU2Xtdqe+BRks4+JwqIgl1IFD/8BTaF+5VrQQUOdD/8ZTizzug0U+pFJEPWq5JmAFd4BAygglxZTMIP71nhY4xfHipSxktVhjxdHyx5VK1zfuiWnIVjuh7UqgklIG5QkUyPp5EzWosJDssOss0j1Ttl5U2Wm4BHYflNVtzGe3B8ywZwRTQ2ASqx3OBGXFkHFSBKPN0R0/D6qwuuuL5rqfMsy3Wgwuu+LgUGhcJ4zfEVJWQf/Sn/kwWV5xLiUqhces+lrPpwocIrhsNN8i+sIImyCDEJ/l5FjpCLboA/DFfY+nVc4W+BTQGoRErYQu/s7pNZAcmWg10svkeBz9qyWcO19maN6rLCOAlDhSfqiVsUDbsCKsSD8MjI50IlaHB5Iaicj1cpVYhnYa7QqEc0FqWSaFkxx4pYZrTp+Fwpx1zATIkZwWRlytuHcbKUtA9BBSdv1mo0J02vuSyVC2KeDD6YZ5sxraZmm/XtZwn3EARGhBMFS4dDUFHdA61+yAVfKs4cQLIOKlhA7I9kZwrQoqxlmsAVq7kDFAGi4BYp37LwzApttidFQ7vr10LlAk6uhgqv++I4CSSWqbxYyjSC6cWL9cMgeiUR1cWFZrhFuM6STcHaTDWOsSA7sxEtbIJBAZyw7FasPE/3H7HyNksMUbmxVN0RCjfjyjqoRJIuSzgU++I1BdTF6XMFzYpwDa6smwB2MXt/dfXXT12p8Y8PVD708NfyjJbzHhSOkxeAytKUe2qVp2kr/qkd9iUXd/SSlQmXXVHIi8qFA6NTqgBCEl67MT+UbDdqmKpTp5wKhW7i5QoQBbPWqTRalutB5blmhXeucK9AUKGjOYBEuNR4QZSLjSbXhAo/9KkymNMlQEupDH9j1DBkxxE7TSBKvN9iLTfu2dFGjVWLEdugKf3xSglEiOJdk+FQGAKMypprQCMjWrfVXlvKVTBzFkAl6ejVoZ5vaTnP3HhdNLbJhZwTpboVDn+FiRJGS9LZBcEFXoegAh+lI/703JheETSLcvVgWfrjo2zRA2tCUOFcCW3ZKrJ4gdZHXuVUbg6VYBDLMlQwJ+9/2MeH0V5IIIqCkTr/NePvohS9XwDm6t4coMIyQ1AkPwMhUQpIlGhpX2vdZ6UtIb8Zz83wMak+rQMgrqxTmCvroOKPTHYWxdAuLy7w+zeBKw5w5fpQuWhELhYTr9DlDip/N1BZiW7dNKdyYzjdECrcoICwGljLgF4SKnw0ZDS3KEe+DCor5zt/DKXrKeqFKRb/YaxYpkZIgEqq3Y2blmhaYFYIJ4QWe7apWjbLZDGkc73w13PNCu+FXAl/XQGV83zJS0AlHPUiogTGpVQWKkbcNAEqSr8ttBvisBPtNtW+F6mbUacKlkWyqvFqOVYuYnlxvsTHvRBauDhUgCisXAKoaP0OX2KPAUzZBIrsSRlPzXeqm6/Ha1uyO1fqB4p9iHLmIBHo0jjUGieyc6jWjy9KcY8U9wSUaNxT7GPVOcJYkGRhJwd1UagmmCHaV0hS025rcGh721F/N5egmTx9cs4VgEq8QAmVdWhZCxWxWLRGmUoXvwzNjuRt8yA+NRI/9addHM5P+4ZpE6Uf8goWR2okrCGOFjdSjUMxN2R6i3Y+suwomt+I5jbjBZ8rlT3Vu8cKs1huQyptopXJb2D7faYvlqcA6Xhxg4+epIlh6xSMp8yP4n6jfrZ1gol6hIoVTL/3B8zAX4Q7uzRkCRBFTjsgqgq7VtJ+0RlKG1lo01dY8IGAqsIuooWftndQuQonLwOka1uZldsbuZ9rJuRDUCnSoOILD7sWSyJ+PRhWCukZVCpPxoJQsXJYB/VUyz4mwEkyaGQhANB3hSLOlyQe0Jcsna8ONqzNbRoLFoHbQoFRiW2h0NjcTtru4rwuUOnXilMJvypuofCFpfO8Wox+dqHzOuDwTGJM2yzqzS72NgabK8Olxsudj8F386uDvHgl2Mrj6QnRphiGaJqSbYMU161tbdUPD4ytzfigyVqW2LRjromtmtTjGWrYpCc534xJQbxiQXQdGpqZabdly+JzdBAqUnWLoKLk2uugIli7idZJwjsTrfkVUImb82h5N916WBo+xuyCXyW1Dir4wV8oVt1pe3ikZxs8g0KMCUMlvGz4IlpuCpUgM68E6+iFVAOI4nfRGyiStzejAAAQAElEQVTfowS/jqDi9/9j7E7MRdPtjL0NGKYRLFh+nWjHcTjxGLmS2wSFoSIUpsAVIApwBdd2YRNlByAB/i+Ykw/P83JQ8S+wnk1KuT5XqmRTpJR9TddCRcbnaFlmCc3S59skw4mWleqvO6jcKlSea1NWAl+3ARUyKwASKVPhRLnmlOKwwOUQV7BRLpmjZHs4lnUxg8LpQrRAoiSDjpZgfEt+aaUK765XDIvuUat2fXdf9guLESr+aEiqhhJLFYoa+QGoMtV9XQGV5TBXgUrFlomyDJXQrEmqOruUKJwBV0Al6Fi8ABWeqL/4eHpOAABAJeF5qXa7NB7vvfXW/OMfm7z+WN7oiKOW3vPArAStkSGo0GbMMFSCXn2jgvs0i0XFtvO9Hstml6AiGptKbQcOVjnbusKpXAcqonWY771WGj7R3GM4UtGmrHcqRAgWzSkpB7hS7+xhvCuaC1ARjoD5ZmVdDdiNoUJD7/1banUMEvJiEYuPgx/3XyEWfZlMrzK1wuCjuoFEEfP9mNYWEl2c0eJDBYNUABWMg01XnEo0OwauRItTnyszEIIEfio7AJbjl35nJfqVPHidEbcv5yP0SYVRtDJluUG6fQlUglBYwgauAELO8QCuJQV3PocrK1ARktVLnQq1qlwMiF1KlDuorELlNg3KpYGyK9zMyzgVMihhorwAVHiUDLMyC6LwI/tiZv68txGo4w+XDDxK0LteJmuyghOSVDbhTuyTT+Uq40lxMIr40bCgSwOIYpqUfpDKBtxyOF0TKhxC5FcuhUqQfqcUy3qo0P10e+kDgmQ7eZ3lcfrnU1jWgcqsMNsUHFtpNoYHx/eefezVN1HqtMe8GhLFNs5b7otFTpQVqBCGg1mZlbLebuFolmSaEyWACnz0hg/sV0AF7tGaR1eHv/TmPWP6VrJ5n2WnLDVkxU3qEFwHFSQKJeTjBWCD4Uw6o+NErhneV8+hwuvBLqLlBaDCRxSfZ+P5RLJg7uQyVBKmbvVB2LCiNwAqIIAKdZn4owfGFP6K5bfCUInnJ8AVlhtHChOwGiB4tyPcshTG8CUflX+RKNeHCghsis+Vc4RQbZj0PK5wnARo8aeHcYNC0TC0LGuaJdeNCPvoT/+fLKhcYVPCF9dhyQtDRclV5azBQ16XEeVaUGFqGjwK+BU5W6apJxTaujSJQgaFgydIwCRzfAA+EEUsVTkJyGScD5fMFM6RY5jO9i7VgImWxRbnI02vgnNZMy3iEDzhSk4lDBX61fSCgw0uiyDYpVDhk1r8e9aHvxbzxMJQWRqzT3ignw1BxWdh8WKeJmxWgCixhiO6jtbyJif3Xvn4u4/f/uT83qtgUyJdV2hYrBasFONd95dChTZxxSqVmL8fM9FpB7mfdVCxdt4Q7R1MnzSPVMeXn3iHe1AXWAKYAZwAabK9VyqTN9X6KRIlOUq37scqOzTIhA6+uC84oyN0iItLYKBsChClOz6pulPensLLwFagsoQW6iDxt9AvQUUul+xxutyL+ZVRoQFZ2NuBqXvaCMml5H0VQVHVimk2FnoJJiu29PpUyDeZaghqXU54TK9HEg3sT0z3mNqMZ/pSZQu5ktuMZLGkOFreVZpnLI+xLwp/gWgyGHAFDAoWGZNlyQ2V6pZUmcXgu8s4Ie/CSIURK8GTDAkqkaS7PJolgIovk2Jfgp9QiSyAEUZL2JeEnUogvYLbJJPVcOwLdDFFv9jOAnRZTddHL/MuK7yJyPmPnhB/B1D5kDDzwlB5yeovwAZTs3zVI6VV1hNlLVTwrKEmBi1DbYxSriLnl7oIw82MLJGNLObbE1GCkBc9lW9TVobek2NYgcoyYNCsZHsDreFJNqClFjcM1XHoUKa0NuAEHgm3xBXuQoLfdcGvUIPkVU5lufUkfFiHtZS095tmKIPCkyKUaacOdhooGe5HWcnZcMcT2Av4FZYp1B211wYVdzen77w5fPakON8GqER79Xi9xqHCncr5CEv/JcXLlaDiy6jAA8DqgelRvSbTUpFE5lpQSTROQVodzcqlUNGbp4AT4Epl8rQ0fj1q7LHsBD6np1sPr4AKKbK8T4UQQrl6sCyAFj3bIJDwArCLUAl6WRYn4wpXwlBZ5B5s6uQI+mb8x6yDChPAuDgFa0u2RiztMN1kiVpMdgAqsZRHUAEqwK1amsjGNsvCwyboVNZAhfBAaAFJ1S2RhhkncCIOTXom1/LyUCGKEDuDoJZfZ0xcWXEtF6FCXCG/Qlzhe+8vogWIAlwJ+xU6NO+gctveZYUZK/fcFC1XJFEAJ5RE4ZuD1xNlLVQCovgdjsAS0Mosr4sGJVjpGMrJ42DKxQD8lU0qnChXQSVXEE3L2t5NeG1wKnAswsdtBegSggr5HgqpgeiZeUnxRaisVItdCpVwQdd1oEIwwCrnhach0bFOzFgZWMkVfiqyNfBTmu3o3bbsNaJ1GyyL3GulpyN9MpAG7Vi/QU4l6lSDVZUXoMK5Ips1wbFZpQxvXdQwkt0OKxYAKtHk0jSE50BFb2AN8aVQAaLkB4/snXcy3YcsO2b5WcK7Xx49TTbvPxcqqGWoUIoeuMIiWS1Tb/bmtcZmMNBFrYbTKqsVYsuT7ddBZdHG4TLqmJECfoSEUAkm6is1Pd/JWpu4Alm2ACEsbbOUBad5LN2Ip1tgVsipAFGw+ivl5+rTkyucCkGCC0AilqcAEtzrleyydF8uz0BSaSoU4KdGJI6WaHEDbA0l6p8LFcqsYMPKsjsBEVeucCocJ2GurIS/lv3KzUbl30HlQ4fKxYsPBSq8yitMFMLJeqKsh8piOiQZFLilySucKCtQWTUoNJgymSNm8BQLPiyLug5UsGclm69MZvnBCNs1LEs0Tc11V6DCi8fAfABgMB9zJVTOzcp6qIQP/eeKWIJQWUzIvz5UsBnFdzPws+BsdMdNNZqqZQM7JXBmpglKDHvxphvvNuVhB4jCWhZAJeaatI4s4Ero95Jhwh1cjWbMwm5HIJPUbua9NkukmJ6+LlQ091ivnySax6AwVMigwG1x9Lg6e1Nxj1h+Ejf3KpM3S+OnmfYrmnv6AlDht1gVFssDLYrm0Pa2uWVZCxW/Vz/ip0P4tMSL4S8p0wia5MVcQJFVrpxDpVCbpEp9HMci+0NZFJslayzrBmMlNRe4opWnlFDxEyQ9HCiZmV4TKkAUugBrQiBBtCQ6QBEgCt3zMlAJaBGCSjh3QjXHV0Dlolnhe+9XhkveQeUjh8pFukQvi4O9GFQoLX9ZidcVWjuChU+HpNGQfEBkuNEkPHU48CgLnAR5FB8P1EV/U6gw3J1lRCpVZ3dfbzZxEb1tpzwvDBVehRyM/Fr87BVQWWNWXgoqKykNHgHj312ZwhIah5whVwFEoRWWQdujX/4r1GqAUrnjAVSEngdcifbqAJV4vRaxseb43KyEoAIiPuFIm0qZVY1YwwEy0fsWw0b6Zajg/EdnLuW68Hnc3H0r7uzJjWOleaI1znzBxYnqnUr1I7lxqrXuS/WTVO9Vc+dj2eFjzMaXt+nLzORJYvgo0XkIyrQfxI3duFYX9AZONNHrVAm2WGTiN4ErVTldV1J1f8RkDURthsQDTHgIBTVb94aHdnsHv/RJA4BB4xLOtYQXdgWmpwYCtPhQ6fCwD5yYkfOQlwEKpiPH05KUi/hL6dVsq2hNgUNchEZ4c9Cv+H+LmGqpuV4k4aH81cLRVN/XEMSywIxJyj0MmlcW4uZjRZHcEBhDORXk06KXBWvGcpjkD5hUnMbzk1zjJI7Vww1Rt0GCZvlyQCtQoTAXiFZ4gQUEwVsHt/ClnLRB9K3wd1Frd9dfrotD8q/WxZUHH65iUv5WFZcLN5OS+5GSoOZX9AKFxVeIrTTJLwwK75SUgSv+RdCKT/vnF80fFzIoGaaliSiRSxc+8inF66CSrYTFUkVQbTAzd3ZFty5VrUJ3QKNcgvHDi0OcpiXyJV0rJ/g5M1YWcPFVJYv5xGFLAboaJytpebQm5ULMKIHgQrKqdBGtLEaqlBYDu4o5uIX7ZctKNBogIgQtCsMGFKOCvYqVsug6gmNzxW2LGuNZuUQrk4PH53LcuJCfg1u4hxllZhpAFCATteDEk3kSX8V2LajAl8AVIIrq3StN37T3Pym6x/BJPGLup/uPyrO3ACRqD3V9qPidengmAgBiigWiGcbh+BWhJVftt0ZH6WKbxQt0LIahwsQ8bRFGBdl7bIMHqJSdDYAKD4sFfSchqNAIS1HMAlfgsE6XB2BQgC5hqNAyLpz3pdhgUMRsB4fey/aHBRWeoqeAGKIl0wd3Ipu7orEdKUw4VMD03BJU6AEvA5VL0y13ULmDCl+xRRMnCSecKBwqlxgU2u4FUAlt/eJe4cWgAjiJpAFdRbFgugeHiU43Xq5mW911UDkvnboAlXOurNT78uT2wqO8AFSw9d3v9kdHUg0GCVO7u1gz4Br4sQSVYg7uVJya6lpw+uOW+EKB4yQo6CKoGBWgSMyqhYX3c6iUSvQj5GxYJqM6job7mA0qI45YZsyx0htDVi0HUwB8nNwYKnBP3J4DLWq7HweosOoeM3YJMOBX4P5k9xW9+xAUhgqcxbEFVEgrUKE4GNJFtUHcqXBRRIvF83LaaQ0OndYOEiWWvwiVAC1BTMxAPqlGxZ1kKt3oYpxlkMmn9L6YBzEhh9vs4VzOepnKUEi4TKisQCVYxkUexV/li0RR3fVQGQAeUu6cNtWfh7yuARWQVJkFaEn2pOqOZs+FyhaghaCSrR9fEyqcK5dChbiyApXgMXdQ+SmDykW0vIzCzSh01hBFlEwZJKdLIDFZAF0KlfOuRsrMhyJj4X77q8Vz+D6fSlwsCZaoJOSrLJEvDkaNvbnqtaI1i+wRTp8slK8PlYArF/pIVta03EgrUIFrQAWABIgCwAhDhYFZMUqCVRVtU3YtyanBl+hX/L0pYDhovj2tTiELgi4EzIdhUGYlLIp6UeCLQwXMSsrz8r0eeBTsmffvB6JkRoOM12LJFL0htDE6bFauBRUgSmn6tLr9DgADp49YB8AS+BJuQUCUF4BKRKnSOej3rFg+V4KwFYcKnImBa4nnWTSXN/pe/yBT6qyDyqL42ECuqIZRn1KfSuBOfN+zBJV4VtANrdxXSz1gCUAF675k8yJUhExbLQ6YaIJlAacC+rCgEg5/UdEXhb9o8RewBNCCsa/yJkAl4x7dElTOuXLZlMnrQOWauoPKTzxU+CdWPh8MPMo6qFBmhbd9BBmU5fn2nCgvABWKd5GAKOBXpGJNLlmxStWbH6b7A9Gtw4/gaq9yleVLK1DhcbBLobLaF+KP0OdBsItdJryx8bnhL0qEAF1k29TqNgguwuEvBe7xWQJQAcDwCFjAklLpEi12qMBjuAgz4WJiAgxGunK5dKsl1WrwXcW2sYwYgOTale1N/GPTGVwa5oe/OFcCqGDFsHtAm89re8/E+pyCXXrznlrHnHyqfb+6/ayyJkd5VgAAEABJREFU+WbE3GeZMStulmdvmTsfA3ik+49SvVfhQmvdT7Ufgvx6YuDK/Zi1L+Q68WzbnxLvolQHs9z6uVPhispkVjCtEq7j4ol3QAKmUqI5uK01Nm1vm0rCsGZskTem8Bc5FQ6VdLkDLOFRL3jOOHwJiBINXCRc6IGwJGzR6riQRaJuFWxY0c4V3KM3UVoLpXdQiT4omu1r1U1aU7Y8L/J8+EoYKitVYVzEEsz/J7pwLRrb0ex4BSoLuaDrQ4Vz5VKtrBZ+rm7qbPj80FvSjQ/9G0pQijfTmkP8R02i8rKS1AJI1HIkSc+D1FSJRDhZgYq06FYJQl5aGuNdiwzK1UmUFXhQup5EdWU0OGSFKGBTACpiwRSKhl5z6/sHyVYHx7ZnClHDxG0riwOdyqjC40kuFW9m5AihsFVkEUcKKnQXCj9nuOMdzmtKgYQTIXARrxmV6bh//7S0MQSQkLSmezG/Emgxe+ai4FcQIfiToyiNv3jlKB8q/H54kbhl2c/8y2atNpvhH6WlxGwxksgwPU1BzqXw1zqoJLz7onWY679q77yTHz9mcMAZu8APwglYE3Aq66Citc7gGdLWDI5seFoszAW04G4r61KowAdtyqkAV8I9esQDQgvQgg5HFsvnKr3B9B4YF8BMEMKiWNbzoAIXABUWzYJhSpT6Yr7r7yjzd3MtQwWoA8YlXR5cByrxzBCOfrApUn5KOGHprlAYvQxUwJpQWgVzKimcWakaOwAVYCFwBViiphtXQyVAi3YuDpUruHIHlTuofIhQkRMF0BVQIQycp+VDIa+bQuW8ooxqkIJx+gFO4jlAlwE4AaggV0pV4EphOC6ONrKNdsKqy049uthdHz5qr4ZKONjF0/VYDUwIWaQ0uNa6Fv4Af6ojz2oAQsavPjj8+Nvds+NUxwOcRBY5lWAH8PWgAk/FU/ccWqhQaRmHCt1PLAGQ0CozuC10e5l2mykK4CSWyoF8ruD7zIlyFVQU96S88UZQNIxE2S5O3qCiL2CJ6t0DluTHT+BL4grhhCTVj+BJcs3dtLslZjsg7O2Q/Y28uJfXXHUqKpyGDg3GJz9BLOEXOHTET8LTyciEIhx/Xv/Abe/CuUZcucKp8AgY0kV1ormulG/jYhKxjKl42eAJnkVvJrwqW043lYx3Taci5sZqaQugEst0QPFsN5puwy3XyqTIazqVSGFCNgXz/7mNpDUH2uEczGDSl+0LLu6gcgeVDwEnsvziUpQCSFJzspYnKXoBRFAJ+5UAKskKKNj2mAgmr3CQhANf14GKkqtQ/p+mVUYXC8Q4TkgU+wKpVRv7HAtGf/9Y9Vpx20m1u9negNfg8uaM50KFj9DnfgVb3w0jHGU6DzctO5XzMZHFYJEi5TxEy9IaDb3ZVFt193Bv/+PP4DbumLii0V+oFSufK1oqnOtCwC0oJPNzJ/QruFh5CSTn0bCF6JXABb2e2tYWgATdSVD3lRVSOb5K5/lQqW29k+09YqVNVpiK7qEfAXsGOAGQFDaegqgYDG7BtQBXwlABpwJPAkTJ1LfzzraQacNZDGjBc1y3gw3wIagAUTDWpJi4bNiv0SJ3IqcdMhkYBPO7IOlkDIa4xPLZcre7cZSvdqNK6QqnQqPACCpyZRwv9JFtgj+QWKnCubwCFWAJmRWgy3WgopZmABUMf6kdlmgCToArLOm9DFSCMuLyJnAFLAsIoKKbe7QMJsbL5xI28vgOKndQ+RGGCufKClTiiXKwzX65xIuiYS8AlXBkn5xQmChhqJBTYXIiZTXs/TmWF9tuwmsrNYvy5JEL03kv18LZ0AwVaj7HBLvr4lbEC2i5OMsLF7zXLDq+4afg7JYdR7Jt6lqP2VW908xvDJK91stABWedUd5+OafCB+PHfKIIiwZJls3Cd+mauFKdzeAiCHnRcMwEcaUQJgpChVZs6eURQMXafzvZu5cZvGrvfzxuzllxC6BSHD3Oj0lPyJpwZQavRWvw3+MYYAN0ASU8FLa21I+TxoZWGkaSNZzy609yjOmNIMutulHdpMVZ1MGHMTG9hAqS+asKEcii3SE47dE3GXZ7rzk4gjtpqhjNgoTztOxsJIstStEDTvR8M2v0wvCILRumxUxGd8m1BKsVbX9niUMCH8P0NlNxULFS3MC5mVo9ItsRXOHl+LVh2NdCroV7lxUJuR4qO7hU0UJPMnBWGA6gzE0j+ZlS3QHRfOUF/Br4mvWGnGrF1Q7K71hkCQekK4aGi8VMHDkj5XH5ZqbBch5rzXztoLztC9q9XbVuWd7W7aq1fUPd/p/8I6X6Nqrny91kzR2W32LlPVZpsnJDKhVYOskKCVAsWY0mDMp8wAV8KaRroGDx1zWy8TF//WIwymUR7wraYhaBNSFfpXpisWCqFQdwAlzBAjDcQFxhmRJL5pu7h8XeWKp7cbsety3BsfkQeAwc+UW3axsVQ/kSnreAA9ra3t568iTh4ZAxbN33p8LgvCwbm9s11000GvBIrsArLCJgXJJTCwtz8uVC1K8zvjT8FQ5kRReD9HG1JXBiQRROF1ZeuLGyv3DFf5HY2wh/cs2IuBazKsxzlGYjOxyUOj2mJzE5v1iKHE2iiOJBhQWFHMGpJL0TAAAcggAVUHb4iMHhlZ/JzrExfaMyeXoFVMCjxO1D6ovkUEl4Z4p7pBYHWIOrGf70eH+domTBgUtooRm6NHaeRj1eDRX/I3nAEs4ADF4JJRYrJIsd4EqhNvYXAJf8orJKyR4DSIAoUsoGy6JkXD+edjlUFp/0Vzv/w1Dh2XuECjXAZwc4Ax9YIln41wWrIR3aYx+GylqurIdKrNiPFsGvbMRL27nWA622x9RWGCq0Q0VKemqmcylUQCwOPs+W0jU157Ckw4qdz/7qF3/ut3/vZ77w1TV671b17m/drj75hd+/Vb37W1+9oW79T/6R0ud//augt/8F6vO/+Qd/77f+8B//z7+HUDHbrNZJWqZqlFleBwFFUFRSvCDKNaES9ihB2Zh/nNFkMMqsBBl7nyhAESCKZrgAlQAzJfgwXooXqgmrKVUd4Ire7glOAw5Qqe6mWy0ZPtr73R56uwWkuQ5UaBMJnM4JP1J08M477t5estWi7n0+bQyzJrSzZBlIKzghibbJJVhVgkrEKF2eUFmGCo/gAVTYIrp1KVSCafaVCiCQOlpiDQen5bsma9qq16xszhAntB5mGSqBOwlDBWxKZeNxpjZjomnuvqV4R6y8Ccr2Hrl7n6zO3iyNX18HFSBKsvsK2BQwK2Go6M3TuLkXT7cAVJRyj0jBsnc/NmXGVTvwK2gprCCzAh/24TP+GqgANtRsM+rDibzIIh+DfoVF83CnUd8E16LlPD+oVSvUhgAVuMhUupT2vwIqYWgtP8YvE/DRsgBGg+lNIethNE/zE0VK1Ret83ICqGjuClQu5QrtjiSFoRIvjmRjyvIT0ZoX2vdE+I8SryK0tAJLlIJNlP7vklLDRGHmE9qUpRZI0sogIVEUkyVmt5nTYc8+ff9f/mH3Gz9s/uH36l/+s977P3S/9r3L9f5f3Krsr92urK/9+a3K/vr3bqZb/nt/5OT/1fT/Uu9P/oP5te/WvvUX5je/3//gB/Xf+z9ZHbzLNstboIRaBbFchhVyVHYcZNqzOdB1iHJx0GS4AGxRrIxEoZAXRr0KJtyDqfu8oZn1lOUBbFiqoNcajaNTpdnWWh5ABQCQ7nTghIVz1tja7Nw7o3owEi84vtSpYM9gsQg/W53Ncv0+xY54HIxls4gTv5tkKYF/ASekeM3gQpZUy5ioX5elh/tDP0t+K+iEXzSprECF2KM6DoCQuiBjjiXUHTAo8W6TVNqcwp3BBJdMFsXRkswslUWQgCi53gMakljefMIq04i5W9l80975eH7wuDh6XN54sg4qJGyn95MrHCpq/ThS2aa6L8yxY8uhQfLRglyB0xBDYQmbH+7BQJQ1UCGW4AfzlEtHP195gp0uC7qkSl2Q/+AKQYVXkVGV7RXhr1DhwBqoBKEt7FAJcAJ/kWTQNns/mmfQ7AAqpL4IlUu4sgYqkVyfZbrg+XBep19YHAOTh9mdBVTUEvONkZwepUpbl0IFBFD5b/7XX3/wr95/+KWvAVS897/f+Mp3B1//q/rXv3+5vvaDW5Xz9dvVjQ/9G8r54Ps30y3/vT9y8v9q+n/J/dYPrA++B1AxPvjz1nvfbf/hn4OV+ezvfMAKNiil10BAlEgxT/3214HKUg9KcrGNOJE9j3f59cRcPOoFaMFKYt+mAFQUwwGPAvezVDGaqwBXMoMxcAWggpusXJcyCqxUAsZkBn34sM8lVc1ztCyDgSq+RD8dQs8gOw4Nr4TryKLH8GqQLKl6riDwBRf+RJaLRFmBCjWdUIsJT6LwOBiJCoXhxSSbzWjNxCEudSfu2gAVedgR+6383qbSarJKCZ4H4RSGSjJzOVQEcweEcSrVAahErZ3i5AlApbzxRnH0BGwKKDt85CsIeXGBR4FbMCvAFTArcuM01X6Y6b4qO4eY4fcP1rju+GO1/LEoAVrK1LQYkYui7iqpZlzz5ecq1kFlxUBcoWBli1wuWiMMf8nBtvmFlh4sp+v8p863Ui4/G9WDMdGIJVwx3QRhttyvN1sMo6yEdJ5TiabbXGu5EoKKlB8FS+8TbVaYguHL2JtMxfouP4vT8lVjWrBkLJaw9WInWRoBniWlDmKpMgjzWGKBbdx7+K/+qPn+D+rvff/gyz+Yf+kvPv8r733ql7+Umt1LTE4r/Xvl3tllun+rKt6yCt3TW1Wxd3ZD3fqffMP3596tKj04BRltVGZ4BorOH/7C//DLn//1b3/u177V+upfe7//V2D4yr//J6y9zeyRmipJej6WzoDkXB5EbFgHFSlXAeG4MDjI1DTTMnxUJScK5wqOQ/YLiIEl1KECiucMvVoHwTWtHQv67bNFZ3vfOzxMtlpKs0Ez3lEACcuiIcGUjadMfjBJ5bL6XXQYhBD/ECeiBC5h4WmuZglFybCtJAQV8Chc63IqYWDQKyc0kgsBbAQLUcrBSuCob2LwzywVI66FeRTbjNZtwAl4FGNnS++2WSpFiILXg3seESfpFagQV4KJ1GGoVHfetPbfBqgUNl73iYKLUsCsXAcqYFZAehMFn69D4a9LoIJc8aHiz5G05FRH0D3KgT83UX+Fq3gBqOCDxfLVUIFngxem5dqIE78qjMnmy0BlCS0hqIi5oeAv71KKG2hQ8hMGlm4ZKrE0mBUkipByk+WenG2iMVKcMFSQKJoBRDn73W+2vv7D2lf+1Pmnf8De/kds+022/05m6wFApdS9XMXO2a0qf8vKtY9vVfnOyQ1163/yDd+f01tVqn8CqrRQQJfi9BU2OSi/9Wm2/TF29nkgCnAFDB9w5b/6jS8DV4AoeqYCRBF9ojwXKsHA/MXKr3BaPuxR4H4gil62OFGAJZifTxY0w804bbgfq439wf5IlERetuqi6U8V6dgAABAASURBVDQPDrDMyXVUr4lcqRpBoe2iUgt3ijwPKsiMRbyLCnPPw1+L/pUVBf3qcMT736VuEnQ81fKlXImtUbiyi3gWZFMIJzTmq1KGa5omyfyXipgB1QxcuFIz1F5b6Hm53Rk2z5ewWoHlcgRCzbT0mo3JlUTqWlBRvKPBq5+vbj/LDF71ifIUiHJNqMAtRsAaZ2r9VLTmQm1fLQ5on1UwPR6kVpmyaG4XsjEpGAQZU0xRt6VU4wqohBPpYV3kyo2gwjM0a6EiNQStrSRbotagOmYWy/rjQHDCcVDE7P8U2Bdf14VKoHSPi2leNNXNWLvp2g7TXWzMVGz/PfT8RI7ft68OQGKqI2d6St5mWpEJGnxkkxUTlFCKIPIo9W/8Tes7f/tL/9NvR3bfMPrHoGp/2+htWa391ujM6x9cVLM3r3fmbnv/9uR0bld2e+dW5XR2b6hb/5Nv+P7s3a68ba6atwWqtLaqnR23s90azgvt0/rm0wdf/u7JF/+k8s3/J/ve37CGw1xLS5cBLf7orbKYsUDroBKOtPDcSdid0LVSqCYqNo7ZXxCFWiCBKLl6VyyY0WQxliqJSRTTcnrZkapOpIAZkcHZWXY4oLWGcPLiEnvTDMY7liu85vhqqPDUBU+PkyjDgcd0YTVUFYYKxdBwTvAyVDhX4tUyl1gzuAJs+JLqLoKkXKIlKBwq+Ee5DpZ4VXBwCybnyyX4bqzhAFTUQUcf9dLDfm1/l7pwtEJFSOWEfCmewxJqzXYUw6RWFRRNQPC5cglUWGGktU+8k083jj7lE+XJi0EFw1+FKdPrZFaWoKJWaeUiQAVEM7toPnFUteAj+U2hcpErN4IKj4Ctg4qaHsTVFoubLFb1G/iLnCgfOlTAoBTqB3plxhR402xfDigMFTE9VfPbQrLNBItJ8AZmmJRgclJRaxwqgUf5zt9a7/+QbT8BqJQ6B5XeUX16WGpPnc7BFVDBc7+1d3u67UPNam3fqm7OoVv/k2/4/uzeqpzWDoig0hwcAFYbG8cElbI9rA5fKXXvsUc/t/uFb5vf+c/Fr//tP/6V/w2goqZKwJXrQIVvkAR4ADkoFBasg1wIDErarMN3MTK2IApLFYEoWbcjlyy4B4giZCpAlLhekPNmqtqIlcxosUrFtfb+XrLbAagAWiiXEF5tcl2o+BO3VvpUiBlYvwsuZE3sizwBNcBfhApxZR1UCB4kePE8zBUOfwURMAPtCy8jRltWM+SOp/Tb6ekIiMIqwSQ0IIqcLQJRIukcdeGAX1GrtbVQkSv7KecUd0kpLTk3YlJd0L1G797g/ufLG09SvYfgWrKDJ1zpwetcqf5juE10H+mdV9Xua3L7Vbl5X2rcU9yjSGWbwbPlRmRWsFtQtoMjmxZzgU3xubKiWKoNCtokebXxoqg3SNoDflINEPNrfHnvyApXitaGnm/BRRgSNLaSRHORw9ORgy1hsgl4kBJdIIqgG9hZyQchL3a38BH6PoT8WWGKg9KaoCCZn3JRyQaIEBLJoqK5Lsu0WbqL41v8zfax/Eyt7ufdQyE7Am8EGAuWAlCZADyV4rJElxnb4P+ETFsXa2ocvHwWpepMTyrpblxrssnjR1/8N8Nv/WfQf/1P/rm4/4yOEjrQa+1zWZ19UPieO93p9tRo7de9Pac9A5n9Oej+F7/+6Mvftt7/v+2v/Ufmdlm9p6RNEBUBS5klCcAAf10Yk1KRREHKVYEEcAtgADyQ0Hz48yKTNczAi1kDRD2PLFeKVWrpVk+quXQPYAb8Cl2nLI8GgoGUXBVVqzube2q7q7Q6YsOL2i6rmqgifLS346YVhY/qZYOVKqtRr0VG5HxCMI1d8f1KcE+oeZ6XY608iQxnPc15tMywmGmQwndG7RoIC7QcS3BrYt1iZllrN+CWK9qoReom3TLHYFYZbuEakAn0YnUr5rnCoB3vtwAqteM5YIMGaK4sGWP5EihaBihiAymeP7TgILzlE6CSsI6l0iZL9CJ6G7gCx1NUqav1487JZ5z5J4ArhJNM/3XU8Ano+lABs4JlYHqDCog5VOJy4VKuMKHmH6AOrlmkqVz+evklqMgmT5j7LMHeEb8t/2WhElMMELAKnlxO9ljcWRqtH1oItphQWb0mVMisEFSAKMAVIApwhZYQJ+0jEHoRrQ1QiSle8Ao1rI1mogXPhgPZOvdpPAEQRYkZAVT0JEjN9ODTwOkXvvnkS/8WiNL46t+w2ePI1pN1ULnTnf4uFYaK0d0DsaefAa64H/yn5rf+3//21/45s9tXQyVYQJksAioIJ2GiwDV8C3wJEQVrvUJQAaIkmx3ZqsMFfun/CoRNsqBX62rFIRphAiZVgl/H8hWhYtkHR7LXjjn1uNugIfmRShWIAoIL0ApUzqc0Lpft8ln05yOEfa6w0GSUMJCog5Kqk1egwtES/pJwQgKiRC1D8Vy64AJ+xJoWc6vAFQ4YsY27L7EjxzGBJUAUedyzTg4iDftSonCosAJyhQZxMjW9ChXJ2lPdA7G2y7LDSGEYLY6omJUJjpDuOxuPRkefsLaeVjYe5TdeAd0cKh0Q+RUCAAW7FoPKixEhHxaLZxiGxYAElpjqRNQGtfstJe0TLgaafL+iZDyqBfB7Es/jYOugsi7JH2RW/LJmNe0JmoP7hsXcFVDxObQGKv5IfMLJQt45VMij+FCR8qOsvaenhyzmxAQnLroUQFtMhekypc1KMww/1g+Z6gWznKVKTCzTCmQtngUxd/vdf/al0bf+Xef97/3SP/kSm71dqM3t9oOP/DS5051ARncOomuru2m2p8AV8CsHX/nag6//sfVHf1L5xh+zgsPyNtEibFCIKLThGHACAlpwnHCbAvcDITQj8CIEHhrNojueajUiBSNarFKrCibtU+hsAEJwDcaFUvpYXpwuwrMxMQl+pT0/Aa6AWRFbntbvAVdYGZhRBcHndNClA77O+RGeQu93ipzfSVxZoIXmshCBhFqNJ/mZU1uSbQYK3UlVW6R4vRZ1qmqnEXNNoWFxRZo1Vq9GPYs1wJdUmWvALdwJ/ACJ/ZY67iV6HWu+Rw7pUqKcQ8VXvFDRTAdbhZTkElRyvQeCucNKU1acAFSEyiReHLFsD4jiD7Zqqsase/JuY/9tIEp6cO864S/ZOYwaOwiV/JigQn6FqphwLeMCKuH8BAmLqeAoj5VQshvTPbApPlcuqzP2i7Loaf0gmPWSUKEdMP7I5Fqwx34NVBZLX24AFTArQfgr8CiIFrU0YZoXEeqi2gaiCFKdZothLkqxWaKvlbdxxoGxzRRwZs0AyVIFtASVzuFnf+2r42//FUAluv8ptvkOEMVsnn3kp8md7lRbhkqtMwOuEFTYG5+Yf/n96rf+dfFr3waisGwNUx3gRXyoxJNFELCEiALXhBx6TBgqkUQhaWChMJ8gSQ+Di4TZ0Owm4IRlS2hB/CwLLoJMFritOR9gXLYAKkzLwXOyZA5Q5B6dqO1uxHWQK6220vSAKPA5XSqb14IKNyuLkrBV2CwU8XfI0xr58wx/CBhY78vRsgYqEdsAogBFACpi0+YCliBX/FtAC92K3Tp4FH3US0yH+mRQPz5klRJLp7E3c0GUS8NfQRAsV4J3QII3Vs8sQWX24DOjk0/qzi7LD+LVbb1xBLfRymasMMaxhtkBS3VZrl+bPBqcfLI6fgVAQizJjd+4AiqxKjzhGBSUz6JZaQMDoovxWXQs0ifusCLxIoiJWVQsA8e3oDck+JifcKOX1YbFQjrvo/TbIcvOVM02V5sZ/QAXKVg8LGPDf0x2BLWOM06kfERMgy4ByXWgoraERDcSTAarnyvpCbkesYSm4uvmllKZigBOwWJqHaU0ADCC1o4pHlO8WHqAnaeDR3p+k8kdmgTD1CzKxwm8UehXdIMBr9774eCDf//3f+s77P7nnM7E7U7t1jGI/hlXO6iP/GS500+t4P9JEOAERfe0Z25n0xrOQY33/qz1te89+9Uvss4Wy2C7O9kUwgknStwv2Qq7E/Q0uSr8iwA2ZJw23SnnTQyI+XVfQsUq9sZqxSGQYDal4MtfAZlv9Mi1cMULVYIKxdngArjS2DlIdntSvSE79VS7m/DamFApluOGSdVTvBOFZjKuRYu/Jov8yuq3gp6YEq34FRwcjqK3W0K7AU6CuTVU3QoUvq5j8ArdRqcZbTqRupkYdeKeDbdSp87FWhYo1nWFfoN5NXHQ1CZduEce95SNfnE2cQ7nOM0lm6NZLJcsTg4WJPsLm6luwl/YLNVseCuWoJKwdyb3fubwrV+sDB8AA8C1AFTgVjY2xfI0QEuqDUq4e/3jT1R3PgEgyQyfcLpchIpozePmHkKlsPEyUAkWpUh4XksZT0g1MKHiB74+FKhgKsXfPRxXa6LWiEo2WhMh+zJQiWntdVBhegM9SqIVyw2y9Tlea00giiA5SBQNiYKdKEAUsZ6s7rQ339QaJyw79onSvggVxjLoV9QyS1S77//V6Jv/4bO/+nV28En6B3wHlTv96OhSqIAqnW2ASvvr3+998y/f/JXfYb0dxXCiOSQKUSRMlBWo8FQKcIWiWIQZyqaQF0k1Osl6OzwAn6AC9wBp4KcugUqqwOCXglPR8/Bs4G9iJdPY2s6NxqLlAFcUt6E3W4rtwmEKRKGeebggYCAzFkGti1zh23xXpgVTaVZwWypSKwnSpd0gxTwX6RLmykJS16NvwW160ld6TbHtxprWElTqBkEl0raBKIlZn65jPS+7t2kf7LNysHCMU+RSqGASJVPgUAHAsEIJ44GhtAqTkm1B99rTJyePf37z/ud1c0+u7KvVA+YcMfuQ1Q5YdT9u7LLCjOkDpvWL02ed+38fWAL8uA5UqK0PPkkzf5QvaAGVKikmGmEt9gTjoLC4XPKzLEk84pUamJWAK6pFWoEKseRqqITLi1k87y8txsnEMdUnWTTDYlmcky8WXwYqcBtROFSaOA8fDJ/eAmxo5alW3QS0MNFmukdBrYjSjmndSHoD3+TcZmXwxJk90+2jqORGRCcOb4VQFuMGiNLytNoWZ8MAgB3387/8v5S/8beNP/n/jL1XU6PDdnMLlOs9AH3kp8md7gSqtg9BhBYKhdW9PZA5Oi5199n9tz/5219tvfdv3K98Bxc1Js7dCU+rkGIXBOd+pkYjvIoUEyP7ArQA+1Loj+OGFYYKK6LgglogqSnyXJlKJFFgyTwmV/xbisLBGepubLlbu0rNiTmO0mqlpxus7tDRL9VdreUpzUai0xZdh/rwL50KzPxme7I14S3xvI4L8/DVCi/xwjnB9RrzcBhXpOXiBcayLLzl8hyx34KH6ZOBPhrEvEZiPJR7HbHT4op0PNZqRLstYdBVJyP4UtkYgqyTA/v0MJhxSdig0WRroELL00jkWvD+Eu4dWIIKlqIqTb003Xrws/PH/8AcPgWuIFFQR8w6FKp7rLgZzUxYaszUHrCk/8ovuIefuSL8JdQxImH7AAAQAElEQVT2gSisOMHZiASVRPOmUMHzPZ4DosTkLM5vFypAEbIs4HiIK9GQbgoVJeNibZU/2JgJGYAKJnXiuduAChAF3oqEsakUN5hSZ2qDJdsogIrqAVFimJPvasa+M3vHHL/JshOWGMTkOnDlIlSwTA4rGkoo2/kvf+3Xze/8J+Nb/zE5PEiPj+6gcqcfNa2DijE4dGf32ckbH//C72185/vAFSAKU9JY6AVGwa/FCmuFKJRKSZtNnpyHewAtlE0pt0fpVi+Ccf8a5wpBBfiRdTurRPGhAgYFzEosb9BMMAIbTeEt9Uet/UOt04nadrRZh8M6bluBpXBsDZMuHtyD8se0rOCEMya8uSRgjF8WjEO3TIOug0IvIIprouDC5wehRRq0uYSep4579v3j6sk8M5skN0ZStw3AC0Ml3u/I4wHgBEQ4yexuua8+yG1NsOCYWmSAH+ksjrwsLJmVdVBhqRw5FZYrqHmDmxUWVepcWrbfHr1y9uhn908/lXb2VGOmVbdBqrkLEso7kfxMBVTIDTE37u28PXvw+dr4cbZ1lmvfS7fPUM2TZP0oXZsnjF0xsyFlJ/AJHeU7FSGJtcX+Rinc88gVND/6WomGcQWY8RVTTDnpwg+yeAluRd2mrZFL+ZJEuegO1JwV00t0j6jUQHGtElPLGO/Sg5KBoKvf/+y/UjVw3t7oK/w6qTA6eM2ywwVcEeBv1BtRLOJqID9kF26lXD9RmajZERODVHwwIFL364/1djzVM1uvDnfeLTr3I9p4XekzSxoorQjSkiVRybL5O7Ov/Okn/vevvfOF99yNM7N/SGXE1e4W6CM/Te50pyvkjk6LjW02O/zv/umvuh/8Zf0bP2SZAUv14omykq0lS3W4BckZEySlq4KvWLICiugluM5ZXSVvaykLpKRR2DuZrEoF1x7uwbdE+MFsjX4EruGWqQW14OTtHtwv56ywLrVHPttQTE2nKnZ/57DWHetVJ1mrJ+seeBe4ViuWUDTUqh2zbFYxxKKrVVuJWkc1PKlUhy+FghOHF5O3hFxNKti60czYXbjQKo1E1VOrbtptK4YDF3DLJZtuWKrVSDU66WY34aEAmSmvm231a5Pt02efHBzeyw9G6U5Pb7ZA2d6A1lkWhmNzZ7e6vQPfzfWHRn88ODydnDwwuiMaSSDnjZVBnHw2AR/8TKIgJLwhMpA77CCB7mVH1AogsIxjLj03SJc24LZY21YqGKVJWnvIldoeSK7uA1fA0GjFiV7ZAgFpss0TBb5l7sar22JtV3cOQBnrIFndA6LIuSl8NtcrM62yAUqVx8nSKF0epEr9bPly5Yodrnypy5Up9bjwYZUBKW8M4Xbx412ujNkGpcqNjOHlDf9bhW4m38lW2plyCx4MP0g/BV+CChVSZ0W5So9r+aXSL/Jfc3mDK10aZSsbILhIluBPnoAS8N6WN5LGNFmcJgqTJH5rlPYFpIH7E+UZSCvsJEp7yfKBXtznf2Dor0MptS4oWWmC8iUH1P+dP9597/tAFPbaZ8rAkt7BHVTu9OMis3tQae0BVEDtP/r3oP/+f/wXrHOvYHXhXy78+9ULDhcwJlFu0P/8oBQ8wBfcmS16oHQJlSh7yUoraXZA6WqLRI+HMwGu9VIdvoRbuOZPQoKTMVVx00Y9U22ElTacrFknpaquXrYIKqrlAlQSpgtf6jU3aTekekNwkCi62QYBV+Aa0AJS4GWbLS5gCdzKRQcAo5l1wAmhRa81uDS7yaU7HihZb8OtZDdkp6m5XqLRVmp1vKdswZNItis7dRBc0LXiYn2B6KKEmi1aTsKC32XDawYlDQcEfxGIrsOCO9NmPaxczYN3I2s2C3YbrrngHcOLcr1Y9Zige1xKuhtTG3GtCRe97dfvv/nz44OPAxU061Ax52LtWDCPouVtDIUVNlluypRWLLfRmr0xO/l0rvcg6Z3ojSOtfghcAdLECpN4cSoUNuL5sZAdxNI9IdONpztiqgWWhW9RpGZ4LkE2uZbDYktOBW7BIoDbkFMt9ASyjeYgFAoTUm7Bnmg5z294BFNixaVaTDTVhAt+JchJxDOgSLwMiov5kIpc65zK0lgXqvvy3V5M8aREV0r0Y0qbSZ6YHKjZDTk9ggcwyYL3Vkq2cQgxKNlHpYbJ5ln38N3a5Am8P2Bc6Nn4soDzVTT+64zGiqh4HsTkJNOzzff/tP3Bnz/7ja+y+58wunMfKnPQHVTu9KOv9vie1dpv9u9b3lHz97/nffX7b/7W77LdIxV8A1kTf5X9uRZmBUTRCGAD2A5qnCRDE8+iKt1p2umSOwFHQo+nW6bkC04ffgq+BCsD3+W6wqnEaUllMk/TkYv1Tm/7oLS5mR4O1UFP6rYjrhNr4IEOB7dUs0HYdm5a1NcSN0yQVHdVrwmii2S3Q2O4VK8FFiduw7UNWOKSO20uqd0SW1682QBFm/WY14h3W9Kgm93blscDYdDVpmNQYnMCggu4v3x8UDqap3c2Czs7IOfktPXwleJoygoVlivJVh08SniE2nOdCpmScOkEiek5agliSpoBRbjgvKMLAAzT3Io3n7/6s8ev/3yp9wi4AlBBmfssP2XZCXBFLm/hsSg3M9Z+7/TT5uxponmsOHOACu5UvxIqy1Vb5zDguZaVdEsYKnCm84u4VgeuSEnPL+c9f55Yws77fSq4skWuAVfURENLNolVtGwciSJk8UupGo1nQ8pzLXI8qOtAhYnIFSSK2ASi6PkpEAXoElNdeKnwxuJjaIh9ogcyNp5683eT9SOm4XwaLAOLw19nLv0uHy30PlB+hYBHvawElbd/8w/Yw3eBKPnG1h1U7vTjIrd72BycuJ1Tu3Vc/8p3u+//EKGysQ38AKJcFEWxSIATYAPTioAHNVMDUawMiCIVbHOwJRQsgoqcs+D2HCpqwe5tIYqWiXIFVAQ4YbEqzB9JkszTmGQ4kctbW/bBQWY2SYyHqfEIe1kaXn4wki1HcxuK7QJIomWDoIKAsWpx2wKQ0CDkRKddnk1L04ne7gBCCC1K0+MihHDB8wNdlG5H7nWAZInpuDjfVTaGQBEgR25/B0ACKh7uG6dHoPx8F74Ertinp4OnT5v3H0jtDuCElapYv1CpASekXAVuV3eiLHYzRxcoJfE6b0ILF60P0AwXx6yFoRLOr8SS/XhqoJZmzvDR/tP/YnDyabVxGK/t6I0HWv1+tLTPsluR7Cya24xlp1izlBmao9c6B59MNZArYm2XeirjhU0QACaSG8czw1ga6YJZFj9pTwra/XytzHY8l7TElXPJuOwE7I6UatDBDYIjXsm1y/XtZLGHfZFqTU66MlxIcF6nUPEclgBQG39QQJzlisj5c63LqQRpfx9gPoZB6PPUTlRuAVSS+amUGkbVTkRpg+B+AbPxbRDiRG3Lpb3Ozrv1rXfipW2mgecbLRBVAl10KiSFFUFiLC8D5xIZlszWPvi37rf/HMNfr3yKUqB3ULnTj4vo/9VS7xhkf+XPvD/8wad/9XdZd4tsykWxZDmWqfp76gqFxlCrNChFAcwQFx4lmq1m3F6+OWSJIiCEOxXub4BDzmgXflbMWyR8hryFPxvuiQkfmosB71x8jW7Wbdn7c2tvXxz2WAvdgzzsaYOW1KkrvSZd4MQtqwy3kXaNNQ3WqDCvCor3nMzO0Dzb1SbdWNdlXo0UadsgvB7W2ajBBm6gUSOy4YlbvehmR9obaoeT+HZP2x+njmaZo83kfJKab5bvH1ZfOSmezY2Hx/mTPfiy9exx8+FZcmOAXZPVoO+SRsuEoRKWvxU4DU5lBSo4WTKZjWgpUCyR4cItkIm0UCyDlhL1YcGpF9G7wAAgAXBidPbZ/bd/qTJ9PWYcCOaRap/FynMahhjNTJAr2RFTW/HyZmPnbWPyOnVQAl04VKL5jetAhW91XBF9YA8fr8GBK5skQAv4FUFvAFSALmK6mbemer4jp5tapglcicTLvuO5FajEtSauhNGaEcmTEv1MaUtJDcGgMLkV3IpNgI2Q6EopjHqlncPx0edqg6csOWTpcSQzYFL9RlABMT0NULG+8acBVHyncgeVO/0YKQwV5/e+C1D5zK998QqoRFIV4AqBpNzaAMCQLwlDhSVL1f5m0mqzVJmcCuXnKcMf0QFIRXe8B1CBH+R6MaiIBYNpaZbNJbs9cAYYiQK0eHUiCvWIyN2G2vfgy2gDiQJciXVt1jLFQR0EF3BPvFcX+g3gClyIgyYSpWXBNevZyBJAy7BOOAGEJA4m6sGGfjSl2/y93eprx7XXTsoP5rVHZ803H4HgAtACOGm88WrhdD/adLC7BaBSM24PKtFcQSxV1kNFr7NEA9sp0l2WGMDBVxk82Xr1F6enfy/r3pNK85R9TzCOo6UDlt9luZ14CqDiD6pK9Iu9h+35JyRrD5yKUN6LFraRK/lZNAun5wi4EoWDVW+eC/v+AvE5xItJ8oF4IIjjJLzyix/6mGVJulgolbAz1aGarWPRsJBBUQaFJlf6IAkUDOG/GVSCXhl/S3xM93A0i+JF1ZaUbKeKY6zSFiwUvJlqC4RmLjVmcj+enjn916aHn85Zc8B2XPZiUjMquVg9LNd8nYe81uVU4rE8iGnwHzLfeu97/Q9+eAeVO/04iv5fLXePQQSVT/7GF1l/i7IjFwUUAa4AVMCmZJ0e04tAAvgyGByZR8UL1fpsT681WLoIIAGiEE64TQHVN/Z1oykXHRA5FeLKOqiEB7zHQgpmlqTy8N1orlQdbHgnp5XNLXU8EPsdkNBrxzoe3MI92sYwPR3JvRYc8dTSKHaaJKBIGCrqRgeEdNnwopMWsETa7iu7Q32+kTycghL3tuWjCeCk9HBev3fYf/3hzttvgIZvPO4/eUSCa/v0UB10sDWyXIxYuJgLR98XS7gopYD6sKASS6aiiSRLJuXyFU5FJ3nIFaAFfKBOjHT7ZHLys9sPfqEx+0Q8vxuvHKGqx5HygZAeA1fimTGIJXu6c1Dfe6c6fSIZ8xeAykWurCQYLoUKtcfjvEW1Rol6JeNix0k8DVCh3o6gdFjOgj4sqFDdcExrgwtRMz0mOYCTiF9JTFABg4JQ0QdKYbe3/W5/+2NacYvJHtM6UbHBYg5ABXUHlTv9lOkFoAIIgVuACvAgIErWXIFKY3OfrsMlyNymEFQSVY+gAjjhdLkxVJIZlsn7TRt5oegPDi9X8uON2tmxcXyQmI4BJ+BdpEGXGJPcGABXUpOh0m+DiCuAGcKJPu0lZn1p6IEAKvAlB0n6eBMMCpd6Mkve3wGimI9PJs9e3/zYG9vPns7eeLwBtx97a/D0NffeMfwuqevBrwCPErVr2FBp+K37tweVREICGxRRS6igla8GoknyuM4EVff3TXnUSwESS7v12Tv7r/+DzYc/m7DnSnUn5Zyq1YNo/iCSm7P8BsuOYrkBtosn+9bocW//Y7nGUTw/kUqbamVPyG9i33hiiB3mVAQVfoqJdwAAEABJREFUrF4PFA6FhaESCRSOifmvmV7/QrTfFy6ErJdzZmrOwfGUQooHuJY8ipJF+fAIBp9cVLA35XzQPfaxqyY24Ws1JtsIFdmJpdpKcYrxPdEEIVdASgd4LCc2BBWQPDS6jyanny537hFsgr4Wv98lWLEcKgoIRtSAhNxS06UfsiO0MLXI9HLzvX/X/eD/+vhvvscevGt2D6qdudNC1TpbqI/61LjTna6Q0zkAVbsnoPpXv9d6/y/f/c3/gw22L419YU5FQ/OhVRrOaJd6PggqctYA0QRixXDau0diqQaigBgpSMYkwawUWtvH+eZQKjkgpVLnwnZ6OU0zWiIY9QoUW2YJV/ggDuqjMv56ykIp3xu4B4dgXEpHcw3oMhmI02Fks88V3RrALZt02LgVnTTjs5aw2Ra3OvIO+JIuXMCX0v5EOZhpR1sg/XiblLk/r54d1u4fD155OHr06u7Tp3tvvLH/sXd2nr3lPj4rHG+Lo1bUj6cBqHAysV2m+TG49auMaY9YvhjLFkBCJlAsBX9ChotpYDsy8VyRJdIY2lpIzBbxu2qSaSmmp88fD14tkWU6/Ej5cqiAAqhoru9XyE+0UJkpWJaUezi9/7mTZ//Q23lbruwrxlw2zoArLDcGrkSzfeRKss/Utlbdbu88s8evg02JZafRzASgAgqaIgktIaiEUyx8HAtOZPkwoIL8+JCgQhsnyanI+YGUgz+2xRQvLtVA2PAou+DeQEzoqKlpc/Z2f/9T8G6wdP86UFk7HfkOKnf6CdJNoQJEAbcBJqPW3+JEWYGKXmsAVMCvrEDFT7eUCSr2eNfozVaIAsKOejkdxsn1oUI7KGkNJcvmWTLN8oW47aS2Z9Wz49qj+8WzQ3k+FXbHbNYDkCBOZr3Y9hDokjgY6/MR4ARYou0PQcpuHwQsUQ83CSSl107Lj8+Kj07g1n546r3+ClBk9+1nB8+ebT1+7J0cmzvb0qQTGzZjgJNBE4iCA76aNYJKxCdKpFRCooSgAjgBRcF/hKGipyLpHEIlmbkRVNC0Rc5NQC04Ov3TmY8EximQ/jh3Ep6J6T5QIZ6buRtvHj/9h1sPPlfwTrTanmruSqV5JLMVzcxAmIzRPZYeRjKjgnfW2n47ZR3JpR0wK4CWeKZPGfsVvxKMjl8LlTVoWQj/BIJKpp2zt9RsnQkFPiDSP5TPg13hMNdaqPiU8vcTG4yIEoS8ABsO0xpAFCUzxKEsABLJicttkCR2QRF5KOgTxTzsHnymNXsDrAyOjAS9FFT8nBCN3VTgn4fR/IO/7n79b++gcqcfR70AVJhaqHZnObe/DirZRre1c4gJleISUeDBQBRM9evFbL0PZkUoWFq1ucSVAhyDaRp9f1OoBCt1fajAB3YhX4kXKjiBMZWNlYxk3asMN+z7x86DE/fhae3s0Djez+9tJqZDkLTZUbZ7if1Rcj5OHWyA0ocTUO5ws3S6W7m3Xz7bs149bjy5337rVVD/6Ssbb78+fPNR69EZPCC9PxF2+uLuQN4ZiFs94EqkX6eqs3jNAIX3S9LwFWAGiHBCWoJKIh3sD74CKiGuYBPPogp5GSpikUNlacK82uBiyS4qNSYla4eT00+fPfsla+N17LovHwBXhPx2PLcFZsVfRYV5FKZ14vkJfFovt19RyrsAJJoJhmPBuF/xtaCX71fCr+GloRI+lD8UqMRSbSHTxQ2PUoPJzcCdKB2QLPVAMXVstx73Dj+b9R4yrY2ZJLnOYrVrQUXIXT587A4qd/oJ0otAxa/d0o0mJ8oKVAqtAUIlVbgIFSAKBsH0om56g4MHABW4CENFLzs4BfyFoMK0DPkVbCTMlvAzeyITy5dZ1l9DksnjbSnLrIo87CRno+J8u3K0B4AB2a+fWI+Pa68dmY8OQXABX8KdQBFQ681XOs8ewW3z6QPntVOgi3m8W9yb5nc2yvPNwvE2SDucKPNxfNaJbHhAFNaxxbaLO4ONUrQabHBZgQpAghPlUqggSF4AKlKqQZsTfZ0fylHV8Bek0z4rv0txaVZVN+ZHt+BCyvWN1tHZG7+4fe8zpcZDKbetlA6E3G4stwE4AVMSTKJMDOHxYFncydOkNacBiwAVjhMSbuVaaKnsWLa5Fh2OZqj4OAQVfyejmO3lnV0t1wBSBgexf3AHE70uDIgM4LGInmEkzVfwtIQT2STfBo4EXryYGwbb48U6QkX1QII6jEo9JnfAk/X3P9XbezdR3onoffgTMAEjmPgnBK+ZQH5OjrA7WTvO8g4qd/oJ0k2hQvXBw/kDqWCTUyFJmYqSw4mQLFkAqHT3TzBLXzTDjxHzVuBUEiWWKPb272Xc3koEDKCCCRU1S6tZbgYV/1TFDsFMCUFCSgfj4sm7rOy0j1UqomlKtZo2aevTTnKzl9kZZndHoNzeOL+/kdoaZnbG2d2N3N4ErrnUnWFiH+uJE8ez5Nm2ejQljxIZNdlgkU2xDFYtxQzU+brJQuFqqGCjgqzHsoUAKmCzsgWyLHABUGGSFhBlwRVQ+N1gQsIlrvhTfukA9Q9WpeJz5QJUqExLbYP5ILTAB3ZQ1t7bPP2ZB2/9o9b0Y7pxrJYPlco22BSCSsAV4JDSEgpT4Epj4zUkCjaW+wZlkWJZB5VF17oT6pz/O4eKauGkZLWhF0b4sjUPI2AYB2sSVGLJLkAlJvez7un46LON6TNs4kkOmdbjRMERLCGorMPJHVTu9NOgF3AqSt7u790L02IFKnmv35uf4lKWK6AiZ+rTuT3eFYt2GCqJiosRMC1HK1U4V64Z/qKP6phTAV9yLpwSfzVUWL0cdET6bSvUyxLvObzCmArDuOStPnBFPdgAgwJEkeZjabvPoYIruepIlBeBio8KyrgQVOiRIMBMLJVjohrGySVQgdMznjDktAOKLaJM2EsoF6MKzveNq9W4anNFFA/l73LHzbs4cQv7MODDOJyeTv/h8Ws/N7v3uWLrnlI60Spn8dyMcwXjYNhM7jGtVe2cdbffxGW6IaIgVPye8wVUglBY1O9n5IouTbxf6pSkOBVcLKDiMbEcNDlSZfDFY5pCT0sJeQIJKnhDSJIlpdtKtsttBwa+QPAOpPpU1cYyfWP2ZHT0brF1ygTqi6zjci2xzIfkh9s2g+CbmF1RGDZL8PO/GyTq4dWqRuO9v+58cAeVO/1Y6gWgkjK89tYx1RZfCpVcszc6fgBQiReqa6GiZMGmbJw8uhj+Aq5gul6Fc7b4AlAhs8LzKyjalpgvxwtXQKXCGkbUM4WOLXYdkNRz5X490ndiw7o0aSmzTliUg5HmQ/lgpMyH4m5PnXaUSVvs+uVejsHMIjNLKB8t14QK3AItwI4ECZVQ4AtjX4UyPoCgEiKK34WdO1dMr0S1ckyrCokaLXsPf4KOyhV/brzFRZ/Klwer+M19Ws//SN7KWXsAlYPXf7E5/Rm5eCyXdjhXwKOAdwmyMsL/z96bQMly1ufd1Xt1VXV1rd3V1fu+d89Mz77eubt2AWIRGBs5gDmx8ZI45/vsYxw7JzkxiU8cx4nzERLbn/cP28E2BOMYE2xjjG3MIkAItO9CaEEIsdmY73nrX11dPTM9d+6VhHTFnPOcOtU13T3VI93318/734oRrVfsnYUuF6gkrSGgQjEVwiohlku0mZLMlrV2X1NcfWk8s8g6rwjVAF+mfpcOUdwKfLc8Pmo7mkR3jqFyrO80XQJU9EK7sbhNJZAHQkWrtocnzl4AKkkrqGWbKyfM+sAPFSFVgFNhkRXJ8JuVowfqyaxcNFQKJleGWbEDtSzQAoUaeQAGRAkPqpFhDQJaPEUWGuBKeLUTWevG1rqRlTaIws81uEqWK1pcwXK4ctFQYUZEkONmxt3yIpzIKoSHsVSGWZkLQiWq1LxxikGpFAJXEiztatLHcDxzl+Z5TDVtHHeEDEul8W5Ynym5UOpdt37+zYsnv0/Ob0WMRT69FtaXYum5sNHnlD4ns9QvZyR7XrR79dGVcm4UlOfDyohFsxOMLmG1S5UxVCXjL5acShxwixBp3XfzfVkdidE0K0u81nBqXBhs6FPsSUGeyEsXZk+2OCdZOSLj3UpcNAdDBqIQcWE7AsymZFkRD0FF68FvJfun2udeW6jsiskBFy6xqcDjFjLk/DyAjTHmBP8P2vJy2rRYB4qLaZAfKuW/e7Rx8zFUjnVZ6mKhEpDSRrFTW9gEG7zOXRCv2YKRi5o5LpmS8tX5k+dxZFBJ5fwKGTanptkU+kSKUzJGrd/bPIMvZrF0CUconmvE7JqUa8YzWGrSnAx0FTkxvR8eh2tqkU0aEI3g9c9+D5vpSMqKpjNxOxew0yxNq5SLlPPhehGKtMqwHZF+3VO4V8MxOmjwcy1+oc201I0tdqTlfmTYYI3CShaXd5SzAJJg1go4e1/BTMrFmJmCOMOEaIOLcsDcGVyizCUU3A9EecZ0nZ1IrK8Xp2jhuAoFBUc0koskszZo7CipXEytgysAiVfHDrQAM9TsxB1CRThxu/NOsrD8aAFUHK6ABF0htQZCCNZWa/k1W1f/QG30slhqFVwR7BGrX3GSjDmpwbKKtRq4wknVYv90tnllVFvipJbDFRZoOQpUJtOF2ez6nCc/VFw3QwXqR4QKb4UTNqtxEctCqhfX2myzK5KBt2DjHVlsiSmu9rlYNWQO6ysvKe+8nMuPApEaL3UjYhNcuVioMJZ47uQYKsf6DtBzARXAY/ncNXqt48bqfQJm2DxHQEUyIyaMS7q1uptuzjGPMoaKkGdESeRbjCsi8JMJJLPPCCo+tPihEjJSHlf8UAnVCoBKqMG4EuxUPAXa7CG4AqjERx1AJTpqh+BOWkWunuOKaShQtF2o5KyjQMV1JASVuARfAsJxsuKHCkwMe2jgT5GcCZXEWPiYvNnC+htWayGliiOXgOdglY+8UmN9f7FkR22PH8G99SKTCnzqfEVo4YQukziAZbFap5bP3rRw6pWp5gaf2hKsnVhq2Rl3P4AvCWNRllqcXOfiJbWwWh6c14obcCoRbcCJY6g4mgmVfRUtpJjeNssrY6g4N8/nA7HcnhTkPaKW++6biLmAXnMjKG6FPH4Ra7vCOg1DuHO1LdW3eide3dx4OS8PQvF2OF6FQnwFRxcbjvbPkXQh59vaOjpUwsEUBKgEBbv40Udrn3zBQSXXWH3eF6xjvfD1XEAFLBnsnKkurrux+gPNimiE9FzYyCfyjeHOeTgVKVdnBfawKcW2YNfFbEMutMMGsymcbD8LUHHkh4qfK36oBCq5YDUfqOWD9QK1KyZ57VvE+bY834n36iwgX81yZZur5lgLZLywlAVXSAQViJsNFYaN5DiNWFFj2Zy76zX2KAwtSRV3yKIpgjwTKlKS7ZIl5LCV4YR0B1yJaHXiComhJWoDKoLWCPlqRGj2yYFcYYGWeH0CFbFH21mc0o2lFxorV+1c//pc5yXgSlgfgSuOKRliXWZcSdQYV3g2aCTbOuu6CaAAABAASURBVG3Vd3GRhb6PDJWJX5kNlVDc4cpRoAJjIRbDqSbEYuyQU4PChp2IVZpCz+rnpVZ67nz/7HcbrZMsEyzaiIhd4CQQLXHhAtMRoEI9iUlH3/66TKFSaK0/76vYsV5Qei6gImTLpfmV/vbpA6HimpWkBZvCKXAtmfL8en1pm1q2wKaAKzSrEU5FLffY9tdzBhWPKwduf7EdsF7NEz9oACo4iXSrLHBSyYI0rL0xPbNZjrUqgArpIqCiuHlf4EEobbnJxPugQrGTC0BFlPhcnouZPShqdCN6J6y16RhSW07rLTasEN/TI46TYPlOsdl+xdkUcqvuCS1iBwor82BMSF5OV67cve71iydfCS8SM+bE9DrjijAXkheD8hAQYunFLEm3IWfXgBa1sM4mS8p4bTuc7LhNYsQGAEOpAa6mO+ez+LlUgoRUz6qts20r58bYqBVn/uMhOAmELXe3Sq7GzA57LT5ytOLUNuIvAD51OL7NSX1GTWO+tnnjcOe7pNyaIHejQpM1G45WYYa4iA2xE3+aMiULUCrwdI+vg3WZQyVbXyGEeHQ5Jsqx9usSen+ZpW5r+QSXSPuhEtezEKAS1u24Xcp05nauf4VWbVMHMNJeqEgmjtFUEcfB9rlMe0HM1sRCi88ymwIBKpCYqYe1AieqlNZFFY4Hyt94kTa7SAHF9DQLKsFMCuJI2RSXt8h5sHj7tFwfU8l54CEfQ+ehRpH1ZSnDvmTdrTAnUB+0LCanlSQEtIAcJMeXqCxlwLRY0heBR9PZ0QnR82mbJRY7TSRnQcUtcDH1eKPGxdMDiLgC0Qm4Ek02WLqwkzsbU5q82sJDlvU0/uK/HypBp18vC5774itYgsEMQCWcXBEzg9HuK06/5M2V4VUgStxcjaorEWUZ4Akl58al9V1wJaT0zMp2sXPOKbGsE1eYXwFXhPoeqHhDWdzzS4JKNJ6POrnUoURZsodcokJAdZOGQRShyXDifByjtNs99brs6HqWzCa23Pb1Tr9hjyjHUCl3t4rtDUAFJzjiyvO+hB3rhaaLhUpIzsCpACohNeuHCmwKQSViZAGVRKG2cfVLc/3RTKjAozhOJWzkcRTs6ujU1XAqIAqcCuEEiqUrglWDWOmJwxXqF/ncQsXSOdtkOcGUxOXJQQWIQkEXWBMPKqG2e05cYYNbyq5fcYP2PqjAjgAYk0qUuMSlUmHbJsZ4UGGSVSINl1AOhwozNGKSs1J8HatlZoG35qFYeg5HehgxB1ENJqPFBtxKNbbtI9VwJaK2aTdsP1fcuAXNV6ecKPIrMbiNflTtgQqR5Ijje3bt7Pb5f7q4+xqtuCamNuPGekzbjCjrEXXRyf7qc6Izl4VvJO2VfOtMwlpyENUEWmgrbBoqNZ8mxZJCamDVNuMa697oQiVeDvGl6RYvvlzkKBhQpDKU8cfJsZaRNGJLYHQMKAtQsf/S3vr3pJpn2UQAkVEQb+7kg9k+okziJdTuxYWKo+8EqIAiUKEFliwV23i4jJN885grx5rSRUGFV3Nxo5i06+2VXf/cRg8qIAq4AqgI2XJrbWf9qpccApWQnmNoSaTimQoAo1d7cyeuiFgViLHE2f7CCZ9iku1SVLMYV5wZ3s8cKmDJLKgECzYEHoTKOW87C8JDKFzJR6oFUIRNiuw46lehYI+JmkiSX6GXk1/xQ4XZFCszbhapRDJ2NJ1hcR0HJ9Rukm2ROWYFBOIEOSgxqBwSUwnISU6UWIlMNccJ9sjjCk7oIQADhBBF3PZWrIq+ghOK3u/nih8q4wrzpiOQoEv7V6HEfFRZDCWGsrW+fOq1m1f8k/rcKwAVwdyJG9sxfRli41hgVrBSKwMuwqYaW9UTuebpiMJCLIxMSvc5gYpUiWotttHHIig5rwIGRAnEm2RQRHuzv/ndreXXCNYWDS5jvIlUKe5C7mSs73So/NS/+++fu/8rn77riU/d+fgdD3313/zcL9cG28dQOdYeXSxUpHRFztQ6qyflXGMPVCAPKmqlBe2+9FWzoBLUshGzgCMnGsysJAEMozBYGexeFUqVvJgKQSVmlnnDlqwCceWZQ8UFyYWgQlzZoz1QYW2+fFChBi3kV/BMjyt+qIAojB9OMrFQKAIqbgaaDyrEHvyIU1hhylGgElLUWKfK5VOcmF8Rcsvx7JInPMTFeHYUy8yH9F5AZes4XIIb0hDKWHmprQsXzrDQd9jiQmmqGXSH7Lr9VJxZ9/E6FBYasUQ7IjYhnMSTXaAlUz2zfcXrN87epBc2pPSioG/HlI1IcjOUWHdi+MOA1GZeh4fFmc+1zyTsZUo4Did7+BHV8DsnB0hMzWdqO7w+oJZcruI1aubIvJcTdWcJXfFyTO8G9TaXZLca5Gu4W4iLljnJSfFKdjl9qDVOdrZflemf42TcUiUoFVjycdTyReOd2sk9TSFJUWP6+pgoM8hxcJEmIeoygArIsfLT//7ttz/4ldsefAq64+Gnf+YXfgU3U2gvl1qrULG5sk9rF6Vn927dv9UMvfoN/+yWexga8YnufPgb//wtP1dsb0CF1voF9byv2i9wzYKKN1LeryigYteg2sJmvrtEg4RpylbczEMEj2Aqm6y24vnK0hXXDnbOULXKHq5QtnFYt7kE1v0UToJyKpRM15dOtFZPcUqWuAKBKwwtesETjfkiEUIC49b3nmjJ3iO24+QYFPgAtoL7qiA9qASzFkFl7E5sT1zVUT0baOaDnRIU7lUi/SrknUS6ZSjaLkVaMCtZVlBZTOEYss2ApeNXxApZzlA5VWbxjwIAnGNVKWnGG9wVsYR17Nct0S7Sph8hhHASjiehoOBIUjxxihyyUnKnwamJmVAR8zhZhGthW2Fqb8IVZywVoBJX6xGxhG/l4Vg2wuLbVI5uO1PWJ1DBGg0RWggqpLA8FxD7gjk3WLvh1LXf35i/VjJPgCtRZYtxJbnAuOIUVOJpnNDjohWtuGFWtlntOl+PqgOaNfmMoBLF/x9VyZpju3yJKitmjFVxt26VCT6v0mUYSy0UFq4dnvoesbjmtvwSavuIsg8qYdPrNOyg5WKIcgyVY6h8Z+gSoJLI1jPN+er8Bo0B3g+VsJWXK02pVM/PL29de4NSbsZgMvb5FSZAJZniZJMlIjuDudhQyIWt9trpiFkCS6KpMgTL4odKTMvTWBdOMMmgXBRUIPIE+6FCHYUPgQo4QW3BQJQQ+OGAJDqoTY6sm6QLFa6SYVwBhwpmOJvii3Y4a3G6wqUNvpgTivlwJk0bX8QS4gpFXBK5MrNZgsLx8pGgIsaVelVoVDhFOgwqxBXeXoin5iKay5VQss6Jbp6VnOqwZpRC0an/8HdJmYTu/SOKnUZYtYhUh4JSidcawfggmljIVa5eP/FPt87cVGicFFJrcXM1pq1z4iiUmGeSmTXhxBInFGPGINs6qeY2OKEdVRahi4aKUPEEloAozK9EC9Tq0fVV6pBtvpmLnNwXSieqazcCKgFz3n2VmOciaRoTcIA8isxwJ0ciyosAKj/7ttsf+vJtDz4J3fHwUz/zC7/0TKBSaKw+p1DBje0BSa65eAyVb4NmQYUGy3sT5j2BKGqxLWaqw61zOHrDgP1QiWQKfK4Ms6LU2pvXvKyxsuU5FT9X2OBhZwhxQEkzv+I0ZQkks1wiY7cWG4sn+FQlrIFbZcHaCxUIN+ZMvHezwvxEORAqFBgPm2naXGLr+D6ogCjhvH0gVMIVhodQw200yQ3K3LASmKtCwfkaDY5kx0E12GNmhTWjrOe5ciact6JFO1bKsvh/SgdXhHIB4vNZQIU8irfxxVKHVV3I5oVUjkWP8Ol4GcfA2K9QuN4PFTYaErJMdX4QMdKsLP+CUIlnR1JmBK6QX4moTXCFMsFCIquRjCdrvFzFUutrw0Xdw5w29T6o+NESSrDcXz65GBKGofhINrZ7i9efv/4HKoOXiOn1iMK4AmZEkiMnq7gbVOqcXKW0Y6t6MlM7FVOXuFj3mUCFjWt0tr9Y9Qk1FhtDhRNaXHIg1U4Vl16uNM5y2sBxSM4YFUAlehBOPKhMDMoEIRdHlGOofHuhUu6tXRAqdz78tWOoPOu6WKjIuYZW6sCjDDbPwrUQVASrssepBEw7nq+ku3OV0RqZFT9U3KeZ2ZCWIa4wsyLCc8C12CE1zwmpVG2uubSbyDbBFRz9UKG7IrS4w4PdDKgjQYVFUCgFaxoqIcemHAgVECVSzVFbMEAFzABR9kOFaVAN9SsElWA1G6rlgBNwhTOSXMaIFbLRvI0j0AKixHK2RxTmVJwAD4iCOwRL2IB6SSOiXBAq4VpZ6DRZtQoegh9yaZ1wwtuLRJREcS1e2ogV1uJ5JiG3CsUzy7H0Ik1spFmNVH4YFisxGeaDrcvjJseTTSF/Nb6/aRg1OY7IzWiyFUt2IV6ZM/NbJ6978/Kpm/TC6ai6Iujr0eRyKDFkO2A0GlJssqrDWE1MjcAVo7jN4i7+PvxjTUHFSUR29r5qZFDE9DCitv2AicQbYb7OhlqqPdal31jMzr2svv5a/DU4tUsTG8NCPhTPReJWmE/7l/6p5l3OSHk/VC6FKC9qqJTba+/4wz+/66GvfuauJ+544On7H/2H5nCn2t163Zt+/Ld//89vvftLt9z5xXf9yd/90P/11u7oTAlLc2M1X1/BCfSOP/zgXQ99HfrorY/c8dDXqRrmn/3Ef/jjv/j05+7/ykduefgd7/7Qa7/vx+zacn24678rPO3DN99/+4Nfw6tw/POP3Dle9FdyjeVKf/2PP/iJu7/wtTsefvpzD3zps/c/CajUhpv/7Tf+8J5Hvw7hCpyKo6/jF+Edbrn7S/c++o94+Mqb/jl+3TFULk0zA/XOFhPknXhOxaj0uKjSWNyuzm8AKixKb7FGkFDMYoJTAVdC6Zze7GV7C6tXXDe3ew4USRRq+KmQLeNcylcppgKuMKeSTNFQ+mDChkJyFkfBrOD/AaOIL9N5wSyRO9krZyg9o4gzpIvQgouUnuuO7DXSXlEIORVWY5geZ2Q5ogb1bq0iNVlxk74yHlf2QmVsViKLTeIKTiLDGqDCD2rifFNolVnYHDhJa5FyHooWcxEQJc/qIt3fmMmwLpOQrkfTGblY5g18OZbGCJmIIzkICYlKWGJN8lmZfRq/QrdGC5wFFEkRllvMYvJL4AqIsgcqkFjcAFREUnYVihkDjyvUSJi+4wtqi0+y8ntWjj6VWJU/kCvj5vl1cAVEicqdqDyARGt5sHHjqWt/tLnwqoi8BPHaYlieG08dboErEaUPrnBixyztZGq7MadYxE+U/VAZB4SqUa3DGz3mOShQPxaIwqCCp0nNRPUU2/IavYJTFxlRWASliiM1QJuqjZ89XMtrtXIpRPnOgMrdD38NRLn3kW/g4s+/7Xc+c9eTDzz2LUDlzge/Bmzcdt/Tv/vuDzUGJ3JYshur9f6OBxU8Acs6Fvfe8vlf+73/8+hXvvXZ+56Gh8BPeTDZAAAQAElEQVQqj5N7vvDNX3nH+zqLZ2EmvLs6HCpYO/ZDBXf7X3/1nTff8Qiggs8Cm/KZe5687YGv4rfc/cg/4H0+c89TeHjDd//wsVO5ZF0sVMRM1W4tcIm0WmwvnrwaOAFXcHE/VCCpVC/Nr1jt4akbXp3pzHFqOm6XKL4CtEDkVAAViNkUcEXKQIQWTrQgqzoHwaDEjSJuBkc/VEAUaAotThyCZlt5LPG6bD0TqHgxFbb9NXYqYAnoQkSJLrXk1X5ybSAttLhGjrP1QNGKV/JSvcQK9UtstDCgwsI2cCoOV9jgetuGVUpUq0q5yskKdSA+HCogCoMKngaoqIrUbCjdDk5CCRXiUq2TEFjCQJJdcja+JlAhJYob4hgt8cxixJwjrlDhCKGFixT4ZEvU2mHWEN4/OMuli5sY5smpSQxLpUiiTFGWWKIbEeEe+ly8l66d3LryTUs7N5nF3Yi8FlM2QvIiU3IuKA/dFpPxHBdK8fpcvnVGza2BNLOgwqom+SqOuAiocOEcdfHyt35hFZpJoKtrdq9obr1WKJ1gdyIOxl1qJhEjalxPaHEBQ4OzfKPAXH74kXNRRLkQVKihJJ4Wil9uUGkvlzsr73jXB+56+OnP3vvE7Q8AIV/5uf/6W/c+8g+33/+Vux/+xs2fe/QLT30LpIFuvfuLb3jzW4pY92uLVmkO7CEa4SUf++znP3vfU//ll/8Ay/qn7vzip++Ck/j6A098677HvnnPF/7+lru/+N9/8z21wQnvrg6EChwGbjVbXwJU3vsXH/dDBXdb7Kz8x7f/9mfufeLOz38F1529r6/d//i38BvJrABjOHn59/xIpbd9DJVL0yyo0C7TfqgAIQwqshXR86tnr8805+FUYF/8UIllS+AKqTBcMurdymgNfoXcCXEFRzFXiRhZcio4jgP1DCSEFvgVVrksWmapb5a63vbXfqj40cJ2jWSDbQTRXpAz2wpy/YoPKqFMxlPYWeVpuT8KVChQHx3UIHVtaGwu4CgstIKss2QqULHjnQrfLuMYruS5LEtTDhWzIIoHFWriwmUsSCyX+ULB6bMiMyrwkj912MWJ5CipcIpKUGFdwvAB83Z6ZTFusp6brJQSF7lkW6lsZvvnyLLMggrJ8SvL4Ar5lYjCClBgNcCVmNyk2SHwK5FE0SGHDfldyx6oBJ2oDLgSEqos0CK0ICzlQXkei3s8tThYffXJq3+wu/g9gr7NCu+TS1R7H1HbYaXl9r6EZeHrWn7dqp4IJ3sHO5V4DfeJc9wwF8pO8ol9UOH4tpBaKa+8vLL6ilBmjVPn2W0I/XG7MyfXi3QoVAge7th5/0yUiyLKdwZU7v3C16DP3vPkg4//47/7T7++efoVy9vX4wQ4ue2+p+j6e97/UUCl0FjO15c8qDCuPIw1ne1B/cu3vn1l92Xgx/f+wE+CLrc98DT8xB0PfRVoOXv993pm5WKhUumvpytDvdDFPb/xR36SnIqjr/3f/+o/G4U5vBxvnq2vUMuAY6hcmmZBBYbgQKhwUirXWQRRQmq2Or8x2DwLs5LMN/c4FQhoYTtgtQ6IApwMT5ydP3keZgXntAnGaiQzJbIpgEpEzbDRKQ5OCC3MrDhQgQSzZBQ7Cau6ZxPMDxVKL3bDKlSs7rQ5ceninD8TqNDkrli/Ksw1kiv9xFKXBMAwX9LI4SQx10wutOVhEzgJVrOgi1vdUmLy9r7oCKhEy6VYpcyZJidJHC+yW42Jeyrnp6CiqB5UaMiKubSQ6HfcDmCq4XClsBRSW4BEpnHCrJ8AMOBakuUNobwZza/GCmtiZcsPmHh+jc+tRu3lYGqBJUQZc5w+ZHFsuc6UwGJdiql1KCwVHJDY/m4oRBrnYv7AnTHqdhyQ2g4h+pnaqY0z37dzxfenyuBKP6rOhZMDPrkQk+ejiYWINE8NWji+DLClayekzBIndbh4M6D3tdo2C5AkWoIJ9zoIw04FbBq4Eo6XI0IFxigUb1L7S7N5TW/79YX+dUF1FEu0WQJ0rBSOFsclkLZDlNREMWOig/a+3JNx0H5mkaMfGE48JiRYzjtYkzRlpwYoLOUiifx+qBQ+9mj1U5cFVEaF9qIfKg998ZtwKiAHUFHtbjjaggCS2+//8m33P0nIGa6cKzQXIbyWvdBxKjiCPT//tv+PeINjub12400/gusAEp6AF7791/5Xujhfbm+15k6XWut/c/P9tLGG4wc/cieu5AAVUKG2XO9vvfcDH7/3C1+56+Gnbn/gi7fd/0SuPpdvzOfqC/i9N37vD93x4FN45zseeBpM+uEf/1nqF0CfF+Q4hsol6xCoUIjeXbs9qAhGabAq2bWwloNrWTv3Er3cZWbFGQPsZX95Clo5a7CgNDpCqbZ0xbWtzd2wmaW9LzqBXwFpWI29mmaiuSBYH0W3uC8kMnFRNSCYolHUsg0cBb1AxZhAEQSXs0+ToD05GMo85uADIFljUs2QYcWsnJAtxvMFoVCEY4CSzSYkt1uQ0mup/bY67ECJQUvsNfhujdUY1vNMtRxXzSZGXX1t3twYyYs9IIclHNdZVD9SzQFFhBP4lUDRBkuixRzrBmanABixVpZSNq+lKOROQXhSSFQOlNvjS1JieprTksBJfjTidJ39oZypZawc0mpsmdV1Guurljet1ik3H6y0IVW3gZZIbsUPFYqyEFcimSUPLSBTUGmyBC3IGZklaDUoJB7MlQNavIyhQi1ewJWIMuTEjmAst0cvP3P9m+c2XpWwVnBRNlfjyigkDAN8nxqUBcWa03OsmbCXjfKOkF4KmUOzuQtfxVujKNASYb3rg6xCJRcQ84woY6gE5WF1eH1r/XVS4TQnDbjkvFsCGS1CPqIcCSqeO3HR4nDiiHJxQi9xd9ssCpwAJ/hLOr/3xQOVz9z92GfvfeLTdzz22jf8Cz9U/ud7PsSW7wefuvvzXzkQKhCoA3Jc/6o3ZcrzgApeW+ttdhZO3nLn4wQVPAEUcUIyq+DKM4TKnQ99md7Tgwp9WCLHIZlgz/uq/QLXJUDFbi1opQ71/motn2iv7AaSGUBFskpe9hdEUInmSpDW6gEqSq29+/JX5/qjkGF7XKGtMDZhBQJUkoYzacqZCuyDSkhKB0XnX1/cUDK1pFUFWtgkSgcqB6FlApUpH2NYUBArsmoyKQajC8NMku0sadpEhs6U1jnLYK3AoILFOnrVC6FGUZxvgyXJpb66MqSp9bF+3eksmYdlCTXybDKxDyowPaxZC5mhgi00Kny5wKV0DydHhAoF56mrcbBSzKwtx4tF3K03CpNBhbcXlMq6VtmQckucWInonWx722owckilzUR5C0eAZI+IK7HsioeWkN4Lal1Ci9s/3533VcYizgZneSOwHK8Q5POepsYVOy0pya8EhVYk0aVGL1b1xKlrv3/z3BuN4nY0MSeoiwljDU4lJPQh1rlS7LDkLr4a1tp6eVVOD8qd3XRphfVXDqbDQjEiliBQhG2yJTqOumF7tbr8yuzgOnfKi9DmIrUQXwnGyuFYHtoTaZ9o31T5sSZOZZJbfDSnMgUVZw+NFJFs7zpBhRpThqJWhL/soLJY7iy9413v95ZvYKO3eBo+w9EG9Gu/+8cgyn2Pft2Juzw2XD1VaGJxX8BrnRc+TVtneM5o46pcbRFQAVoo9PLBv/sc3A8zFg8/DXj0l87ZlWU/VIgrHlQgu7IIqMAeHQIVvBs454fKUfKJj6FyQR0ClT0bX972l5xr5LtLnGwBKsl8c/PKG9Rimzdy4IofKiSwBGZFLNdhVvBQb/bAFRyJJdSyxTthXKHGKk6W8JRTcZotsX5LgslFFABGMktwLbBHMT17OFT8AkhotDAUTWfJpoi5EuuVkrFj+TxfKETyeShcLEAsZatSiNaKEGyK0K3DpkDUjoXNU4FfabCuLdT1i00gbuSjtTyIghd6GV+0mRYr5eOVolKvRmyLkxKcKBFOKMDuh4q/sJF+SgoKSV4xGe3sjLm+JM51Q0lniteYKAwqRmOb1aPYI6W0ZlTWokYXVsOorBit03JlG/w4ECrEFT9aaFQwdc4Pq7WAXKZpkqFE8UCuHAIVxhXyKzEmBox4i4s3eH2us3TD1vnvq7Sv5pMLcCqCuowTMMbtiEzZw4ka55TRuDtjIRss8X6RG7lxoKI2z9Q3bkyUdjmxF9ZHnNBhv4hvgigeVGYWMB4BKp5lOaKmtr8irhEJC9lJrxfoRQSVuz//5TvwhPuegs/wQ+WXfuvdoML9j30D/uBAqMDB4AkwOqXWKgxKobHcHO4AKlZp7n1/eTNBBc/5zF1PLqxfXe3uYNnC2xJU7njgq3c//I1LgwpudQ9ULlit8ryv2i9wHQIVL1Y/BZVEmk+VqvMbFKvHw87qSZgVrOxsB8wu7YEKX6jEi1VwBVDhc2VOSxdHq5vXv1yrtiloD9dCXGH9XVhLfGc+o7NVNQsqjCvOOdCC3wueEVqOAhWaV082hegSSdmgC1WusOCKbXOWxTJ97QyXtSnATnER1s2+kmMdGyHgpOF2AGPNvrpe16+9UKE4Cpgkdepys8a2v2SJkwRAJZicAsYsqIRlzZPrV+xMdnkptbHMFTIgSkQ1p6DS27im0N+R88NEbiAXR8nSolgYcYlKLDOfbu9CieIKJJdWk+U1yM8YP1d4ezFqLYTMftDoOftgTnxFKnOJIieXuGQZYsODpQKTmHdbLsbc0fHe0GIqmQzwZSfsz4ol/e0pQY6kvbZx8g0r2zdZxdNwKnFjPaIssxrJxDz5FfgbJh+0WLdHJ4MZJ2F5geN7AW2+MLy2tnoD7p+9udSiocjUHt+tsHHubWpry9cUkpb1qSuki9z1mnI2zjmggpMwn46JdlTIcGF9KhHgRQQVWsHx9Z8iIh5U3v7rf0BOBcdZTgXIgVkBDMijAC0gU2Ow/aGP3Y5XEVTufeQf4FSs0iJB5a8/cR+I8tl7noJTed8Hb8nXV3DR2fvaAZP++hP3zILKq276Qbwb7hO6+fbHf/Qn/yNYQo39j53KM9QhKcVerH4KKjK+YqcAFXgUnIuZaiJbXzlznZqvAyrwH2w0vQ8qsWwpnq9Q0J7oEkhnC4urG1e/1Kh3ARLghArs5WJdyJYjRiasW0761pRT8UDinbiKJoOCHlfthFmABC0bldORRMoL2lOqsRfAJ6iQQJSwmSH5k4w5kpOXxbrWF9xguzthZQwVGqPC3Em3SlO8ABW2/VXPcpUMUzkbrhf1YVcbdOR6hfVoUZJcQgpICSgsMM0CCSex8AmAQbOEo1qKw3PAHicxWh4NQBQhm+cUjUXmk+5fyQ3sY62vLpxurVwhZftSfh5ckcvLidJSODXgtI5a3bA6JwEVKrCHAJUDuUK1k1FrDlyhMV9uDTyIAjloCarjh05irp8rHloOhwrbnhLacCf13nW759/cmX9FTFsNyYtO8+N5p79kl6Ay7X5KNGqMNSGOdvT8bnfzNdneVSy/7aQaJgAAEABJREFUINkNJrt4f8ryoumQzwQq++Mrh/sVNvBxTCBvTD2OIAq44hDFeHFDBQ4AUKFKe6pwBFTgNgCVWU6FzAp05Uu/F0TBC4EWwtLffuoevIqC/B/++L1wIYXGurNyreMhvMtt9z0NqHz81kfSxfnW3Mlabxsn3dGpW+/+4iyovPJ1byanwuL/9z39Qz/276v9Hc+s5MeRlWOoXIIOgYpglggkITnjQSWQzHCCYVb7meZ8SGVlK/Ar+e7S/NaZoJwCIdhe1jRUYFAoyTiaK8G4ACphu9DfPr117Q3p1oBqIWnGMKuOTGUDCiNBTM/4oQJTshcnpJgSiGMx1cOSCfFKBmiRjHxUszyWODOsdMo59lgCg+IRhcliokywgCPmVKCcRVCJVAvBap7GDDM5RAFFPJyQa6HOYHy3IvRr2qgvD9vwKywwk5Q4JcGpStDQjwIVCpyQC+ENi/a4WFWKrFYXluyddQ7OCUQ5ECr4c0BWZWFu/UqzvRvLjvjyBqSU1gR7xEn1eGYh0z6pVzflwgpEG2KH+5WIOfC2wkJqg6EFrgXC+o6jE8yfBMCnejLa0y1eJt3D/FAJxnsBviub66s7r984/8ZM4zRVmUTEERSKzwf5OUpTdruzyG2nTr7NiXWtdba+caOaW8O7RWKlUKQQFvLQVJ081ZpQ2tUUM3z1KM6yTgFzV2EDuqj9Ltry8gYJkyISmzEciqXIo4RilydUxg0lgZaphpK+QD1bqR9kQfU9UHnbr74TVBhD5Ynh6plxoH4CFdL/8yu/D7OCl6cKAziVN/7gT95y16OAza33PI6X/+Iv4ac7td4JLFvF5tp73v/x2++H4fgKoALLsn7yht7iWau00Bic+Il//Z8feOybHlRAMuAk3xgRVF76mjcRVO595Bt3PvwNOBWrskhQoY98DJVLVqG1CeVaJ6Dy395f/9gFoMKcimjGzGJtYTOs5VjZo1XByWjnXLY55JImC7/7oEJVKYQW4AQCV0AXXBzsnDl1w6vBlaCeAVco+ytZqFJ33j3bX7OgQusncYVcC9ACpwJ+CHA/dglH3rAZTqglvuLI2f4inLh0mQWVsVNh7e5rTME6E4VSKKZCfoUfNBKjbn55HkoPuslGNWqlmTWJxzlZZvNOEnLQEUHFj5MD4iia22mGRkPS4HpcTC4OQZRoLsdp7oYYpRXQ38otkwRa8bfA6hlTy9WV6yrL14IokcKqVmFcUcvrvDXPKe1UYwdoEbOLrMB+NlfIr9BElvGU4lZYa7poIUllPIwkiiExP6kovBioUHA+JAxj8gj/5NfPvaG1+PK4uRxLLHlcCYs1lkPstOsPan0uXotlRsX5q0rLN3DGAhcuE1TC0aK/7uRZh8pRGOPPGQuLGYjRJaw7Uqd+6eUGFVbe4ejf/qdf9kPld979ZyyQ/tCXKatqFlSAHFgWQAXre7G1tMepPPD4399+/5d/7Kd/frB8Fn7lTT/8U2yH6oEvsWjK3Y/hpy97zZthRPJ19nW42t36rXf+2f2P/iPMCohy691f+tV3vG+0cQ3Myht/8Kc+c9cT933h7+/+PO7nS/uhcv2Nb6T7vP9RVkj/+//7I6snbzhi+6/nfdV+getwqFDe116oOIOEi/0V1q/FCbGAMclsdfX01W7zlWmoABiAilCoAiecng5abB+MXbQKldHa9nUvB1eAE2ZWlFRISwMqgMF+p3IgV4ATIooneBd25GVOwPd9AzhJZIokiZXR5KLpLIHE2wRj+WC+FpMcyXKUMcEVNhCllPVvfwEksX49udTXVueyu2v2idXU5qK+Nu82jtSSrLk9iKIqnKL4oeIS5QhQ8XoBEFFwLA0XcrubXAUAVnGfM6HiLqa0FSNa+Ac/v3kF/v0n7L5RXkxk54zKSjw94BI1ITtvNjaT5S0ht5oob0Gx/AYpmlv3B+1JYWvRywoLqB2QiZMqTEKBSSp6cod9ueOtJsu6l/7E5FZNOq3DnMYwVIfPiW21sLl86qbVM/9EL22H1SH1GHb7siTarLOL1NMrJ9vrr7HaV/KJJhcu0MAuNgyGjZS39m5z+Zf7/VGTwzVrm8v/WXyCPcLfH8eokKEgCttDC6rAiafLDSpMP/6vf/GWu790D1bqR75x2wNPv/UXfq3QYoMgaZ/qd9/9QazRVDaPk1xt0d9c8u2/9i5c/+w9T1I9yvzaFVT5OIYK2zdjJSz3PvFf/sfvgQd4GrURu+2+p269+4t4iJO3/b9/QC1hCFR42+tf9SaqcaFnUuYxnf+fD3/63X/6N8AY3hZYAtKo9gVHvLCzcPJvbr73oSe+xZ7/0NdhVkj3fOGbH775fi9c/7wv0Jej8H8sVGiegPJ/d3/5E+PW93oeqMARLiSkZj2xxsBOXq+UrrQXd/AQ7ElYVYCn0F5c2DoP8OBHuOhWvzvwoFwvci1wM+xhvhTLwsEUCgtLm9e/rLS4wmkmR1/MZTWazkj5Iuu5m9So0M9bbWlWlSc/VOicxJq1HCQhU5DzFa3cgPRKE6JzuVL3lKw2Jqo3IaXRgjLD+ez8qLC4XFpera9tlpdW7cF8ujvgc8WAadE21NQWll8+onCi5CkkyeFEMpxUIorKaY50NWSloikmNnfLMNmIlJyl7S6bp9fEXIEVbzqlnbQhxqL3ifHYLtr+8kOFi+pcSJHStf7qmdbSeTk7kOyhWlzUSisQpza5ZN1snkq1ToMZF4QKcSVs9D2uBBJVKCiVAmLRDxUqVaF4xlGg4lbj0wZXosuqHRPdyvCajfNvrM5dG9HmWI9hoc7q50XWLizXvaqzdmOisMOJPcrsCsaKkEOUg2In/kr45xgqRBTafHOK89mbOHtflzdU3vJv3+Y0yPoqiAL9y7e+zaospJ2aEqz1v/OuvwA2YCwIKlj6/VD5H7/xv2ivCVy5++GvLaxfCersgQr5mNHGVb/+u+/D0wAGWA2KpeO1v/xbfwQS+N0PYFbrbf6HX/xN+qV4Dl7FSizve+pP/uKTo80r/uB//9Wn7/zCrfc8DqjACfmhgtt787/4N3gme3+nJp902wNf/eBH724tnD6GyiXrYqECeHCwC/gnAHT0V5N2HVdwjBtFXOmtnOwu7+IKjI7bUdhpek9cobA83Ay4EsnA0GSxHOPEbPdG564cnDwTSttcXGJcUfHdXOXTNuutIqmBuPxsQYWLYSlXnH4n7lBIeKOwbvlBotSanoxOT2t11GYbUOELpWiuEEhnOJM6zI/l4IRz/MQhUPE8ykyoKMmQaYAowTSYkYTiqTT8TbRSaJzcNk6tcpU0DRmjBi1uGD/hEHc/VEgUGebCWjCernU2FlavMApziTQr+zAqa4niSiwzz8VrvDVKt0+xAsn82mTj6yCoMK6k5kLmkLgS1tpBpRlwxmH5ocIrNdbbOGKDKxeCin+ypDO62GkxGVJ6OFEL66MT39Vff4VoLQaSi5wwjGpLpd511cFVUXUQFBohsQmPwojC58NCcZws4Gx2HVQS/22ACl4Cd0JZXkwh7cUBlZ/8mf9GTR7f/+HPYSH+4R//2XJ3izXjcqDym//z/WAJXMVHb3nwgce+SWu3p9/4vT+F88AKjp++84/+auvMy6m80Q+Vh774TbgKXMTzf+TH3vqe938UnPjEZz//27//gdf/wE/gusuhsazSHKHrDW9+y7v+5G/xzE/d/uh7P/Dxn3rrL7bmt3P1hXe+9y8pO+Cvb77rY7c+AKKQKBEAx+96/Y+ChbBffgEqeSem8ryvzpepsp1NiKCS++j9pZsnUIkaBRz3cgVQEVOMK2JKztTKvRVYExAFZgVQgWBW7PocnhZ1BtpTZhdxhXWQNGzXr2gmiBJMZRhIjLRYrHS2dxfPX8W36s5gRB1LZyShCVo6qqVYgNpJiHL1TKDi1Oq7J945L3PRxEQxeaKoxORsprmbSy6c2OyssKRHEgaOXpB8/6YWiVWleErInlhWsaKGdD1sGOGUGUmnwBUWz0+bDC2WEulWK+dPmBujgGVCrCu+qruuiIL5VDs5CypY0cCVsJgBVMJCNp0fLGxei4VAzMxBcmmVqbAWUHtAhdU5fRSoxDIjPJn8StRg1ZFsHEuyvmf7K5IoR6XyEZzKPqjwNWZHIFaHz3xJoXtu4/zrlcIpMbPdW32NUTrFxVnfF8oiY7teDlSc32UfCJWZGV/PAVRiok0GBWaFTvBfgekyhwoEikDZ+gqdU3CbsaG1ChtBJfSa3bErC3tmq+B6ujgEFWAvhivn6v0tWtb9UKFSFTwBT6aQDI6tuRONwbafJZ6oNBLPoZoYOrLrrSUnWrNc66/nG6NCcxFHpvoSmRUPKsQYatCCDwXZteVKb/t5X5cva82Cijd8nqAy4QpBRUyxfbC4Aaikyj2yJqAITqCVk9eouSZOaPvL4woV0rtpxJkcpxoElYBpkezB/Nz115hLC2zdxFd4SY3KekxPh5L6swaVWIIIwXl4cDpruXX7jgCJiWQDoiqQgNM5BifsijiVcOXpmUAFRAkaOsS4kkwAKtrqXOPq0zhy1SyX0rm0wWYhOxlf8HPUsmU8YcUHFYoM45uyt6jRbgwvZbiAjNWwUB91V68yyotiZqAURkphSS0ux8weJ9eV0lqqsaOUNuTCJAFsP1e8bi5Ai7cbxkruEyWCCtWIjCvebSy1/jEkLmOENDTdpNKZ3UJTtjw5nSJjeldMbTolLEOWZ0xhf3cdp+KVLNvycssYD2jeNdGzBBWv0SR9OhZNEbIQJXd5Rz9LPKLguicKDwInpBcsVGaFrL01mk68FZ+W78PlhwqIctv9T1LUxK89IPGfz/gtsyaDHXxLsz6v17jlWBelw6Hi+ZWDoSKm4EXqcxswLlSBL6UrMCvwLqPtK8AVPIdCKWRQiC4kMVeKprNU1h5J2RQt51QzWa11tneaJ3fFRt1tlyK5+zysxI8NC0n6tYclF4RKIH6w9rDBB4mDNfv5M6DiICQgJz0BJxFNB0hiGTawizN1Zk10FfCAI+Hq+eKZrcHV58R2LZaz2Z6YwxuGW1Wn0D39BdxfMf4UTqGoUuCTeYKKnyth3oRgWaBkbthfv6bYPylYfcEaUogF3oWT6iBEunkSSpS3ABXSLK5QqjEpotU9rniFh4BKVMpjqXW3hvwtUuJM0+30D4LKBC3zXHzI8U0uUuNiBcgPFTeO8m2Eit97Uak8xEgzJgrxYz9RXjRQIa5MQWJ6xX/WobIHMM8pVI51abqgUzkEKnRuVQfpSh8soS0v2gSDR9k4+xLmVwybJtJzatoPlbCZiVm5uA0rk+WSOvXjwkVO0wNmSh/06yd2Kuvr4VwO6ybhhNBCdKGdH4LKfpvyQoSKz6MAJ1HdENJWws4yU8Li8wrF52FQQJTswrB93TljfYHLpdmML1OH8EwPKowoCWUPVIgoDCpypgHFlDwXYaGUkOByhUrw2ENW4J2KJPK13nZn4bRZXpHtOa2wDBmVtbDGiqMDk/cAABAASURBVD8S9qLWOAmcAB5SaROuxeNK2F6FiCtRayGcmiO0xIymxxUPKk6cI8XLxXiyNJXdG3F7Xo3R4mun74Tc9yvKlyOxkkMOi/V8ZC2sTYg8ygW2vJ4DqLhheYclTueVFBc2GV3GROFCyuQ4vev1oofKEblSooaSVODiZG1dLFQuZozxwc9/3lfhF5mynXWo0NyGch99sHTzIze+94Ncb/UoUOGcBF8gBGYFFKHMY/wIaMFaAdeysHVeLtY9rvihEjEyIS0dS2WlbAknXNJwa+l1E4tmyEiJuULrxIn27i7r664rnl/x15lDYckMiYY/pdhlzAwYUEv5/XomUPFvnc0K1LPE4rF4y4Ji6XQ0lcLDgKoybMCjGKrcrDVObld3NsRame13aSy4AgIxT6OoLJgPoigOUaSkHyp0G7Rlx3GilbDqWrbFqwXyJeRXqLqbCrw9f6Bn+4P16zP1DTE9lO0FOTfSy6tSZgSuABvJ6g75FapcIa54UIF4ezGWGcXSjCuAiscVNlJlDBU4FfpGjxPaCnMBEKe2V6wr8FGg4jaup20uH1SOFEd5LqECokzt7HlECSb9UPHHUWZBJRzLROPZ4scfq336S5cFVApOau+zDhVf67BjqFxmOgpUprjih0pEYechWc7UKv1ViqzQjyjzOGnXBztnEoUap6RYC5ZpqEBR0wZX6ISucEk1krIgnGDBlWq14s5m6cRWutpkc3YFmVjilpdLSiSRolp6oMWv4LjLyx5FhIP1TKDij8H4e3n5RSnCpIhpsrC8YYR0neUN62zjK5aza1vrg3OnrcU5zk6xbIVMKpAymINRmFyogCiy4o4g80HFHw3iqLO6qFc1u5NMN3kF63t2T5t6b6oHFJWKrcFud+kK2erF7Tm5uCTkFpXKeljtclJDLqxolQ2aSQwBIVF70VMkM4LC1kIwNefURXYgt2c+dYGUqhHRLXEPxXO8XMZDGuLrH83rNzHed/ajajJZ6wAk4DpVilyUvDdkNfDTs7bcHbawibflpSyAzQXV/a+i4PyeN9wjZ08yTf3sgBPSZQeV2bCZtbhPBGb8xu/96b2PfOPuh79GcyFLrXVqF+aJEoifOx0XOT67ynZWoWmofIjrre+HitsAX86EJPavgDWid1o60ondWrAac5xgMCXSIBCOHK+BJb2tU1q1zSV0L1xP21+s45bTMcXfj4u2d1gphiN6KBfLue11e3M10WmxL/WyzKnODEQ5GZTADyMspyLJNISTUMKEpna9nNn1/nb6+7U/5H44VCi8H0jorPLfqdV324vpOpNpQEAC0YLPZ+VCLoqHhhqG/1ATwbTOmSorQNGVZKPaPbkzuvJcaWUR5ywan0mFUybb7NJUVj7pEzW9Z9kK/tiSpLhIEzWWsRZXy5FEnuChWC0IV8JSzkPLnmkoWOK5cFrPz7dH51LNLT4zTJbXxPySUd6Qs0ucVIcLSbdPyaV1EAV02Q8V4gqgciBX/FCBpcAJMOagxfaW6WcOlQPBQJUi43ZbFyF6Cb3zVA3KOOkAJzHRpsyuPdjwMom933sgUY6hAhUay7XeJjmS3uLpen+ryJpHrR9D5fLVJUAlDCPisIRwQmjhpFR5uCbZWEOcPQnZoi5hNICrvX5Cr3WobJ7iK/5mjn6o0PYXccWNH7BkJxVLcLRVK26uN07tWoNBKJNhE1BULSDqnKCRCDAgSpiNu9cm8ga8HwqVPVwZb2f5njOeWRIag4QmtXgjW2J6Bi4E5iOetYVcNl7IQYAK0BJQk5wic1oSXAmkNCicMdVGpbO7vXDF2eb2hlgpsvh82qDU4SmcUGX+LKg4GXFR2WQehfKhgRAIBoVNFeQtnKuZdixZpKlQfpyQqDMVF1DxzObiudr8aTE/4O2uYI/gUeBUKHVYL6+a5TXZXqDGLSS29zVWON0LpbpQ0OxAnN7itCaXrEUSxbBUgEIiUJej3i3sipD1uPIMoXIgGC6ZKIdAhRAYlfK8XJxYmWlsjNux6Pt/dEGoRHg7JuRKn3j8OwYqq7XeNvWrh/AQF+3K4nMNkmOoPHfKdpcht1nLRx8u3fzojX/0Ya67uQcqECUNx3xmJeBUQbIMe5w7SV/FzpJglqiKxd0ES8C4GLFUvjhYMmvdkJaJmrmwztDiCdTxRB3p3QlassYpBsEmqllsyIqsiblScX2jsXsytbzElYpswU3KnJxwhXOSrE9Eg78SmjtT8kDJY3lzIUmKPlFS84kVJ7IYiaoGLSuay8WLRUgolXDkc/lYNhc1rYCiuz2GdUAiyYJDgEolp436tStPtq4921xd12sNVpSTsjyLBo7iiicXq077SHeqipdJPB64EkkYlHHAoELuRDJq4AoMCvMiYhZXBK1yIFco0ELP5KKZVHW5tX6VXl9mbcEyC1JuCaKE40Rm3m5sw7J4XPFDJZoZHMgVXqnEkmWImoO503yjlpuAu48rFwuVmWAYVx3Oos4lbH/hhhlO4jYXNmehglhCUDmEKIdApXzzE5dLoP4ZQiVfX3EarqxR13q6+O0kyjFUnnVdECoxswjhhNcZV2I+s+Lf/qKkLyldyTUX8DQiCq5wssm4IsIuaPneKNdduCBUJlzBmp7UmRSDTRf22kHqBpfNqfNz6ZXl6tJiut2KpFOMLh5aIEKIo4BikmhSy4Fiv8XPEk+q4cmrp4H4QgEiisi1WqJaJZxQ97CAmYJCmglR7IeZlZQhN2uFlcXu1Wd715wzN0Zco8CYIStgRthMuwhx/NkUVDy7Ng0V/wgvKsZ0uUJDf0lxtYo1HbYASzmgArSIenVcGsKIAivjb+sSkjJczOD1Un1uqzo8B18S09vJ7LxRWFCzQ9aLJZ5P1zfN6jqVT0Lx9IAkWEMcqekkm+s1FkEFRPFDhQXkx1FuQsuELtSCflwMeFFQ2b9kkw5f3A8XuRNKNABRWKJX2OQC2uFAOrrI73tEERJFEAVc+U6AClkT74RWee+nex4+R3reV+EXmWZBhVjiV9xg4tUc+/8/YUH0BYsUjJsB3sBR1Ap2uS/pxZCQCovpgKj7ZRab9eGKnq+HkjAftn8Y8FhpTxSx2BO3CDrViJ6keiW7OF/f3sgvj9Jz/Vgpz9xAUnKm6sre3CpPvJKGorKJr/aClvEUN7OeJKvgSc5XDpSUL8ftwp6ulFBcz/LO58IH5BgFU2ErL5XqlZO79TOnu+fPFzY2ktUGnysyaiZ1CgV5ASFP/r9JIGF68me74Twqw2CYgbgWjhqeODnV8gSueGs6FzHjatnM92k3zLMstOySX+HirAdlAGiJp8zy2mD9pWZ5RUj1ZIvJLI7iepMTK5I9bzW25NyIcAK04Aqg4nFlSmOb4m2CEVr2pOQSVFi4wg8MH2Bm6uJ3ty5OTuoa7hBQ8aL0XMjYs811aVBhniaqsqSXIKwV3pZZFkCl9InHvwOh8rzoeV+FX2S6IFT4VIkEFwKpdp22v3D0IivMrETUiGQBKlwomcq3wRXQBVyhsDmJ4h8xNVPujpRcLaZnaRIw6OKT5ck/sdEPGH9sw+0HbJl8uQATUNlYLa0tp4Y9PV+NqWm3NsWfUjxO0wJU/PJvhfl/19Q2ml++wZFUvEkT7/HpIN7ICalCYbjUWtsZnjoP1U6fSi0vhctlNlbS8Tr0Kno+yQ+YoJzy5IcKtWFmFJEACBuAwTnDTFjzxGn2wFOqsKBnhzhRrF4y3YRT0ewOoALhXM928dBItz2p6Zae6RjZtmo19GwfovdR7AHMSiLV13Mj1RpCWmYOonOSbo+0zAKkWvN+KXYPSma6stVRs32Irhh2F8KvgzSrTWK/3Xc/ptW5sDKt51T+O6Rz3HYq139W3tywmkqmlrSqqtFIajVZrUrJ8ncOVF4Iet5X4ReZZkFFsmukRLYOybmGkm2ouaZZaEP0r0DLNjzpdkPL1HFU0lVItWr0UM/W/FKsspGrQ4CT91qcT5StelLsiif/m5j2lFLZupVvZgotI1PFOT1U89VEppjMlvViHUdPqVJDy+ENSxBOPKUKdU9GrurJ/xy/8NdI2nUc6cQ7V0rtRL6Bvxv+YvhzKePPCIhCmiN8fM2u6lZlzwfB/XvSxk+GYOw8eR8QnxfvgGfSa610yxOcSseTZLRIgtag6D0MCsdbklGDcCUo2H5nwL6DR+AxM6xAkrfhJ0Ji0a4sN+ZOq9mhoHeUzJxuAxVDQW1FpKqZG0FKeiCbPdnEcSDpvT3itVpMrUaViqdIshxKsPqViJij7S/39wpZdmWcBwUdZftr1jbXM9mS8ssLokw6zThOZdZW28Vqf/bXMVSOoXL5ahZUqJUktWkh0fZXTMkCJ7xT3jjlVKIaPAqsCfwKhIeSXkwXOv4qd3yhxvdrLiKzr9sRBW+l55pkfSaasR1ExSikqDhRTEqRhGSGT6RxJSIYgagCcyOkculqu9idby9teKoPl+xah7gSSZqe/LUmUzlg08bIE2hhFDu55kK5t9JbOTm/eW711LUbZ18yv3tlc+WE3VrQy13BLMW0PBk7mLAY7Ywl03AYvJLBPeNuRcX2hI/gyf/Z/W4Pnw4fE68N8Rr7mM4RCgY0T5yY7nsSUj3e6LjSGjG1HklWKTQiGC34D1ykxZ1lyoaMqRxfpwKfHibT7Y7TD1wwGvH0IJFdkKw53ugFxZqg9+BRlPRczJgT0qN4agHC+UR6N6p1oIjaDistUijZBJMgKpOk6A4Xwf8fJqXtetlW7AacRdyLfvtRwRbl6ZlXk0aNMxo4zh6olaLCHarjAX1jySLLX5jxnjOLK2ePGfaaJYPZtN/I4E1VxOOmLyBr+VNPFj7x+Cv/6CPc6RvxLzPf3KjUmahV4vO+ahzrWIfo6FChcH1Yt0NaJpGrBpQ0C78nU0zSVOCEUnshwcjBWETltH+OlhcSINJghcXXdkHLEjAoGuHf/KH9n9BM+dJ8fbETfwNK6uwipGzZLhjz86nRyF5Zya+vV3Z2ytvbxc1NnEPZ1VVraQk/xXGi1YkqJ3dqp3eb5053rjw3d9WVgyvO986dbZ8+Vd7cMIaDeK0KxSzbbSSs6jihbK6gbnqTHNkolITCySpTUuPTNiWJsYwy5wqTlHQ333ybclQHE0mwXpZulpdf/FisLscHFT9XQBGPK6FEmYvaQamUzPTVdIviz9Sha1Lf56yVbmUGPIGYrw93u0vnlMJS1OgmMvPgipJZCEn1kAB/OidnV4CQS4aKlzhAVSD+xDC3QHJGJcosqMyqYN9DFBr9yxZ9hyXsGDFxJxR2YufPHlTcdgb4qwoWtY5mL6d5c8dQOdaLQhcFFaZUHjgBWkS7DLq4yV0JY09A3uOKqOfADHCFIgF7pjQSWvC1Hc9RM5VIAnwyQBFwxUMLxRKeCVSmqjp0nckwmHK5YLEYrVbjjYY2HII3meVloKWwsTHR9kSp5ZGxOJ/od4ROM1TIB/M5Nm84Y3GGzqRrOAIknih3yy3kpAE0LZnuAAAQAElEQVSOwEZCIbR4gx29E7ejl8uVqRgP1cQAKpMUr5g83as/MeHKHqh4XAFUPK5ElRq4AssCyakWjEhcrUYSRcrLAj/CUsFf6+7sg7HoupkfdlevyDRW8CZxvSmnGVckY47ja2G1m7AXhfR8PAWWDCbyQcXPlZhcZ1xJlMGVcUqYg5ZxtpU/K4yg4qX5eiUgDl0uHSpTXHGaQtIunBuTh0MKP8tQod5rHlHYDRxD5VgvIu2BSvETX3j1e//6EKgAJEKmFDGyoIuUrTCcwLJMOxVO0CZcEXS4EMUqk0HxtsKmBgCHsTIm8bRUoZnMlHnNpgLGPTs/FwWVPa23Jh1TnLA/1mhaqZkboB74XnlKUnerZEisM8pYqsak6UyGyTQ+pxxiiHBCIImkLCo6YdnAjgsBPNjYsTFF/PaFTly/IrulmuRXKBeO5T0LSohXAlF5v3CdfsRFEgdAhbhCUCGu0BFcYWiJZ9VMF8IJpYqBH2y2vG/riaaesPqSkMmJucrwRH14KpHuxpQ2BKgo1mIw2SauyNmlS4CKI5ug4m18eZ21nEaNKW+WolcC8syh4u2AUdQEOJlkeY17eT1bUCGcQH7jcgyVY72YdLFQgUcBTqJmjk8XQBeIuLIHKh5XCCHwIsl0Ka7a8CL70eL2FXasjGJXwBXByOHlRyDKRUAlLGuRpJud7M8rc6vinTbJlMHlr/D3aAF5LPFfdK97ckoUJxpXnIAlhBNiyX5NiAKzwqY6soQ03B5lwbmTxPi9LAFC/ERxL0rWwJOfK2CAlOpAIAqdw2oALWG1xvoKK9VkbiikO7zZwpWAzNBCxoXVwDv9d6lDCRUoaXans3DSKq/GlGYiNZTMgVpcjJkdTq7iqJeXBasf0VsQb/SIKzgSV0h8sgURWrycY+aHphuieO3lXST4Vvaj4GQ/VLw9KNqGcrkS1mikvLOftqe6/uDYDFHBv6l1oIg6boWpkwGx9wnHUDnWi0h+qDRu/VLh44+85o//hrvhDZJd41OlkJrF0V+tApx4Al0AFRy5JHMVDCH7uOIP1MOLgC6wLPAlfq5Mt6zX8FaimZetUlzPAhvUeeUoUJkGzIxuwTMq6v2v9dfBeP32vb7IJDIWE3sxkerhhFwL9ccknOx/Ps21pOYrXgPmgFMhH1etqGzuCZ8QQvYYFIgZlDFgjgQVbx8MRzb912wZ5cWE3RetLs7HnYYLkwL4cV93tr6LKZaw5GxVlTu7jeFZXu0Ieg8skewhWBJU6pxQxLlSGImZAUwJEUVIDY4CFf+Wlye22vImQWUPLS7ZqUw2oCJ6RLJpYuM4TvPsQMX7FWAJfoUzdGDf/tsxVI71IpIfKuVPPuY6lY2rO6snw1qOWRPnOAsqECwLO1EzB3IF/mOiaDIqp0U9B8sye7iWK7wboCKlCgDMCwQq3tLPum/JPvkgMQmiGCkvuML2wcZE2QMVAonbzktirb0iqskbFq+k2QxHd6Qxi5oQXfa4E+rb7+56OdeP6lSAE4qsRJJV2Z7Ti0v+jbKY3o5qLUr8pWr88RKvOwslq3RlX8DDGkyMVVror1xlFBbCel3K9qGo2eSSZU7E/x8ttbQAnJBZOdSp0D4Yg0pEzHkd8gknbg/HaX54IxSfCVQ8okQTWYLWfnRNvfYioYI/EY54fz6ZJ8DQJtg0VJgoPfpAqOQa68dQOdblIruz5EEFRAFXXvWev+Kqi3q5C67ApkT0/IQoRsEPFb9fEYzcwVzxQYUxI5qEU5GMPCzLLK745YVkABi8/9GhsjdQP5Z/9olfs6r3p1yIrB4o/y6Wv72KHzCznA0zPc60McIJjAvNTp6E4sc4oRO/QSGcuN4lnCBxIemoTgVEwVHPz6v5kYcTesk4BbkWHVfju9YBIInoXBhfEDR3RWY7Yym8Z3t0rjTcjVudEF5lNkW7J2S6DC1SQc0vkUcJJOpHgYqX+uUfvuLf/tqz3B8FJDT10pt96S3oYTGD5Z4ZCPAyonlcebagwobZSDbkj9XvMSvHUDnWi0kElWJ7i3Hl44+4TqW6yMmWUek1l3bkXGMWVCJG1vMrsBQHcmXKhThcoZpwqtU4nCu0S4YjF5EjyTSv2Qeh5dsHFT8Y/PJDZX/2F2nmdpmkuNbEsHDCbpKXmCZpXT5FE95+l7cJ5p6MocK4giUe/EjYfd5siZmBJ8mao+ISLPEUNjdKq3pxRbKHEJ4gWH06xswOhJdHdRZxCSlVqm5hs375nBea9q+qEP5/ao/OKHYPKHLvIdWPKU28hNcayUwfDAuBH0ozprSjwAk7aUaTjYhcpyN+GnKSjB0VKHTvtSmjtdu/gh8eJHcROClDMSZH5zoZFPIT7PqsepcZAfk9H38PY8iUUFjevWdfY8rxpzBYdyNfF2QuJnKh2NzHHpr/+MMv/ZPPcGduys6tpbqLZncDqld2oOd91TjWsQ5RobZU62xUWlv56qrxycfTtzx50wf+hss1WNd6XtNKHfgVtdgWrAqgwkL3/kFb02KzHY0saxbp40o4rod47UBR6R+fSOM5nvwE2rN1houRRAo0SqZL8DrU9oqDH/JLMiBKQfbSmqd1UN/7hNPJ+ECpuqcpC+IHiZPN5eZ0jROIIUCCJh+zDS7FZAMuFcPNLmNH1qFSMjJxNRWW1KCQ5KIiF5PoeGCKF0Qjxbwtr0lwPiwxOVc4szhKl5ekTE/ODvxQAU4AFTINicy8VdvEQ1ZuMhsqHldoo8wpKHG3cQ6IDUQtmJvWwmmrskgpy4LeAVdAl6BUgtTsMGkNwQ/KGbsoqLAKkn2e4AJQieiuMwBCnI07jyi4CJyQQXEZEJ65dXZpUPFyvSYs9Ddjdl/OuuZNQSXMhxJq+8N3d/76npe971bu9OtAlHRv6Rgqx7psVF2Eap2dZv+kfvNj4Mqr/ujPuMEqm4nCa1wincjWG4vb4Aq8C5v/uGcq8EFQ8fsVQsV+olDdO0RowZGedjBRptGCk5BoCFpW1HPUPYyjrTaHKISW0EyuHECU5w4q7u6WpLAeybJORAmbGSFbZD0ljXQgLkOMIuMjnfiB4d/y8ojieRSKpkwpqrXEdN8oLbMdsEwPEm0mIIQC5qnKeqa+lcyOxPSQ2ZdDoUJcoQBMzOGKl5e1V1GLC+B7QbbYXGvNnRa0Bq/UWJMYcwDxaouLlwAYWBa8FUsTmAEVSjIepwnY3qhKWqY9rlwwkXf/XhMFM3AEUVzYhMfMcLa/nhWokAeCyKwEJtnDhk8OddwtviwTPUdUuajE1TbOfeAzrb97pPG3D7d6c7VWr9jYgkq1Xej5XzWOdazZ0prrELf7uh949yfTn3xQ++g9nJISc5WQmgVFGFciSaClPFwr9lcIKrO44kGF1yZc8SzIHqhQixE68bce8WcYH4IWHKk4H0QBV4RUAWKNgYkrEqvHZIWZ49pMTwcS5VmEir8Gxa1roXJLhyUxK8ekZ6johC0gY5DAqUB0zrQPJwfuejGEjD3KRPn2TiIzjOntVGXVDxUQBWbFbmxDVA9PxwtCBYrrTZYq5nDFC6TvhUrY4UokzfE2WNJbPF9sboAQca3rcKUH4xIAkxJl2epJqc4hUPHiK3u2v46SwutHyH7weMu9510mwHiWoEJZXt5One+GD4CK08VgAhWWPA6oVNev/svbux9/rPJX97f78/V2/xgqx7pcJFeXs3OnuK3vetPvf8yFShILsR5IZmJmkXFFwD8lJazl7NYC0ALezOKKHyoeVwCMA7lCNoUEbuGIJwAtXuXKYVAZc8WJuMgcS6JlIAFX4maeN3LMuxBOiCs+zYzBPAdQCabSoTSb38Umrzh98plTSYxHEYsqA5vDkimcTENlD1G81K/Jltd+qCj5Fbu5qxdXQsmmVpyTsz3Raka0ciKL/4RnrcYWTpTCEiTnRqyLlwMVDy1QPN3zoBIzmnAqMBasZNJRPFmKSnmvp4uvrUuKmnfhhMryc7XlWm8bUInIzbjWBlTAEkAlKJVwIqcHHlH8gPFDJSRmPbOy3xAcDhXvCV4puxtBiWoH6pC6lgNhxoVNiqvT38Frjz8LPCHB/dVO+hzLEaDXuhtflIbPG1xQ5nILP/3Ovyx9+sn8zY+LO9cHl88VGztQtrkFPe+rxrGOdYjK9cVqc5l76ZtPf+ShzQ99ZuuvbuWSefadTLZgVmBN3KnAWPp5jU+V2usnzEYP4Imm80K2DOGEGLMfKqwppIMToAWaBRW/WPuvcYGkCw9HewL+/oyyyXWnMp/Zl0RKtkrJTJk6HItmniL8rKX82J2EZcPfUPIoUJkSzIdpcqkUl06zbvaZTNC2oZhlC9l8olCS8kXZLvCGFZbZZC3atnLBIExEOGH7XaSoSDrQnfjjKAd7FIqpJOxFKTOyapvZ5k5ALgIqIIpeGuY6u6AIpBaXD4cKzAq4MgsqglIGVzy0TDp0RSdccUsmo5ao19sLV+m5JS5e4tUWBfBZcQyfgykBV3ARJzhCgEpQrBwIlT1OxR+6OCSmQnYkME7qHVuTZwkq4x42lPeMPwgvFyleciBUPJsSFr2IzqS0kwq7cBuMPXKNK69kPvoI9JY/+PPw6hXHUDnW5SIQpdld3/rLuzc/eBcjyrlXMahAUopLpIkrOGdood0w2aguruf6o6CeAUWIK7OcChZxIZmJiiYocohTmXYtMg0LicppGhbi+RIPIbOgMlWc79TzU68XKVUAY9Qs6ydvFusQta+XrYJoZnnNOiJUprK5MplIPh8vl6VaTW40oES9jnPgJJrOsOJHGcyQWbcxHAXZj4f9UJniirMhdiBR3NrGGTiZ8EYtrCv5NdDCqKxlGithtcJFtEJ7uTh3ls8M5eKSJyk/EnNTUPGbldlQqZLiyQovl6NSMSzkQ/Gcu2S7LbPSgRhgwwIGkWS12t8td3dY9F6qwrLwagf2heOLEOGEiELaAxWPK9Q1y/fF3zqEKP4w/t4trxn+92Kh4n1AfHb8KXDkIiBEdhZUyM+BwYDx/uwv+j+YlzJcEN+M8oDx5p/fufUXd13zwQe4a35Q725B2dYK9LyvGsc61iHiFq8NbL6i9bkv1m559C2/+6ecXgNLOE7gxBQ3njzP6wWaDcxmzvMyuGK1h83V7ZhVCBm2txt2IFT4hMsVL4hyAaiM/4FTyIS016OM7QvzJb739LjF3iqcJAUjCheSvXPwI6amAZK4nqGRKqlSw6q0zFrbU6re8ZRuHSyzCESVpJQtjL2IOzf+/2fvPOCrKu8+fpKbu/fee9/sxUYUFHHP1lUn7rbq29r2te3bYbVD7bBqFWTKtG4RUEBUtiB7q7WOCggECBmEJHDf33Oem5OTm3uTG0gg1MPn+zmfw80dZ/6/5/9MiQpAFSKljrQOpe2DFam5fvmqKJAS+EVe9FMFKj3orJP2OvmC9Gp8vlHIfw3eoZAKTUf0nlJbeIDGHmEkRmNoCLyi8w+U2kq6lQqSFTpkSxdSSVMLrUho1FbDjwAAEABJREFUq2LBI7wDasEKI7YDvbM0VjGatv5SmUsgFakuKtaEkcGwrxTRlAWZilRLG4DRaSLbpULHOMmYr2STCr8fe6qFsdjYW1KBRaAQCBVHgOwm61Eq18z1LuyExGTyGDEnPJI28aUillvw61Ktn0wEGR0FqYyYt330u58JUhE4U2CGfudHr6z0btzt+OhLBk+0GtJumDT9UrAoLXCJSGOHTrBkTcN2Slcb1Z4QvKIPxJCySKzuLqTCTXnSI6l0VkvGOvy0FmWkUTJbSVMgNVDEMiPACowCr6TG8ZWqOwzrS0b21bXDm9+eDLvCoda2k+pNomDE8pQ82IykQK4FqUIt+h4WOrRwZ6mkGhC3GYU0LKbJSpYmxYxICal0Hu+rg2Bo0RaFzvWLFaN/EKMKKK3FkYoxlsAgjaNMjazFUaZ1lmc2CgutXJGY4nxkhhAHnX0r1fdebSNT68hNjNTAr5Tm+saLla5YyQhPqFqm8ZLB9nUxsT6OxAUiyZO7tdZCINOFaJPijjMQE7XQojZ+A9wUcjqdNVvMxU4MQ39OorAqNE6E6W5HCUsVf6XyDxtXJNUW7u28kfkdZKhNdki0PJlfrApDgfkKT6qynRZkyd2AG3GZvIg3KDzYGGxS2nAALHSmr/b+lXSFMbl+9c8342v3gnOWfspcdHuwuNoeLPTGywHtDmmLjwCB8EDgiA/OwlCBXsSZGNav6PH2x3oGbSRiThCsLIEQwVA4Cvii1SBRca4jUMVUXSw++1rzjl22T765eM32s979UKRSAbHEDjqPYw9DwBO8STvIiL/B0mp3vFSstypMEIlN2rZC12laQFcoIrUxjx0VONtou+nd/bgxr9ig3Jm0voH80eC599AsoevvSavDOGH4RVt8aXV+Jx1hhfY7AXxJZGgl3LGAq2s6SIXWmrAVJ+X28FCpMS7Sht1xUjpPZp53lJGWxzlIha+WbFIRa+ycV9Kkws24xRSY7d6ywvKRemuMUYUgFRgFmYpcH2ZkLqRBensxlmwJWMoo3Uol9Ss0k2hrNUC8pbLnOPQkaxRTjlKhRslXuGTaGKTC9gZ1ZJMKrTURKb1wD2cUrmd+RqlwMDobY/cHV/6naEPN8Pd2jFz2r1jFEHhFkIoglf4mFW90sCcyCFL54ez3Hf/aZ9z2n9HLNzKlQ7NJhVOLSG2Wm50kUyGP9nq6YgsloBa4hBqF1lJkkwqnFlprfWJSEatNBSpkMAY6OWNWwfA+1a2cTrFUqE4kytRx4OrwM0viZKRCC8GQrChspUhTDJ4quIRR+vXuSn/xKLwCr3SWSmevULqVCucVOj4Y13y2Qz1HgUGmdUdLhtkCAxiFR6T2s42VAwpDCMEaCkG+ojRG6ViWuUmlvaCJKkGicrMTAOtJaBbpQEeLpM/0xddJdqk4OZB2kHRKGWCkHkbqEymCtH4opROZFzAKO0FukercSpU/X2RLG1qms0XSkbjEMg9jq/zFzA+8m772bd51zoqtzCXfsyUGAmeiGNiKCPHQgGigig7ikoHoQIFexBcb1K/o8fZHekYwNBjQoi36mOKNDmUZ7IsNoQ80TMUVTOWV9k17nFv2nrti/ehVG8kEU3qdROoSS5xtTV31nSEjmmjNMpNDYrCRbhZqI2lSL1FpHL5QSZXe6Ycw5EZ7Z6l09gqdtTfDDIY5QJMPbEyaWjoPasJZhHuxt+SRC/xAT/MSClzCNQbLWi/SQ5F0n6kQ7MQrRm81shNGFYBdfEUjzf6BnY3SWSqcWrqVCvVKgdLKeYXfz4Pf4cMRGuSODlWYYnlKL4wi1fqhFnZ+MB9beROS64O5FX+113bgPchR2K7pZlrKlGl8sPSJ67NJJTVeckepsKrzkVIvuY/1hx9kkwqMkqewFogdUpm7vVxLpOveKFJTgdTN5NsYYwljKfdv2Q2vDPtgw9nLt6RJxVpYBKnEgtW++IDMnO6o99+HPz44d/p6Y3oqFX90UI8IhYeArqVSMPC7D85a4d1xwLph16jl65jyIUQqGjUnFTLKbyapkHFzlXq4BFKBWugctwzbBRie8CXKHKEEPpuLVCSadq9kLc7KAaoWvl06OKbT8FmnSyoQCQdVC/eejOY4KanQdsOUdqM4K5CUcMAlEkOsQBdxRIbZo8OoP+jA9UDtLOOkQr3Cl4rcGOZLhUOs9YrUbiwlOp9YTRpu0eFV0gax53WWNCmNQdwVjkAFo3Dkq1yQk4y4JEz67SvdcIxYjWDN1tKrUj0usRQrXakhJtvW6XRecq2PjrxC+smzPeSzjDjZbpSOrbnapUJ1koKdB5MihktUPiRYrDz8+fIAowwyigBjQP4XZtRxRl+srRqtqz6f0XgYrVcmtUjEKYlmG5gyq1To6JZiB2Bs8Qemz41s3udft2vUR18yl97ODL+KGXSpPjHQWDTYUTTYEqsOhrMQGijQK4TCg06A077ZaYSDuRJNMRjEAgRPBA4bbC4cbCkaYi0cai8ezpx9PTPiOtuW3dbNu4Yt/GTMyt10nF06nDutZBYpLCCbVPLYXnswB21DRStI2J7hpN7b6A4GiyuVZifyFcAZpbNXUgPLqwz04+2cnGA6O4Z8T4dpd7N8NosM+KSVX4naZjHpMJcJW/BF94XuKd1x7v3dK+GERMJ9OX4oJ6kga4FXDJ4qpCxwiafoHI2rnPaoTzNKRqlwXuFLhbhE66VIsWzzSocOkjzgCdq1xeYr8xcOler9+SoP8h7kATJdiAyNrHRjqTJFiFGUTqoQOhEkllziQvulE6OQIq/2YVeyjWHMJSjZpMLlKJxUaEEcJEcnYAb5pPgrRAq+lIR8UwmjihTYqtzll3jP/S4TwIF1MVJrgcgAqaRai/VQKim1iB141mPMERBYvxteOWf158OWf3Lv6yuYs642FQ8BkIo5WiVI5dRwYjoJBAf0E05SKsHC4Up/qavibEtiCKRy/fyNNy/a5t65X7/289HLv2aKLuZLRazQ5SgVzisKk4OIQaIiUmFrEWCUUEmVzuHDG7ja+2xSoV4BvSIVrnAMS1o+RmtfkBXRFdDh+3kV+z2VCv0vV8eOUC5VmWRqM7UpzdWwm+Tg4MhIMozldfJ1J2mfbU99cpEK0LsrIRWjt7rAEIUqfCWjTIGB0Aakwo3a0rlmhZMK9UpGqSBfkfK8wh+tqyNapkCdpzAzBVqNPRIqHWbyFuWrkZT4uIp62jMfCQ2+ihsehnb14P4r03gVOj8RVb4xNdilWJ8nyzoqfhdS4YrU+FJhFC6RmowuA5eQAi6FJ18ZIANfKkOAUYQJ6iKV96zAkOt8g65RWasYZaxA6hZJXDKxSSbOoIqcpCJxgTyFAhD7KhyMJfbDGfMHLd4x8N3tkS3fhDbtDmz8IrjpS+b8O5mzbmRGXpuF6wV6k1E39ADuU+dc12+4vmeM+B5hOMu532OPwFWV81a413/m3/yl8/0d4dVffmfequsWfCQyuhiNlc7czuitBHbKkLb2u1mkwmtSxYhVCNZKowPLVDtd2qFPZXBHiz2xEoiERtjOXuEPL89Nl0tGnj8JqaQVeaVmtWI3NVUhBM10LIXj4A99n3UiL94kxBLsFHbN5JAjLTM7sU6nkedGESYZQ1v/xJ4a4sRItRTAL+YiFZWthFuBS6ANRukzBwfRKYGhEK4orAupgLTiL3iFqkXaBmTQPvZ7mlfEGjIRgtxEvCI2MEqbNVDqLxpMi79oFQvUgiyBERnJgJJtSQkd3YQmLu1TyotMpNNlahxiPSPSZmvrlVEqtB9JRqkgeUIKRYq8FJ5UpqLwA6QpJFNhpWKJj4kNvd5WdhljqWYUUUYeEcs8vSkVGAVescYZeyETH3XOyi+CG3cFNnwd2fq1f8Pn17y9/dp3dly3cCPlhnc3d2SrQC/yvcXbcof71HULN/cTvrdoa4+4acF2cOu8reDKhZuvWLBp+Psbhi5eF/v4m8CWr2Jrv45+9B8mPJBk51obA3+kSUVryFEqXFNdPP7L9WyndOoV2t5JolJZXL5Emcbm4Xslo1QoJJorTqp+JUMZF/+/9K+81ln8GR75woAqMgJzcKQ2mB3Fq73vi6SDRbrOe9Kyk66zom7hBsMnXjH4qsXGGKyAnEPjSnVD4VYotAaFriApwUfwZngFr9ijw7AOi2AJi9B38qUiNUU5xIYwB4Ivh1jr5+BPS0xrWRipicCrtE/1TxQb5TqPv2SE2lHIIBHR+cWGYJ7GC/BfOIYIRoZUxsMUWLBUGEJ4JS1YkzbEIh1ZijuS6oxiKpBZOejUWAVSJ0gNmqJwILtCdgKR5CNn0gZpMVe+3CdSkFHLkLIw0Jjak6eKEqOYy+1Vl8fOuUGfODdPHWRUAYnCLpbbyJdDWh2bmWWhk3J4DbI7/1Wmd0l1Tkbv+/ELb4xd/O8b5m33bvhPZPu+2LZvOKJb9/DYK9CLxLbtS2drDY+D/ZzItp5B9yuwbT8oWb+v8KM9AxZ9MeT9r2/9YMd3561lHCWMJaGUmjQKKARpvTnTnLv8cXxNHWbcUnbIJPhQYYioGNqqWGAUX3m1MRRjNEaRwVpgtOXpzPSJnh/E+V4hrXvZlCK94VmW8JovTic1V1W2IJ67nLomW7bU02KrnuRhROR0H3nu4aYZbv/OcOUYV2KESB+hBVnQSZpROkuFlnchTWE0wQJDFB9H+gKR4EVa13IyUkG2IW6bljg15DCuP3l64kJHXiHrKrc7MdQRHURdIjGGyIqajtqSqjNHHiPXB+nwYhmNQtY7GqV96C2eVAqkdhYilQ4jmMmdIrVXqg8zZP6YAKRSoAwAGIVIReEkmyQNaB3VkXNudA28Kt9ZzWjjjMLHKP0wSp9KJZXbmYIE91lM8aWQimf9V751X3B4137O40uBXsS37qt01n7NY3c/x7OuZ9D9cq4nFK39Jr561/Cle5izxjLeAUzhSMZaKPJX69UOlcxMpKJ19JZUYBFayyJmy7JoNQlRi8ZgjRW5CstkVhej0pNpRVQGeIUvFb5XkPTQmo80r/BbTPHt0lkqaWH3BIJ4tn3MJYvqLalk617D37tUeRdrwQ7fidDsjw2IVZyrsSUUznIyFot7oNxZnU0q/JIupCzwB6PyG/0DbJGhVCQnkKl08IqalGVJUykLO+aK0gavdCgTY0flStWIiIxA50gEioapLBFkNiK1m1E4aCWKROVWG0NYZ/IMqXIqTic8oxC6nGclNZJYqryLdF1s69joBth+SIUMjqnAfeIBYlUQMLKQSIkEJcToC0XhEaHRtzjKLmUsVSJSGuaXK51iqZUzyglLpbumxgaJ3CSW6QukOpXIABgDO0qd2twONwkEwSLQm6itmVHZzwzUPURj5RDh41KTTulWiK3KggAQKSwStT3fpmdMakarYgxaRq0BvSAV2tePLVOSG+3UKCmvFCj07qC3sFzt8jNak9hkxzJNKpxX4CRaxd2hSZgycylcF0H8ZHqk97S58EabxOoAABAASURBVMlwYnrrsBmdMjOGxOV8ndZeGCkbCaPAKzAKvJJNKjQR4VoS6zyVtCgM6/boMGqUk5eKLDXdvZs05VLZ4RVuIK+UTrj5GWn9gcSSp3S6IgOs/nK5MSgzBORan84ShVHaZ3PJN7JNk/V82qsrskuFGqWzVJBLkQlgkKCw5WzYAOIznRdQqUg0CbE6zhiL7cXnR8bcpioZwxjLGX0pI3blybzEKKdEKmRIu3ylVGFUFxiJVHSGdKl0IEsQFDgxNLbMqB1nBpoeorWl0FjJbauyGzU+eEUlDurk0dSEDhatyG4QmQ3EKzyp0FERT0wqNPRTtVAxkKIwtrIhn+14D2E4E6XmUJwWgnWWCvUKqd5QG+k3dCEVTi3ZYv1JDXOSfZSUE26ddTJS6dybh9/HBUZJy8wYOuoZDaCRytHeohEyeykdOBK2aJ+yvlMTL+51WhnDqAMifQRe0XurSP08pxaeVCTGCDUKO+VwILNX2OKvNtzEK2oHLk0ustORKHm97nkj0ov1OmvQ4o7LtE61ngyfRcp/sg+70qEQKVsPeYWVQIdRkdhYlyCF8ubLA2IV6dtPStUUBFotL9fEJMowXJKviDC6QrFroH3wVf5zbtAGRzDG0gJlIF/uK5CYAJ0TJbs8ekcqeQoVKJBqAIyiyNPJCyx4cpRLzEDKIhGbeFgEehGpxJoF82lBJrX0CImsZ1ANyGQEpZSARBnkwxxqDZ3ahFZN59n1QKo3i7XGAo0BtHklXSod6FRd356p8IYnoUVhxCtc9QOpilAZ3UFPrERpdkqQjuittPtkRsFQUm2x2srTUh0zu2yCzDX6ylxBcgqFkUsm1G05Gz8t4zTD7/JCC8T439lBKozY5ooPC1ZdKLWlbMEtO0uFS1/on2iFPyP3IHcx+gdAJ3AM8cqplQqSa/I0hBUFkgBLtobCJyYV2mQZUsmTu+W6uFQThWbIZDA8qRTIg5AKchRIRRcdmTjne5YBlzOuATAKo4oxUs/plQqAVABtaSbJwOkPxP9NCFLhSwVGIbOb0LkOTSrGrNY7vQqTDTphZKpsxV98Oo+41VkqdKAXOhGWTGeljY/ZmEhq7xUmhytSpHX6ac/8LozCeSWP3eBUPY1Cx+/a0rlMjK6kxWJOKjllD/wZFXmcFqlkrM7hf1sGqZDmVRwSC8PobL6ykgGjTYGBBYYoVEHr7TsbhUtWuD9BP6QoTOGFXczBQTBKWvFX11JJeaWHUuk86TSZ1Jo39HQaPZYKb4DItuZkPjkZf8xHjhjbbpiR+wCVCqMoLNCVM4ZCQ8n5obOvw5JRxkC+LowjwyisIDX7Atv7va+lQgVG4Vfm8ycX6jDREDuKc+6wo3Oewe9vm1vT1C05vq3zp9JhJ6xtI3O5St9BmzblTtqc6t3CaHVAIieIFQRGRxArVQSZQ8I+mQHS7VFrkButSrMd+QpylDylNhepdG6axe8U2V5gRb2iMsIrgETDtjygQK63BGKAjPLSsf9Hnq4DIoNVYnaQEjOuEwltxUv7jig75FXc7/KXHVIoRY+HVzlJZ3T/W7kopE2WBNq8rVMBWnapkEkY7VhKtd7YgIu8xSOhh4xlX/zKFc4ryE5oAzDYiNEEka9g/eSlQktmyXy6SnvXUmFEajpPDpOvykUqHcYe5vXe5wsmTSpslQ+ZwQX/JUMAsL3lOamw6wlIxVZ1SXDEtbLQcMZcQvo2aklzBkbpY2hLNtZ//VMqJxA3z2hoSz9uyW/419kNfEn01F6CVKhUAO0zQPvSI0Ep0Bi0drfO4RFrjaxXus9Uuin+4uUrdMQUicYs19uoTtjyGRVSFr076IgUqe1ergSMtAozpOC8Qmr1oRaDrb3ZMY+03efrJL2vPi0966FUTkA2vSuV9OMsUqXXoHSWSrYnd9xd0ZIhFUPHWLxFakux0VWpMJdpHdVKW2FGFJYiDjLtig3B1E+GpHSX0zm75MYoXaFeERkCgDERlBpCqnJe5wYqdQAw2hBDitQCQCL1sLgADcf5IhsZzTff3EfkiywsNvpzdAQU/LpSGZZIfDJZQCz2SiVhiTgEsCKXRWXSiNU1oGLgFSWVl2hNJQpxQCbyyQv8LF5QUOCh5OU5GcYh0Pvk2XJElGdnsaYhzjMDBWMqYDR0HtcQIx/AOBmzduzMKUxVCVMYZiwGxmFhjDZGb2HkDoO3zKQMa8RepdjDIRe7gVhCKJD+lyOWeYBE7pUqfBSZ0t81CjVBqXUBld4JZGqrxuimTVeofujXctCBJ/IKHLlA79lUuZ/UWFCgA/n5GoZRYimRGPCiXu/2eBIWSwD/lclMWq1TrbZzKBQWpdKKJR+53ExJ+y8FX8ItuVco+DkKfotuTC6oJSZZnlbFaJWMRsyo5PlsLxxGUlCgAXSeR0bOotQQOsm1a7quSqFPIXncSAESdU7iyVocJCPjl9j8JdVnXeQKD5Mb4kpLeY5SkRhi0AnUwsg8Un3Y7K3EElKhXslFKnKFFzC6MLySpwgCvlSkMjeHROroY9p/Tib3wCvQCaSiVkexAovk5/mgE5UyoVEX+bxnDT37+mjRaJ25VKUvVMvC0Am8ImKcMpEHQCdQEQVfItD7pK6T7pFJPFKxWyp2piEX24FTH9ZLnXbGGpD7Fv96WhljZsLee1+ZdfdLM37y9pt3TJv8wKv/zC8qJ/P0iUyMwilmLEDEko83MwaG0X+bMLCYGLLvFEt3mBiRlU6OB520o3IiI+8sFWovKhVGZO8W+tBJawppNIdLdDoXIjVcgihPvQJtWK1Btzuu0Tj4RgH4U9d0Nk0XcGrJUSp4G1CJjfCKXmQyFJi1MgugzdK6kAqXFZ2MVLjyrryOY5SdlFRwskm+ItLLtO5E1Zhw6SiZPibVRXORitQYF+ujSFb07krSH1Dlc4QG6RwlnFdIP0FWJxAJGcHe0E6exivS+VMd4y1OMqHmoAhT7mXKPIQSB1NsZ4psTKGVSVhYjH1LlMfIEsanYqJmJmJiCu1M2MicXcYMijEhExOxMJeepbvtSubsYqbCy4T0TNjAhIyMW0XeUOplgjoWbYqARqBPCKp6h1Iz4ylgopZbnn/sR089/suJzwxcNn7oqknnrJuOleqFTw1f+vzIuU9duXza9fMmX/bS04xDxriVeD8hYibgOolZmDgLLtduSV3PeL/5zINuOfYC9yYF92m34G3kFtMxMS0hoSdcUMH4FUyhicAdE+6w4DaMGJiwvnsiWiaMS0LG+CSMv4BQaWGKtEypgYnImbiKrGMZljExJVOiZ4YhyBiZYh15Q47gUxR8qlvwcyChJj+KX8wFvL/YxJTh8tASccd1TEDOOBWMXcboFQRWJym1qDSAX9R28lLh5yg59srsMlNh/0v7rkMMsELxgEv0jvJcpAKjwCvIV2SmhNFdrrIkREh1TTFAvdKtVCjEKEbbnW/P/MHil++YP4NlGrh93gsct82d1HfcPn8K/RX86J1vTwd3vTPj1jlTsUng7gWz73x79vfffQXLexa+hOVd77x4y9wXbn9n5ti3Z2DljrnT75o/8555hLvfnnHXfPLxuxfggzPvWTjr++++KND7LJ7VK9wyb8I97834yeuTH3xt0qMzJ/1+1uTRm18cvnrKiI9eICtLnz9vzbSL35t4xbIXbn//xdvwkfkz7p03/a7XJ9/52iRw+ysTxr42Edz6xiTCnMndcsubk8DNb0wEN70+4cyCbja2n9ud296a0jWpO+vtqeDOd6aA2+dPuvnNcXcvnH7PohkAK/RmoeDeAbgH0yJAVnDzzp8y9p3J4LZ3JlBunjfujkWTxy6YeNPc5+58d8o970/DOl7BCuWuxVP5612Db6DgG7rl9oWTAH4Om3HL/PHdQjf4+/MmgjvemXj72xPunjP+zjee++X8mUyhowuppFXnnEzxV+49/LNKhU+BiJBfQGA7rutV5kDJwHO9RcMR91X2BMFWAm1gCfhSwYsc1CUUqEVjK6LJikobBAXGYL7eTyfdUuiCgHGScgamynzx4smDt04dun1a4abxxVsmxLexbJ2URnTL+L5l84R0tjzL8gxh65Od+GsasS2ETO8U6AvSj392uvqews1PAe9OQnA7IbD9r+GP/w6inz4d/dffw5/8LfzJ49F//Tm+8w/R7Y/Gtv8OFG9tp3AbIbHzURD/OFeiO353RpP7nuK4sfyJ5XEe9BX2ryd9fMJbnwHBbbkS3vFs7nCfCmx9Okdy35LU9rDb79tOSHw8Prr92cE7phSu/vugFc8OXzOBCSiZkJoRixiVglGpGJmM3yw7rY1ARqmkNYk+8SIv/jSXuUgl1SOEDCRlCZSeHak8V2oKK6wxqhOYQ2ktzkUqSFmQ9KithUBriGj0YSoVGEVpDMu1AQCpPDRr6lXLZ172wQsDNk0auHlyydaJILGdZdvkNFKy6Ts6aSy+bRzLs4TtT3XiyTQS2wiZ3inQF6Qf/+x09T3FW58B/k8I4Z2E0M4nYZTIJ08RPn0SUol8+gSkkvj4jwh/VB6l29sp3kGgsolsfzgXTiQ09zMSn/w+Vz7+I8tjLE/woK+wf+30qZ5uD6IwyN0TkZ3P5U5nu/SutADd/sBOAlbgleotE6o2Pw+jDF753G2vjxv7xvg8vbbAZMjT6wF/VIKeSoUMccbOhskUKHs6FhmFTiHTjVQoTJ6GHciEVN0zCrslWFE46AKDt0ysjxo8VSpbmcKSNVORmWMctKCMUbgV1oTFUyEmI/i6FPa4yhBW6kNMif+yubNL1v25astT0R3PxHb+o2rzJDB20TRw7/xZGbln3vQ+ZmYWsrx//gvp5PRtAr3FyZ5xWrZ5z7zZ4LZ3/gluXkD4wVvp3DOXhX0n5b632vn+W7PAXW/NBGPnTO+WO+bOBHfOmwXumj/7DOXut1/MlfkvEea9wTKHx2uE+a8QOn2qH20/b2PoWcuFnm7PrQsIdP32d1/C+ncXz7jmvZkV66cP2Dy78F8vxj6eee6KF85eMomJOBinVtTWT/MEpAKjEIuwHUV7WuSVx85BQMfizEkqYrmlQNY2h7zCzqicEmMoVD7SERnGNvQqZb3SvVSkpiiWKntRnsYv04XM7nK1q4jReMRKD3KU7y567cq3X6rY9GTp+r+41z2e+OS56i2Ty9aPZ4aHmEFepjKYmQpfHxPIQpb3V3rSyenbBHqLkz7jVQFCRYhQHSEMYCnrRDkLfSeljEc5C3298ltDVThXKqOEimKWUh6FhMo4IcOn+s328zemIpgrPd2eASyp//qZYQlmVOLCN8dVbpgBqUR3zgAjPph43spp982ewBR6qVS6UEsXA2XyK1E6jxTQNUhQyMchJMAfxJBPh+FP+EjbCZcMDhUPUpl9CqOHTqZCutCbOxR8pUmlfXBJY4wR2Qq8ccBUqc5bNqHq0wnxjU+ev/xV8IN5r98z5xWlMwI0doLexmKNpaGzxPsZhQKnldN+AQgI9DmS0J0bAAAQAElEQVRMqPCnU2Zds/jl695/dfi6WQNWTinZPCO+bgrjMjNhD6M1EnizRmazi0hpSCUoOdad8JIYhp01mSYoqTkf6VyTJyMVRqwzuqLFA86x+gohCW4cyVykQvVDhmu1BWCUc5c+X7bjueKtz4xe9sqYFa8xZQmmOCpIRUCQioBAGnprggnECYMi13/wWvWKycPWzoysmZhYP/WXr8xkrDpiFF3bdJbdSSU15qZYlXtJF5fBUKOkBspsm72451LhIVbZ8mQmuc4VLxvmLRpBCrXY0i1+5bzU0o7EHOVgLMWEodYLl00p/3RS8Y7x1yyaecP7/1SES0WemN4et3hKjNYIkLsIglQEBKkICFAMpmJgMSUAU5z4+asvlX04uWLNVNgFiQvjszMeKx3MXyI3gGxSoS7pUTcU2s2e6oTU6tNGYpxRTlIqTIGOW3FEh0QqR8MojNqXq1TMRed/MPGi5VMjG59KbH0WRmFGxBlHSOIv1NliBkdCkIqAIBUBgc7AKDZHpdNeSqQS9DHxSOmqSdXrpg9cNfWcTS/9ZOZkxu+gYzBLFUaQdaw2kmSo8jJNmtKFVKATsdqUMopYlT6kf7aBC3OSSodh540I+iUDRgcLhyoMIZ0tobUWaiyJzgVftLqeCVvumDuzauv4is3PXb18+qXvTTKaKoDOEgUGc9RoiensEaByEASpCAhSERBIYaoERnOZyVJutBcBJh7/7RtvFG2aXrJl5oi1s0rffZax2xmrNU9tlJkcWccAzVIhnz4IdFsdPs1R2gcEk2YaULK3pFKgtLMT/ZrDxcOjpefAKzId1FKUphMOpiJ4y+tTYZTKLeNu3vAac0HMbKkymSsNtjhUIUhFQJCKgEBWWKnojSVAa46pjREmEIBXijfPAINXTh22ejqMQqVCxlc+OanQwjEuQUkzStoMKz2WStah49smWGTyNA5feWn1aL29MF/hkprCLNQlYY7i1U9UrH9yyOrx1cuf+ePceQXlFVpzwmgvgU6A1kqgVfQ6HoJUehlzcTqnfZMEqQgIdIdZNxAoLZXAbio1aRNaQ8RiL7548dRrPny59KOplRtm3LRgGlNk5jcv7loq3U6akOqG0tZU7FRIhRHpUiOGiUw6S7SoarQ/PjRNKhJjiL4Co1RvevqcjVPPWjeJ8QeYRKHaCN/GtIaQ3hQRpCJIRZCKgEA2+FKxGoptyFcMEZuzlBkZvnzJjLK1Lwzc8uLNC6czpbZekYpEYyZd5WnXyLbGxx2SFX6dSraphLLJhg7c0hn+ZFBSuTVPpJfILNH4QFf5EIkzpNSENHpSWaLQ+Zmo4vY3n6naOhmMWTDrgoWzTaYSg6FIow/rTTGtNd4j+vrk9XR7zgQKCZbizJz+zTup89v3mxTtIaf/GAp8e8gLlf5m2qtDP5o2YOWkQZumFi5/Wi7XA1oRwrXa4hCpzRwd5kNrm8+NVstzc6OllXq1wxsrrNekAotwUMcweVqsqwOFnsphJmuxQh2Ua32AKTfdMecfpRvGV2+bcuWyN5izCmEUnY6kbwZzjw+iIJWeI0jlZBCkItB/EUXKxbHKgasmj9gwC1IpWfWsTKajUslI57k1KchLqFRoJQpX45KTVMQqW0YkCntmZJaM8KUiV9qpVPA6w6h1Bl9Z0bnx8PA8rVNmCTDnua5YOj6xdULxjsn/88IMJpqw6IuAVR+xGXp8EwpS6Tl8qZSmc/o376TOb99vkiAVgf6LxlkiM8eGznv6/CVTitY+W75pAuOxMw6zTGftjERjlqosEqW5M2KpWSq3Aqzwi6NySSoYkzOaEbM9lhlruFvszrjVHrXYIhSjOWgzFdnNxRpXDFy46Kkrlz1PpcIkiplwjBjFUAyjCFI5JQhSORkEqQj0X8SGMLzCjHBfsmrm0E9nVm+b8rt/zmAifoMjMyZ7kMPsCHFwARwrCOl0hQb2jHDRHjAihSUjBTIrB79TZDY7ZUOUz8LOB27xlwRLhg7ZNGHQhvGxzeOLtk8y2BAIohpzEQKcIJVThSCVk0GQikD/xWwsBEyl65ZFM0rWj6vcMumO+dOYOKlmzwg/OymQG0Uyg1hhkqmtEpklY16SS8zPSSr8OhV+hXy2VKhDBT4d6jjfAfJUdpnRJ0jldCNI5WQQpCLQfzkZqcAo3EouxVwnJRWx3NaO1MzBF0w2UkNPShxArnRKZLbqjeMBdrhi88QCbzzPFSmwF4kdxW09VHp2EDvGFNLATGsJ6azhFOwrnRvRas28tsipprTfMqmk1FKqMZcAdqWo31bU43xxp4yuaM0JvbWon0rFFm7ndB/AUw69tNpf0Vh63KRT4CSPP1PuumPBjKqPxg3eOOmWd6YxhVmlktb6K09pZBQGRpZbhXw2cpEKv6L+xKUitucXILkxlax+asCm5/uPVPSWEkEqZ6hU9NaEjh20tf9IRWeLCVLhv8KXiiCYU3P8T0wqKaNQTkYqjNoOYJF8uZm246IZSb6SIFLZOfDfPAUcY+YQSU1ZO0K2kZo7UmQniI2MxFSx7llkKkUbxpVtmah2xBXWiMpcpCbh7ESKC9psQeRhckZ11qDWElAaPFZPQqF3t0mlPSOxOCu1piKtOWK0J9TGkMlRCKmo9N+q4i/2uNmKgNbuVVlcGpsHKxpLIi0cnG7I7aEzlwKtsQzozRU6UzlOn1JHxqUw2Mh5t3lK2T6w0dQjRZ9vVedchO2oa4koDAGjs5CTisYaAKf7GJ7q89URoliVKYSDg3W53o+3md39roj1vwkaD5kK120LZ5SvHTdg06Sxb09jElmlIlZbQIHKnK8wMlIdR56kHUas7ZYO72c0DlCgtMIrtA0ZzUj4OuGMcgJSoRX1xCj5tr6WCoxCpUJRm3xt4SaVkQCDtdRoK4NU8Dr+qtQH8N9vWaZCQfgr0jv9CpMDXiF2McVYr5z2DWvfQoKphMBKBUahUmEfC2JUKgZbnELPdd9vVVapIIBiCa+0/SlIOP2H8dSeLx7Qid4eh2uxxLpY7dbZEioyXsZp39T/WnoqFZnOLlKa+DrpBamItUGQpw4yqkC+kiBW+kBnozByC4BI0uipVMrWP1uxcVyfSMXmZ3Hr7R6Dw290Eq/ALlymgmCkNhSp9IV6W0RnDauMfpMzjlcQtr59Uom/tWjd7tojh5qTB5qOY6mxxPpb6QRiUAdhtD0KUJBo0vOOdeSdtNFH329VZqkApTFocCRem7+ypjFJOEI47cfwFMJrAMKuL1y6+Zva5KGm5L665Jd7myFdsdrb366x/zJ6KhViFIkWpKnlpKQi0YWASBuGV7JJheYoRCodFdLfpPLwY0/trz92oLGlvjXZeByXcvP9P30YXulY/FU9bfaSpmSyviXZ0Jo82Jgsrbr02ymVue+u39fQAqNQ8AjZD58ire6S4aOu/uNfJr/61vIvdjf9Z2/Lrv3H9hxI7vjs4KIlm595/uWHfv23eOnZMAr1St9vUmapIGLS5/E3F6w+cCRJaCKc9gN4CkmXytvvb9hfT6RyoJEscXzk+m9V6nYa6KlUiEIglV7OVBQhiTLMGMoKHIP08dESz1CJNiZShdOkQtMUplOakhG+YDrXqfSdVB798z9w+cIotUeP1za3Hm45tnHn56GiSgQmPNUqdEEiCVPRq3PW1B5NHjySrGtJ1jQcL664EC8KUukPUqHZEkIPW/IePffi7727bENdMzmnh5txWkl4wj+8UtuU3H2gtaElWd+crDuavPu+X+MCkKjcfbRhyJkuv/Ze/DquGUJr8v7/fZQvFURMuiJIhZPKvMXrahqITqhXcIhwGNmZlk77pv7XkotU+MO0dNZJihzkkQ0GRqFScZRdGjnrBt+g78j0iXxlKHPx15kjlb11yEPgjNaf/N8jMAoeY02OYrUxklEqakNCkEp/kAoFXlEYQj9/+O+7DhzfVXMUOSWN5jhryET31yUPNCSPsrkmjHKgPll7JPnDHz9CS8P6aJO6lYrBkRCk0lkqNEcRpHLK6FoqqUEk2UG92saINPS+VMQyj1ThYyzljoFXhkbf4h5xHZlBS92DOpUTk0rxxvF9KpW61uMHm5oPHjm+84s9keKhWkvI5ik1OQq15sSrb33ISuU4K5XW4soxamPaEPpRHt13uDu1TVrZvWZvzlxu0Y77wtsjW2Le4g37G1tpnUo/k0rkf3/zt8MtJDQjKWk8lqypT65a/8ktd/24etgYm7fYGSgrqR517c0/nPnyu7trju85kHzw548rdP4uztfJH3AqFWiM0JJ84Ge/4zdbx6VFV+a8s/pgIylWxVPLwTO1TiXa3vqgBz1P0ycgmPfuGiSUh48ScCr1jmjHK1boHNr7dCsV6hLeAJF9kKnkFTjgFcZWKQmeZay+TBIbWaAPMSpvmlQ4r5wpUtlX30hKwNiSk0ceH2ewR+VaHx5m/zukorXm+tB3Jkpl0NmXf1ObJPVex0j4RmCaMmuOJ1xusIeN7BygRkdMZfTjnGJ3YiUjHn18wvf/52GEdYvrRFrx5XQYv5VSUZlCPZWKwVacUSo1jYJUTgW5SIU/w2OfSIVRhaTGQpmpSKSNYp1RBimdpZJSi8yUEZHMkBHaBRLqAjBKnswCo1CplG+dpHEmlLYojAJ0thhp439CBzFDpkLKTFpoWfy+w0lPuJLEIGtYb0q8PufDuqbjtY2tDc3Jg/XNpRVjtIaYyVoMzLaE01Pm9JY4PMVXX3vHzH/OX73uk70HWhpbkl/url2+esuf/vJc9ZBzjbaASm/Vmhx4m8bgN1ojby9ag2/Dd+451IDfVZsdVm/ox7/4zYcbt9U0NGMzzhnzXfz64hVrG44l9xw6svtg4/66JDbJHgj9/HePLl2zadeBhs0f73n4T886/KXIq1RGr91X9OAvH12yevNX++phwaWrt/3kl3/Ec7raFCAtoe0JPJuTRlCmQKx0+HmXfPeh3z62YMmHyMw+33MQu//VvsMfbflk1ktv33bnj52+hC9canMVGixh2skUH5z/7jo4FXKlimWNG8neOKdzLwS2H0mbhrnOIgj6Jmf8htseeHbSy1ZPEXbH4io12AqhXpD1PLLhBo/GCGTz3vuotpmEoVq27gSxCfto95XAJThitOVeJuWTV9z+ErXeoza4VHqn2RG64ZZ7p8x4Zce/vv66ph6W+uKbQ6s2bH/ksecrBl0g0/jJ04AtobcXwqZGJ9fxs5B24uGYMP2tmoZkQ0vyYAPSpiZCS7I5mTzUwFJPuOSKm8z2iN7im7tgGS4DDos7bnJG7/zhQws+WLv38FEc8A8+3PCr3//Z4gmrTM5UTykrKZuds3AZTsR/9tfh3O2vP2bz4YPx/3vk7yvXfv75rqPY+HMvvgpHEu/E+3E8r/7e2CmzX1u37V+4nPDBf+8+sGT1xkeeeKps0Ait1aNzBJRmN3ZNYQjRHdz51b79jcfZqqnjmz7+Qml0qE0+jg8+3FTTcJyttTr2kkbnaQAAEABJREFU1d6m0gHn4hpTGYJmewzXDK7wEaOunDb71a0ff15zuHnLzi9+/9iziZKhNlf89bc+qD+aBPtrW5qOJe2uEj0OpoXMCP72og/rjiRTf60/prP5ccXeOPbBN9/+EPklblX8KK5wiyeKxwUC28yPXif8XDz3vFzAYC4EkMrYhTMq1o4buCk1TItUZQISpbFArqczydNZGjvMLc+baIs/k2NPYWAUsT5OdKIIcEbBejap5MvNvSKV0s0T+loqO7/Y1XicreBtSv7pb5Nwi5KQlEUqGn3U7qrA/aDU+M674Nr3l21GpKipPb7/0LGGo8kj+M5GEkEO1h/fe/DoE08+b7J7Ae43ky0KOKkQh9U1hYsrFi5dhS05miTt0OAVvlSa2Bf31ibdoYqFy1Ygo8LW4p3QTF1zctmanf7YAGeg5LV5S/Bt+BOWeOY90ECe+MZNeRURlmvsREK5NfzbP/4D4QDfjCXCFuIC/UL8F3txsC658qNtI8+/QmsM9J1UgEzjxSZh86656Qc19cTlyBHhgFwyOcR00oDYkSiuPu+bw6TSYtfBVgRu7PX5l34PeQk1StdSwU4hsgNIdOCw0djrA3XHENHqmsihwGHEYcee7j2U/GJ30xN/n+H0VyHa0piLHW+LXEVpTJo579P/1O8/nJJKQ+sRXDaHGlpwSRAaCBdffqNMZbc4w2lSwZPBS28ubjyWPMaedFwS2AAc9vnvrXAGE22dbAo5qeDE4T2I795o2eLlm+vYxOhwE3l95IVX2DzlePO5F974wcqP6VkDeD9OPa1zwjfDMX97brLBFdI7g9gvzpq5S+Xr/c0FSjs2DA5QaNx4bLrnh7/cva95fy3ZcRxPXOqNzclPP68ZOfqqV99872B9K3TSQppQJPFMllEq++pasUcvvvY+9oXuETYbNwI2+5W5i6FerSXQ1lhckEqfSAVG4fyRWQa9JRWJLsAoXIzMkad056s8WFKySUWksJwRUsESiQKeT9lM5ThiU0n1OUqDR2+KvfbmirqjrbVHmhtajh9saCqtGM3OxFnucFdq9MEBgy9CaoJAjJsEtCZJSIJL6L0Eo+ApFetTZ77s8IbpQxxfKvjI/vqWiTNepjLYV9dMYxlfKrjzSTRvTI6f+loT25oAz3HEH82psgKEoRdfX1TLhkKik0Y2Jh4lERZcd8t9uPdoPMKzpN1b9oc/T2psTe6rTdVaIxaTx+pG1l4tZPtxz+NpHY+WJltYawiZrHGE5vmLP+ogFVMAGdKJSQU2gpMoiPvf/9FvIBVsALb2Rw/9weouEys9Sn2INJTIch5p4FMag3c/8JtD2NmW5O5DLchUdn5+wOIuhFSweTiANN3kSYUH0lBbxGAJOr1Fo8ZcuWtfAx4CIJVj7EHAoaAhDAcHum1oJQcKMc7sLqVe4UWudKlMnDEXhwifwh7h8YJcCUeP1TYcbWhKEo4Qrrz6Nqs9arIGFry76nBDK8cz42YeOMyW/9Qn6dGm7d2x/tNfPeoND8AZxNlEvkKlQq2A90yc8SqCO8RMz+MXexovuPwm7ODIC67Zc/AYrg3aLJ61FDEBvhlLfBzbiZXJL75h9kaxX5QeSWVXzVG8ojTg9YDG4L3+pu/X0oSs4diBupaaw61ISvAKHrl2/mvv8g+34QLDYcE1hhVk+XpzCDcFbo23312JV6hUsHn/mDQDG4yNxxKWZe9TokNc3j988Dd6W0iQSu9KpXLd+AEbJ94+7wVIhRqlGxn0llSoURi5EyucUbqWSsZkpb9JBRfrd28aO2H6S7iL9hxswZ351PiZNm8hlUp987E0qZhtJTRTWb3233gKq0ewwGPjkeQfnvgHnnndgaKrrxv7xa5D1C6IVlj+z09/SQuU+FKhZRH40eVrtww+Z4zdH8Py0T8/zZcKwlwDW1uArbr/Z79yh4vOGn3Zhh1fIAQjWCDeIQBhuXj5xiEjL/LFyh/67WN7Dh1tYYMI/vTKW0vo7Yd4hHzF4ir+8UOPTXtxwf0/+f3Zo68pqToPEcodrBpz2Y1TZs2FBXG3Y9uwwb/49RMIuCqt32IvPAGpkGFdsmcqtGciHXsN8Qip4a6aFmgS+3jDrQ9aXKUqQ7iLTAW/i9iHTOWvz87aV0/KvqCWbw4fe3XuUjw1c+O5dS0VkseYA3Z3Yt3mf1Gb4nwhmZg07ZXCyiHeaMlVN9y+ceeXuw+0IqhBKnhe/s6N99OYq21v/pAuFahOb4/fctdPatnoiTT3UH3TI398wuoIE+xxoDP4TJaQ1uB+Z9HKepijDcTix/7yvDdS4QmXPzdlFh4ycIXg7IONOz/3RwfhmYAvFdKqrTWVVy1auhFZmtVTVDH4/N899hzWka6tXPcpvUKQ1+Jp6Q9/fW7AWed7IsXX3Hznf/bX4VM0Yd3XcOz+h35r81UYHEU9lQruFyTK+C0cUpeveMen3zSwKW8rm4tMmPpS1eBR/nDFrXf86Mtddc3HiU7ok1Y2qTSwVZtQ6R//OjFaMgzfjBVWJ+RZau/hlo07/kNqywSp9JlUujVKb0qFdmxMG+aLioSuFKgdYo0TS674i0w2zKqFswsj1hfIjRz9RCoXXnmNIxDHnYaHU4QD3CpVQ8/PJhWjpUijj95824M1h0hqj7voeDL52pz3jbYAx3kXXk3vnGaSvhzf+dl/cP+kSYWty0muXL/DHS4xucI6m19t9qhMbtIH0xpcvGINNg8352G2UdMTT01G1m9yRo3O0J33/QwhHnc17j18ya4DddXDR+rtPoMD3+Da8fluWj+EaIIdoUVACLW0sgH/xbO8XOdBNKdlRCyknPrjf39DRQiTrV73idEaglTMtkRPpSLVerlhSPiYnHEW3gxvrjDQ2wPTX55LAxyC+LU3/xDWydg5kfZNoc0EIJXnprxOjYJkBXZ5ec4H9JGZxjhE2HfeX4ezSZ/fkQFgHScYPh426jLsr97iu+6muyESGs6w7y++skBr9GEjZVo3vqS4aiR9QMY34IMbduwxu4s7dspLFyf2GlK56vq78Vs0esIWP33oNyZLhGCOAZ0hgPXOUnnljcVmO86OF0fG4gkjmtPmITiVAFKhkZSTCg3rWH648eNQ4WCcVjw0IP/DUqbxXnvLPVQb++rIpfLSnEW4NjjOHnMZvpmWfNZBWp98pTCETqD4CxcYtpaUR9lCN952bz1b/IscBdnJ+8s2GsxRPJTgmoc5br/7J5BKbeNxel9gmU0q2LC3Fi2lF61E7cTp2P7vXVAsLfHDeQwVDhSk0rtSqd4wISUVn6qvi7xInT8dTVLKSqWzUdKAVKhXiGx4UuGWZFTjfiYVRJwrrrsJt/EjTzx1NJkKPVNmzVHrQq++sRw6SZIyonap0Lr6cRNePXiYSIV65c57f8aXis0dXbpqEw1YkMqBuqODh1+MW4gvFbbwIXnzXQ9AJBzwCl8q0AYpoGtJXnTlTbh18YyGKIyPILLT5mq4zRYsWWn3I846jc4AvLJk9UZ8LW57KhXcmbCCQu9F0KHFPngFERPQCm2WCHhn8aqaw6T2CInO7n1NpDLZFDmh4i/SVucn//dn2u2Ao7YzbGTELhxLpqoxoM+v9jYNHnE5UquMX44fVRrDAJZ6ZuIrfKlMnT0PMoAjsadilcPmLV64ZAPN2CASOiYCJxXsr9kRGjdpNkI/ThOWB+qOjb3rQYMlSEflwQ4inEH5tayNDrK9KMoHX4BknbfjXUmF5ny5S+Xqa+/QGLykbAfYfW8u+ADHpJk9MhmlgjhLa0fufuAhenKhE+49/5g0C3+FVPB0j4vhxjvu40tFZ/O+u/wjmuUcaCKDxAw6+0qu0ih3qeytPcZJ5elxU+EMWoJ64HDy+/f/UqMP4qFEawzgyg9EKr/+prFbqbB1Ks1X3XAbvVDppYtDsetAgyCVPpUKuO2tKadIKuwwxmQlX+EQKZ0Z4EkFOuHgxsbnMhXqlf4mFSyvveUOJAqhouqdn+9vaE11nRs45NJXXl/WyGbybEV9K5WKWodQW7x0xY6GJmIUUsHYlKwePBqP9gRWKmZH4IVZr7WQZj8tMAqWV11zp1rv40ulmS2vL6keRasBCLSyga0SWLxiLZXK/voWRMZ42Vn0+d3iLrzyuruoVGj3uqeen64wOBV6N+5tgyM4/71VtMQD0RP3PD6F288TqsZe4ynY4o4PGXnBo39+Gira9PG/axqawYHGFnCo4RjueSz31x7FfvlC5SdaUZ+rVGi1EK0fohGfvnjtTfdn65xIK8lppvLwY+P5Upm7aDWVCsIQzYreWriSlmfiUOw+2EifzREKh517CRI+ZCrzF61ABMTDNS37Gn7O5QhwOPgQLR1CdNzU2bSyCmAXrrn5fmwAb/TcLFK57t7atmrn+qbWn/78V3CJ2RI3mYuAwRSCVHRGT5pUooWDIBXg8BSa7P5ps1/HFZL6kqPJYGSQ0RIDePafu2AZQjASAlyb2OwBQ8+zuQpJ+aoZkSIuU3ptztKF769uYJ1Ey2CHnn0heV5pQ663TJr5Em33uLe+FQq5/Np7qVSwg1QqrLHapML77AcfbqAZEpb7Dh+nUkHmt+iDD2klPPF0Q3Lk6O9oDSEAteAqwjPKitXbqXW6lgq2OZAox1koUNpxEuGVGa+8RRPZLFKhZY+CVM4MqTAyFoUuX2VgMhtFmcpLaDlYSidUMOx4xlQqWKeQ9f4nlcuvvdHuTyAi/+xXj5GIXH8MacT4iW+8vXD93kN1rR2l4g0MMttK1qz7/FAdMQqesg/VJxMlQ/lSsTiDj/zpSdxj0MnB+mas3P2DX+C250sFRkHoxwM1Vw2ASE1g/0ulQp8l9x0mTYqpHvD+i668hT7jU69gX2BEmm1gF5au2ULDKJa45yEAegciRDoDJX/4y3gaEWiWw4fe0rjtwZ79R+PFQxARkKycmFQe/OUTNQ1JPgeyAJEcT6bq6pvYhm0Vgy4gnU+znEe7v5KNfZEf/+JxvlQ27dxNi7/kOg8OINYR7/AEDY9OmvEGV1pIpYKEzxsqWb1+Zy1bo44UDV6JFg6xu4vgeJLYGYJQ+DMTp9NSSnq47rzvVzZfhQKxMrtUYLtcpGIw+yCVVAU+C5IkGMVkC2MFUhk3aWbN4eZUuoNIGh2cJhVckHgCgDCQFiMbINHZHNebYjBKIDz4o42f4MqkrQ/w8VjxQPhAa/XRpUxn/u2f/kLGKDp6HGlK3bHk2O//Hz2w2C9IBS/Su4NKJZVD86RCUpyOUlm6agOuHBzMr/ce+vqbpnjxMIe7FJkuIFtuDf3z1YW5SAVnCmk3ziCMglMJpr74Oh16R5BKL8KXyoCNE0+xVPKUeiKVPKUzI9lkA/LkdkbvBXjoAPgW8l1s4sKvaElV4NPukKdDKldcdwvbV46UeGz+eE/q9eaWz3ftxmNXzeGmhqOkuW1bnUrCbCtasmIrm4gQ3+DWrRo8yuwIWZxhLO2eGDKVp8dNxZ+IPzk1fKIAABAASURBVI40H2o8eusdPyLBwhZ+e9GHDS3HST1NSiqF7OjIbZN8sF7BSgep1CZJHYOZ3EUZpPLEczprkEpFbw8sXPoRjf5sCUkrLUPAp8Atd99P26Hurz+KR1SaptCqYDwe0tJwLEnz3MPJWNFgpFYkWlli7yxaR5/lSYvbxiSVTWoKrE7HOZtsuEpygEiBlAuxG0uHv/Sp8bNpM+jdNccRka3uEqM9Y4FG+wxXGmsoVDyktpkYBU8AWCLROe/i62kkQsqCL6cV8rDLhGlvcKWFnFRc/vjKj7bUsZUfpOVrC0k39eYA0Bp9pEW1JTz7lTn0eYIck/rkjWMfNDqL8+TOru5VRxHeRqTSeqg12XSovglSMZqiFmvCbCnW6qJGc5hKZcG7q7JJBdfPhKkv4omksSWrVGAUdpk02YMIzQRLAl4xWQuxsmTF5qbW5J6aBvoNyFS0Jg/QGN1I0Yw2z7hJ05uOJ0mVIZs13nDrT432EqUezxBF2/71DR6tSEO4Y8mtH3+p0tvxQZe/UG1w4Gnp0y++oYW62DzIGNc8vhDb8ObcRSTlamoFjU3JUeddpdJ4aFmf2Rq12EOr1mw73NDKpmVkf53eIhxqyAb7+/a7yzmp4DSpzS6al8McWIFUuJJSnMdQUTXVCTv3WlZOe9Tu5/RUKj0lX0yg67R1coGURa7n6LFU8hUOud6vCZQBGEWksMEo/VAquFI5qSAEP/CzRw8eaUXMxS1Xd7QZQbaBrTXhpKLSBvEw+PRzsxqbk/SvuLFvvfMBPDAarH6lzoEbzGD1vrtkNe66/bVHaH0MAhYNGX0qFWQqnFTwV6RcNO+h1SdvLVrKJhyteGbHDv712Qllg4Y7gzGDwwveW/ZRXVv18slIJfvxb5cK9oL2dceGPfrEeNp4FFa49a7/jRafhbdBKu0f7CgVZANkUBB7BF6Zu3gNkhukKXvrSH3MnAWr8M2QCowCoBas44emzp6Hg5kmFZwjmg1gf1vJ88Gxm8c+gABncZCyGo3Bb3HAOpvYtPI4wuvhJpJC4Vleaexqlka84Zob78ObW5JH4JUjLcn7fvRTgzFCpQJo/YrR4u8VqeC88KUCkKzgoee5CS8eYWVJc52xd//I4Y0j+iu0dmTSDm94+eoNdUdbcWXS7LBy8KUwCm4Qk6P0068O4hW29Vryy90HkTbhwoY8cMSCsTK8wma0rfAKXyp//fu4g4ePwigNR48dOZq874FfwSjQCSUcq/xqV60glf7DGSkVRmZTGAJqV6LA6E81L1YaQX+TCi5TViqkxxytnt2w8xPcaUeOHW9Nph5jcQ8cPJxsq1MJwSsXXXYT7aGCcAPeW7YOCQpuV/o8eP7FV+492IDbknR8O9K8ZuMWxCl+poL7GfnB/voWmw/b5uM3fuWkgluI1p1QqaiNkXSpsBUSCMq0GoDsgiO4YMkazjdIRKhUSL9CW2Tdtk+wv0m27nf3wSarN2Z0hnQ2Pz6FG/Wzr/YhTrGdN49Tqah0XlYqiXcWbeBLBWELnKBULFFadURbOd9y58/qjqZGe3zw54+z7ozQ4rX2D2aSCoyitYVHXXzdV/uP7m8gA0bVsu3WHn7sr1ZvSG12KI02ud6CZSeptAwbdQVRmt5+9XW34tzRQhssEaxxEnGO4BUEu3PHfAcHhCuAWr91FzZPqvV3XbSiMkUuuuL2RvxcS2NdMwJs8te/e9ThKrLYYhZrCTBbkamEqFT4dSppUpk07SW+VCLxobQciZMKLUrqLBVaCHb1tXfRstk6tsnA+8vXO30JuAGZCrjg0qsPIhPHX4+24hJas+kzq7uCGz3lg1Vb9h0+Tp8w8A3Roip3IKExOqGiJ5589kDdUfZwkTYdkApSc3wttuH6G28/VNd8tDXZiMuvIbnovdVub6lW77faoxZb5Gc/f5Q0ZcwuFVqH31kquBggFfY56XhmqbBT6glS6Sl9LRVaG0/VQnWSGvGF/56eSkWsdsMrjMrBqJ0phZwJUkHUvuuBHx1saj7UeIRmKriL0qRCSq5dhWs3fl7H1gcgMOHe/vuzU4srhiEqDR958eYdn+GWw+tQCxTyo//9BaRCmqu2SaW++RhfKjTop0mFFlufmFRoNQmkQnVFc4KFS1fhR2n/efC7x5+OlQ12BAovuOL6RcvW1rU1WOpWKrRCuKcjmHFSoQXidP38S27CQz2M8vAfx7HDkMRsntJU//8sxV90gBaVOQCv6B3Rhx9/jtas0N6C++qasJs33fn9AWeNsniCdn+ketiFCz5YTzokHmnlS0VtcDi80c07Pt978AjtjoeM84knny+pGIGTdfHlN27c+mVLMtWHEXv9/f95mNYk0YqHzPvINiI4/5JbkOYeOnK4tolUyC1d+WEoMgBeMRgTRlMhpGI0B2nnx2xSQXJApUJTYVIpUjic1k/kIhVfcKDLV4rrk36WtnB7Zvz0ROlgCGDo2Reu2bANu4xL95uDh3EV/fjnv0eCgrtDa06oDNEps+aQOrn61v21pOvSzJfmlA84yx8p+eGP/ndPTR29sJGmsCXDreTXbQEsXd7Ijk++PNKcbDmehFoO1R3/65NT44VDsb/X3XDP3hp8KFlb39IjqbCXfQepAEEqvcIZIJUClQsWoS3EpFqvXO/Pl1sJCiOFzBemtOSprPwmYXyvnEqpPPLEM5AKG15JSdENY++1uAtp/wbEX080vmTNWmQqCA2p4q8m8vw1YPAlVCoaPSlwP3fMNd8caNpf28JVqOLNNAYdZ1McUv9cf/z1ee/YvaSYHiFDrfe8OW8pchcAYQC12UPmoGRDP422uJ1kGu+8xcvZRmgtpOP94aRC54dUJCovNnLMZTfSZqa09dQjj4+jnU6sniKJxgqp0PoDxNDdB+tpmiLTurFy2733E4m2tNQfO0a6brS01DY3Y1nT2LTji6/eW7a65nATvbcbm5PBaJXdXQSpYH/fnPshlQo4UHeMBq8TlkoaN9/x0z/+ZTJ23OmvQO4CUtbJLhXiFVYqwOYveeTPzyFZaaYdRVtJ+kgrimh2QgvWaDxqIaMSNFcOGYPDiEdvJATDR16487NdtCiJtgRDuKS9vkmSejTVavyNucsiRcNpm7QuMhW6nVZ3ybZPa+gRa2ohFw+WtfXJA4eOb9uxC4/tBhNU7X974YpsUjHafJOnv0y3h7bBhVTMNhz2GLzyz9fm02uMXm8wUKqRCFs+Rppa2RII2RdeesOBuhZaXQTom+k6zb9xNL6paZ792kKdNShR+TmvXH7N2Dq2JokmK7RZIFbwhLTsw/UQEg4RNgD//XpvvdrgwjaTzTb7rrn+jppDpA3+gdomdpiA47hrsOMwzdYdXy1buQkvsq8cO1DbnCYV/ApNy2oaWslMrHTMBXYkiCmzX2NHAWihjwWCVHqFvpYKFQmjNigd3gIjsgs9tUsPpAKdAHhFaQzCKHlyUolCUJJ5KLuQCueVUymVhx97al9dKyLOnkMN++qaL/3ujXTCYFq1a/H6b733BwfqG+qbW1K9fI+Qe6O47FxaZg2paAx+eGXwWWPeX76e3ni0CKW2sZUO/wXf7D14dNyk2b4IHriciBdKrQu30PyFqxpxb7emAh9yC0iFZiqcVLBcuHQ1Hfpp7+Gju2uOs823yOAl2M5RF15LUw1axYpMhVZHk1zH5l+49KPG46kvB6T7grsQbyC9Ap2+iTP+CaM0kmF9j9U0Nu6pxZYmP/1699kXXPTS6/MQLFrYpm54qPQGy2jjHOzy/AXraNXREbY/Jl6xOUt7SyqIHYjC9MmUM0q3UqFG0dkjSFaMrujl192+ZPXG3QcbaUuEdqOwUqlve/HrmsPzFi+Nl51FukGYXADhG15Zt/kTLkujtQVsd8jWmtrjCLuP/3WS01tCcyxtblK578FH2cqYJAIrQFTF9XPocPKTf+2DVEinemvg3ffX8IdpSZPKlBmv7N5/mEZ/KhXkKBCG3VUyf9GytrbCLdAG3pwmFYiHDGvmLRpx7sXvL19Ld4107GUHGaMDXO7a17D/0LEJU14JxKsVejcSFLUxZrAVG+0lVk/iL89Mpb/Llf7haOCxo2Lg8PeXr8HDB9sOuxmZCicVqyPscMfuuvcnhxuSNYeOHKprxqVCbfrvL2sGDD533jvL4E4kK/AKzMOXCvaIbclGMjNc8FqrR671AYurGFL5+/ipZBy2w0fok0Fh5TBBKifPKapT0Zm1nqDM6oJdYBSJ3NCzTAUoDAF4BUZhpULkgW8B+Qq9SGmgUqFti9O6sHBSEUlcAEZBllO5aTwo3zShcssknSOhRkxhJ/ZJBd8eHsS04q8vvjlMu2jsOXTk2lvuIh2S3YV0sHSd3WkPhFauXffNwUO4cxrZG6OuMRlNnEWb1hCvGPxAa/JYnOHrb75rxj/f/GLX/j01dQArS1ZufOLJ56sGnW9zFaoMZocvaHcncP8oNM7X5rxfU9fYyGYSuL0lGrPe7kt1eWPVAj3YvMWLV6yhLT6RUuytTZLSLXsCtxneNuayG2iWg2QLPPSbJwz2sNLgwfHU2bwvv7WQfvPhlmNAZfTirw4/jltAbbG5I7EfPPjQomUffr4H+VVyzeYdf3tuYqioXGm0vfjqvL0Hj7Ch53htQ7K08myTLUqa2GqDr725AuGDBhc8PrNj1RT1llTgErJfbOk5VyxGyN76i5OKWOOUG7xaW5ikLN7ii6+69fG/T1m6esfuA60cqzf+e86CVY888eR9P/1FvHyAzRemTw94wEemAq9gafdEbr3zvlkvv7n90y+/3F1zoO7o51/vW756w2N/mTho2EVKjY8MV9Pl2MkUpTFM+qWzYwNfcsVNc99Z8cln3yCG4sG85tBR2OXzr/Y7PXGLPaTWOecvWJ5NKi5/fNK0lxC7afqLUwWpqLR+tS5gcxbPXbCEzR5oVXmzO5DgSyWFNURGzHQEHN7o9269a9rsVz/7z+5d+w8CrKxcs+Pxv04oqxplccSNjgiuDaU+ghwFyQrUgmsGpvnerfe8s3jFrn11uP4/XLftoV/93htKWJx+SAXHh2Zyn399ENc/npaw2dh4WsA7/JxLX52z8LOv9mHbPvl8Dy12w53y7pKPaPcaYo6DR/lSmbdwKZsYHd9fewQPeQUqI81ZacXbxBkvs91iWuhcebGywYJUTp5TUPyVJ9eJ1EaVxSUzsK20ci/+QoICnSA7QY6CFVKPIrFAKlQeUoVRSoq/MkuF75VTKRWJxqo0uiyeoMnlNzj8bFiPcBXaeofLEQybnS671ydTG92BGG5mt68CkRQ6SbWxMYfIyCtWP1tR6QVGm8dgdQM4hFaKqvU+3LRStc7s9IjlFtxykIrbX4JXTA63MxjDBkADCoOdLxXqFW+0yODw6u0eLJFkkElBaPC1hWAIbDNLECAowCgwBwkNRofNF4UhEDqxC0aXB+/XWYOp73e44EuVyY69xhK/rrW6kL7gzVhiF2zusN4wD6yTAAAQAElEQVTiUepsuOHVeg8dVhkKcfuqpCqL0RbAfjm88d4t/qKBw+Qo5EZT7jpT4UvF7CmEVGR6D6lfoQ8E7AAtqToq2vyBHfADewoUBiuWnFQA9pd6Bc/7GqOdDimNFbXBpre46DCgqYE12RGUu95HWo1Pxy7DuUbExMM7a5GA2eb3+BNqnR1GARq9y+XFYXRzILZy4BRgw3BFIYgrtFacF2wANgPXIcCm4hWHN4ztxMbjnakPmqN8qZB4bfVanEFckwqtmaTLJqvWbDPaXVRdKh0ZPBsKwfUDo+DusLjKkazgUsHlRErVbD4sYTiYCd+D7XH6Ivg2eoiwXlp1Fq5zXNj4LZqvAKhCbXDA0wDbiRtEbyF3xJ6aI7RvDbKfDVv/zZcK3u/0xbCz+FpcwLgpuIo3hc5v8YRxtcv1FtwLWqsPd64glZOnr6UCfyDs036OMAqWqY70fKl0GJFF6eZAagKjANoxhSNV/NUJscpBSXu9QGYGeVIXYOSWfKWtcsvzFZvHV2ycULlpot5OpvnTmooA7endWwc3W1epVNeqE5zPrp1sX3Lar6r049CDPe2P259tdORs709lHuZYH+1vpquixwe5V8l8fbapmn/EyCvZvyfDkwFxgC3ESAx4srF6EnCSxR0HdLY0X7Ty8acmkAme2TG261uTD/32MaGL4umFL5WBmyalxv4KaPhS4c+h0nUxV6pCntdcOCUVuIQiSw3Q0jblF1uTnyaVApWHNQoetAOkWl7hQI6Si1SQhVC1SNROhd7L2YVKJV/mBnScMUiFeKWPpZKN3rppz5Sg/O2USt/t77dNKkiIbd7Cles+/tPfJpx9/lUVg88LxKv9saqhIy+dPPPNg0eStOVhXUvys10HfbFyOuLO6b5mvr2cAqkQeSja4Usl9dc2nbQ3GkayrzJFZDofjEJFQqvrKV1kKvlyK5Yqo5+O/UfbiaUyFbkbMAprnspesW1C+dbTJhUBAYHc0VgDcoO7tplMm7avniyPJFMj6Bw4ktxbdxzr+OvuQy1XXH+HTO/Stg2+IKjltNBbUknlHLRoi+3eTuFEkhEkMSSPSZMKEhQYRa4PpoZjYdMUvlS4Yq7OJV1ULTKtG8kKGb5FkIqAwBmOzh4Cuw421zQSl0AkACtQy6GjBPx362ffjLzou3pHWGsjo1DTZCX7IHICfchplwqpZc9XuERKNxUGjEKq5dUORmoS8RqAdej82GYUaIMuqTxowRfIXKciSEVA4BSSvbgvmoXM34NMxeJNREqHjP3Bz+YsWrlkzbbPdtfvb0j+e0/D2m1fjZv6xl33/9ruL1eZQnTGndO+499yek0qSp3E7BBpzYxUnVbY1V7MxRcP/3Wx2guviNVuXBYynY8kKOy0XfwmxfhrO21GgTAkpFO9la7IdZ6MuYsgFQGBU09vSQX5B8XgjNAVlTmgNPkBaafnLsYtbHAk6ARuiCGnfce/5fSaVDRGpcMrMzn4RukiR0mXisIQUhrDcn2QkVuITtoKxKhROkuFGoVr8QWjyLTu9vIupf2/Syo9uwkFvh3Hv39uSe9vld5eyDXoonN0srM+FwG8iKDBzoJTxP31dB+Nbzu9JhWFTmawiZGpdFeDQukgFVwTkArNV+iEwQVqh1Tn5oySVvzFdwbW6dixWGckJmoUQSoC34Lj3z+3pK+kgiiB507qDIunzO6vxCtmd2laWy9BKqed3qtTUdMaFDKzSRapiJQGjg5SoUVeqZZdvHoUqdbb2Sjknezcw3Qp03ugH6wzEmNGo/xXSEVA4NtL7s4QjNIf6KlUstWLpMmDy0Xo28QyMuQXzVFSTY35QoI2aNPhtEoUSAXLzlKBS2gRGYyCnIYYhe3SmNEoglQEBM5ohETkzKIvpEKNwn+nVGHkxifunPEwNE3hj0lM6UIqyE5I+ZjaAbswUhOWZL7hTEYRpCIg8F+DIJX+T19IJe1PcIzEYMvXmPgdIdOlkqE2vk0qIE0qcoMXkGbHbK0+7SRPcpcsnSIFqQgICAicGvpEKhI1/WuqvEtllJudxCu0ip52YckmlbTKeW6F9quno4F1GNaFD08kqTlXhM6PAgICAqeQHlfU59BEOK25F6li0ZhEWjM/U+kgqmxS4YzCTalCq+4FqQgICAj0T/pUKu25i1LPtLUK65lUuIoWJCh0/kdGZusVqRAEqQgICAj0KtmkUiDXc0G/8wCRPUUs0wN+RX1OUhG1TamCBIU/C2RvSaVs/XhBKgICAgK9yCmQSr5C341UaFNgCn8IljyZRaZ1Kw0+fhd6spKDVDoMMSm3gHyFh0hFacsmFZ25WJCKgICAwMmgNyUAU+a4bcF0/iRd2aSST+ZaNObJDTlSIDeKZIauySwVAKMAOoI9Z5Tekkrl9omCVAQEBAR6l2xSESsMnEiwziFSmnoklW6NklkqdLBhuc5DB1+hs29x7+GLhHRPaaOnUildN06QioCAgEAvcgJS6ZFXTlwqyFGQoHQ2iiAVAQEBgX7LiUkld6/kKhWugEuh9yJBoUah9e1pRhGkIiAgINBv6WlFvfr/2TsP8DbK+4+/trX3PC1L3vK2syebUqC0ZbT/0kIpLXslZCfslkLZZZUVIAlJWC1QKJDhnUUSCJlAwt4JGXa8t63/971XUWRZsqXYjp349fN59JxPd6fTvaf3c793Wj0SjZXIDVKtAGCXfotUkPtrzCmQCsIUNi1KYIBILhUOh8M5JohVKhqLW2VywStUGGoLFnoOWaKSCpurEQEKq0Q53Mrr0GsPxV99af3FpcLhcDj9S7BUWPHXlcuXkDR9JKkgRoFUoBbmFRgFCz2UhkUlFVbqhegkTiGwniVd2np1C1m4VDgcDmdoEiwVGMUvlXRDz02KZTqb2pzo14bawsrBwnolKqlYbZlAsGcBmyO7Vxz28NhtWd2xCZkWewYw2PP0tlytPUNlTWXDtHCpcDgcTv8SLJXRm+dDKletWEq8Jrs7Q3ClMbAcRGZYHIkRcGT0ColLMEtkgkxhV6iccqWjV5SK8Cjk9u7IZWF61NOBv3ikwuFwOP1Nd6nQSMVrIlItkWj8YFmqPTQUmCEQYUiU5gBSRXhkMlOvEDZ2PZvJMRrC1t4DaKk7UvlhqRBFIpGZidwCqfBIhcPhcPqd8BX1aXo6Ir3okoBODpWGHXaJVGUJEGhqHAIrLutOsJCIypysMHrYfI7BrbkiwfqydCdsWEO90q1OhUuFw+FwBoJgqUzYsRBe6XmU4kj1IpFafxG5ISyIeAIQhA5Sg1tm9CDHj9c6kenjNUHnwkJYgqMWohSoZnQu+qq0R4BLhcPhcI4GsTYpjkYqwREJUZl6B2IAsIjSkgK7MHMwu/QqFbgkMK8wlwqHw+EMLkNCKqzgi808rzQlsbCDOoMNd68WEjQ2P2x6la7DurDOkmw0l55QJgKiFuI0tpEfLwBcKhwOh9O/9JdUJPLDBFfURyMhwqro8UrkFqYW5hX/lCqiVCRaO+guFSKz0J4omojd6blUOBwO56gBo9Cxv8Z4LitaOvhSASxkgVRU5mRWqNW9YVggOgnRRpcOkkFr/LMRKyjxGkuC1jpm+yJQuPnJ0dvn652ZGlu63ppjEGgvFjDoqcLhcDjHKBZrjsmcRca4r1zxQu6uZ3N2zr9y2SKSqgnuyRhcnBX9oPfdC8TYQGFEbgg5DmHaCMiDLbDKEtgl5F2sZMO6sG72XXrOB7UEC1YLlwqHw+EcHSAVg9FLxiUNkFRC9vJXtMgNPUmFtRumVfcam8rsURiSoYQ4pYPOMax10m1UAgjWRs9SIapEwLqtxGtMCVrzzzcuBiO2PAWpaF0Zakea3pplELLt5jQw6KnC4XA4xyh+qUxK+mPxooJPns3/eP514tD3AyEVFqMc+vfwfMNdpOIfb1isume1KUpjisqUKtW6xfoVcTOlVaK2sUKwaIq/uFQ4HA7n6BBeKinagSj+CsQoYjlYkFQi9pzXQiECAhRIRSd44RWYhla60DDFxiKS7lLxF3kdGoOSLshdQCq3AaIyEJmGpOuvW7547NZnRm564rK3XiQj0o2WLJM122pJA4OeKhwOh3PMYbDnALWTMnLNU+M2PDf6o2dHbn8mwWohun6WSjjNGEEvUvE3+tIkMhCyyA1uVvzVq1S6FIspEgGLVBQmu0RnIRmGa95dNHrzUxM/ev7Kd14ho7xcKhwOh9N3NK5cS9ro8RufP3nbi/mbn4BUYJSjIBWmE6aWyFJRuxCdsHiFKC14hVQURo9M45aqE4NnW+lZKgqZE7COkERhkOgEYlLNWPR03vpHxm9/9mdbX5+4brHF5LWaM+Uuit6WG8TgJxKHw+EcK5CkpCmvvXbS9hfHf7DgjIp/nbXmKaXGHCdRD7xUgurtI0mF1aOweAVGiVNZ/TX5KleC0hmYbDisVFjBFysEU8pdQKZyABglTm0mdgOAUcZufeaUTa+OX7OIS4XD4XD6iE7IIjk5M956a8yGZ0/75NVfbXiOTNSSOEW8tJ+bFEfSCVsmrKEwCJke2N+vXmxkHGhqTCvzxY70eGWTevXa7dHfrkxsMxavsYiYwLmrloJJG5aesvnf1y17XXLemXZrOlDbc4HWRjEIFLOForZnh2Xgkyo3Rgb/3uJwOMcHWltmWAxCNpC6KDZTPrCKjN+86IQdL479/JWRO5dOX/oscZnUEh2IExtrDbRUDkcqAYWENUqg8+MhPfhjkUCHlSOTCsnVnVO66PRtr09cv+SyN14kBRkwisueyaXC4XA4jCil4nGMsVtHCOaCkRvmT9q2pPDjxQUfvUDsemLVwCgaqf7oRCqHpRLS8zHSvyHTBgdClu71K12lIoQQpzbTQjCX629LlozZ9krexkUjt7yS9d5CkpNNvBlOQz4wmykmC4V5mI1pY7Jmh8Aubnf6LV2F/NgYuONzdXE4w4xIUrGZCgVjgd2UC8zWNMHuJWdk/aro+bEfLy3Y/PwFpQsAUeniNYYENWuadTTqVA4Xf/nbCne1SCRYdMIClEBXxx4jlQhSMZmITjfiw6Xwyuht/57wyX/nLl0Cr3CpcKlwOBxGr1KxGXMgFYuQDqOcW7KwcMuC0TsW/7Z8ERllZlIhMu1RkEqX6VV6UcihACVYKgHiFLRrvdLgUejdwbX0vUhFZaUoLIB4km5d+uL4D186deebJ619cULZQlKYBeJdXiKk4HrhqjkSR5mFvFil0n/kxshROCUOhzMs0NsyA6jNaQZ7lk7wKgzJRosXkMw04k0lkx2/W7t41I75BVuePH/5/N+XvUCbEWs1TCoSuUGq6GepdN83KqmwmhU2ymRIpHJYGEobkVnwyoaYDBuydJcKQ+zsYic2yuiNi+EVSAVMffu1a994WeLOIvY0JhW4hEuFw+EMQ4KlAqNoLOlsZHedMc1kzST52XNefxVGuWjDS4Vbnxrz8XMXr1pKMlVErwNxaj2AUYaKVFi9ffcGYCFSVX7cnwAAEABJREFUYbD5VMJ2VQlrlASNTa9xGbSJcplVrXKQjOTZL71QuG3pxM/fKPjopcKPXx7//uKxGxaRMbmk0Cu1pSucmRpHDuheUa9yDDDOjCMn0hG6HD8tati+mSKRTrjbu64USqRP7w7bvufrEGZNz2cVxfXsvs1ApyyHM+RB1hdA7vCqErORHypdWeRU59mlT07esmjMhmfyP3ohZ9uC35YvoqVeehPRGoiRwroisnnjI0klVq9E2iUGqbAOj1KdC/jt0j0WEaXCvNI9XokklQSiV8kFQnRUKh7qldwPF8ErkErW5kWQyqQPX7z2nf9c+ebLuJS4iFwqXCocznAjWCpx5mSWGd7x6IIL3lt47prnTtj6wonbFmdvfb7wkyXUKONsRKkhahqmELstSqnEpJbAxqEjEwdLJaQDY3A9PGs3rNC7lQZPcEOvsATilWCviMcRwqJNsAJEKgqoRWWJ0zuI1XHfwiXnrF1yZsXCSRsXnL795ZGbnj9x16uTNj5H+fCZyZvnT978dAiTtsTG5K3PDigTtz0zQPg/YvPzlA8XRs0LIv7lEzYvxtMNOPmDpSe9v2Tc9idF/gUmb3kMjN++AIzcsRRM3LoYnLPhGXD6B4vA5M1LKeIR/PjXLA4i6N2tCw4jrpm4ZSnw7xXFvuM+fAeM2fpvMH7bIjB52+OU7Y+CidufoARfqO1PUWK4qpxjiVh/7xM3P3XM8gyY9OFzDPzqx259bty258d+tLBw8zNjP148avtCSGXS5oVTV71yxfIFRC0lFp1/9C0VhelEorCCnqXCGk/5m1CJUwL3qdK+h6FWIg08HJZACVi3UKYXqQCiFtGbidFKRpvOWrXo5x//e+zaZ8YgD/roxYkbnj1x00LRKPMnffhUCEeWVAPH+C1PDRBdbrJNC6Jmkcjh5YkfLgAnblwMxm57QuRxMGnzowB3LRixfQmYsOUF8Iv1T4PT3l8IJn24hLJ54WH8a14IIujdLc8fRlwzYfMS4N8rin3HbnobjN7yKhi3dSGYtPUxyrZHwIRt/6Jsffow256kBK/pkVgzKc7gEuvvffymJ45ZcPJPTfhgfoDRm+dP2LFw4q4lkErhludGblsAqYzdOJ9kaIhXSzQyYtX3XSp++iKVkDnnQ8qvArUmgTbEkaQSMErIfPUSdfhgxd8GTCRBblHpXFKVBVC16EzEIfzjpSWXF794ybsLz/jghVPee040yjOTNj8RwsQtsTHQt8LYzY8PLH4NHDnjt1ImbrsHjNlxH2XbE+DE9xdQNj0BTthy34lb7z9xyyMnbH540geLJ29acijioQTLwB85icrvSmhMeYhI24RfD3OcsOOx8R/dASbuoEzaes8J2++btPVJypb5YMLW54+ELQtBF431wgucQWfih4tiYvwHC45pRm9aFOCED5eeuv3VUza9fOqHr1xT9Mqf3lxArBYgV1mVGhvRmIA/WxejDancCvwZeKxSEUOWI5RK8ORagUZcIaFJ2NglBDZoMRu7JdDNXnzLxggrFVbFIlPZKGprgsJEtEai1BKVnJIoI4WOE9c8A6lM+OApyqbHuVSOmlSoUTY9NOhSOfGjx7tLZfK2pwCXynBjeEpl1AcLwfgNFBiFnOIiGWbiVhOLmcikGr1TprT0USoJWisb8aTv8QoJKIEZJUCkzozdy8TC93kUR5MUj3k4WIlXWgMQrYjKStQC+/IqKYVozUAlo+gTKEo5JaxLqU5jBVd/QFGbBgqEcUAt9Bncf7jsUqndRBRGYvWoJC6zNj2dkP/ePeWneXeD6puuB1/dOefzO2ZWPPlsfoLCqdFICCE6Y5wBoaQtwZxIiFJicScYXRFwByBETdS2xJxx7tzxMouHaPFUJcTpHRKTh20gLnTfly5nacnql+e1rb+gee25vtIxtf/1frf811+/c87ajfNTvIQeqo/gUmj8d92xjc5yGL21C0abxOoiKoPM5h5zxjn27EKpkNidBIsz3uzAxocxCH5CDjiIBH/NaBj0dOkjeuNhNBT2OE782AmdCJFhI7Qbu1j8I+aNkaQSDJ7jgV8G2At5sg7XWSAWB9GZicIAObFtoq9rOSyVkKKtPkolUM8f1ihdpKKycqkMglQ0MmJUyxMz8K9G5gYwytr5d8Iou+f8vWrutQBS+fS26dlEkozcmxB4BVIRsZE4FW3mobfDDRFwBYBRiM5J5GZTcp4jcyTNyuM1EEZgAygk3L50OddAPvzf31vWnefb8afW5QVN7+Tur7iwadPlZWv+hZ8Y0dn7ilagxJpVDUGCc96ADBj4TcUr4JLCU36ucafJ7R4oBJoBTCSMLjrhUhki9CwVGKUfpaKxUHPoBW1imjopnXqlL1LpWQ+xSoV1hwRi/UqoThjsawevYRVKShnFX3UvXjgmmEMYQ1DKY0MhMw0oMplhwNBR5BoRVRR035KuUcg1SoVWrtbGyxSIPaxqTTYhFY/c/uOj//fZP37x060X7b3t4oZZfwKf//XerbNvM8XZtMSkQkoorRqVQq2Uq5Qai1nQ64wyqUKn1nfDeBiVmaFRGE3IEQgxaM2pSRnJ7jS1Qtdlm+77ipxiIz8UX+4rO6lp2bi2FfntKwsOlpxbWfQrr5PIEAFptX3kuPnTB/0Zuv6ZzebRo0efcMIJKpUqISHBZDJZLBaFQtHrMTWH/tRD5k8V45/yGP9TKWQiEiBVUSRqJUWlBvEqfQC53AiC60iikYpETglEKtQiTCppmURwHrlUgpsR94tU2Kgth2r4wxglRCoslOFSOZpSUWr1RCJzmy3g3btnvvfkXV8/cO7eJ/6w/45LQOPsSwGkchYhbk2qU5lkQ8RJEmSSeNziSoVagaNJFWaTtVepGDRWvGpx+8bhg/VyicpmcXrTstOSvUadBY7xbxNOKnj3i7cv3ltxTcuKCe3Fk30lIzuLR8Ao+1ecI4UOlUShUvWR4+YvOOfVdP2DTlJTU2F0LMtkMmwA0zD9cKkM8b+jKhUoBF7RWuIMNmJPJFYHzaI1lpilEhJh9FwbHyKSQFOxQCcV1q+l6zHDSwU5EiCaZCBTq+QatSQuUS5JkkmIWilVqPAQSjJUJNdAqku9lUVpTasKw9JcERv1JdlR0lCacwQ0FmdGoqkkC/SwQW9kg+ai3D7CjsNg37Sp1CuSDhpLU5rKUtmalhLKoXcjIH6pfkY8cmtFdkt5FmhfndtentlSkt5WhvNJryvNrqWXMbupJOfQLjl9oKczaSg9zIB8U06MxPqrGfQTPnLEX0FDWTqlPBm0rhpbV1TQXHzm+RbiSSDpSmKU6DQEz1Z2hSmVNSP2F4WJD+WHBEMHa4kklWj6PyaoLTH1kSQ9xyI9SyVkTcAowQ2Re5GKOgnAKEqdNp441Yo0k0GjVcstAlm3/vlPy67bWXJN87qC2vKsxoqCsDSVx0ZzRf6A0lqeO2Dg4PntZYV9hB2H4T9nMfsealIJQE+vJD1AfVkOvMKlMjwZnlKpL0uiFBfWrsxvKTkLXvms/M4P/zdbUJrNMgMhOiKFRYyUgZFKwCsxSyWafo6RJMSq+rvqpCep0KYFtHVBYpzSHSf1krhUQUu0EnK2hfz09u/aSxNr3zb5ijS+El3LsmRfeXbzqnFhaamIjaayUVHSXD76CGgpHRGJ1rKRoIcNeqGsALSV5onkREH3LbF7waEDjgLsm7I1TcUFlJI8ClseanQ5txEifT/sCM4xRGNRYUwM+gkfMS1FlI6SROBb6fUVZ/mKvb7SrPaV1o4ioXaFsaXc3rQmA2QoCbDIjfp4TbzCBfyP7GJVPxusZfClwhoE9yqVQHEZKwcL7ibZa/EXkwqMEq/yxMsyZapcGKVi+fy971x4sOiSthJXwzKrb6Xat1zZtiK1fWVaXclIRn3pqGAaSmIDth9QGovyB4riXNBclC2SGQXdtxSLv/wHpD+5wDkHMll8BJcKZ8gyfKWy0tv8P7evJBNG8a1y+9Z52le7Dqxw1pQmfbN25lerp2uI0ijRBaRCe670k1TwVsArUUml58KuSD3nA7UprJVXcJFXiHXCGYVuRohZIrUTiS1BmWhVE7OS1JVlgKYKO6gvLagryf9i1bwt71yf7klz2xK19oyw6GPE4EgfUIyO1AHFbE+OmlSR0DX+Q9nTgf+c7Ycx2NLwanJkRAPdRTyawZ4UBSkivW/jP5mg82SYnGkU/6dnguB3jwx2nGMUo93LMNgyhgl6IT0mBv2EjxiTkAZs1iRgt1CcdsFqNjpdkmXLF+2p+CPYV+qoXZfSuKagtjxn97Lf5BNCFHqioR0n4mnnAbFATGyO3Pf5uAJqodqQ6UMGlOyTVMSuJ45AJQrrJhlilGC1RJIKNQoxQqqQiqAh60ufqC1Nry/3HlxhaCgTKpdlwiujbGS0nQgGa5o7Ve/MDIsxRvT2tCg5Qq/4s84wHMp/I24QDSZbUtSkiISu8R/KlgbY1wzKYWl+bXZ6La7MaMCW0anCL4wo9EO38Z+GK50pBJ/CsCRmUPwfnRWQCvsuRwCTCg4VPRZX9tAhcFaDrrej79EoGfQTPmIs9gzgsKVQrMkUm9VmNXuSFIlu2SkO8l3xhZAKqCnLrl+VV7PqT/AK7bc4MFIJiWz6UyrBHRtZjBIyNEsUUqFtiInEGq9w2PXErCI1xdnNq0e0lLqaS5wfrJm2vvwGmzXFLqSahUkW2+QkxyiLLlMj5IRFFyMGe2zobdkxbW+0ZfWAQcgE3ddEB520xz9ZmSX/iDk0mRg9JpucGP8abXm9YrLnh6wJmpQsqvM32nKi2ebQ8XOCltkJ5Irk0zMRCoDBWthH2HGOUQzWfIbekjdM0JpyYmLQT7iP6EyTKNYCvVCoF/KN9kKVfpTaMFpvKTDbR6V4JO+tebVh7Q3fvfUH34pk3zLPd8V/KJAT1hKMTbHIOn33l1Tgkl6Ly2KWSnDZV9gOLpLQ8SjDSyVB6QQwytriBZBKXWlue4Wnc3VybhrJTiEBqdicJ9lNuVZ9ltKcGRZ1jAz0nNKxSCJWBlYqkeay1FtzGMHL7N9YpRLFlmyb4CN3n1VTXPbnp32VSqw/8kA+HiVHJ4fVGLOHCWpDVkwM+gn3kYBU1KZcSEVnzYNRNMYxkApwO4lgJuc4CbwCo/iKUr8vueiH0osTtGZIJUHjGAipEJk+Tqy97zepBEYG6x6gdO9XTxErjg51wKGddOigHRq7zkC0euIr9zYvczeuyassSlu/5r5UDxGFTJ1M8efUbDbNgZXBUUMnZIGgNbnhYVcgGP9b3Y/Z075hJNHlON0/2n+GIiy8y+qB/rgm/o8OCij9nx7h+3I4wxf261AhZLH780mlI13t8n5WdvEXFZc0VQgtq+2fv/azEXFEobJL5eKYLhI97W+usHSHdWzsX2KTSsAoYavlwxglslQ0OlK+6vGO4tS6t+x7lyVVl3qTXMQpHP9S6caQk0q3Ix/9K3A0P53DOfboLpUJidyTVgUAABAASURBVAReqSsx1Zeaq8ov3Ft0gVxpkykEorRIdY4hKpXg/vM9j+nSpZ+KPAX4O+CIa+SSFHDROPJt6Vm+Fengq9W344oo7COVjlHhriDPXDgcDucwClcGYMsqR7bSngWvgI4VBfX/zTj4VnJnReHkLLueEJXJpjBYJWpbWK8MplQCRmGlXt37P8Yqlf3rL/im5MzOd1PARytmjRKI3DZCai0IdwW5VDgcDucwAakY7DlsNnvEK6D13dzGtzJ968e1FOe8v/xlh4zEKXUkXu4fcXEoSAUuUejdIdNB9kxIj3q51AVo/YlWHy+xKFROSxxxyomvPKnxXevBopEgNSNPb3JI3UlxDle4K3h8F39xOBxObLBmIEwn/pViUdhEI/mx9Lbaosz6kuwfiyZP1BE2wXDYsi/gn3K4G7GKJHjfiFJJEMeLDJkIMlajhEhFqXaReFOikmxctrD+bXPDO5b68nENFeNhFLPgJnYnsTnCXUEuFQ6HwzlMD1L54p1ZNSu9DaU5latP/37FRIXBhlw+Up3KIEhFIg6+csRGAVKFXko7edqATicolcYkJfnivetqyq1tG5O+LbrjNBcx2DLUpmSnMdNl6pfWRBwOh3N8Qx+1mVpYUZjKXqh2jHDZkj3OtL3rvaChzNu8Kltv0WmMaonCmiC3dKe/pBJV8VeglVdfjBIiFbXaLJfrUzVky8pLaiuExrXO70v+doKVaMwpTCpmVfJgJxWHw+EMfcJIBRi1ArzydWli3bYR9aUZdSXpMIpCK5cqhbBe6S+pxMkMAXqKVI5YJF2kInMAonFR4k1Sua22wltdlt62pqC+JNPqyNKZUjQWr9qcobd6teb0wU4qDofDOVZRWbJ09rwCO/mo7JbaEm/z6rydFTelqolUYWbzcYUiKqR7D/mIxVxhD9KV8FLpY3QSSSpypQPUr846WJpWszIdmG1evTmVS4XD4XD6zpCQSoLGEUK82h4lcSpbr8QrHIConCAuwUzijE3rcqtKUtnERwhTLPZMJhUYhUuFc+wSGF+gnwYa4HBiJlgqNcUZkMrHZXMhFbncLKOTnYfCJh7uDps8uDtRDeVyxEaJTSpqF4UY1Fp349qc2gpv6+r83W84IBUEK5AKGD5SCRmwknMcgKTkUuEMOn2RSrzGEqBPUpHKbQFkCnuvBG8fDV2lQruqHCxNa1iTXV+SWbMyXW9ONQkZ+BEOK6kAwTPC5MzjXjmewD1sdOQChN24pW1JIwf9lDjDjWCp1JdlNa3KZVJRKCzdgWnYHJGs2IotB6/pTlgzhUBsjuwADldurwRvHw0WZy7QJuZpXLkmS7remFJTnlG/OotJxWhNH55SQdYTMrr+oJ8Sp4/QekFxQWVKZ8EKT1bOUSZYKtVF6UwqWUaSlJTbHY8nx+XJdrqzGI7EzACBlSEkJvYOkShsAaRKe68Ebx8NwZGKRCbIlQ4mlYbSrNqiDBgF6FmJgdVL6e+rfNR/2D0P0UgxubIMDi8wOjNZsQmcKp4nH5AmlFiH1h+s84RR6Gw6jmyTk75qLOn+5ieDfQE5wwqNJctgzyu0kY9Lb2muyAWflMxJU/YSqXRvFhypaCu6fipHXSrVZekBqZht3gGVymCUL/UuFXNi9ltF62tafVVNvv11vh8rfXr/cy6XSijRTe01+FJB6InXt4s/qGvzVTf78FrT4uMlYJyjTLBUkMEyqWTpaJ1KWFihVvde8X2Sin8ar8DcWZSIMzYeEeKM9Gp4xREvMcmVtuqy1PrVdBSB2qJMs5BlsmayuTT01ixKjBfx0JTOdHbY+x97prbVBw42teNXff9jT7FZzf3TLIrTi77w6v8ONmGDzoYOX02z75Y7HzE7es6zssNypKlOuyyZEzOXlb9f3eqr6/DVt/sqG9pN9lx8d//MTv36uZGOE/H4EYfcP9rCCySByZ59zwPzG1p8lTWdNQ2++hbfwfrOxlZffbOvtdO3r6pt09YvX3296PKr59gTc/GMYnVkWZy52OvQ3Jrdp/YKosv0X8HXOTMsPdwqeCR66Y3lTCe4x/ZV+1wpo3qZiCzGKb/CTAIWaeqEiAxyrscZULRm3PN5IwWys+SW1vLctoq8XSVzMpQkUh1J9EOwBP8b3P44TOfHwZJKU3leXXGWBY/tAlWrOP/gEWWax5pUdIK3u1TMjrw+SiVSi6PjQCpIICYVGOVgna+xjXqlrslXXe9ravM1iMt79jdX1fp27Nx9+pm/E5zZKkNK0FTNR0kqNnfBu6XvtfroHQivVNX7IDYuFc7RZCCk0t0ubLL6yFIJmeX3EP0nFQobpiVeapCrrNXlyfVr0gdCKvc9+jSTSk1LZ8xS8R8nlEjTyEc+pfCZkR97hs6WbnanLat4r7q18wik0sNjcowz3kcqPhoqmZE/TBEyIIl773+6sdnX0OxravVV17XXNnTWN/kaERDUdlTXdYKaeh/+8O53uxuy80/QmFMsLnpvIMX9SRn1Q4NY2hYxHSPdJxpTmjN55Lula9kdWNXY8eP+drUxNdaHlV6Ub81ir2yhh236+2GIc4xgyjILeaMF8mnJLe1luR3lebuKZnsVfZIKPBHsFS6VvkolwsNmZuSqmiOXilEoOGKpaM3pEU91iEmFXbpeO3N0lwp0ApFAJ4tffCM5rcDpzho19pRrrp9T2+BraaeOgV0Qtfz1rsdhFLOTprjJkcnSfaClgkPhHhM8Ga60HLXZqbd5kCIJSudASKVnc3CpDGsGQCrB2oiq+CtYJBK1DRy7Urn3kadqWmgdKbwSg1SceJhNM9rTpRo7cgRnarY9OdPoSNbbkrVWD97FW1pLss2TY0/KFdw0t0JW5c9i7DmsMjZB7dZY0nWCF9owOLwSrd3qyVZbkjTWZI01VUjKU1tSoBP22k0qrRCbGGrkAb2QLrhzlYZEtcmjMSc5U/LxoSZHBsCC1pIq07qkGifOIThTU5uScWLITO1J+XhOB9iSgQNiA7yFbbCg0LvZV3CljsAFcaePCj4OK6BTm9MM9iyTM0euT1IaU/BvXyalZ23brO5Csytfrk/BcjTNorpLpaa+A7EI4pWHH3veIngDPLfwJRgFXsFbkMqzC19zevIt9kyVMYmpBd8LyYcLiKREIrI09QcxYpCHGw9eBzCKyZ6LV6Mj2+zKxUXAK1AYklnyYV8kjcbiFjyZanOiwuDAMm4VHEemwcoM3DwGe5LK5PCkj0X4EiySeIUDa1SGFHwiTgxJg2RiqQNwtoF/8ZbS4EFKsa8AsB4pG0hTJKXNQ28Vu6cQHyQk5rNnIzbWkStlFIIkLOM1JH4d/FyPM6AMmFRC6lRCIpUuFfXBUjnWI5W+SIWxvPw9sZa1s6qxY3dVE6RicWX++eqZRas+/Hp37Z6q1ve3fXnjnLuQ6SPnBSx/VBrTjI5cJpUzz7vkkWdeWvvhru8PNP1Y1fLN3voN275a9Oqysy+4FHaRG9w9SMUg5JodBcgp4pU2fO7vL73+uSX//WD7V9/va9xf2/npNwcq1u+4+W8PQwNQAnKW7lI569xL/n7/0yVrtm3Y8uXXu+sP1PnwuuOzn55e+Pq1025n2RPyJnwEy5hwQf63cn1tiy8ApIL8dOYtD6za+OneGt++Wt9pv7gIdunLjc66BEInf7xizkNPvGxy5jET9yyq6KUyY/atTCoIZSCV198qM1rTaXW9K5uZQ7xWaX/48w1L/r1syyffISl/Otj2yZf7V1ZsnnXzAzZ3AUSiNiIvHoMFcMnlc1p9/kZc4Ozz/0IT15ZudOKyJyNpcFO9+lbRgfoO3Eu42SobOp3JIy3O3HdK1uDm+am6Ceyr9gXn5v6b0JaFj7v4LzNeer1449avfjrY8eOBVqTRf/5X8Zdr5uC+QtKwJwMseDJGf/zFPpzJvhrf7sq2hS+9gy+CFGSjej+z6I39tb56xOVNvnv/uRC6glrEuyjzP2+tPlBL1ze0+b76oYFLZRgx8FIBvUjl0MiP3UwQVIF/rEjlnoefPCKpZIn5Do1F3lxRjuyAlYnvr2uHVF5/t2xfbVtdq+9gI807kI9gr+LVm+0peUqT2+rOx8Ms65eQUTC5eO22ykZfXbuv2eerbfP9WNVWKzYwhTnwespZF6nMyVZPLpNKTUsn1je2+Q7Wt1rteUZLltGSA/QWz9hJP9u09cuqWvrcXdNAWz1hobGVVkpX1vt2fLb7gj9ciayNBVgs38Tro0+/hM/FeeIMccL1bb6GdpqtAOy1u7Jl687vx0w+EzmLUp+MC4JX5FzvlrwfLJWkzPHFa3bgMoL9dfQynnLW7xGp9JoQPQQxCgMdM/Tnv/7z7ipcWN89Dy8UQx9vz6FPd6nUNnQ2t9Firocfe9ZiKaAESQVvVde11jX7HnvqBa0xGVIxQwPWVL0lcfIpZ23Z+Y2YrL6fqluQjvheuFa4PrhcO7868Js/XOdOG4NrArtDKrALvjs2ru+gzb6ffuENpBqeCSAV9giSnFW4v64VB2zspNf5xddWwCg4wtvFq3Fr4dLVinn94QJJ8S7Fviecfu66Tbsge6QIkgmfjseFxg4f1ohnsu+Xv71YYbBZEjPMrnSDPWXpa+/iPHG2bT7ftl0/4AiItxC/IvU37fi2xUcTt6reh2cIBC4WZz4tRLV7P/2miqUmjrzgxbe7Fm9yjmuOilS616kc/1JhxCQVpSERGfSysnX+pjuNHXhd9MpbrIUoy6CRg9B3m2kGfcWUeUZnRqCkKGfUaZ98fQAKaeikUulCG82d8dR/9vmXI1eypxREkordNVIid8MoH3/2A1zCWs0yr2ABRmk4dCb7ajrw3M2kwsrB8JB7/6MLkTExqTBoztJMwXJVA/0X2VZK5gTW4lZloLXZby5fFyyVpa+ViF8fBqUgUjn9nIvhzojX/1DdErQRvDIY1rtz+k0P4JrjAuKYs259MDF9TC8p200q9U00HEGwEiIVVvwFqdDir2bfVdfPNtu8FnsmjKI1emCUbZ98hY8O3Bi47JQ2CuyLb72/xnfRn6fjJsGVMdpyzI68V96swHmyFNxT3eFMGwGp6O20BBKX/eob5+AOYfcGfICYEoECdv9f0SqswX2y52Ajjnm46Em8S2EUhJvM90imBvHhg50DUgfLMA1cBa/Q8jR7iiMl59rpN+NQOCD0AEZNPAMpDql48yf+sL9lT1U7PqWxnaZveu5EnLlCl3LSGb9B9MN8iXNDYM2lMowYYKmwahWmE+aI7vOvkP7SxvEilTXI9fbXNbMcH5s9/OTilKwx7oyCux968kB9Gw6LYGXPwWaECwhuVMYkhd6tMaes/eDTWjF/Qe6APGLtBzsv/NN1juSCJO+YiSef98sLLn/59YrTzroYeZaQmG9JFMvZWtvxIIwc4WBDs9WOGMWrM2aYhZyNmz9BzgjZVDfQLPJfzywZOe6UxJTciy69dvvOb3FWOHPauKiy3pVagEdXgFwGD7C33fXIghezGS0MAAAQAElEQVTfun7G7ci8sgonI/sD5/7uCsQikAQCL7zi2fbWvz+KAAUqYiVmxau3BkulptVXsfGTk8+80JZUOHLi2XfeP/+0X/xR7NkXcVJnswvhWg6rOAnb21QsG/SanHk33/kvnAP8Cl396ao5gmcE2zdo49AqcZOQJjgz73nwyQbovLG9ucOHhaefX5KcOsLmyCwYccrlV86GS2AUyKayumXdxk+cnlx4CFLRm5M1Bnf5ug3VjS3YC5e0qd33yBPPF4w70ePNv/DSqzZu2wVzN7fTlsq79zWlZoy3u/Ittly9yXvGOX+kPm6lVxspfsUNs3EL6a1ehcalN6eWr91U3+ITT6kTMSVCIpM1U3Dkvlu0GuvxQUi4g7U+2g1LlCL7Fms2bMcuOAdsU1nb/s/Hnx8x5lRvzvjf/v7K7Z98j3gUjw77qus++uxLV3KO4MpAzDrhxDPrIFKf/6liyvTbcSh8rz/+eQpW4oGjudPX6qN33fm/vwI/nzi5c9Yt90E2MBCCGyRoVuGJXCrDiKMSqYRUsQSkEqb1F5cKk0p9u/8ICFyQWTtTkPGlaK2eL37YzwrQ99W2wR82Tw7yZWTQyLjx708HO1iU8Nm3lem543E0SIVWsYrF3BZnvsaUAanQwvcIUkFedvGfZlQ3dCCrQtazt6r5mQWvuFPzjEKyVGUx21PP/vXv8STLviO8cu20W5k5WBU0JIdvwUpI8KoXUvEvvponY/TmT77G92UVAGve38Uq6sNKZf3WLz2ZYxB7aSzpYqlX5qEhZMJIhRVesUBEbc5go02DQGUJw5Y0EkbBBrDL8y++i7iNxUDnXnhtcHwj0otUkL8iR66qa6mu9TXg69T7mlp8ew/UVdU0I45Zu35r4ehTsD3ycYc7D/v+7qKrf6qqqapvwvXEEWAUqzNVabRLNGajI/m0X5zPihaRX8MrM2bf40gscCSOQOBoduRs2Pw10pq1J3y39D08DSAdEQONHPuzg/V+veFk5t5ybw9S0RiSICGLPQNngu2xFzYAjzyxEA8K2BGxFM7zjLN/hzOB4eC/mqbWabPvgFFMthSLI23bzs/gFdZN56V/L8cuOlPS/AX/ae2kUjlQS0vA8Bxz1wNPmey5WrP39XdWsyAMqblpx7eu1BFcKsOIoy6V7qHMcSsVZASQitGRShFLIVjrUkgFD8uQCi3LajncpBgxB96FRbBvi1iKjR/qby66RmNKUxtp7oxooHjN+5UN7WLnyk48HqbmjEbebXFlPvHcK3QXsRADapl5873saCpDGr6RyZ4PzPYRzqTx+CwcsKtUOg42NDKpqHXJTz/7ekNbe11LKzImZEAnnf4rPLFanensuVVrStxzsP5gUzu0h9NYuep9sytdorbhuyuNzgS1RW9LZmXxbMGeTKt88cWXvvZWZUOrv/SpxhcUqXiLV29m+Sbj8utvsbrz2XiXbOgRfcT6Epr162zpt9z16P56X2UjrX4Iy766Trw2dPqqIYBaWlHB+OKHxkmn/VauTwk5ZiSp1DV3IjtuEssM2zupTlraqFoaaA7e9s9Hn3O6aWSAGAX3ldaQin2ffu7V6sYmXGGEfQDXEzk19Gx3Z2IBl/SnyqaaRn+Hyoq1O5yefK0hHfGi1pw+86b7WVmZWIDZmpl/Ei3jsnhvveNRljo4pe9/qs7JP1lnTIskFejNaE3HBy1Y8jr7lPrWDkhi8qk/ExKTgNmRiFd3mnfXV99CJzVNzTjhlWUbVHoHThJJ/9ziJVX1EIcPe23+aCe2B1s/+bSRVph1PrXgtWYfLYVD1IUHF6Mt59Nv92HNvtoWJPf9jz1L7wd/o2culWHAUZdKoCXx8V/8FSIV1ogzWCrNogaYVLABawoFqbDypVqx4Dur8ER/sbgtDVL5z9tFkAo7OJ76M/LHIYhBvlyxfkdjx6F6lw7fpFPPxWc5UwoRmoj9HvLURq9KTyeUNtmzFbqkSFLBpVjz3i6sgVfYUzDyu4P1nchQ2L/gQH0Ly/0hiV3f7HWl5UF4iFE83kJ80zEnnHHn/Y+v2rh9x+c/7DnYvLuqaU9Vey2tI2mD9piKcJ5J3jGRpJJZeLJYS0SLs6zuwh7bENOsX2VOnnPHg3uq2yCVSOBrwiv4FliAVGpa6Ss0881PrRdeOh2fEnLMSFLp8PkC8UFjM5UK/hCysB6RiFTeXrbK6qBeQS7v8ozAQ/26jZ80dXRC0riMVXUdLFvHmeDC4l+srKyllxpg+avvalK9Y03WbKOFJro378QfK+tZmSeuzIx599EaF4t387bvq+ra8FTxU2XDklfexD2M+IZJZVnxGlbOxqSCt2A4nI83d2zZmg9ZCkIqkAd8ACsgLmnupKEq1hyobRDDlGac7dc/VMEokB8eJqbMnFVZV0+DlbbOvQdr03PyswtHYXt2nPEn/bJOLKPDSaZmTT7htP8Tb28ayO452Hjx5TfgruBSGUYMnlQCXjmupHLb3Q+ydl8sf3xs/kI8sONHZXMXMKmApa+9i19du8/fbodGFeKQHhpzCpMKMwqVU6uPtkkNkspLb2DfDvYR2ABSwXqTI2Przu9rmunRWPV4avZ4mydP7GWdIXZGy6FY8gDTWySpIFfa9tFuPJYiW0HeRMvK6zpYlhcAGVaAvZWtyHOtDq/Yxsnz0GPP7TvYhGyLlbHgiR55X0MLHc4EuU8HbSnUCZClZuZOsNgztEYPHoRLV28KZHaAtSAKrh2J7BV/pDL79gcQqdS10wZvYcG7zaJRWKM4xCuIWiCVHyt9oyb9EvFQ0Ef0JBV85Vax+OvRJxfYHJk5eZMuv3Lmdz/U1jZ0Atba+NmFr+Fq2BNzaV29I+39LZ8eqKupb2thV6y6oQOXJQBbySxFj9/qo6OHWbM1+jToHyn12jvFtJGYmGWv2fiZkJh/4ikXHDjo3/5gfft5/3cJBIbkiyQVnAad38GWgjNh1xl6YEqoqm+CV5gbsJKBO7OytvmjXXvUeg8TZO6IcVV1LdgMaVdZ13jJ5Vf94dLLoKKfqmrWbNykNyfv+mIvDlvd0Par8y6bPe9+FiqxWCo9e6RRoMVrFGumOM7eYOd6nAHlKEqlu04GQSr4DgMqlVm3/r1ZfB7Hg3lNS+f8xS+rzYkGe4rGlKY10+b/eiH97eK1eI5rFXMKPOlecf1NYoVHrtaSyqTCmnjVio2CuksFIc6hTvuHpbJqw0dVDVQqrMp07Am/YIVOWrNXHFHjsFRY97RIUsFrxZqPkV/gcVWsOehAvsDKbQIgIwvw04EWll8kJudfesXUXV/u8Wdn9TRvQgaKZVbBi2Puq66LRir+gUCiuvj+MQKSssbqbKlAb08LweBIByaX1+rJTtDYsLzwlXf31VG17BXrVKATtTnD5MzrcswopGIwJZssqdm5E3/xy4tYmFLbQJuHHazznXz6eWxKBTzml6/d3NjRBqmwK8ZqVgL4v3gLvWhgX1UHrVS3ZguOfDYe5cWXX4eEho9x0X6q8p14+m/vuucZfAqOg8v71ff7BVcaCzEjSSUpbRSdic6WgjMJlgpemSfgFUZTB6WumSYQPhFnwqRidSZ/uH0XjfNacas0P7Nw8T0PPYLd4aR/zX8e6bhwyZswyoGapjvvfurV18rY98IZfrD1E7M9mUtleDEMpSJTWmrLkhtXD4hUzj7/IggDVthX24K8oGLDFldaHqRCG1yJ2kCksuPzH/DUiW1orXWLb/Jp57ExTuAbUSrrWQk1azrcTSrL2VshUnny+VcPNvpYX5aGdt+UWXdiR9o7mg3mz0ZfFtVySCoZy8s3+JsUs4p6RxaeZ3WmlMefeqm6saWpw/8sPHbSz5xJ2QEcnixWxcKQqWx4Kgc6U9ILL/6vrom2KRKl0vnPx5+feNJZ7tQ8V1IeHmaXl6w+WN/KctKIUhGhncltMXR1ZAGNypQueEZY3YVhMbvylXicdxf+9d75uG7VzbTJ8uzbHsJKW9LIiK2/gpoU3/PA0w3iAzitWmiGVBbhcql0bldSAS7aitL1WHmguoO2hmr3LS/ewGYURVb+7KJ/I/JrFcvNkM+Om3y61ZkawOKgNeHAbE8FOKY7ZQQiD70pnfUtNTlTtn/2LXanLTvaffc/uvCLr2ua2/zFZXfd97jWlNhVKutCpIKURcwBLyKECggMQsodMUFvSXR6cpE6SAiKKREgXbBSrkrEEwYOi4PLNcJjT71Q0+BvXP7htq9Wv7cDy1W1vov+dD1sce2Um1lUurz4/R/3NuPTWUOPu+57FDeMUUjmUhlGDHZF/fEmlawRE7/fX4+c+kA9IhXflz8eKBh3MqTC+qvDKKMmnvnDgYYGfz/2zp8OdqRkjVMbU6XqxL5I5Yrr5/50kBayQyqNHb73t33tyRhNx0eJUSoWe+ZfrpzFykNYhcoDj8wPKAQg+0Meobd4ABaYUWjTIyGNZTTN9FGXNhuDe5BDIVe1J2Z7c8bv3l/T5vNro7XThzX9JRX9oa4qMEeg9VcIeBf+uOKG2/fX0RKwA/W+eX99ROw3muNMHXNkUnF68mkFuDkV/Po3l/xU2cTaceEPue2EE87RGJKQpV47dR6r+kaei6z8wUefQWwRQFSL/8ICrTHZ4c6DG2hLPCGdtrZwJN/90L/wCFIjdjv9fh9tY9Yq+mn3/oZxk8+gKrJ4XZ4RPUiFzhhkTkbWHyyVv979ED7d4c5BArEUpAkqJONfbIxjiq0B02E4ndl92dXTaRmm2F0JoRjAd8RybuEJ0NWIMafisHurGmGUyhp/Q+fK2tYLLrwUB9QYXVwqw4ghLpU4hYUR/G/YDXpdTzRWorZIFeYepHKEAxfaMwKYXN4nFrxa20Yrh2uhjSbfh598+5s/Xu1IzXd7R57z20s/+Ojr6hZamk+bx9S33/nAk6zcRmNNxqvBkf5u+XrkS9X4WYpF/+bETIPDyw6utqS8+N/l7C36bqsvvWCc3p5mdGZgs9L3tuGwB8QubDWtvs07v/vT1TPc3tEpOeNHTjrzD5fd+PqyNWNPOgcfISTlmN0Zyyo2BA193xloAWy0p7+//fM6sc4foc+eqtYFL751wunnZuRNcKUWZI844cQzfv2Hv1z3+LNLV23c/vtLr4fVsKMzJf+/y1azDnRMeLf8/cGU7FG2pKwzfvn7D7Z/daC+46dqfw0/tknPHQ8Xqk2eLhX1YpNigz0rUn+Ungk0FeuOjiZxzlnnXbavloYp//jnouBOLT3PosYKJ+9+cD7rM9jio7J/+MmlrM0eq6PSmNLeLd6ETB/vQurtPt8Lr7yj0LvU5kS9LXnjtl1iiSj9jrurml549X+TTjsHDwRJmSMKx59y6tkX/Pma6U8tfKViw7bfXXIt668uuLNxP6gtSTp7cv74k/fVtyKlDjR21nf6eyniAeLN5WtYqrHHESa/ZUXrqfxaaVSBrB/mPjRMMn3oWbdpFx4+Ag3WF7785qlnn5eSPcKZmp09cgLOEoJxSQAAEABJREFU5KLLrn/smRex2W8vvjYwCBg+AunF2qGx5yEE4pUN7ds+/caW5GV9IXd9s7de7O1IG7WLs7kcqPOxoerEjw4e222wcz3OgDJIUok4SnHPUmFropFKuEjlaEhFaXInZ495f8dX8AGcgYwAgoEkWC0xqzT295GuaXlv666UnLFMJyqzpy9SwWvumJO3ffbj/nqxWkVsRwuxsRppvNaKg4JMOPXX+AiFMTGSVJDLI1NDdPXFD5VMKrThVsOhvvEM1ohArF0493eXqYxuiysTNrp22q0sWmL99RrFPnF7DjZj96931yIwCtQVDZBUeoBNtWty5rGxv/SigQIu6btUTPbs8353deBCYbN9NR35Y06BVIyO1MLxJ32/vza4A1OgKUcAViL6m4uu0lqSWUKwKiK11a0RPCtWb4BOkFi4bXB8XMDdlS1XTbmJpRobIyeSVIIj6fEn/eLLH6rbxBuSfSLrYMtUAROw5uwQw4V/uoENlCAOH0lPae2mj3GfYEc21gPuj8efXay3eVisDFPiXSYVsRuWr2TNlkMDLmRwqQwjjkWpRBOdDFakInolKW/sae+WfSB2ieiAPxA3IIDAv6x5Ehb2VLe9+MbK9PwJcAaCGzyQ4tUvlbKNVCpix3K8Yn1AKhprKvZib9F3D0kFe8FJiD/glaI1m9mOuw+2QirsUPAKlIZzGHfyL2AggMPSSbpa/IbDW3TEFzFmwtHsKXkF409b9f7HUBT7Fuy0GUxX4MeqlgsuvgrbiwMhJ2OvJa8tx7vYfl9dJ/bF52KzL36sPuXs3y59fQU7MXY+sCl2xBfH57JzDtBDz/kjhsUlrFNkyFusN0yP8UqmyZlz14PPsay/WRzn8Z9PvsQCIzYGjNmVj9f3Nn9VI/ob3wJ/DzzxPOSNUANiGHXCz1Zv+ujHg01wQ/Ohh4ZgsAaByK9//2eDMxUWAdhR70gB2P3yKTMb8FzSSWFjq3y/r9mRXEAHqxbjCSYVqyNrWdHGYKmYbd7gDB2bFYw9fc37u1jdG2uAzkYAw2tDu/91T1X7H/48FQdnU8KwoYvve+Q5Vrja6fOPv3LRX6bAN2wwhUuumMZKXwPccucjbIBqdhAuleHCUJZKWJfEVOR19CMVhdFjTsy2enJ1tvSfn3vRv55/pXzDjl3fHkCujbx75zf7S9ZtffjpJSf+/Hxk38hPEdmwXB45LNPDkUmF+QAbw1Jnnnfx0y+8hqjlh8pmbPz9gSbo4Z9PLT77gktsyblWD044LZJU8Ao/sfI0BDTnX3TlY8++9MFHX3+zt542wK1q2bzzu9L3tkEe10y/ddLpv2ZHYzvCK/g6V91484pVm77cXYNjbv30B3xu4YTTcbSX/lsEsYVIBbscBamEDAIWWMmGLo6iEKx3qbCB9K+ccltAKjDED1WN3hET4AZgSkxXml3/d+nVT73w6qoPdnz6/X4Esthgy6fflq7fsuCVN6+eftPJZ5/vziyEQuAVuIRJhS0nZRd+sfsAUrzB58/3H5//CrLsWKXCJiDAjhf95caFL/1v/ebPftjfJHaYbfv0mwOrN378yn+LZ91y32lnXyi4c1XGpIBXsAuiUtbCcH9tJ84BoVjhuNOgEwQxCEdGT/o53g2WCmIdNlSEIXimMi6V456hLJWAV3qIVKLhKEcqh+l5sqxDGB3ZUW5J50rp8tFR7RV+oid/EVNPawYaNhBLuM8d8Ps+OF7ptU6FtuDocnv46WWStEO3AR4vQMSbpEcO79itoXP3zNpkzWRtwEKIfZKuLqPl+8erF2d8iTQlF5tVLMrJ3AY/1+MMKENZKgEfJKiEgCGCl48PqUSfmx9nUmHfaFCkEiODJpWw99IQlEqvx+FSGUYMBalEkgGbp6vnivroGUCp9JJ19j2dgqUy+DO39yNHNo3jUSTSxMY9X/9QcYoJd8TqFY8p5FOYzCJk1ocskh1CbzME53ajZ3OEbi+2U+/9CHw64eHCUJbKkcnjOJaKyHEllSFPP0ilz4jHHGyp9Lh9bEcY7DTlDDBDWSr9xUBLRWvL7AZWZg+kZjhHk6Ep8tA7KnJxU6x3YP/esfz+H2ZwqXCpcHqDS6W/zpPf/8MALpX+kEp4uFQ4R5NYpDK4DP614gwgXCpcKpzjAy4VzpCAS4VLhXN8wKXCGRJwqXCpcI4PuFQ4Q4LhIBWJwgr8UpFbZQqhriS1qcLLpcI5nuBS4QwJhqFUQG1xCpcK5ziDS4UzJBgOUpEqzECisAGZVAB1K1NbyrOaynPqir0WeyZgl4N3zuJwOJw+0U9SCZZErBxtqUgSLLUrUrhUOBwOp/8ZnlKpX57SVhZWKnzAOw6Hw+kDXCpcKhwOh9NvcKlwqXA4HE6/waXCpcLhcDj9BpcKlwqHw+H0G1wqXCocDofTbwxNqfinEFZZGURpCYZLhcPhcIYoXCpcKhwOh9NvDGWpBM9Lz4u/OBwO5xiAS4VLhcPhcPqNoSmV/oVLhcPhcI4SXCpcKhwOh9NvDGWpJMjDw6XC4XA4QxQuFS4VDofD6TeGglSIzBQeuSEscVJTWCJtz44WJ7fHKxwKZSJoLM5sX5XfUpbXUJRlFbIt1iyjLc8g5Jqs2WDwU4XD4XCOTbRmr9GWM9JGdpbe1FqR3bYqZ2fJzAwVYZMlhkDjhAgKIVJtgDiZLogIIgnangRaeYWiMocl7MmBSNv7m5DJ7dQrCQJoKPJ2rC7gUuFwOJz+JZJUpEqhO9QrEYKSBMVhopFK8PbEYEuLQEZYTEJaWCJt7z+aWLSl06eqNUlcKhwOhzMQRJKK1ugJQWdKopjdeounO0ZragC9OTmI1LAEbx85UlHawhIxUomwvf9oCgeQyihcKhwOhzMQRJKKTGXrDo1XVBYgUZpDCK5H75rV28ISvH3kJsVKU1giVuBH2N5/NLH4i0uFw+FwBo5IUomUb0eqqA8uzuqKLgJBxV9cKhwOh3N8MLSlohDCErmpcfjt/YhSkcgdgEmlrTSvaaVfKjp7ntaWaxCywaCnCofD4RyjBKTyScm8LlKJKI8IxCqhqIq/uFQ4HA7nmAJSMdlzh6xUYusU2QsyJ5AojSq97evS/9uz7pLmosyO8rwUR4LLTNT2TKB3JFEGO1U4HA5nyJMLDNZ8oBcoWhjFli2YsuyWnFOTyLflv+wsG9VaVLCu7HFVQuxS6UOnyKMqFZnaTCSaMSbyRdEFvrUjW4qzVhct9XoUXCocDocTC+GlYjNnQypfFp/1XcWvWlbmV7+ZbtGS404qQSck1TjjFEKakoZmDe862kuSvyn/7RnpRO7MB0pHusqZMdhJxeFwOEMdg7UQWM2ZgFUcyF3ZisScZGdciiv+4OrUlk15deUpB4vdRGJW6dyRK96PcakQGa16SZLSlgmdZamtRZ7d6y76uuw3AamoXd5BTy0Oh8MZ4oSVCkhykPfX/uenYlfjxuzmtd6a0iSp0p4gF44rqbBJiBOUGhAn8xBJokZBQN2a9MpST9ua5MYyV0GiK9Nq0VhGqEwFOiELDHqacTgcztBFLPIyCLmAZZhGx0S9bfxpLvLNyl+2l+U3rczatXqe10CI3kiU6uNZKoBJpboiBTSUOltWed575+1fTZ4EqZhd4wc/tTgcDmeIEyQV/Guw58AoOmHcnorffF9ybltpHryyecXUJCUhOgM4vqSiSASsgwyTChPMBCk5sPKu6rLsymJvZfml57iJ1ZwLBj+1OBwOZ2ijtWUCRWKO3JVttE/WCxNdLpKYSHzFiW3L7a3r8urKMgjRqNU2okgDw0IqIwn54tVZdavywN7ii/eXXuKwFUIqonIHP804HA5nyBIsFRhFZ50Ao1RULO4scvlKPTDKgeUeGEUiMRBJ0tGWyhE2EY4av4rYOQWtj9co49SKH0ou2LvqwqbVHvB16a8n2YkgJAOZOdWeMUZqOxmonBlAax0J9N3QCoVAbcvvFbalwTISmMyHYVVeDBZUcjgczlCAyUPrSKKwZetYoDKN0FhGaR0j1bZCJyHpClK5LLupYnRdsbehNGv5f/6hIsjbhTipRaI0gr43Jg7xSg+CGTSpELkEXhmhIN8Xn9+8Jqm+3PVN2bnwis2WYrdTo8ArcsepMvspXCocDmd4EkkqlsRJettYJpVcffwH/11cV1Lo2zC5viSTzqirICYZgVFYu69+lArTSc8hy4BLJaJsZJoEhY7EG+RK2zcrTtxddnr9KiNoWpnTuCL7l2NItpEYnCbA6lrYpeyOWhgNVLaRvcK2ZHvpuzAaaP2M5HA4nCECnEERxlLYsjMFZKeRrFQyXke+fOf89uVJvtKMzvLxvjWT3yt61KokcqLRykwqqQ3IZCa53DwspMJqWSQyi1RuHacj8ErzOitoLytsKy3YWX7HtpU3calwOJzhTCSp5KSTdeWPfv6/c38q/6OvzOsrSe8oG9e8ciQCFH0C0cnNynhdQCrguCr+igShrY0FokwGSo1ZItd9V/zLH8vOrV4lNG/0+DZktayw168+cd+K0WOTiNdARhjDU2im5EdNoakb4hFGmDjDkUIjhzN0KTBTWE41UqCMc5PN7/7Rt77AV5ruK3V1vG38vij/wJpxG4oecmoI0VgBntSBXK6XyaAWK+hfowxyRX1EqVCjCETugVTipRpIZYSS/FD6a9/WjD0rtL5VKe3Frh/fLoBXdpTO/Lh89heltzG+LLs9mC8qbgWfVdwcBdjs1i/Kbw9FPMKX5YybOcOKL8pu4nCGLJ9XzKWU3Qa+WDVvZ8nMr9bd8N3Gab5VWb5yr29Vkq/cXff+id8sz3GoiV0VKhUwjKSikDgBUWiIShcnVyQoVXEKi1Rj1xGyrfT5Hyuu+K70L76ysa3LC3zFFl+ZzVfujICdskronQq7iDMUdgRGhcAZXpRbOZyhS4WeslpOKdf5ilXNbxk7lgntKzN8JVmfFV//RekUEk+ATKoCrMhLIzUCojEDudwIhpNUVDoAozCpAFsCSdaQc7xk79prfOXjqFSQ15cKvlJ7BARKuaV3ygQReyjsCIwyC2d4UWLicIYupRpKuYRSovatMfmKnL5St680G+RqCJAp4+IkRCHXgGEtFYmMopRQ5PEmvErlNolMYMViCTI6o1eckSSYyfvlcz7b8o9P1twRnrW3idwSYNcakdV/B5+uvgVs33DDlnXXVr/z54aVV/qW/IHyssgbf/L9+yLfKxf53rzss5KbOMOKL8puAYeKPW/9quK2SGDjT1bM3v7O9G9W38H2CiZwwE+L5w1ZAl85mu/LGQp8ueo2WrBffjvYWX4b+Lj0ls3LZu0ovinXTJQ6rUytkkgVICFBK5Ho/PXnwXms0gxYUVic0iDSbXr4I62lH4oV9cFSYcAowVIBxECIjjj1xCAlblUE1KEkqUSUlGSGQBJN5Ew12fbEqZW3jwE/3kn5/I7C7/4xbs9d437422ivgnCGFZlKSpbKT7Y6IngX22fIyVgbyUdB6j4AABAASURBVNOFkqv108MRhgLsa7JvPegXn9MrGUrapTFVTkk6hFtK0jUkRUmkKmW8XMakAqMcZakMudZfTCcMhfQwrOkbUWuATKEAJAHLlgTiVEtSJXGJ4Yl3ithDwA8HxCV4SLw7kWg8RPftjY+Cyhv+Bnx/oey94a9V0+8uuftv4wmJkzs5w4p4hQskKBMZEpW7O1iPbbAxkdplmiRn8miFLiUErGdI1Z6hTOAbsS/FGeLEKV1E4WTDXBGliNpDtMlEaqPg+Zs+hdNcNE6mo8hVdASs4JxWYQ3QXSdHJpVoSsCOAako45MBU0gCcYUS5xCxhQDTAxgFpBLTu4++CKN8P/3xmml31824x3c1pWbWvfun3gmjZHKpDD/YT7dnqTAIMZE4C/JlV8qYSJl1IL8emrAzxNkGFNjdjpwhhVyfItUmJWhTAHUJwH2Iu1EixKndRGEHCEECUmFjKh4FqfTqlUGTikx6GLnMClRyQZZgUsoTZBLiiJOaCBlNyBhC6qdNqbru6uoZc8Izc5bIjAC1MygN02aB5qlzQMf188DBmZSmG+cA3/WzQMcNFLZl3bQ5HA6HM0SonU6pnjEPVM2YWzl9DjgwbXbd3FuvJqSQxI0kCcYEqY7EE4WUKGVShR748/1uue6wk0pCvFEhF5QyK6RCCFErpWPdKa8/8cwH99219s7bIJXmWdO5VDgczvAhWCos72q46fbqWTdBMI0331F+16NAH5dgV2kSrCYiS5ApDUdHKkO3+ItVzrNKJJlCUKjs8UQrizOeQ8g39z7smz69/ZprWq+71jdzRv3s+0DDvLn1c+eEYxZl3ozDiOt90+eBqptuBW0zbwbVc26izJ4NmqbNAm1TKGy5bvoMDofDGSKwh2P20HxwFqV27tyqmTNZDlZ55V+abrx+3w0zKm+cfRKRjyMkgRCTVMsKu7rohM1a0k9SGdIV9QGpYJnE6ekC0T98//xdf71ny9zb6y691Hf99b7Zs1quvaZ6+t37b/hr3ZzZEZhJmTv9MOL6zmlzQeW8W0DrjJsAjFI1ay6XCofDGfp0lwqAVKCW/dOm1Vx7JZMK4ph1f//nqjvuN0o0hgT10ZHKEGpSHFxFT4hEpbcReVqcMsNMJO54XeeU2b4b59bdMK15+uyaWbPr586r+Pv9q+56wG7OcFozM9wFbqvXqvUAQZdk0ycL5nRgs2QAqzmz3zFbDmOy9g7b0oqTEU8pSqwxEv2RGdGceTAxX6jYvwKHw4kSk0AxW0UMKU5blkvIevyfi764bdZnt8xonnFZ47Q/d86a2jTl6i/n/vV8QjRSo1pi0EhUVq2ZzaQSp3SDQ1bon0m6hqhUYJQ4mQ5SIcQFo7zx+MKWa6bBK60z59ZcNxVyrpo+40yV8WdyncPitRpSIRLmEocx1WlKA12yZi4VLhUO57gjIBWL4LVbKXjCBpcQ8sncqR1zr26ZeXnLjde2TrvuxzvuhVe0MhOTChgIqQy5OpVgqSTIBYnC5ohPcEmkNTNvOjB11p45M3+cNX3N3Y+X3P5gsi3fZcqSJ42OdxaYbelGa6peSDfYMox2LwPLBiGTYs85xsmKCS2dSTQGBvr8B31eVQ7nOIb9ivVBP2SjjaJMTFd7vGP0SW8+8Oz2224FHVOmtl53/ce33n8yoV0jKUo78liiNoNhIRWZykGIHkZZ/MCDkAqAUfbfPPcslf10qRlG8VhzlSljpe6RgjPTYs8wOTIZw1wqOntOTAz2t+NwOEdO8K9YY/EaRKmoDGmQisKVVqhygv8jBFJpv2GKb/qMD2fdCa/I1KoQqUiU5uO/+EtJiEWm7pg+u+3GmW3TbuyYMf2tx58sNFrk5lyJIctiyzdZc81ClsmaqXHlahPzzI48kz3XZM832vKCGfRU70askoiNWI8/1L4vh8OJHqONEryG5QMWWzayR51tBLCZUpOcOZtvvGvnvIfab5zSNvWGj/92z2RCZGojnQjR3/mRDtPSX1LpTvA2gyYVGGXJE/M7Z8ypv+YGSKX26qsmON1ZKq1KKABGSw6TihWidufDKzCKGPflcanEyND6vhwOJwbE8hi9jYJ/9eI09cgHkDcyqWiFQoclHVxItPAKjAK23fb3nX+/D1KRKPUJYtf641AqErkJyKQCYM2IzyXky5vvPDjjxvq5szbc/+DpUrnekmeyFZqdI3XWPL0t1+jI95cqOgpVAuQRiUG3SBdiLTON/T4b/O/Yl+/L4XCixyBQ2DKrX1HbKVrRLlZzNrBYs8yWTLXLa0zJq7nhsqYZ1zROmdo09cZEQpJJAtEkEkv6EdSdHEtSkSnoOGjf3v6Pz+f9tW7OzMppU0rv+NslSSmQisGab7AV6AXoJFf0CkVmyoJXBksqA3/fZMbEwEtuqF0fDmf40qtUBEsOk4rKmaF0pNdNvaJh2lUwStuMma/e+2ASiadSkVgGUypxUlPgNfjfALHqhHW9YR8Go8hltiQiS5OoGuZMr5kxpWrG7D3XT/UmTzRrvYnOUS7HSL0jX0uNwi5ibhTE1hqKJUb0xHoTxH4+A3v+A398DoczUMSat0xSCaUPPXNwJh0u7Ks7/3EGwZ+mHweUJFI96C6SiFLp1Sh9lIokwaJSOlPiFS/d81D19Bua5s2snD6rds5NJk0GsJpzAVMFlwqXCofDiTVvGS83L7/n8epZN1VOn7Pzljs+mnerXG0nCWFmUul7j/qYpRIimCMm+NQRpigVjnGElN1zj2/O3JZp01c/fM9ZVq3VXqA3ZanNmWI9Sm6MxBpRxlbcNOjx71E//2P9+nA4xxOx5YcWqz3RnVx3y10HZt1WdcPNB66bZ9HaFHFq/2At3egvqfTUpLh/jRKQCp2ATGWBUUAeIWsfeghGARUP3X2CMs4s5Gn0GQZ7njtjIpfKYJ//sX59OJzjiZilYnck7ptxy8G5f6258bbGWXcalGa1RNdfUvGXOSkDHV+ikEpswoimWEyhA3EqW7zaLldZFWph761zPp96TeN101qmzDS6kgxOD2sczJrMcqkM9vkf69eHwzmeiC0/1Ai0f/SvE2Rb77635ca5DdfPXPWPRwsJ6V+p9FxpP/Ctvw5JhSgFidwkVZj33z7vq+nXd0yfC68ozTZIxSDkgkNliFwqg3v+x/r14XCOJ2KWitaWDalsueueY1IqwdNVRt5GBZhUlBor8M2b0njjFW1zbq6bOsOg8wqWPJspH7ABDWl74pjoB830nJwx72Ww5w2kFIMZHKnoBG8/SYXLicPpmdikohUKwRly5bp77mu7cXbT9dPf+8d9Y48hqUQnHioVGAXIlCatwQGjdM69of7Gmfuvui7ROYpLpQ/0muMPdamwQ4mvA/3j5HCORWKTis42QmMtOM6lwjo8MqlIFUZQf80NHdNnN0+f2TB1msmZQ3uJW/MBmzMg1ovOis66wnoMZXYj+zDiJwajFwpD6ZLpR1sc5M4YrzKlq80ZOiErmFi+VLSRh8HhVVtSpDqXLTkfC3p7htGZqbGm6mzpAcJdhyNHb/VqzekAC2pjKl5N9mwhMd/mLgjd0p7RK0ZHtsqUihtAbU5TmpJwtjh5fB3/Br1IK9KVEVMtqoePnqXeP5FfuPuzZ8LfvUd6t0S4Pv3AoOe2nDCwzuM/k8jX3X1v+9TpzddN2XDXA+NJ5Hw+VpFIe2dISMUoFACL4LXE/sQ6dKTChlExOnIFzwiTM49IbVgAVneh2ZWP9VH3P49BKoCJRGH0IFPGK+wycFIJVovRlmVx5sIoGlOaM3lkTFJh5waXKAzJTC34FipzstzgNrmyuFS4VDhHxhCXihCBvkhFDw5JZXrD1Kn9IZUIeZ8tI5Tuagmitx9PtD9dqTYJRkGwkpZ7IqIWkJg+zpEyGiuPRCrBeXG3TG3sSeewvFhUS4bKTL0i0Tqjkkr369PlKvVEZv5JEAkiFajFkTQCsLFUIZsopJIWjNWTnZY3vnDC6TpbKv4Vkv6fvfMAj6O69vhIWml777vaqtWqF9uSu40bBAyB0AKB9AehuGNsIPQeMKGEEEiDQBoJSXhAII/Qew2hhBJ6tY27LNlW9b7/nbMajVa70q60K62kq+//zTeanZ2duTNzfvece+691RZvtPfTwdEyPqCCMpEXS6bw5lDhykhmFyrEdYsLNU9fuqF71ar2ZcuyDJUSw5AabagolIasQyX5SyszlPGpvZyVA6FidlYb7ZVsmSWoGByVCp0fIPn9Xx9r6YhJyuSi0oXKXX9/Ytue2Na2WEsnW/orpgIw7nBDrqHy0BOvt+yL7dwT2x+LfbG1G1sAmEQjmAZUnMGa+x5+bvveWFtPbHdXbOPOTqXJS3SZMFChaCGHCtfoKC+gkjKDK9VxRwAVECXrnorK6DU5yyI1Mz7fum/HnlhbV2x3R+y1dz7XWoJkJR2+GoLKff98vqU9Rvtsb4tt+MlvnP5ayZhavTVlNXN2tce2tcVaYeB27H/subczeWPj0tmiRVqf1lr+4BNv4GiSMrmodKHy1wee2rEvBqPc2s2MMkHF4q2UQwXm/sBDv9kG6rTE7rrnSQYAS/Dya36xpzvW2slot7uTqT3GtHNfDMX48hsf/eL2vy5fe2EgOlVr8eusAZsXECqT9ODjL+/cy/bfCxi0x6zuajguENXKyRSmAxVracW9Dz0LIu7qYMJVyIgyAaCChyGis4Y05oDeFoSc/urvnrL2j3/759sfbsETiKdx886uD79oeeHV92/7w73nXHTtScvOgdsHCFlcVRRjxIrL38BarQJTcMxkrXQcKlx9SgWVYtTpB4jZ/DRmcuyvDD2VfqGxVAdNI6YmV4KnUqI2sQlUVq3NFlTwrppdEYu7/NW3PwNO8KLCVm7dvR8U0dvCFneF0RGhmSLffH8LfYoldP/DL+Jtl6CCt27R0hNgZCUM3Hzb3TSBQUZSGkMgSm3TQQ8//daOvTFJmVxUNqFSrC294LKbtrfGOmOxlWdeDlNl81adf9lPAFeAgYgCAScMEvsZdGHpwF0UEWzf4qVfl+OE9PBT/8YO2BOFiSP3uoAZeyoTHioQEK42+a2eaOOMxU88/x+wBIWGB5WEdQiA39LSQ3WdaO08gAQ4URuDWB51/GkoYWhPT2zTztjK9T8akPTBocLVp1RQERTmpMqQKOlBJZ2+JtlqqNcZHWqddd+yVdmCislVDZwAKhqz72e//lNbN3v3YCK7YrElhx1rdII3UbzVQEt982LpZYa53L5n/+fb9jj8FWZ3mKijtfsu3nAjDDSsc1sPiyZ959R1Ont4iBQm2UtrcERRM1WbQ8V6n9ld9cCjr+BQTKLVzuDl79eancrIsp/76wNPpIIKnTmWuLRX3vwM/AAD/OXTcLEOX9V5l14HikhuCmnL7q6trd3gMawbihH/ojzf/3x7ZcMc+Cv9oPL0v3aLbN60oxPOCgof7iAKWR5GS1Vi8uPYSsvve+jp3Z3xCCF+zugIy3YTrzH2AAAQAElEQVSQHWfQUkpm7vtZQINjkPBmKg1hmlMcU34ObP8SvdcVqAtXNb/y5icoK/CDnkAIN4XuC5b4Fx9hOW3WUpunBv4NhFrR0SecCtLQ35bW2JpzroJLnebzM0h1hDTc1HAOlfxVzj2VdBrqLY4ySWbYoGzLZo1AsG7MzFncgEr78tVZDH+hDgioYLly3cWtXbHuWNxWrj77YtgsEIWg8rXjTiai4BVlVcI9+zftbG+YsQBcgb/i9Neqrd7b/nTPltb9sM6oO4MrMxcebnJH46awd2UQqBj7EsDY1Ft2X53dX2MtrcI1xjOn0/R7en9xJFDR2kI4Asp8+rxDt7Uya/X4c2+iyixGBcsu23CzHCdX/+SXzkCl1lo6Z/Fh515y7XYxAEhCQZ1xzuUoXjkM9Ha/J1zjCtRg3R2shbOIEqYYY/pQAT/yHyrJ7lqV6CsMDRX6LkoGuubG2+D/AR7gCkh8590PHXjY8SCNN1w/fd4hJy0762/3P0ERxakzD2GxL0cEDiW+CKh8sa19m+ho4rFcddaVeLo4VLhSKRVUdCZfUlmcocwk40UqpQ5/pdAIG+pVWkvHijXZgoroqTBz5gpWVU2ZjXcSdnDH3h54Kg88+ozeXgpgkG6+9S+ofUN4q7EbdsD68jPPNbtZsFtnDbhDlR98sQ0bYdpAprc++BKWVGX0gljUbIMKvs1b4fRXo+4ptdOgLmn1VMJSk7sDq21yVLBUKFdUbLApSzCRFBpC1Z5YKAbumNHBEXBM2BF8EZ9if3zEAvF2P3wplclt9UbgLrBz8NTA6GCpt0bIElErEfwwsQkkiPPBaeCSsYLa7hnrL8fF7uuKnXvhtVqjX28O4q5fcfXNbTDivbrhZ7/B44InzOqMmO2RX/3mbmxs2cs+wt8df7hf/Fa5KPbQGKw+uydidYWxUhqqUemdbn+l0ebHFmzHDlpjKShl8ZTBj8SVYkkOJdZL9G6sUyNNEqg4gyRcOD5lrqSLxesgXJEUSkLJYAnhxoFDKHyISlhlCKCEre5q8UawLAynb6rOUpF5am9cZmetxVVnddfbPA2QSl/OEtDt1Uy2WiZ79YCE4N6UQnul2RaFPvy0ZU9HbG8XK9VHn/oXlRWWdnfUF6rHEiU/c+4hd9/3+Kx5h7l9tbgLvlCjw1v+re8v39Has7NtP+7ylpaeS6/+GViOW0+ZEbhYieV4FHG7qYjgkqJwxJJhwgNJ7V5iB6NKKWUZX/FFpuJb8KUgHAePltoYLNaWugONLn9DoHw69qHjsxLud3UpkgvG2qpOcqWCijwi1S86laUOjyk7P44CVJQac+fKM7LoqdATz+yXp+yzrbtBhe17uoGWT77c5QlX4ZVQGX2w78+8/C5Fxv7x6Isfb2olwNz2x79ZPCEYcRip+Qd9FXYN9ndrayfq9bf+/h6qnheq7VR9hk08/jvLbvvDvW+8u5lCFh9tbPv7Qy9cee2vghXNOAf8CnsznZWsD4cr+sAjL0mhc0gOlQcff3nr7v0Qaq/4COYS7/a5l1z/5Atvb9rRjSOjGgvLy2hn8wEqcCB+/fu/vfPRVpzYC//++Ce3/ClcOWsQqOCHCCqwL8+88E57d2zLjp6qurnpQMXmqlix5qLtu7thyPZ0MiN4z/1P44tyqDzy5MvYAdq4dc+nm1pgHPWWUpevggwljOMNN93xylsfffLlblwjSvv1/37x6DOvoba+4syLonWzqBksFVRMrhB8JjAJfuQ7H39JQUtcI27NijMv+eHF1+FfVPZhYVF6i5d+Xbw7/bLXnnz+v60drB2iZV/s9Xe2wuhrzdFhQwXCEfTWSpDpxO+tv+raP+BZBWOwJd7JKUkvk77cQquj0uasatkTg/Z1x77c0f7L3/zZ7AgSgN2+aldpVW/Jl+Nfu7vSYAkBKrfecc+2lq5dexiKcCNQAlQfQpFSK8uOtthx31oJflBOCqomuOMnfn/17Xc+8OrbX3y0cbeUBXDlj2+dMe9wEAh1ETkSwAk8pTgyhEfri22d1OXonAuvf/rF9z77snPLrtjDT732vVPXUxiZQyX/NRmhUqI2ZRcq9ChTrf/O//2H6Kl0tXTsh4VaetRx9DJUNc7f081aoWG/YLtBglax2eDNDz51h6JkiFesP3t3Vw9th4Fbse6CuCch4qpp7oGPP//ajr3ME8KhYMrxblN8HK/6J5v3LjrkOLgaeEuBMdG6lf3ziX/JU4rl/so/n3xp+579m3d14Gg4Triq+eGn/k1R9b2iqzTvwMOBE5hXcHHZ2h8Ck3C/cP4Q9gFC3vpg64KvHPu3Bx7buY9lAbR194OKJ9SAC0cNtK5pEWzZ3s7YMy+8ZbQG4UDozX7w44oNN/WDyk13ABU6U8DqjMICrlh9CYABc4aPsHLjz+7Um8I0iA6h5eEnXgJytuzsAHJg8uyesMtXbnb4Q9H6lWvP3b67s2Xv/p37utvEMscS69vaOnbu2w+b+MTz/yFXgyWVlZbd99CTA6GC5bQ5S978YGMLNYC1sUr6qavOha+Ga9y0sx2XjAvHnQJrNRavHCoV9XMBZkLRnq7YDTffaXXXakxlGVDE3tAn2zRIpavBcunhK774kiXRXXXdHWpjhHk/8d3kaBkIFaaWthi0bVcP/JX/vPNFqHyqN1ALiqDAHZ4qFCkKHzjBElAHUfDRrXfc3drOnOb2HgYVytBjD0BPvPVl847YYUf9D1WqsGyeu/TF1z5iyRcidNnli48KNd5s3tlz1fW3wuGTlxXI/cCjz+Eh3NbWQ7hC5eauex+n0qOSxxHw9XsffMYXaewlB4dK/mqSQqVr1dr9Z6zPcudH0ZO4dMNPYHzxkrAspr1da8+9CN4DXqRjTjwN7waqungzjzz+B5dcdTOow4LUHftnHLCEavS33fnn1u79+CLMH6rY8w86AgdELRg2a/aiQz/atAuGjHwdqYkVYulPbbGeGKwe3IsT8Ft4LWHZbd4KQAVmVBSzgHKo4E0GUWAxCRJ33fsoDoK3Gm8yluDNoqVHAyrFesdhx5y4aede/OjmXfu2tnbjOLgQgGdba+y1dzYCKjgI9seJyaGCJbHtByvO3QcKdsQuuuwG1IXTgYrZFv3VbfdQ+AtcgTk75fTzsFEOlYcefxFEoe/i2gEVrckFqMxZcPCXO/bu2tPTw66iU2qzQTljifuCs336pbddgRpq+U8FlblLvvr6u58ROViBtMVO/P5Kh68KHAKQfnHHXfgKrhoH/GL73mDlFLmhPOeia3GDyLnZ3R6bu+hoi6tGjPmkjG5Bg0NFa6y3OJqXrbq2rZ2BClw558Kf+iOzaB88uqmgIoa/mD78pHVPewxfx+0A49/7aNvZ51219PATXaU1xBWwxGgNwyMEUbAFLstvfnfPp5t2gtCt7cxlbBcbC6la0xFjPYTgh33jO6txr1F7mLXg8M+2tJPPQW4HCo2yy7DEg4qv4IG/98HnpJ5bWOIZ+8djz1MqOe156+/vw3fpUaS0NPbpXrZyy213SVABLKm7K4dKvikvoJJpinDeQgVatPTIbW1drOFErND97YGHVEYfzCvqaHhDYLNAGtj9JYd+A2YO++CFOeH7p1BzyOfbdxJU8Pp9vLnFW1bbW5suf+G1dymvDEKd7qZf3dk05yv+8ilHfP37r/93E95hvHLQu5/shIvQmwQlduZIARW8yUQUGEf8HDjx0JOvLPjK0Z5Q3Yz5S9edf8XCQ47C75rd4Vff+QhX1CniEOdw4y9/V9kwzx2s/+4p6975aDuZY6KdHCq4ItAUK/DJYMWgWfOWDuKpXHP9ryOVzagpl1VMX3f21TtaYttaugAVYPjl197z+Boc7ho5VB589HlUoiksgxVAxWD1WpyB1evOp2YDIOe/H29beuS3cKqBaFN98+K5i49cue7SP/7t4bsfeJL1fbH5xFaT0H0PPS4mNIOX8Ma6dDbv1NkL3/zgc5QbXRp8lKNP+IHTX03NA/jujAMOxnZQGZRFGa466yIqVcogf+jJVwHdneLJP/jYq+4A6tdVKkMoNU6Sj7Ag31NvrbS4GDbOu+RmgGrbbhZ6+s7J652+qTZPQ6rwF4giQeWWX/51V2usdR/jCgleS+f+2PaW2Btvb7z62l8fesS3yWUxWEIAjKu0yu6OokiPPeH723e34x61immEK9dfCOjGUxioV5DYnvTyG5+Q+wKc7+2OXf+zP8I7x1N93LeXw6nFdngh1C3mlJXn4aXAR1jiUKjfEKHJUQaKUOXCM4a6EZ6xL7Z19vRCBc/5/CXHil1nUHTV3FPJT3GoZBkqFk/oky93kZHCS/j+51+6AnWwrf984t/Mne/Y/8QLr8D0BCuaN+5ohQmDmb7+ll/jBWucceDGnS1tYugJduqfT77k8FeoTaVwVo4+8aQtu7tg4FhtrouZdWpmhy8CGzdvyVEUZNjJzB8L+ktQGcRTkUMFX3/p9Q/BA2rQxi/WNc/3ldeDKMd882QRhD3YDct7//mUO1SNKyrWeWCsj//OCnxKXUwSwl+wMtgtVDn9860dO1tj/3rtQxDFYAmkgsr2lv0wc7DCMHPdsRigQq0pjz39SmXdDKMlojUEB4GKzR0iqNz8q9+1w6C37cdHt9/591BlE06G7BeWWBf/ZUFFq5fFFeVQIS+wae7iF157hwJ9KHYYu0O+9k0cB3QH41GArORLyx966mXKTMO3Hn76X1LuWc3UBZt39rAKhNgH9swfbrC4mH0fNPxVRW3XYu1brlpJ7kCTBI/f/OFBEAWCv/K1ry9jLSup21Qgh7sOUGmaccinX+xr72YlTL4jCcW+Y3dsF4uMxV5+9aPvnrRWbw4SVGyucgkqezqTQKU38MvIQTnKFPL6w18e8UeaUb8RO12GZy88gj5CseApfePdzdT6wnxZGVTwKdzfm2/9izfciI/EhIjKU1ed39rbnIOV3/7pn05fvc5SDq5wqOSnJilUOlav7V6bdaiw1wzuxZMvviGam268KvtjMVT8Yf1h7llf+r091/6MIQQv1RMvvCru1vn8q29ih++esnZraztZeei8S6+D/VIZvTBhN/z8DgpJQXBTFi09GpVlmEWHrwoMgO3+8ItW6lCJ9/mBR16SQyVVm4ocKnjbv3XSaupuzaJtZh81zuPXb7jldxT02LRzL7Bx6qpzxR9lx8cLj7rkOx9/KXVdlENFZw3hMk9e/kO4QbBcV264BTihDEKgZSBUyLpBsHp72ln0Hxt/dfufSkM1RptfZwwlhL8GQIXlg+Gwl1/9U/JUusUSw2VecvUNp605e9bCg4OVDUC+rbSsSGtzBmDRgnDLpPAXoELhsnc+3oSLxe0DLT7atGvukq+iTEB3FDWWFAHTWLzf/sEqakza183OYf6iI0BNVO3POvdHUqdCADVUMdPsrBwq/FV93iU3bdnF/I+4WkW19YjqglAzQPmjMCF8RN1NwK0PPts7Z+ExKkNZUpyQ7K5aGqobAwAAEABJREFUkSvRryz9JugOB6UnFi/wlj3xModoBTWAZasuAFTgr1id8FRCx55wEhzSPqisu5g9RfK2DWc5y2zsjvdFxcq3T1oH008tfPQ8PP3S29QVplM8/6Y5h8QbV1yh+x95lqBCMdWlR36HXhB8F0wCmQhXhKV3P26hnDq9NeVoZmNuVSe5cj9MyySDCmzxNT/99dbWeDQf7+HJy89ecuhxlKwFU/W901ZTFeyGn/8Gu1FALFgx7Ve/vXtbWwdVlmFBjvv26Xh1KYL/yDOvUJWZur90iCF+CC/h1t1iw4zYS5+clQ8+3z0MqNQ1LaDYDojCOn+4QrgQMOaBR14gc4YlTn72wq+KSVPllN+JC3nx9feooSIBKqhpwqb8/i//xMFhxQ494pswuPBRoKRQgaci1aB3tTKugMcwZPc88LjDWx7HSRpQOfRrJ+Bf1gDQwwqKLhBGmS7hkWdePvfSq3FpEAoWbJZDBTeConm9RNkxZ/FharOHUmNL9G5qNmMJsu6wJ1zz30+27BDTBHCqP73l99RidP+DzxJUcDvufuBpyncSq9UpRwvWmiPnXvxTuB2UUsUk3l+qRqAiApHH2SMGIalLPKopeKg+2dR5/LfXOEqnDA4VeCpWR6W7tB7+xze+dfpddz+8ccs+lDbKfG8nQ0vrPuasgChYbtnRUz91odEaZkWdBlQC0aYnX3ibLpmaQ6bOPISS2qWo4FXX/6ojFm8CxG5f/9ayuK8jgwq1FMIDphQPPEUKLcq8/JmX38HBt7T0MNDujgWjM+Cp8PBX3opGKR5jqAgllqRKBZJ0tsilUrggXaENKtCaC3WW9jVru85cv3fNmtaVK02eaoOrEgUBoWoGZVyI/QdJPPiIb5ERp757N/7yjtVnX0htlXhtwlXNvlC9xVH2P6eeAfMHe4qq7qFfO/6FV97a2dZJJnJbS4fbV419YIih19/6DK+6uL0L++/aE6Nc29YUMtvDlCcKA4dvSertGdRnlGF528QaK3bGRzCLcrm8dQ8+/Ap2wIlta9nX2r6/smYeDJPH1wDZUCWxRe+5/0nYJrJKuNhARSMsNfXegB+weWcXLvnN97dI/QyokzZMc0Lnx2tvuh3uWqhy+gnfW/XRZ7uZgWvrJCfg57f+weas8QWb5CnFDz76rASVtn0xu6vMaPFZHSGtwX3dT369q3V/e5foAHWyfXCclr3dXTHKJWt/+sV/eYLsICCcw1OBUmrr7GrZ176zrZtuh5gjsH/Xnp7jv3Wy3ROGj4KLAmsZTsREZKsrDF1zwy9xL/Z1slaEjV+2+UO1tfVzW1pZaQCNO9pYIzZLvnJL7fDJjT5M5NpzrmkVv7K7PblAmt1ieHBvNytnRnrRgm/avn/BQcfBDSrW+gcemcJodlc1bqXDXWO0ROgJp/u7YMmRZ5931d/ufezL7aiZsCAYPBXyXY79xg8k1/DY40/fvrubnjc8xivPvFx81PugCLfm1f98hq/jqkEpkClQNtXjr7O5yuG94WnEM3ztjb8mDzIm1oG+ffIa3G5WmK7A/Y88LUKlGzTatLOdQr7wkrEDlniQHn/uDXqwcZYoh2jtPLgpKFUOlfxUpp6KRII04ZHOPhMKKrCbFbAsHTEp1+idjzfhtaFo8kcbdzt8VbDgMGdV9TNh02NiL8gbfnYrTNiuPYwZsJUvvfqOBBW8mY899SpedbxR3bF4a8GWnR1dsb4OKAmiPgfM8j7y4kigAoPy8GOvkWXfI5rOuQccCcOE7XpT2BecCmv1+NOvASpgAA4ihwos7ze+u5wqp7/67T3UnkGV1qRQufyaW7zhehoJ7dAjvr1PRAK4AkOPavKiA79hdVSnAxVaOe6Ek//3vkeppwv2wWUCiljBEseEXV5/3oW4BbhGOVTIxdmycx+Igq/gwrEO3uttQeAE1o0anFh7jAiVhqb5rA8HCNTWs3N3z/dPXr1qzYV7xSYKmNePN+7TWyMiUapTtXbIm9Ox4glOG2QfjamMRrP+xR1/QlFTAu5Rx5/GhlSxlItGNvmRDeYy3C/KdJBDBSWA+14arKubMv/9j7ez1OFuVjmA73LKsrMzgspjT73O4pYd7EmA39YwbZHBwno+E1fgwN14yx07Wnso/xse9tEn/GAgVDrEEUVRF8F2eMl4iqj/1kuvf0i9oNpFpjp99WLsi6cU56nGK1SSnNlQUBG0NiadWdBb9qw+oyM3UBED6FXP//s9ll/fHc+Y+mjTtjaxgvmbP97HRgcRXzO81S/8613YL9Bi49YWsTa9n/JoN1z/C1dpDQwoXleczy9uvYu97bBWrT3YYeqMhQ5vOUQ9uuWifuNs5ANHGSzFQ4+9PBKoGC3Ra677LRwUqunDrHzjm6th3IkrVkcloPLhpzspfrJXhKg/2kDGF8vf3fWPba0xsR/lCTTmBxElKVSuv/m3MNwUNEMl986/PLSna3/Lvs4tO/eAtX//x0twVlJCZW/MDjfIHLDayyy2sNNdAbQ43BG9pTRSNe3o4797+qqz/nrvP7E/yI1CBj/uvv8Bh6fK7au1uyv//n/PEVTwEcB50mlrgDGUDITjf7Gl7SuHnwBLh9oAdZmEbO4y6sz/x788AKRBQMtjT7707Av/obRdmObrf/ZHPAkiUarSgcqQAjlsnroNN/yOUp+3tfX8YOVZ1Nuc5sHsVWXC8eFT4pbpTAHKFZaggucEj6LFGTI7gpdddSPIgQcMTyOu+pTl6822Sou9Cjr2+OWDQwWH/ektfwRR8JQCKliBo0PVGuIK6kbPvvQmQaVF7Cpb37yQZbW4y+VQoeSIpUd+C08CPc+Aii/S+PnWfQQV/Po7H+5UGQLyPvkcKvmmYUNlIFeGHQrLGCqZajShgmqUr6zp1t/fw8bZ7aYhW7qgVrGTyhnnXM6GOXGVewO1qCeCFnEzt7cblWhqXcBbd/qqcyi5k6By0qnrtrewGjfqxdA1N/zS5asIV0wZOHYvtYuUaJyAVrR6Blyc9KGSQBTWv9pZc8K31sCsUzcFnMA//vkKSEPDfqDye+QxP6DOdLCh+7riUKHxS9zB2i+2taMQ3v9sp9Nfy5JHneUU+xLzpxOhcsMtvxPHt2ejoRit4UUHHbt5R8uONhZzA1S274rNX3hsOlDBCpYmq9/jqyTTb3EGzA6/L1z9f488Q77Inq7uh554EjjB0RKgsnFrq8HqXbb6bGI8OYXwLxcefEy/YSjFI2O5+OCjtu/qgKcCrrSLjStwWba3MNs6d9HRst7jg0EF0pqZTwNPJRVRLK4aeCqnrLhoy64Ytaysv+BKh7+C0nllREkCFeAf+t+/P/XN766SQwW2Hs+hzuwFVOBJUDCWHoljTzhJbIapTgcqeFZPWfbDzv1xLwf601//SdUmcAuPVk3DXLpZ9Mh9vKkVbkp8OgMZVHrElJCbb/0zSxWxBigbBf4u6iWACjUZ3n3/sxpTiEMlnzW8hvqBXFGorUmVFlQKVDZJqaAykgb8ApWDSemCCoXi4kJV14ozO5evzUmbiuisHHPiKSyC300RsP1Ur/xi+966pgWs7V38FZgzvOSAhFh920/1aDFE0xWtaQZOYPJoT7z5L7/6AQ64efs+ivjf9ru/Hfq1E1yBGm+4HpW+uYuPOO7bp9/0qztfePX9I48/CcbCbA/D8mbkqQyECvjhLm388LMvJU9ly/bYT2++yxec6i6t/873z/z0i307W+NZW11iqzhLRBbr8gcfcWKrOFQz+EqZPNTVPx2o2F214Nm9/3iERd669u/a2wFu3f77v6NGLCqMc0sFle+fdMZjT/z7iqt+euzx/zNz3lcqaqe7/VEQBf7HtpYOiHUO7+r+7Z/+TB3IUbz3PvBMa0cnRO0oIBA4dNZ5l8FfoZAjLuS/H2+bt+RrJXo3+WF2TwSeotHmd/srX3nt3V2t3YBK137Gld17WIX9X699DNuXPlSG9FoIKgcf/r3trbGtu2OXbfg5ZUPQlCd6a1S+s+yA7IF0ePAslX22eTcetvc+3vKr2+86/lunwN8NROpRO5m36LDzLt5Az1WP2Hn+/U+2hqKNuPt6UwRcqalfRM0he8QxWh5/7o3ZC7+Kw6qNQZM41wDuSDAy5V+vfYjbBJ8VQP3o8x2/uO1PNY2zUVDg07sffUkPCQ0Vs3ztxeLIdSzGJYfKxh37ABWU+fmXXR+smOYvn/LdU9Z+8PkuSiYmrsxbfIxUqqmmsxxzqzrJNezsrzT9lXTCYhlDpShZx/tBPBU5VEAUvcbUseyM2JqzcwEVGkYwWjeLpVd2xftyE10+3twS78simnXU72bNO0xqGSb7DqP24Wfb2RhWzihBRVyykf7wqtO7TcMs7umMD1pOsWZKj8Hy6986LVtQgWWHTTny69+Er0AtE/AYdrWyaA+W+2Bq39/x9PNvon7KRipkHVli3rJaFtNwlqG+uXU3SxI9adlZ1EQvcWVIqKB27PVP/ca3T2Iw29cJqMAN+vjz1oZpi4ABIBYXmAoqp55+NqvI72Ha0doDPwMgIVp0iYQQQdV92FFHS9iWoEJcJ6gARRuuv4WKCCUMr+vdT7aDKxTZA0sszhCLQLrCa9dfCE9lbwcjCkpmt9hKf+6F1/bOGFaZFahAjtIGLE9edsE1N94uTdVDszoODhUKbP73w81wOPaKjVUoilYxu5e8B/xLTej0HK5ZfxGLidkqUaVQavx4Bt5+f2Nnb1I7tdvh303b97/1/nY2N5rYhjfngMM+/HQnjRyKY6KcO8XSprF2domDPmD59/97hnCoMnrZsCsyqFB6yy9u/yv1xqecRiIKnvA93ayCAqIkjB7GoZJvGklKcTqhsFxBJYErg4e/tEUOSNC4oAME08vn/3rnqjXblq/MkadiEmc2fP2/m+JTp1AEvDV2592sd73USw6vFuprb33wpRQvpu7Ev/3z/+msIXmaMgRTO232wU++8HZbV3zYpS0t8akSqWsYvXjgyvHfWUaeAb714OOvSDn+kHwokX88+iK2sGkTxZOkVtNEie1DVm9k/QVXwtNiwwR0swylNnFerLc/2DFj3uF/+OtDFJ2gPs+hyiYydq++/QWu5fOtHTTSpQQVEi4fdW15csENt/yBDbfsroaMlkqbs85o87z06luw9ft69lOq8Y03/0EcmapchIqYUtwZo+Ab7prYMlx+0qlnwXJR7oA09hTKh4YMwfVifdW6s20en94Upg6V9/z92daObghwxbeIxxAq+D//9Z937I5t3M7G3Ny8s+etD7bOW3IUG4hXHN2SQpTBcON7H2wFYsGVXbtju9tiX27vLquY3n/q6CxAhbK54LL4yppwZJqTETgRVSkOWpwEKmzextIqj7/muZffojFvKN8aDjE1cuBfwIYwAAZfeNm1BkuA5cW564ATg7kcdFm19hKUA/UjQUl24KnrYHrt7c24X7jdeD6d/trZC4/491ufo7jwHFJPRhrrAaUH7wrLa9mnf/cAABAASURBVG/6rTfcqDEHpKThhH4q2Ke8dvbDT71G9w5baPQgfP3uB57GT/QOzcKhkr8aYT+VIbmSd1B54Ye/eO2SO7rPu6B17bpcQIViAnhzbr/zgQSonHfpda5AHY0zT9278FI98MgL+EjsdtDDRnLsiq0/fwNLwO0PFfoKXt3Dj/2fX9x+93OvvA97jS9u3tkFLD3/7/d+88f7Vq67eMb8pTSUfaZQkYbBlwsnUKwtNbvDrmDV4kOPufsfj3+8cd/mHcyU3HDzndHaeXi9aYhZ4hxOHnVP/HpV43xx7svYXfc+Tq5Jwiz0g0PFbKtWaUNWl//UFWvhVUBdsXgjMIy10RoEVwZChfpVwP+Yu+CIc86/+u77Hn/xtY/e/WQnigh+xieb21587YNrbrytac5XSsPlFpfX5qyihKikUKGZeGCL77n/SZoMhnrtvfzGJzPmH0bRS7056CqtcXurrrn2V3BTWtriUPnz3x5hLqarivrSD5n9lb4oRVg8bAUFvnpBUp0KKpBS62IRqvKG+Yu/Ci/kt3fe+9Kr78IhBkJ2if7cG+98ivI854IfVdXPDFdMUenczLlxVHt8U0AUFgRzRk/8zsq/3PfYRxt3xwndzmoY8FTcgUY224LYGRaPN+71id9f/fu//N8b727EzrizH29qxfOJ2z193qFUnZLqVezBkEGFerrgMcBzvnLdpa+8+RlAjjJ/4vm3Tl11PvVfkfeP4VDJT2UFKkKxMRVX0oNKqiwvYkyxGZKDJ9M2FVUxk6ByQZYi/R9uvr1z3Vl7Vp+RLaiknOQqbkP7uhzSuyQNhMesQ39rKxs+XW5NWDtNyj37D7oe31nWbybpPgkbpTkT42dI77wYswZU2LAcpIHvsOwgNB8GjMJFV94kTk8b+/bJa5nXJZ+NUTbvSJKzitfW5bODiKKT7O38KEYF5XPylBNUehtd4kpwj/rUr1lbphT7GxxRmkuKZj+z++ootIVCY7OAlNYsOuhYimFS4vV3T1nHgnguunFDZ3+l6cEMcGiiIloGgmSA+j2HfUo2u1F5n8TUL7n63/okwBuwMdX+sicnBVRSPeHSzUpFFA6VMVcWe9QPTo5Bdh4MKpLvkg5UUnFFDhWDoPbqHC3LV7ZkL/yVPlTihrvX6A+GitGFitT5WQ6V+J4SUYaCCg0iaWJdoN+FdYAv5S+fRnlfcqIQVJIaegkqiaKgmZh1BlrA5PWf3JNtyTVUSCAKluRRsck6TX64LKcuPxd+DGr9rBfk1j0OXw22O0rrNKZQpuGvTDAzGaEyCEs4VPJE2YJKOh7JMKFSqLZDaUIlKVdomJYiJZOxyGhX23vWn91y+vIcQoUmgk350KeadTwzpTQ3GZ5nv6l23VFJqabjTXkc0TSjFm/z1MCkir00KuU47IOKo0KeAptgGZNAJT7arhwqMnjEzWsiJAyOyqRKs1+IJPl3tdZyi6eWTpU+/drRJ//n7S9ZF/rdLLXp/Iuv11sjNMWhLPqfC6j0ncMQUElRvUgJlfiIOMSSGkmphpnJdJrk/mdVdv/Dz9Mc25TihXITm+KHhgeHSn4q61BJMzcsM6gUaRzpQ2UgVxKgAu1Zubp9TdZSijlU5NdLFoFwAtsqN2cpfIWBdnwIqCR6JCk8j1xABSKozF107OYdbEKRzh6WCEdjZ33yRVvdlAWUkSX3vXIBlUw0PqBCScMcKuNdWYRKmhuHgIpc5KMMAyoDuMJwolaIUhqh9uWru1aNIVTSOab8PUy+T15BxeCIJkbe+ofI+jWlDBpISTo4PCQfUFKuTMs5Y59A/BYRRWOJKI0hjSl05HGn0iChbNasDoaWjz5t+/o3lhktkd4030hCQzqHykCoWNzl//uPpyhDjzIbTb15+Rwq41TZ9VQySgxL3lDfT72xr4zCX8m4wqEy2Hlm11NJBZXUkfHxBBWTq1qh88MFOfyYk2lS501bO+Gg/PLW/517wJEGc5nWEORQSR8qOmvgL/c91h2Lz4392Zb2uHfLoTJuNTpD3w8fKsNoU0nGFQ6Vwc6z3zmjKHqVzv5pQWUIjQAq4pbU5ZDKqGWmhK/rbJXUR8Thq2G9NcVOlGR2tYaI0VI5/qGSiJPcQYUmdRanBaqhRMFUkwRzqIwXZQsqCSOyJGwcHC1DQIW4Mjyo9HKFQ2Ww8+RQSR8qdt8UjSVK8RkaIMBgCenNQb0pChnMFXZXPYdKOlChrrU0BCqNhUq9uFz+hhE6K2NuVSe5cu2pjAwqg+Z0ZYAWcZgWaq4nqOxdsbpjdRKoxPtnjPVd4UqqzCHKNZzy5OXMNRKlmqQrpX1OY1j7VNtTDyg5LKhkgBYOlQkhbuxGpzx5OXONRKk8lZS2PQ1g5Bwq/UJh8g6Sg0JFUcJEUEmVUsyhwsXFxTUSZQqVkQwimUOoDNHWwqHCxcXFNSrKa6hIAa7EMFcKqKSMhnGoTAjpU2jMT2ycipcnVy6UrfDXqEIlyWhgvVBJzhUOlQkhbgR5eXLlv8YlVFKFxVK23nOocHGlLQ4brpFofIa/0kALhwoX1/DEocI1Eo0DTwVSqOyDQyUOHlkorH9/SQ4VLi4urtFQ7qCShZTijKAieiT9oEJcEVtfOFS4uLi4RkMTCipJW+85VLi4uLhGTbno/DiWUEnKFQ4VLi4urtFRXkMlKWDSGZolsdGeQ4WLi4trVJRdqAwvE2w4Y39lBiEOFS4uLq5R0XiFSiquyD/lUOHi4uIaZUmjFD9z2TXZgko6IMkCVAZyZeBHHCpcXFxcoymCypIibb5DZUQSm+sVJUxqlR7as3Jl+5o1e9esbV252uSpNbiqTc5GyOqohMb8rnBxcXGNR5lc1SAKQeXZy3+caY/6wQNfg4tDhYuLi2siikOFQ4WLi4sra+JQ4VDh4uLiyppEqByo0D1/5XUcKhwqXFxcXCNTjqHCG+q5uLi4JpMmB1QopXggVCilmKDCUoqtjmpo7O8KFxcX13hVDRSHyso17aev4FDhUOHi4uIatiYBVIpKXFBJsQMS9CVQ7LSTYstPaV27ZtfqlXrPTK1rutpTDzls1dBY3xIuLi6u8Sq9swb6SoHtxctu3rtm7e4Vq1659NJ56XV+TAcegjK55N/lUOHi4uKaIJKg8vwlN01IqNggQeOCCpRMxWo9tP/05bEVqzpWr9m7YmVxsL7IX1tSWg2ZXExjfle4uLi4xqmU7qjaW3mYYHj5wms7V56xb9mqFy7dMJNDhYuLi4trGFJ5KjSlVWMMFbM9LMniKJNkc5WPWBWQxVUlqgZyuquM5tDGs87/Yv157avObFu2utLkKNOatd4IZHJHIaOzQtTY3x4uLi6u8SW9LWxxVywrNH5+7o86l6/qXrnmzz++uc7kkdv5XkUgi6OcyV4B2ZxVSUWfkszOyqQyufokKFR2SYLCLCkrnkqR0lGochepPUXqUkgQTNC3BeHzdefuW7m2e+3Zd9348wanj0OFi4uLa+TSWoImZ/mby8/54MyLO5at3H3SKcEifaBQV6JxQsVqh6QSjRtSaj2QSuuDStReSQqlW1KxyiNJofFKEoodEEWhCjUeSSmhki3pBAekKHRBgqoUmi4Ir1965a5VZ/acd/F7l/zkaEFjdYUhhz0CcahwcXFxDUMmV3XIUlnhqt+97uLNy85qW7ls35qVgkJbqDHL7XxcaqsosyhjgopUhqQq1BglFagNUJHWpNCZBZ2pT/J5UJL88MiEY8qhUqQPASpzBOGFH14AqOxes/6dC697/ZyrOFS4uLi4RihAxWeI/Panf9542rq2sy7ds2r5th/8j6CE6TclmRMr3nYCVJgGwqOgRJdcIkgkAS0gSrHeUqA3S+rXgJN0Mq505g9ObPyRfbdQYaMZukTZJO1bfk77ih/uWnNe27qLyozuoM6hdzWrrI0mZxmTo8Joj+pZhlyVxl0D0ToXFxfX5FEqfuidFZDRHYD07pDBE9Y66/TuhhMF4aOLL46t/UHszFNe2nB1syAoCxVqRUnGA0Sq+6RQ9gl8ggSNKB1YYhWMNqhIy1SosWL/nENFRpREqHSvuaDljPO3rTj7jmtvqbD6NPapBvd0DhUuLi4uUjpQ0bmCElTeO//8t885p3vl9/aeeuL/nX0WoGJQa7UlqqxDpUBrLjTYIBClwGTvI4rSNApQSa4ZgvDMRdfsXH3ajlWn/mf9md8pEJTuapWnxuSognSOKKR1l0HgMNNY310uLi6uUdbgULFbGqASa0Tnrm42Rr5WfUDnytO6Vp2+e9W6fWf+0FqssSjUep1ZpdSNBCr90oU1caIU6a1FRjtxhUkiythC5flLr2s9cwX03vnnfnjRBYAKZLRXQhwqXFxcXINDxWFthEAUvadmijb4lyt+2bHi1Nj6NSBK6+r1xoIScIVGXMwWVAp1FuCk2GhXmp2EExYB01n6iFJiTN0pZgSASQcqyhKnRu3579offnTORe1r1nauXff2RRuOEkpcqlDQVEVoUbnrIJOdiYYfGPN7zMXFxTVqSt0szxKarLYKu6OqwWCZYrK1nHp227Jzv1y2aueadT8781yPIOgVZkhgqVlmsTU+yTCRqQaRlEOlQGvtk+igkMAVBaCiNQsqQ7++kGmyISOupAOVkmJHUaF1qSC8tfqsPStXQ2+cdyW4UuFs9GojIIqjtIFDhYuLazJrEKgYHFFAxWAMAyr33nAToNK+6sK29T/csfrMkFDiF4qyBRVBZRI0cFDsxUanRBT4KCAKHBcWEEsfKsPmylBQYY32gtqh0HtKimzqEuf7Ky76cNUlHcuX71+z5ov1l286+8rZCu2cYp3JFYC0ripozO8uFxcX1ygrFVQalJU1RZGlguaNi25sW7Gq5fTlsbVrY2ec8cA1NwYEAVRQ6Z1aZYFOVahU6ZWpw19pQUVrFXS2ApNTYfUUmOwQRb2YjwKiKA2i0obK8LiSJlQKtS4QBTpWEMAVQKV71apP114Crjz1458+cuW1HCpcXFyTWamgAqL87Yo/giivnHttz/qzu85cD+PZtXJlTYEqLIAqekAiW1ApYg6KE1ARZWfpXmI7CnNQVCJRSvTpQSXVhC2Z+isDr0TcLigtgjqOGRAPeumsX75+wR2dZ67at2Z5y3dOiJ2xYscZ66DFWsO8YtWCIq7JJg10QIGWi2vSaomghhYVMB0qKL8qqE8Q1O+ftaFj+eldK5fHVpweW71i85p129ad8+A1V9UwH4X1W+zfk9HE+swrTaIsCaIU4d7gWJ+oUyTgUWJxFTrcUJHNBSl08ezhhAEl05ukK9VcYJm22w8c6lLcLocK5agtFMzPrb157+plgEpsxamxlaftOvOs3evPefSKq5758fXPb+CabPoJ9NxVN3JxTVq9/KMboBd+dD30xsXXvXbhjz857/qPz70udsbqzhXLYmesAle2nnn2Z8tXVwpC5QCoiGOumIcBFahYYyk2OwGVYndpkdNTaHUKJlsfUUp5QCI3AAAQAElEQVSMWYBKHC2ZttungoraBBUWMwklOnCFtfko9Y5i1W9/ctOr51322vmX7zvrnK3LVvSsWduxYlXsdK7JqP2nLxd1OhfXZNSyU6HYKaJOZdq37Afty09pXbm6fe26Jy+5/NkrrrIVGPWCqrBQU1JiyBQqcb9EPUB6K4hSZGHxLqXVzdbFRhRApS97OFtQSdrKMlKo9HaogYxCAbiyUBDAFUBlx8rVnaJiy7gmp1aIWsbFNRm1/DSmU0WddFJs5cru1cugtlVrWpavbBaEqYIAqJgErVJpBFfkga/e0SGHAxU4KBC1oFB/FECFcUXeHyUVVFKyITVUUrXeZwSnEoUBoqYeQku8rUVdIkoDGRQqs1L77GU3vHz1zc/96DquSajnr7qW6eprcqSnr/gRlk9cevkLG36cu1/JEz131QbSM1dexTVQeBgy1VOXX0l68rIrsis67NOXXf7M5Vc8fynT0xuufuyKy/9xw1UN6gKTwaXT2AS9W9C5CjROgVlOZjNHApX4WF4GNpyXwsqIohDzhku0bDBjamhJNUlXFqCSQVZY2lDp9WD6oAKiaAuKZwiFdYIwjWtSqinHOsrmmC4IzZND0lWP+W3lSlN042aIahAVEYRyQVArzSqYb42DSe3IClRAFJYrLCYNE1QKgRltHCfUdJ9bqAzClX6HGnCEwmKDpF60WJhYSpitUFkAxZvxi0uVqoCAs9Q7Ba2La3JJ44EKtL4cSdCUMqm9EP4t0geKjaGsC4fNqYZ3MoU6f54o07uW6fHp/mYgeirSkPx8cnd/VepSSNCTvILOo1C6i0pcQomFSacRtOoSBeroJkWBn0lpgDKFSpHWwmRhjSiFVqZ490a1WSjWx3FCIxPnGiqDcyV+wGFDBSpwlSj9Arw8jY0+5ZpEKnEwqTy5ldrLTI/MTAzDco0XJQJ1MihnUBnpD6UjlUdR7IIEpYNJ6xZKbIJgForsQrGZSavOFlQUOqscKoIWBzfLk8EygEpKeGSojPtIZnicvt6UvdN/JT0+bRnyIDlUqj49quwo1XxohWr7wJ2xMVsq0jiSKtP9R0cKrTNNFelSyU1S6D0QrShNPoXWXazzQNJKr1xjopGXQO6U1s3S2jJSxvMEZjiQYqbqnT8xV8p4IMgUdrU/SPrOnPVh1Fnkg6+wLVpz0p9OkwVZg0pmrfcjgMrA48tBghU5cjhURh8q4wUnowOVsTLcIzL0o6hCjTUjcahkESrFGnG0FbEpRT7kMDySYRMly1DJLNt40ONkKumHuKeSI6jkGzxGjpORQ6W/8tgbGCtgpPMgZQiVEb2Pk0BpQoXhCm6fzk6JwlChzkLN8jSi17CJkn2oDDToowCVsQfJJINKUsORYN/zHyccKhwqE0/pQwVEKdY7JKJIOCENmyg5gUq62cYcKuMQKmNup7KIk+FBRR7yygeo5DOEOFTyByr0aTykRvPJ65iksbyoVyOW8XIeLlFyBZW02leyBxUe/sqHNpUEW5//OJkYUMm0fDhUJrYyhYpEFElyqAyPBbmCytDtKxlCJfHr/RFSwBvqswSVTA3EeIHHRIVKtiDEoTIxNDhUqAzlMzkOTAeQtgybBTmEyuAeQxahkl+hsEkGlVwDhkMlfyDBoZL/yhQqSQ8CqIyEBdmDShqQSAmY9AJcGX13okKFUCHvrJOVA+YiMjYuADMIVAgnchUbvPJ/U3+3T6MPlTyBTbrPT5ag0pdDPDKoDOweKE/DzX/1m1t+QFArDhX5R4NCKH1ocaiMb6hI/spkgIrcPnKojBdPZeCDMTpQGeJ95FAZAJWMj58XUElFPw6VEUj+Fk1sqCQAJm+hkmt4jBe6pDqTUYDK0O/jJFAqqKTqUDk+PRUOldxAReLKZICK3G5yqOQ5V4YGSS7bVBLf/bG28nkOlYyPnw9QSXVCmUIi7+CRB1AhrtDLObGhkgucjBwqCr1rzKGSqnDyGiQjgEoGA7RwqKQIc6XjkUwoqGTKlbGnyJhCBZrYUCH7SL+CdRpNK4uAGSFUJK5wqHCo5IMyhUpaUaW8g0oKWgxumjlU0ocKUYFDZaygIvdXRr+hfkjYTE6oJH8fJ4FShr9kSQc0KWJ8vt1Mjz9+oZI+V8aeInkAlREqn6Ei4UQha1PJ4ui/WYFKgsYWKmOFk4FQSQs2OYBKyvdxEihTqIxLTyUtpSDEuIRKKkaOABuDH214x8+UGbkmSmor6c6S0odKv26Pw5B0BFFDpx3nGkKjCpUMIZEtZQsq6YSP8lkDz5ZAkjUnIQ265BdUBuGKoDAn1ZjTIs+hMkIvhEOFQ4VDZRxBhQaFzDVUBt8n76CSqb8y5rTgUJlAUJHDgEOFQ2X8QWUUPJUh98kLqAwkR/pcGXNacKhwqHCocKjkieKlIeuMQo0oo2nP8wIq6dCCQ4VDJZdQSaTISKDSnyscKhwquZVQbIQVpemBaX4U+TDDgzfITy6ojCNgcKhMHqgUG7yS0uMKhwqHSm5VIJ8uRWdn4lCZANEtDpVxC5Xk8a4CnbtQ7+knXWmmKtB6OVQ4VEZTA8NfHCoTliscKhMDKoLGIykdrnCocKiMpij7Sz7G12RtU0lDY8cDRwrlFjY5gkpWMJNvUJFPnCWHRKHWhWU8WtU7rVaRxlWi95JURp+gdQkap1BiFYrxQtok4SO1ya+1BHXWkNVdbfPUOH31Ln+Dw1dDsnmrTM5yoyOit4WhIoMX4GGHUjvkoqso1rmgEr2bVljnzRT98HMBlaSMGXDvXCmUX1CRD4yYSiM3zfmPkwIx5DX4qMOptnOo9GrMXJaJAJUEwAwDLbmu4WYLKvJGcrnnAYRIUBFKbFChGubVpbQEjJ4KX2VzpGFu7YwldTMPbJxz8JS5hzTPXTp93qGzFhw+e+ERcxYeNXfR0fOXHLvgoOPmLPoatsyYfxg+nTb74KY5bE9o2vxD8S0cobp5Ubhutjc6zeCO4uC4BJSeUGIRFCYaCABoURnBOXfSIV5GhyjJxKEykaEymlwZT1CZMKGw0YdK7pSHUJG4orWF4KPAXSjQOAtEH0Jp8hld5aHqGeX1c+pnLJk65+CG+V+rm3t41cylFdMPDk9ZHKhf4IzOtIabNP56baDBEGoyhpvNkRmOqrnh5oOjsw7zTVnorptnr5plLm82hKcay6aZIk2QJdJsr5jprplbWn9Axayl1XO/Wjv/iPoFR06dc1Dd9IVltTP8FVM1Vn+Bxi4ojILSwvihdxFa8gMq2RGHyuhDpZ9BLzZSMliCRpMr4wwqE48ruYZKAleGjZlx5KlIXGGBrBIrgaRyyvyGmQdOP+AwqHragkjdbHe4wVpaVWSJKKzlSkel2lWNpcZdY/A1WELT5FCxVcx21cwvm35I1dwjIjMPDjYtAVcc1bPBFeAEXIGs5dONoakqT02RPapwVEhyBKpLyxsrp8ytn7Goef4hUPW0+dgIwChNXkLLaEJFupU5AgyHythCZRCNGlfGH1QmGFdGLfyVJlpSGosswSZzO5gcHv1AonWrTX6V0YcV1pKhtBVqXXBTog1za5sXgSJN85aGamfZg3VKS6DE7McSUlmDEFiSIKAFKnHXqrz1Wv8UcEUOldLGBSCKs2YOnBVQB9KHpsBl0fkb5NL66jWldWpvrcEZhnT2IKS2+MyecrgskbqZ8GAgrFhLK8AS+C6C2sYCYmJ8DELZUuvLcMuNeyojhYr8F8ecIkXphbzygSvjEioTiSv5Fv4aO48kM6hQSztrmde4NOYAPi1QOfCvp6wRLGmef+iU2V+Bd4J/VWY/a643+QAStS0EEU409jAkx4kpMAWCm2INN5kjM+yVc3yNi4PTDgo3HxyZsRREqT3gqPJZh8BZCU8/CP6Kq3Yu6AKXBYBxVM4iZ8UQnAKcEFEgkzsCkFi8UcAD6wAMfBTI6CrDv4HKabXNC+C+RBtmYzdARSixoJSIK9JgzBwq3FORK512lDHkyniFyuhxJdWtHSOoUNKkHANDTiosd1CGxMx48VTgl0BYKVQ7Ia0lWNkwb9aCw+GX1E1fbPfXKE0+Sv3SWOElhIkl5KMQXQzuqMlbaS6tkgtbDC5RjqjOFtFYwmpzSGkM9AlwMvkoowy4gnB8SOsu13srzIEaa6jOEqzFErKF603eqNFTbnBH9K4yjR0kC6pt+PUAOS5Kk5fcF190SsPMxTVNB/jLp+isAaHIKBSbpeIifyW3UNHakotDZawRkoolg0NlxFwxpNCEhsoocWWcQyXTppRx5KkIxVbgxOiI1ExdMH3eoXVNi1yBukKti0BCUlsCxIB4sMsWgncCnOhd5ZDOGZH3RGHpxVpXgdbLpHYXajxQkdYrl7xTvTwpQNA6JRUYvZDC4i+2BnTOMASiJIgCYuSvaG0BCO4LlpGaGXVNC6oa51rc5VRi8RTkXHsqHCoDoCIoTazbxwBjPYZQkbrKjwQq6XFlBFChBNmCYhtJUFh7lXyoecouGFxDwiCLGg2ujIUG8Twy0sjzuwZqROejdSWXaMGT2HG1p0TnU2i8kMoQgLCCjfjI4a+vn34Q5I9Oh1cBDMCTUJnCkrTWcpnKJCl0pUOqWO9LKqmPS5qSH1N+DnIZnRUQ+UbFxkCJKegKT62cuqim+UBHsBGEE9RuLFlXSr2POupLStmJUtYZsFjtkJQWGEZQ4cj0WUp/euDhKXWXgPxRGlXYtCu1uba3EikGqG8fweIol2R1RmWKJJcrPKRs7rI+ucq5hiFUVLMiqyeaVzJ7KpLLXSXJ4qmWZHVXW1xVNk8NlrRutEch2s3qrTG5KmGR6V/x6zUpVJWRcNikMruimSnDn9PjWnBRnmqjuwqiWBw26hxRrOAj+lSSxRtNKvmzZHdHJY3k3qXzvJldkYyU0s5kSTZXRd5L9uLLLefgSmE3cl2e/RmRnBeCnJmpyNNP6bg/cscllceTJY25SzEJPZURRcD6Dy/fJ3mISVa7p39VpiA8GPgi4Adck6mzl8JN0VjgjgRR00cdH0v8Ky4jkpTGkEx97SKpvBC5UnowKTLQUko2AGUqqS0BavjR2kKUlqYWV0rMfkHr0rvKQ7WzamcscYTqC1iczYWlpFSeilLrSiqpS/8gShUuy4UXm+v3SKFy5r1krlUawb240plKOSca2t8SpHiXnCiD9RhPJyLJw18jFocKCQzAFkHlAj/qmg8ETlzBRjL6anMIICG0yNQX/irS+mTyZqRsQUV+jamgQu1AKrMfdNE5Ixp7WMp4puQC0MXgjobrZpc3zsMO/UeCsSWVPOQlNzpphaRkUOHhLx7+yjj8lVHDeJqeCofK+IXKyJviRw4VcAJL8iqAE0HtDtXMmbHwyNLodI0tUgjHRUzKkouIImVnkfqPRe9KqkwHfCzWOzKSwpBcxUanJPn2IqOzxOJR232QylaqtHpJ2A5ZAxXlU2b5qqZgXVCZis3uQq2DroJ66Usq0STXSO5dLiooOYfKWLeu50ymPALO9gAAEABJREFUpErdwJ4tDW3nOVTyVJMZKoUaD3wRclBMnupp874abVxQYgoWaL3AidIcwnoSnFBcK+V8J+MDKoUiV0ALCSeEFjBG5wpiBTu4IrXRqbMBGEFjUZlLiw0MLQnnyaHCocKhwqHCodJPBWp3meig2AMNgsajETOjABUQRSmyJHkzSb5BJcXvggSS+p2PwU0qNnmhEnOp0uKDsEIdXLARTgmW/qqm0oqpBRo7NJArHCocKhwqHCocKnEJRVZwoq75wJppi8ESIIRRxBKmdFu1tQzLlG3sEwUqcroQUbDEusrqx3qh3iVo7PZgTai6mcappJHEOFQ4VPIAKpnacQ4VDhWZMu58l2JSLGobZ7NglThsocb6OUud0aYiC0MIBKgU6X0ADNaBlgLt0ClVuYJKGtlT/TKpUvxuStj0zrySIJXRqzaVai1+jdmHdQgbUf4GdwQui95VxkYP09gBmwKds2CQS8iUJbKOkGPVmXEkGmvTP9rK2D7nQBwqearJBhU4GQVqN4jiq5gxZf5XDd5qhTWkcVdQvAvCCq0DKkX9PZKJB5WBkqOFoIIVqFB0brzRKc5wHVY4VDhUxlwcKnmqyQYVmqnXXzkz2rhAZY9AGmcUSzlOwBKGEzEINtmgMhAtcFmY12L1l5hLIVdZPSSUmMGVwkGui0NlQmvMicKhkr+abFAR1O7qpiVldfNYO7ytTOuqKLaEII0tQq0pJOLKJPRU5JI8FUCFWvKBlmKT1+gpB1fgrwgaO4cKhwqHCodKXkAlHdFhRwgVGHrqTYJ1LOvnLHVHmxXmoM5dybqhiE0p1EovZ4mk/sCQhdFkROkPsOGDRK6Mx3DMAVTIZSG0UGIYRFzRu8qIK3EEGtwFCYAZAVTSUb5BZTJDiEOFQ2USQaUv6iXOpjX9gMMcZVPhl7B4lzVOFMlBIYrQcIppQkU+fvCEhIqEloS04wKdk7hCLJHml+RQ4VDhUOFQmbBQ6Qt5KW0aa3D24q+5ww1FlmCJvQxEoZCXUpzFRNELkkIxMSxNqMhnFJ7YUIEEjV1tC2jswUK9izqyEFdKyxuT9l/hUOFQ4VDhUJlQUElgAHwUT1mj0uTTl1YX28IKc9BYWgMfpVAcaEstZhITUdKESr805UkAFXgngtYBkAAnRQa31J3F7CkHVwSlJfF6OVQ4VHIOlTH64VwrZVmT1R64ZSRK5x6n+G68i9aALTRpOcy3UGIhPNBu0s7yLypUcVufO5ykMjrygQv7dbJL1sOReRLaUgheSIHa3TT/8NLodLgmSls83mV0V2GZAI8knVp6/+03U/0QUBkaQuk07OcaEv0a+dOAltR9EktraQVNJcnGbjH5HKF6f9X0AnEqZZqCDCv9vMYcQCWVsR4FqNCLNk7BkKkdG3MDO4g4VPIOKkXiUKNsrFlwRSQKAUNOlME9m1x4JyOHChnrEp0PEhS22qYlkfr5SnNI66ogqJi9zEcRNJ5+bfLJiNJ3TNm8kEPsOUGhQq3xElcs3ihBRW0LFRm83ug0T/lUocQKnAhqB7ZwqEwMjbmBnchQyfh+5CVU+kaV6B28mgYwl6MilY8S/1aWcJJpeCRNqEjGWmsIFigcgYoZDTO+orCG9KXVSm+FwhUxeao1toigdicmeqXmBIcKQUXiSqHWobUFDM4wa5+3BGhSllDtLKOnQtA4GVc0Tg6V/FSm9m3MDe8A9Q3lwqGSX1CRaEFQkYJaheokIJGv59ojGQlU+jWkqzylgSnzDjxWYwmrXVGDr6bIWaYP1YEobPAVsWNjqraTJN4Ph4qujytKk7dAY4enYvaUAydgCbiic0Zqpi9m831xT2WiaMytLodKelDJEAbZgkoqxsA6kKcitY0nJZCkbIEk6+EveRMIVGDwzTroWGu4UemIaH3Vxc4IiGIsa5C6Nyb0ShmEKENCZWTKEB6yASL7abSgIvdX4KmYS6tU1qDBHQVdbIHacN1sCoKlPM44h0qxpu+nCS0Tki5jbm9TSpY8xaGSd1AhA01Dmks2vUCVSJ3xBRWV2V+gcUKN8w6LTFmgsIbgoyjdUZ2/xhRpFKzJiSJBJfnAxsmgkj2ujD+o0GmozKVYd5U1mryVIAq4AjfFXzXdEaoHVzhU8lND2rcxt7STCCpD3oxxARU5HiSosB4GGkdC+CvXUMlu+EtCAkHFU9ZY/5WjBHdE4YkWuiIad4WnagblCiclijz7i0NlSKgQVwAVLAGSQPUMclbUthAUaZiLjRwq405jbkszFYdK3kGFtoAoY+Kp5AIqkmYuPFwfnVLojZaUVgqOsL9uTpElSE0pSYkiZX9lBJUscWVcQgXCk6M0eeGU6JwRSimmue5tgVpghkMlPzXmBjOLEoRiY1KN+Zmlq2x1hxwJVNI4TqrOiUXJup4QJBJCUlJusTzLa0wyvvqFy7R96hffp+4j4qApgs4rKB3lTYvq5i4tdkZ1/roie8RdM1vrqhJ0IAeIEpKDROrtyJyYQaEiqVDrIqWCSqqBJuXulHwfjZUNhIwDCsUWhTicDP6lfbAOx4tdF8uncDApbdiiNMWHuaQVOiv5nCi5gEqq75bovUKx1V8+zRtuxPkbXeU6e7hyynyrJ0pHLurfcXWsoJIt2Iw5FXIElfGIHA6VsYeK/JyldTkwpDdcTpQs9krJOVT0pXpP1YyDjjEF6tTeanDFEGywRKYJer/CHBaJEhhNqMi5Iq0P3AGG2Bms81c0BSqbtbZQAoEga2mVO9wAYUUOFfk+YwUVldFHtyBcNcPgjFi8lWZPhd1fE62bhTvOJmJR2zlU8gceqcShMgZKsOlDoyXT5yDHUJG3lEj+SpGsMyMZfem1l/so2ernmHOoqF11sw8JTzmg2BYGVFSeKl/DfDgrgEqxpUwkykihInElTajIWULeRsKnIATq9QCGK1QPtJjcURycxlRWiKOWwVIDNjDWEFbkUCE/hnk5akc6AMgFVBRaYMwLWdwV0Ya5ODcQRW0JACoOXxWrzXBPJZ+gkl0UcahkEyoJ9f1xARV5a8rAzoz0/kvC+5/1IFiuoaJzV05ffJTGXWHw1cBNcVbNZG6KkbkpFP7KClQGb1NJNeEKdiYwJIS/oLLaWcADcKKzh1HNh0WmBDZGC6XNF52G7fBgIKzIoVIkDuYP6uBbYwUVFD5BBXQBVHCBGmsQ1+IO1pbXziwaMGgbhwqHSs6hMl5gk7Uw1xhBRf7dBGelqDfDmP6lxnB6/7PioGQFMINARW1iFXZY4eoZB4Ub5pfYy3TeKp2/rrR+nmAKKBzlRaYQVGwMydtU5ETJIlRg5aWltFJaPrW2eVGwajoEg0tcoVleAAlsBBiwXVpKXzS6yulTrOAjCCYb1JF8FOyGg8PFsbjLoYHWPx1IyLekA5j+x+kbFQ3nCa+LgmB6W7B22gFYlujdaTXac6jkgcbczE4uqGTcjpJ/UEnaUD8wH4wAI9Ux8xwqjCjgiiWAWvzMA48xltaAKOCKq3qWprQGbkqhrWwgVBKIkhFU5C0ZST0V4oEUoYLpr562wFpaBVeDmk+wTm3yOAI4AWxQ7Z48EqkFBbTAEjZaDhWsE0HJTcE+1NSvMnpNzjIskwJjSKhk5LWkggrOqqJxHs4ZZ+vwVfnLpwSiU5mXPA6hUqyxSeJQyU+NCCp5cdnZGgZ/jKAi+SJSJ5WBRJF/KjWx5IgrWYGKQu/SmANFGmadow1zp8z/qsFbrS+tNgXqAvXzBYO/0BwqsoQToDKQKOlDRZ7NlcpTKRK7yxBXCCquUD3IQWDA0u6vQV0eS190GqiALWZPBYgihbkIHtgHS/wrhwp9kaJk+Dr+xS+CK1qLX2dFUTiG4alkGgpLBRVcLzkrOD1XoAaQq29eOMgx8xkqE9VTSWXfOFTGGCrjMfsrARuS4yIfkFjqEck2yhpXchEKyxZUKPsIFnza3EN81bPM/jqNuyLUON8UaBCMgYFQSUqULEIFgrmnwBShhegC5sEFIYEQgIEjUEu5UmAJBb6oTQU7YB0rtEzwVChnl74CASdY4hcBFYjcgrGCCl1pef0cQNTiLjc6wuW1MykoN+6gIn+nxiNUMrVv4xIqqSa/SomTFOY7a/Nu5fiCM34OBqJiKK4khK2Gp0GG+ZJE3QwJNhIPCvtPrJI7nDBHROMq1HgkFWh9UKHOD1HvE527du4h3ywOTC0JTnOFmxpmHVpiBUsC/USBL72nMDs94ROjXgIbnsAZqGyum77YHW6AuQd1sGRJXApzpG42KAJgEEgID8QJclAkThBC9LagJLggWMJGo+5Poo0JKtG7qcQkQmA37AzYEEXSgUrGsJF1yVSavEC+tbSietp8ui57WV1F8wGKIota5cQjrTOnHGhSHm5KR5l6GIMr/SOPxNDnD5xGbtPGnCgcKtmHysC2kNxBRerETm0tEhvGHCogSokpLBQ7I1OWNMw9osjXCKiEa+f7K2crzMHRhAoJ7gjq6SAHquqeskawAbABMPwVTfjX7q8hT4XSwIgu2IdEfgl5MM5gnStQI5fDV4Uqv9kVAVokJUAFn2KJewEGaMw+fAUCV6yeKHYu7N9fJBdQkSZciTbMxsWyIF5ptHL6Aq3GDZVo7UpdyvTisYXK6IS/OFRGCSrss6GgMhKlBBKHStpQkXNFamIZdkAsW1ChFGGFzg/Vzzsi2LCwyNugLZtRM/MQlT2aSJRRgUpF4zwgAWwgUUs7dUOhuNZAwfhKHozkqTBnRQYP0AJEASEIMFgHPIANOVGoTUXa2eatAE6wUWX0qk2l4Ar5K7n2VLAs0Njd4TrAFZescgQjU+f6fbVwVgAVZk/zDCoDjzb48cc7VOinJwhUUhm1dKAiKMySOFTGBCoSV0bSxJI5TlJChdwUJq1Pay1vXvJ1a7ipxD/VEJ0dnbakwJBIlAKDL9fhL8rIgrNCPgr1ZKQlkUaKfWEpQYVSxfBdodhCmWMqs19tCYAKkkzOMtCCQl5gCdbJCxkYAaMomRQxwxJEochYmm0qI4FKkc6pMpfSTMM1TQvBS627zFs1rbpqZkmxLT89laSHmthQyYpNG3OiDAGVBK4MhErGwJgEUMkWYNKHSjxnbIBRyDFRhoBKocrtDU2tX3y8yjdV66svaz7IHpkuGEPUOC/nSrxNvhcqqZrZ00SI1KuxUOuiLdRXkVqq4ZqAJRTvIoTQEluAHEovxgmwPvYlVhrji3qfUMM7vusJ1UkCJ+B8wEfBOnkq2ALPg5CDdTAD8KC2lgQPhtAysGd7LqAiDYmPFThtrlC9OVBlDdU0Ny1Wq5wgyhhCZayyv9L5rmQuRg02A43VeAFJWlChc+VQyRZUMuVKRlCRssLyByqCwl7VsKBi7pFq/zRjaGpw6mK1q7rIEhkIlQRPZSRQgShXmPqa0JJ5G2oHVuCdwKTCWZECXFjSiFhwWQAP6dfJLyGWYDuWtAKRL0IyuyLU7SNU2RSuag5Ep7qDtdgCkECAitUTBXACg20AABAASURBVDxURq/kpkjClviMBr33a3hcSZnBpevjinyelUBlM+Cq95bDWZk2daFBXzq2nko+Q2X0NdBSTUCoyLmSXaik1MSFSkZcyRQqAwkxtlBRakqbZhzinnJgiX8qfJRA/QJBH1BYywe2qRQYfBBBBSoADHrXoX79LXoTZJNKPgIYPBJ4HiABdU8hn6Nu+mKpQR4gkVpNqC+91G+RKAKXRQIJywzu7ZUiD3+BGSRqWYGwTn4JoAI3BTihHvVwU5JCpUg2qlt2PZVUUAFEa5sXGX2sWaWudo7dVgaryqGSP5oIUEkJht7TzRFUUrbEjHOoKPp3jx82V4YHFTkncsaStKCiNQSbZy61VM8HVMzBqbayZsEQFMNfuYKKhBagYsrsr5SWT/VFp4EucFBgSSunzKc2FallnrK5QA5yaCjSJQn/Ui967IPaPY5GXSPhnUii7C+CCgW+wBLwQ1rC6KOggBnsSS32kigaRiVJng0IBGU6nvEgUJG4IoeKzh4GVAyl0WKrr6Z6lttVgUeaQyXVPpIZ5FDJACop+zam4Umk1U1yUPwkaerPN6gMD0KDQiKjOFiasEnKjBxDhVki+cRcCq1bGsdQb/bPX3SEKdKkcFVGqufYPDWsTd4UUJiDLKvY7OuTwQsNDH8NxMlAtBQOEGAwc+HhwAn8D1eonsYYpiWxhBgDQlCfFYXKWax2aY1+gyWkMfiwNFrDFkd5oGxqWcV0X6jR6oySHJ4qbIeD4vRXQ+SpSMnEIAfWKZWLfBQiBHkt2MEdrKXGeUr9kmeRUZ8VygdLgMqQMbHBoSLNXa80eamtXmPwVtTMtPurDM5waXljqLoZrx42yu+jfOK1bEFlJPDI1ruZJ95JAjDSp0I+g6SgxCBpjKGSxGWZoFDJFlfShMqQXMk1VAyWwLyFhxvLpim9NeHKWRZXFeGk2BLKKVTgZASrppfXzwlVzwA/4J1AWJFDBUs4H6izs0m0NG6wRG8OAieQSucFVCKVM4ATsz0CYYVwgk91pgDBA8KKPOpFtKDUYSIK+R9gT7iqGR8BKt5wPTko+BcrkiQ3ZaCnki2o9HFF6wJUXKFarS3gKasvq52Bt0+lc3OojCZR5LYofa6MS6j02ynbUEm3iWXiQiUrXEkfKsMLfxX29nRJWA7cJx4ekRkgOVTM9vCseUv1oSlqX10wOgNQUdrKIGqokEaJ75svS5oVWOOSTxIMoy+XUivjitY9sGGfWlC0tlBp+VRwxRGoBVTkngrW8RH8GEFpYwPUW0IgB5bgCpjhKq2prJ3DPBJXhTdQ7/bV4qMipUNQWIVCs1BkEUosVIBYgQpUNpAA7giYAaKQUwIRLQAPsAfUqaifjY+oOwu5KYScBElQGQiJdKAitdBgKR8+h8JfBBXcplD5VOBEbfEBLdGG2YCKksG1P0sGQEXRm9GbwI8hoULWnEOFQyXLUEmnlWUyQGXkXMk1VKj1GOYyTahIOc0JULE6I4CKxl+vDTQEyqcDKip7hKBCw/cmNLBTC41cCVBRqJwgSjpQoUxiSvcif0UOFRppuAB+ld4D9gAeQAi8E0AlGJkWjjbjX7u7EkQBbIrVroJiFLsDokBZkSzFjqw/o0uhAf9KfRvJj6FRv6g7PeUWY2dfpFHqp0JNLxJ+QAih2EzRM4XYlTVTT6VQ1jk/YUw2yVkBP0qZA1cPT8UZrKlonCMUmQaHSonWPjyo0L94KbDCoZLAlaJJEv5KCyopWkRSomUoqCRunOhQGQiGUYCKNGoL0UI+x22CsAMZSoIH2yJaugQ/hkykBJXetGZGApURVjJgtAbt7ijcFKW3xmiPqo0s9gWoqHRe1PphnRNUooqrWOmUr5MpZ9ZcCRvnIq7E6aJ2wbdg3xWRgyXWC9XOApWDptICWgAV6pkBl4VyiP0VTXCVYEmFEht2NjoibDr3IgugApzg9HBkeCfSL0L4NE4UpUNekvGVIqNQoKdyA0sADApkweLjXyylLC/CBhBCRY19CCdYERQmcn0gKtsElg+kS2K8S6wQSDWGgVChiBzOFjvr7EFBbSvQ2BlpRKJgSYPIJUAFr4zEBq3Jk2CaExACSSaPtgiFurGFSp6AZNhQyW+QpAGVtNpUhgWVVOGvJLCZBFBJyoZR8FSYzYL5KzYPJuxDy97wDlnMBG+GQMW2y++gCi6OjYR/VTq3YPALel+hyl2k9gj6UkHjhoGm6n8iV5TOpII1J5G7QDsTUciDwUYsBcFAG+PnIA4iKU3UCI8ERKEmFl90GuvbWGwBUVj2mgghckQozCWdG06V1ulXiCtySMNAEw9Y2VKhFRqwJf6vaL5po5wZ7NMiY5E4viQZeqCFSpXtIB6tSDaAW4JnmQCVot4hRKU7GAeexi6JuIKPyJURT8MsKHGjTfg04UGiARokwChk46NIZrpIlhmVABVaZ+lkMlPOoZJAFLktGpwr4xIqtGkQGAyCgYygMuTRJhVUUuEht1BRmhQ6ezpvl/RIYAVsSDi9wmITpFCSLPQvVCQbpV9QGFhFVeUSlMxYw+LTc1JY5BAEc6HCUqy0F6usTFhR2pUliWIjiBTbFCWOQoWNYlC0pDiY3hhQqt0FRVbsAPaoNJ7SYENV3dwpzYsqamaSixC31KKnRS0Z/vJpFneFoIBVlajmYM9ekVmtjR+NhB8VlxYIn9IKRGVS1Js7XiAOvYorxbtUrBHLrUiv0jtRyPR4i0VhxorUBo6lUMjeC1ZWIleoFwtxAh6MHCoMD/SmiPaRglHkW5Akq8TsZrLngflJWhSCoUgF7wG3wIAjmN3hSG1z09wDa5vm2V1lJWobhHuBuwlJ96VE5aC7QzuUqPGpSbzYvvdoIFTYfS/W08+JsnKoTEaoDOTKqEFFslaTDSqDECJ3UDnuO6fu6Yzt7UqpL3e0v/LGB3+99+Gf3Hz7gUuPYTexwMAyuyRaFJnKolO69sf2tDPt7WDa1ymqK9beHevcz4RD9cRiO/czYXt3LNZ0wGECrGqJG1z52S1/2Cd9q4Opoz25cBB8+uZ/N5MnAa7EA2JwYkTT/40Tl/35Lw9v+rIDP90m7o9f37EntnX3/rvuffSob5wct87FZthrq6dSoXUDKvBOcJDX3/qiK8bOub33NLDS0cVW2vbGuvfHtu/seePNz+7660M//dnvFi4+Uql2JtxlEPfGW+5obY/t647hUJ2xWFtHDP/ievd0sCNj416xZLCEsLFlT+z+B5+NP/wiRQgqUis9QWXDT25t64q19X7xgCWH93FFlqklFOo0RvcVG27CCdDxoWOOP7mfR1VsgMC8OQsO/sVtf3rz3c/34vb1MLXj8vEr+2IPPvzcyjXnWezBAoWREKIAd0WiMORr7P95+9OObrYz7uyL//7vIFDRmb0oBFYCnUx4kDhUBnKlaAKHvwoU+uQqMkuSqmms1patBvaMj2NIoQyhIkZRkikDGORIqSCRMKlXhqLwEVtHcX3ze6fBNAAJLW1dsL948/f3F/6wQ7f4Ef7eee/z+ilzUXslv4EUqWjcubsLLIGJ6eqK7aev9R6hR6au3uNgufigI2GbVCWlikLXLbf8pqMj/nPt7WzZ05Nc+NuzL/bWOxtRa9bq/5+984CTosj+eE/unpzjzubIkqMEAQHFiHr+zwSIOZ/x9IxnzjmCkhQBxXTmdGfALChJQdFTFAMKEjbPTvz/ql5Pb+/sDi4Ch2H38z5N09vbobrqfetVvXovImidpOZgWOx3wMTP/7s+RddPs5dSJJZiyj3DtfyKT78ZveeB6J4zFSP6LI4CcBE70Jsfr/oGL4srtMYzdfUtCf46ENwX23icPVtLi/yC+O+HH67q0Wug1eEXNC5BcABpFlv0/plz6R2bE/EMf+tkHqFHRblBg1OzAqSBJTwSxGxni0jwX2WS45vv6+PZN/riq++1BivEIDqydgOZF66anoPkW/DnXPDYv0FcZlQJdnw4QELQGAqKy//zxtv4bX1TEl0BfBdAiLoX+BB4zVb27Jn1G7acd/7FRqNTr7drtUwEwSoIZrut4Ksvf6YyQT9g8ZJPyU7tCBWYODZnpKmV1a7WFJN775uL794VePwWJG/z3HUE+p1IN1T+9FCBakOz31QXAxgUwXFZ0Sdk+wOqauOWRGlFXzVUwtFKQIVQoehfUjcQsl1IGpNM6MpDR4yHxlFDJZXmksps5YeRKZUBPAAV9J0JKoIgnvePa+obM80x2bZgkszQqzHJIq2uOQnAQGEef8q5TOXB0tI61FBJcy1PRKQXwYMpgv8SY+g46LJxS0vfAcMkS4TsJAUqTXF2FZgmdU2t+aBCgsd75vk3cqBCRCGoEFcgx5xwTpIznlB05jkXavQWcEUNFZPZ8+gTLxDCURoohx49RwAqgmDD9SUrTBnb3vsftH5TPcNza6qxRe4CxLNFhLfDezW3JKkQ8EXmzHncbPaaTB6j0Q3R6RwawfEprLpuqHRDpWtQcXQu3VD5A0LFOumYk9DOE1kFN3PWQxddfLla7r131muvvQvdQZqU9Mjjj79k1LkVqSirJcXU2sK2H360Atd5cM7Dcx56BNvZs5nMfIDJjNmPTJ/18P0z5898YAHsG2hAGSr3zeJdY2izVCKZuXfqjJkzH+4gCyAzZj0+c/YT/7z8VoIKiCKag8edcC5UM2nSdLb7//Rzr156+Q1nnXvRZVfe8NRzL+E1m+NpqFE6E93zvx5+DGwdhUwEFfxtS4xhbeOmugcffIzLExA8wPz5T7300hsLF34Qj7dBDk/7/gdLbNaoTuvR67zYmTFzDn+GVCLFbK7ZDz44Y8ZcLvO5PKLI9OkPs+2sBWed+080K/Y6HCpqohBO5KEtjf3fr3+I56ePtW7D5mCoUBAMUPeK7LPPwbhpXV1rc3MaltLFF91gMgbMUthiDrGpKZOrqqpfQ1NTPJkkOzLB5cVXFl56+XUoK4Dq0cee+u779TFiV9bovO2We6xmvyAY9XqnKHpdzqJVK7/Du8cTBJWVehPMIHteqMRbGVTSKUinUFGU5i6nSDdUdrh0Q+VPBBWdaCeoJLO91MMOn6zRmki0OhGi11uNRvueex5AAz4QKP7GxowaKuWlPUgBxfmwyZVXXS9Kdr3BrNNLEK3WDBF0JFYmGrNRQq/ZJ1q87aHCrgKdXlhUbjQ6c4SUJk0Xm6QATRpjW1zad3OdPMoEVEAZPjj3X1ZHWNBacH1BI9pdQb1ojZZUPPnMC7Fk25jYxi2tNbVDcSk1VNAxpyf5aMny7K3dXPAALklyWSyeQw6ZuHz5aurRE1f69d1DI7jaQyXdmmjGPxabDQXIRX01N7Qz7WgNTmpfgArIoUCFbBS1Oy+g0qvfyEZO7hjX+dddfwu+FF2Hyufzz9cyureyTsCarzbarBE8lWgK6nVuQEUU3atWfa2MbcYT6Q+XfVJR0wufhkbSsMWHk8yOa669obklnoK1F0tQd+GgCUeK3EzBvQQhqYvMAAAQAElEQVTBziyVXwsV0eJvp7hVSnOXU6QbKjseKmhgecTdueicinRpAl/nbhO9R5H8s/fePLKjYNb59Xc5UXJEDRK1bPulVMjMAxWoFYjRZIWYTA6IKDrJXonFZE2qhkppcXWilV0iwceIrrzyVtHkV4+PkdeW7Lil80AMpoBJCkE6QCXT3JyJRCpkzavzksAOIFG6NUQUCAyXppYMjQvh0ebMe4p8ltRC/kvQ3U8+/Z+6RnnSJRbP3HHXg4Jgy4EKdCW273/wYT6ogJHnnXepMsfT3JI85eQLO0AlFYs3YUc0m7NQ4deRC8SvSLZk+BuZA8CJy1dqcRRgP7cdCVZYLbfdOZ0NV8bTKc6zyqqe4BNwIkm+M864iMqQ5qX23edwu60AhQZjhb7IlCmnsIG7RCIWj+Mdl69YGSqoEjRWQprVXoAdQbDggoDHuedeFmvOmiqZzMcrPjWgl8ChIomBHQIVBSRterMLHayu+LDkOyffdbbuQLT9emZXQei3AD9BbYW0F2+nkg8k+T7qtivxbbQktvX981x/2y2AnSv5PLh2hqWSAxWz2Q1l+uijz8hjXK2ZurpUDlRgo0CjdwUqClcIKiZDJMdSUUOF1C50oiKKAxJBxeMry/BZFuhZaLe1329hQyscJOTWTHY2dqDdsC0o6vHTzy31TWyyoTnGfLpsjqgaKrz//stQGTt2P3mOh1s2F15wQ8fhr65DhS/B8cFmUmbpsUP1WY5NkPWHxDYQLvv2h82wVJqYos48NHcBMACi+HwlP/xQD+TT6By+F4jCcs7jFsxY8UPee295JusggGcbNHgoiAKlb3cWgihub6loDhKfRPRXdI6331zU1JCgN22ob9l7/P4KVLZn+EttqeSGC+t0Gb+Utz1uK1Tydtq6obLzoOILVG2TeIMVingC5Yp4g1WK+ELViuQ/XpFHqvJInvNDZdsmea7vC1X+pkTJ1ZErqjJvd77qeHuhILtsvzOoTNRoDXqDCGEjVzpREAyCxmize75Zu06ZS3j2mYUyUfROSElxRWssBS2VjBNUboZKUsZ5slAhkdECG5eUqVEf1Gv9WagwOwEd/0hBiVEfhgA5kinqclR43dU+TxXE46vgUgaBBjzgwMmZ7KhXY0vmuhvvErQWvmiGdfxxx0Coxh+sdnvLHa4SHEFP/O6pc2IJeYYcP/tNOCJnTiWeYEbA+4sWtR9/s4OvktlhsbpEyb7X+P0buD8Zebsde8xZOi0sFbfNGpkxY26aOzi0tLbifUTJunWoKIDE68BMsbL4YywAAeyVHGGOanoXXu3g/5tClhlMpebm9F57HYTPdNtt97XwkTF+MFNZ2ZeGvFjh69z0bGRawUzB4y1avMwk2gSdHUof/QyzPYqKgS0zH81hPI+gcRx88MSMyg/wllvv0uvtHK6+VavWcqikWxKZxUs/7ggVmRm/BBWjxefwFroDJZ5gKSRfu87XLvzhqk4l3znbev28Ei7fJtlmvfQ7F3VZCcpqry5Kftq3WSHKKmhlIXRH6R7++oWeVJ7hr20183/JUmmDCtkrxSWVY8bu/drrbyvDIKlkZsTwfQkqotFt0Dm2FSrKWkJIe6jgMeKx1rQCFeIKiWgMQ7IhW/w0UX/zrTPIxYvc1fabcJjdFSaooOPPHMO0bskSiUR7lVcOpmmYiUedkuL+bEzvx8Ghe34FVGbNnkueUfQzdLfx2wkVZqaYg2SmgCsQm6sQ+xQuhYSFJNAx8wskePk/78Sy3tuLFn1SUzOACEdEueqqW6D9iSUQ3FEQzAcfNIVcLWK8d3Dd9beYLcySk6yMKKFoTzksDYcKnkerdxcX90inZa+8llgK1WCHQ6VTS+XXWSRdaQv59MY2N8nt6Ln/GURdVnmTdHWS6WSrSjxv4W6rmbmzzdKdXJl2Nmx2yPAXW/FH3j4dfppbZPME6gO6aMuW2NixB9psIbMUhNCEc1FxBTQOTfziaj+s37RkxSeLly6XZclKLp8y+egLyJJlX+02bG+ocjaUr/VzqMxojad4pzghQ0WldttGitjkikurcWq1dp3Oge28eU8zLRmTF5TU1g6A6qc5BpezCP30aEGvYUP37dtndCRca7EEcHy33cZAUba2yp36adMewHVwXBTdK1euYdMtiXQymfzggw8kUISJC+JyBLSCqNeJAX/kumtvovGjFB8ZWrHsc8noE4EKndthjcyaMZf9Ksmvk0gv+WjZko9WKPLhh6sUeffdZcuWfT5j1uOENKhaWCrEFUVwhPSs7ACml91kQBF5QU+iTTLcd+Djj7+0OUNGSR4AJJxj55TT/9EcT7YkUi1JZqSdfPpZRrMdF8TFAZW+A8c6PKUs1I0YJKiw6SuNZeNG/EUKEk8m13zzjdZgN4guk9nzyadf41vHkoBKCl+ZoNJxHgsF63BEWnhx03WmTZtrNvvlVfpc1C7RO33ifVePC/0JYZMXKtuqxLuh8vuCSoa50ibiqp8E/wEnqEMKujz00GM+X5TclqDcNYKD1LEaKhlu8UDRJDpd95eWZ8j33f9IQAXKMQcqOCWeyNx8y51XXXlXp3LF5bfdfNP948cfgsdAf/nxx1+S7Se+PsZu92u1ZvAGT+X1lAIqNdVD+/cb43aVlpcNdDoL8OSRSAU5RtPP00+/nAOVFMdrfX398qWfclkNbKxY9hn2v127LtbSRl9S5XuM2sdmDjltBTlQoR+Olowi5EGnrKmELHxrOUHFZPZ1CpV2UVhMXooTI0meW2+dBtOw3VJV7vb9f/93FCeKXQ0Viz101rn/pCIm3+v9DjxEY5Cok+4NVlXVDmNjXxbgJES2oKBxwEQD9mDZJPjA2cbNm7sOFZJuqHRDZStQyTP01A2VPwRU8lkq6h8olsbG5JNPvlJa2hsKmq+vNpvN3qLiMgCpS1DhEktk9j3gUEFnhYYi564sVPBL5pWU7uzubEwp+4vLL79Zo7GpoZLmrlB2h1fHPZQUqAT8VQMHjKsoH1Ra0t/pDENLwgwCt+hRGVSeeTEHKkCprHhV8QAAiRSPN0Bb+gFgDppwuCCIVmhJncOodzpsoVkz5itGDIdK5heg8vZHUNOkW9WLVBSoUMqstilr8nfQOGGKff3VenCFno3bRpknnnhRp7Nlo7G1WQw5UEnwySSN3qHjzpkVPXcLFPagwJRKDB5B69CbnEuWfw5y0BjpD+t/zq7hd3686svWdCqWSjYn4ouXLc16JDuViGEkoDigQgNu3VDphko7yTv/0Q2VPwRUyFC4b9r0c885Ty2nnnbGNdfe8NGS5cxYaU6TNmxpydTUDAJXNBpLDlT48NfP7Ya/ln7MRDUIBj212/BxGj10n50GtbJQScQSDW0UyemFq4K13HDDPaLoVQ9/tcYZVGp79jOJNoKKz1smmvyF0d7gisNeZLcVoncPqOw2dGQmC1Fcdtp9s9RQSaUUxdsp2thhGB8/b9h080231/boo9dabRYfoCKZPDlQgbqHllePffHhr08UeffdJcuWfTZj9iMsLCMNFvGljiTqtfTqYGswI8AVQbBLYuDQ/ztaoRc9b1VVP4cjJFkDFBFSEXn4KxFvSSZobuPk085nAODTDNV9hlOIfpZlMjvaxnijtWzY1JLIdhRWrv6C4AEBVBJ8moSgotFbQBrchYFBbaygTByReDLZDZU/L1TarSnJTp+geomWqMlcYBDDelOonb2yrff4jUElP0R3DVS2Z3LyV0KFhzOhoCOHHDyRphAgZtHNxOy12QIajTRy5F5sNVxW077zzlKt1moyufBbFVTYpS678gaj5IbwDrgrG724c8mBSjzVRBPgirRxJWup4FEvueR6kANy5ZW3wniiRwJUDv7LYaJkV0PFZo2apTDuotN6aMr90MMm1TfEFKj887KrcyyVGJ+s2LRpw4eLVixbsmrJh5+8985HH6/4tG5LU9b4SK/74afCaKlZsm8FKuRmLZqsshjtYoclkGxSipQvhWvMzp0opomyr3xBOQWAjo1A4qZNWQrDUvnXk8/ic+D6pKnV+hrqft8DDm9sjcG2IKjcfNv9OIHmVKLlfXVmP2V2UTvyhqOVLXF51X1jLP7yq6+DHLRGcsXK/zIDl1sqn335X0Ej4jhMnxxLBd/C7y+l0TMW3DOZnDr1IRzshko3VLwgilGKdEPlzwMVEp3OZrH4tFozuHLV1deRF1CaL1GsrR0kCEZwZfuhcv/0WXw8ikEDOxWVNZGCklyJlIVCJX5/sc9XZLOFaK5+woQjlTEx3J08mjqFCu6CR9Xr7aAImTX0c9jhk3OgwtRfKv7OO2+6HAHWHvgUvUYwTDxySoImfvgdH3n4caBiB0KFCeUsyePO1ClUGupS9DywigAVNvaltbJxJ5Wmhggaqy9YlsyOSfLQLO8wqOicgJY7VKGVfBZ3oeQsoOD/dK9x4w+KJZiNEuPBKW+76x6PP6o32WGXLF2xmoehTIArP2xYT1BRsh4og28o22HD9lLbfTffPM1iCXRDpRsq+N5RCIiiMwa7ofJHgYpTCShJ0b0OOXgy9JRaYKlASYEr6AIfe9zJ4EmsVdYP48cfLAhmaOrikkqQBn/Ooi4yqNxELr/kLNt+5rYNJ+ANn1NhyvH+6Q/EmY+vHEsyEIzSAsmOYnNGmE+t1mmSAhBfoIKCksG6aG5Of//DBsnskKHiKxFFr80aYV5qfK0GLWBcu3Y9m9XnUPnxxy2iyHzJoNwJKo0NLLZKMpl88803LZJPNLqhAR2OiBFIEJ0vv/J6httTfJuZcMBfCCo4Mwcq3Dm6U6ioHYvVztZMdNm8LFurIbS+x+AlqNRvSZLCxvMAKvgiGo2lU6iIFv/ylatJv7M59kSmqscgGrAie8hsj9hchWTWCAYHVPCDc59oZSH0md9wU2uq/+BhsFHAD9grr7z6Nl0nwwJTJgAbyeoRtBZBZ6WBTfrKgmA9+ujTFYsTPxdddC0OdkOlGyoMKgaxgBFF7++Gyh8PKjRv3BEq0MIkoMsVV16nRDGBfXDQQUdCEedABZf6FVCZPuPBBNONqXiyFdAqiJZKlkiOiOYwc3U1s2QeLAqkxiEIdq3ePW/evzIZOSgZ1Nbtd9zbKVRwF0Dl5pvvpeWKBJWpU2frdBY1VOQBrmRy0aJFxAlJ8gEqkoRCcPSo7aueXvl27bodCBWUVRehwtb35IEKegAwVtSaGsVF8xyCzn7W3y+Iyaez7Tvvf0yQpml50RqyOqM4n2PbOuGQyWm+xJLngEkv/fhTQWeCmWIyu8CV62+6M81xwiN1Ji+/6kZYKsqXVb6y2ex//fXFqDCNTTGatxs1aj+XK9oNlT8TVPLkqM9dntJB2gf46tLN8inf7YLE1tHV4e75QLLNsPkfihoS+cK3UBpzSi6rFjnGCW/MUDSTjz6NoELz0xMmHC5JHrXQigdoB1+w5JvvNiSz/lAt8Uxt7yHkYFpc1mNzfascPz+Vufba2yUx9WCYPwAAEABJREFUpNd5tRq3ErNLLUYDm2fWCC4mPIzK/TPnU5BHipbvDZSyvLyCWWcNia5Cq6/U7CnGDksAXFgL3WdzFZMLrKBz1/YemswmfaG0UVdfdzueCo+NjjNTplobOulQqVdde1tTLCMrSp5VrKyyH+U0BJyg0Vb/d11GjrTIYg+T87RJCtkcRQ5XEVuQr7fdeMu9bTP28cytt04jAwhM0uvtsOdmzJifVgXwz0leSaqW4sfgwSCohKItgOZmtPg0PAM8dtrUXycVgIcRMrL0lGDnli1JCm0Joj/xxIvk7qXPpgEGJGB/KGHErK7I6q9+TGZ43hQ+w//cc28EAmWSJcQCtPAFj3gXkOmAg474cUMjxR1Ic4e9SVNOFHRmmGvAsN3uHz16bwIzOgHoUkD69htMwRf0BrNWJxKGr7n+DiptGmVds3YDvsX2h76nwtHnD0a5y2mxnYDZUeD5LQAsL1QUbHSRK9v88t1Q2dFQIek6VBoaUuedd9nIkXurZdSY/SYeddIVV9+ybn0DedhSesd33l8u6KwmM67jKimvZdO5XE1Du7344sLjj/v7EYef0lEmHnnapImnHzX5jMmT/nb4YSezAJEqqJAKgwTCFYIgAopaS9DkjFq8JZK7KFjSG0LutgN3G1/bZ6S8Atzsu+jS65U/p9XyH69ac+75l+0x7oC+A0aOHjvh/Auvfn/xqrZcYfzkM8+5GKRhQ0OCmcVzFD0rVn7dESowjwAVt7eULyG0Wx3Br776AYYRiJLg+awGDRplZC3HrIaKEoPr+OPOOWry6YpMmnIyynPiUadAjpjEdg6ffNKkY04rrxkAltCgUztdsI1QkVN1ZSf5TZYgMz64CxlsERBr9zH7x/mcSn2jzJX165tvvPn+sXse0rvvyJGjJxx77OlPPfVKhqO3uVVOqvbk0y/BRoEtAqhAQAut1rzwzffIkzuT3d5x59RJk48dMHDonnvtd8opZ7/00htKVhtsUUmOPu50lHk3VP6kUOn81x2P56FLN1R2LVQUruQcbDfUoIIKfgCVjpkWKWkVdfAz2UyO9U3p/oNGotvOO932sso+dY1s/UZji/xXUDFbEbrUZ599bTTKI+/TZy1IZt14WxIZf7hKMLoEPKSrUPKWYBupHBAs6ytIftERNVjDlb2GV/QcFi3vb7RFWIRsreOhR55q5iqSlBcRLsO75MpofkNMTvHbFM9cfcNdJqsfFQBbMhGgif77zYZUdiXNux8so2jKoiVqc5Z6g1V2d4mOWxWHHTZFcTnDz8qVayywLfR2CHYoTAspenKWk93YuBA14xlZ8CSxFNsefcKZeABBa8UtBI2FElPiv51VuTaoAISb6pLESLz1Y0++KCfxFdscycg1mVbj0xVOPPUfTa2yCaIsAoXBUd8QIzzEVfnZ1n7/82sL33d6wlqDlQ18CXqKWAN7paqqz/r19fS3Cl3YJ0gksracbKDUNbPXvGvaHPZSXIfoti/KfTdUfk9Q6UiRrWNmR81t7Cqo5FPcv3eoaEQvcUVttUA6hUoyo8oBnG5bl0djOEnVMkauZTbBApCsPua7JbmBlnC0knQQZX6sr5djQzLd1B4nfNUhW1MCNbRmzTpJcokWPIl79pwnlNj12PEEygWTW2P2mdxFtmAFiOKMVBucUQgoopUCnnB1zwF7FFcNKqwYgI/CIi0abOdffFValalXUd9QZyQJruY2NSSOPelMoojZEVKMA2w/X/NTR6iYbUW+YA9/uMYTqASBBL3dbHajD85KJi4r5csuu4FcyyTJQ1Bh00s5r5+QIZ3mOEnyDL5gHmWiPObEs1hz09mocgIMSk3u8PUDXYcK+ZLBtkORkr2CI7Bd9jtwUl0j425W/7MnbImxDGn4OvSQxOY775lhcwaAE1ozr6RCYN9OdI4cuddnq7/KZHNEplVeXjT3Jic//no9URyiboDdUPlTQ6Xj8U7Vd5tS3g4MtFPuvw2oKAd3OVG6CJVOh8L0lgBNdJMIGuvRx51Bua1opbciSnp2UgosE3BL5tU3Pjj775d6A8VkoyhQKSnvRZMZXfwh3nz++VooJrb+UXLfP/MRulGG84BZKhwqWlvYU1hb1GMIQUVnj5hdRZKz0OIu7j90fKS0L4wVnAwtCahojPaCosq77p3544Z6iljGsiAnmB3Q2Mp2lq/66sJ/XusLl/IUpxZocKoD4ARpohWffpPiGh8nL172OY7jt6Ij4gqW+wt6eUI9bO4CHfNNcKCTXre5JR5ry1ffo8dAnc4miu6ZM+els3ZJu/Wb/AiN0eH6NAZFaeHxeIdOPMHiDOOOeDCqnHg8xpjOLBWDJIfURM8AbCDzEd/omedfY2NoeGweM58sFWKJzVWILQ0eYgeX9QZKzzj7EnwF4qLSCSA2/PDTljvunl5d2x8Gimhx80l4BhUyU3iANSsJ0HLRRVd+teY7MEm5AvMS5JYiPsT0WQ8PGjYOT9Wx9f26CfaunPN7l10FgJ0ClV+wSzqiZUfB4DcMlV1Oke2EiporaktFtPgLinqMGLXvsN33Hj58zxEj9oLkzKmM3GPfPv2He/xFBtEF64QmUWjUi9xGscXx3YaPGzGKnTxmDJM9xowfvcdeo0bvOXLUuBG7j8mRYcNHjxm7d9++uzH1ZPZAanoOwWOM3GN/PMm4vf/KxmpMbsHochXUlPUe3n/3fXsOGVdQNdDoKhQMHr0lBAOlz+BxsFTKa4cWlfUFVwxmfFw7S1wIxSc5oQ0nTTnxjLMvgPly/Clnj97zgD4DR5isXqMF2scl6K2wUaCGRFvA5S+2uiLo3UPrDRw6dsz4g3fbffyIPfar7TuMjBiDNejwlwaivSG+cLndE6V5hd49B+45dj+U2NChY/fYY7+ysl60GrSmpt/w4WNlGbFHm/Aj48YfNGrMfrj+0JF7j97zwFHjJmBn+Oh9C0pqiWHYtpkpxk4sFUCFJbXjycrwBQcPHTdqzD7jxk/AZWt6DsKfM2vA4FaMFYIK5f7Cjl6J1Kt3sGjBemtFRa9D/u+Ik07+20UXX37qaWftu99BeFqARNCZaZ08EUUuW2MbV3Q6C4w27j7Hsu9UVfc69LBJuMK5f7/wnHMvOProk4cO3QN1QxAklHOnPfFuqPy5oNKBK53k7mXdw50MlV9Z0N1QycOVrLMvW0BnFIM8ZZaLJejNmi9QNCT0X3niNxuZvKNqYFUF/Wt0q3leQnL8ld1/KQ1Xe6Ff0QNANAavyRLGi8DaoDTsgt4Ji4olDoGZEu1V2Xf0gJH7VfTdvcegMbWDx4aKe1f2Gg4zpaR6cGHVwPJew8prh0TL+0Lds0661qp+NlI0rFqbnILRwbYmp0ZyY2u0RWDx2LylzkAF7B6DFVaCWyPyrL24NQ/JjgtSMHY8G2WgcfvLHJ5icBT2mVrIC052OdPZlTIUzcEcIUuCRM+ziVDpaWhUAPuC2K7O559TgUjWANgAKrP7ChbuTuZghggf/FRDhTzBwBVcsLLXUJBSqedsBlTnoqDRLG40X+OS/dxOMBhbDmy7svqEXhb/BTBopQvVIkHwCBqv3hC02UsErVuj82Sd1zsf29l+kHRD5bcvXYUKcEIDDmp/sD8wVH5TdPl1UCGuqKHCFmYb/SxXtMYBVUiipEokIT8xGophg/VZNZ3zXdhkg2DjYufiEDQuysRFi/WUTCogGdAiCE7JwlJ3CBonzxAVoThX0INQiFB5gsFt8ZYIUihcPrDfiH0AlfI+I4JlfSt6DqvpO7KociCgEizpDa4UVw2IlPau7jUkVFjt8Bbm9PTpCbVmD0Rv9YnOkNUbdQSKHf5yEMUdqvJGarDFPgwgrRTgceAj9KbK/AQ9m7J1uCMULwA44V7LTuyQycUHBt1UhpR5PkfQrFBW6LkTsZTylJsf2p1OdjKWFWUnFcCPEqO8XlkvPqboLfYQ9nUsfYWdhjpzoEKT9qFoD2DY6ilqH/rFJ1lCNE8j1wSuAYATpaV3hArEYmdr49nSFr2bdU3ECMRgDGl1fnxcdFlofT5gz6+WW3O6ofKng0pXpGOzYfHMjducRCsfzLYfKltX0L+1Cfl8ybjUsk0g6cCVIAl0qLKvPsIUqzUMwX/Zkc6adE5Tpx3ZGLJEIBpLVGsthGCHRJAinmifYOlAq78ax3W2Ivm3sE6MnqLqAWU9h0juqD1Q6gxVmj3Frkit5CkzOIpMrpKimuG9huxT1mtUQeVukcoBBVUDwxX9C2sGF1UPKus5tLhmsCNYwcLr2kLQxTZ3gcUZNjtCkisMfrjDZcHiGk+k3OYrBEtwUHIW2LzF/mgtxOmvsrrLPKEe7mCNzVNusBSgBGC4OANlULueYKndEzXY8FJe2DeKgF4Q3AJUoC1TmoIZVRf7uDvYZnVF8Cty4lLXcB33N3P5i2n8rdOK3b67kzeddtsi2ay9yP7W7GdWCK1SsgbMnkIDYGMPYV8wuizeosKq/h3dN6j0zK6oYHChgglG9pp4ayIx2XYk6k9PUMQD0DqYjittGVHMfqqx7JqqCvwrCPGHB8m26jo5HI6eSVf+NqcH85uGClGEcgd1Q+V/AJXt40ogH1fwKxwhn10iCpOttmQ1VPBUTD3ZoiZHkcFRkiNAiL+4P6jgCNWaXGWiuxxcAVT0trCvsNbkjNQOHNVz0GhwxR2ptvpKrf5Ko7NYY4lorQWCGK7sO6Z20PhAyYCy3sOj1YNgsgAqlX1G+It66qwhkMniLgQJ/JEKX7gcMIDWJopA/IVVEHAlVNIDWwqbiFeDsRIq6sum3z3lEIevEoDRwJJjI2MFUMpkT8j6lI+eKVAJF9WAXgADbgSKUOVE1cWfgCg4CAGQ8CtyXM6p5NTClRqu/BZbWvlIdZjXz3xcURms2cE69reWAC16xRaFqbX4UbYQQfJiC6LgCH0pOpNEdERQLGAtfiXHKrb5jfYADDtgGPsKVzrR7wSPPIEeiF4ozxy/xF9nc/xJiPJnh4pg8DBlZI5CsCMYvYLJrpG22dW4Gyr/M6h0yhUcpGkGbNuIwn7byWKXnHma7E4QNIJhAQvD5K3IEZ2zxFc6IFI91B7pqRwRbIWOUE2wtL89VCl5S4aMORBWiMldBGbAoDE6SwVzARMpUt57dEnt7jB0cAJ+C64AKgbm9OXG+f6S3tHy/uGSPoHCnrA/gkW9sIMtDkKNwgwKlfbyF/VwBMucoXII7CHJVQL+QfyFvd3hHnZ/JcQZrMYroxCgWOUOOy9t1n/PmilQrEAU+OQKlTqDJWT9qE0Z6GKzO0K/sngK8F91T5/qJ7Q/YEONnCo8q/kwd/gYozx8J1fFzqGSYxAosY3ZqBcsFWsA8FBDRW8LohywQ4YLBEdIsI8zYdOgWDRmH/bpT9SC05jrhJS37m2lThLAOMjbQjz86lGsPzxOthUqJH9AqBgshRCoFXT0ABXGlW6o7EyobAdXAp1yBQYKBERpZ6ZkodIRLWo3ZRo/wQgynOkAABAASURBVB8yLHnKzN5y0VeZIwSVgpphrsI+5kC1ApVAST8YJSAKydBxB7sKanoMGjNg9wN7Dt67rNeowuphMFNAFBg6kYohIEppr2GRygFaW1iAMnUVOiPVgAoQAqgwilQMKK4aRIwJFfcGSzwFVYq4I5VQnVCgrlCN1VsOtOitBUVVQ8AVs7sUR2zeUgi67XgjUtDyaJLVR+QgqIRLa70FFRDwA9hQoCLorILGLBjsII1yXDZ0uAAn3lAZhHmRcZ8oGraiWSuQBoYO7Bs2iOeggMGUwcirwklb9DYFKgpX6JnBAOBEPfxVXDPQ6ivGcdFVACG64L/EDJxm8RYBuviTTqFCJ4MrHfsTW+9wqOsJuAKhv/ozzIt0Q2UXQ2VbAfMLhbjToLKzwfProPKLLbxTS4WmprGDvjmEcJIDFWU4pVOh39KIvNVT4glXgyiABLCRI2qoWII1wIzeVWpwl8nn+0pBFNFTDEIM2/MvRT2G9BqyD6RmwJ59h+1PNkq4fDC2sFHCFf119ohgCdqCFTjfEa7yFfeq6j2ius/uRZUDARIILBWCCiyVgoq+wZKeoAtwEi5jmIF6BUJITI4iQQyGS/vDZME+3gJQsXqKJGcBCY0LkTaE7cKEj4PR5D/IYbD5sdNmjhA/DHYInaPmCrDhC5ebHWz6B1taDCg7ExscIA2t8Ge/tUd4cMlOiRJQZz1RzBQ1VIgrQAWAUd5rNwIGGS4EFUXwX5yGMoENhxOU3xKN2kFF8nakxdbrW87JZK+wGqWelfkTQyWfDsx3TrvjKuv5f4+KnQ6V7R/++r1A5bdjqXTkyrZChXZAEbJRyEwh2PwiVBQDhU2POyIWd6Hcx/eWd2qpaOxF3pL+gIq7qG+nUCEBWmB2DBlzYLRqaHX/cT0G7lVUMxwGSkHlboAKdmCjsFEvcwAnAyeewtqCqoGwbEprhgAhZKw4/OV4IyIl9bv5/H850AJLBTvgCiwVmClkqUDs/sri6t0cgSqLuxhcweuAK2rBa2r5bLMCFZrHxpZ2CDNyC+dbIkqOsQI1CqjQfAy5gdFgF6lUmCk4QrwhqGQREjSaQ4qYLGF1Li81VMi0IqgAJ3j3ouoBeGvQAkdQGop1kg8q6iGynLEyYClnMmZboaL8YUec/Dmh0iV45IeKUq92OTl2JFR21ET97wUqXQlN/z+TXxP03hSCGMQwxGQuMNuKSE+pxruCyg5DjtwdDpLwkwPq1dqUhANid5dALJ4yK+dKjmitBf7ivkU1Q31FfezBaoDE5CoR+YgTFDqbmfeV2gPQ+73dkWpfYe3wsYeESvr1GTK+vOeIwsrB0PjRikHYkdxFguRn7mHhKoinoKbX4LGFVQNLKvoXlfVl8Vq0DgppSk8Onc4ant4m6Kx6qy9YXFNY2ccZLHEFK2FXEUpplT5QBCC5guWMKN6ozVcIwQ5BhVZHKvMfuuwiGDXRaSuvESHlzhWoTCODCyJZQr5Ahd1ZaLFFRNiIlhCtB8L1yWFMDRVeziGl5MES0RohUcpfTRTFgZjujseu7T/SG6mCvQXwKxMb2CehDgF+izNhjeHdyZigP1eE/pDuJWc75gFXyKjKhwcSclxWtm2yo6CibhFdOL99IgZVhspdTZRfARXqtQhmoOUPB5Ud4lKcDypq+d9DhWLwqS/ym4KKhvtxdhkwvM/LcUJJPK2OEtESZUQR202xbB0qakVG6zbs7iKHp9jqLIIAKhY+raIWwEMNFbJOABUITlZDBThxhio15oAnUjto9wOq+oyClNQMVbgi4E1tYUewwl8Es6O6duAexTWDy3oOLasaiCdhwSWzC6dk7yO0OpMTOIHQvitUWlzdDwhRlqfwmXlmZ/NJ/lrGFU8BwwmJp8jsiur45IcaKjqaY+cmIznOKlCB4E9oYoaUsjKbDZx4/eUgihoqLKeIxUeuYsrIGADJNTiMkhCFZqH9rLBplZxvoQjdF0SJlPZW+KGe28Bv6aAyvufwlxJUcohCU0psR7XqJQcqWxGqnzloYQ+sopF6VdBOhQq73W8MKvl0YFegYrQHmG+eI6CxeHY5OboKla4o+nzn5/vbHfWg+Xo3+VjSFYvkl457lUB+gmBn6aeM7dL2KQmpKKo8pWBiKwe1LGkST7BK0laVNe1XVjJVyPN/ULRHWkanLEKklYkWe0h2JaS0Tl2ouFnXT26p8BWIFmsRRJQKjKYwS22i8+DtWPAP/hjZZXHsfKMYZGIKQwzGEP4kuzCeKUSIP1hpc0QhRtGPPji4AnvF4SmFQA9iiyNQgjZXMYRRx1FotkfxK9wOOxZ3MTQ7NBoJLRBhCyYEMxR9efWQYEFtpKi321/hD9fgajQD5An1CBf3K+8xvLLn7oUVA4JFvfDAgsaek8CYLU40WAStqBPtBrMTO/gvisIdKHF4C/lkeCELnm8JQ2SVx78dLfTLrvVzs3QsWrPNHcYFLfYAtqKFfVmWE4UzjNkieqcCFdgleBFS3LKHrpWZdOCE21fscEcpcgFtrY4wQYV7MHtEm4+E6OL2lkLk4PwmnyIsejx7TlYT1PHcKCsX+GT3RPGOeFNfuJzW0yg1Ab/FluZv8FRWZxR9Apev1BMozx1M4//FCzJQEQP4TXMCCnQqVHpscT6qrmBRZ+Vi0pmlwp4wG1DOZPagkCk0HMsgqbVghyIX4LggGKlpCIJOaYB0hO5OCzYpIoAsPKQQOeBCLJaATucQ0RXQOfBfJQVyznNScgQ5rkQ2YUS2EBzqxMlbh9MO03s8GDZVTqM7KHrDBm9I4/TtcnLsSqjsKK7k/Xh5rJMdBRUa5YMCZTFiKbMhV+4UpoJqG1Uvk9EnQSnzRp6tixQyy6mog45QYXEetTZBY6WsrlA6VHfZBbkeoaXa7By2fN3KAiNuRXjnOtuno5XYjCtanV+j9QmCSzJHcYRdR4eeOMtYTpHk+fOwmWE5oAsnClsmLbIMjMAMcAJNZ7UXUI8bJSBondhCRwMeBBWiC92XJpzZLfQMb4LgwGmMK64iBSroL7OBJmuQ6WigTmR/QsM+iqlksIYVqAwYui92WEQAg4dSw1HgECU6GctuC5AIOo3RyqCiN+slVgOpR8wcrrQuQeOEcFPAD1tHsgaAbZuzTXCEKRe9FXqK1Byuj2tSRE76duyBoZv4HANBBSwBV2jciQREYWJn5YYviO+LK7fVDckDFW8wu01WL4RzJYAjIArqG3Qo+9xapxJMhaWB0dlxNbqIQhRZ8WUtANLd/E2tbcFg+A5+xSZ1eLZHgorbX0YUofhgcmXIVglaCpON5ePtikhWRk08FTjKAKCzo8SwJW+lTojCoMX4gY/I/OgESYlbSmJHx5wv42fY0Fipa0XCC4cdZN537AoGigUAkdHCAwEAISActlqtXaOx0b7R6Fa6gzkpKXFB6hfSDpUwNUP87a6FisbmMXlCek9QsG5zqpHfBFS6Apiun79jHzrHHM4ZmMo7ELeNUJHzj/EUttCeXn+5uudoc0aoVqH+0Q7MFMYVk8cseik1b7SgJBIuCoVKIHK16PA81PaymdjR53Kgb0uRM1Cb7a4CKBF1SBXW9joX+YS2Llj2Udnab43L5ijy+CrszmK8SElZvyHD9+7df1RBSa0nWAp1VlzRR7ZaVFBxeyqxA6iUlg+EaYKWTMyDKHYVKwpH1OFiqRLJfKH5NiVyifI8crJbHkCXhl8ChT084Ur0nXFfmsGm61M5ELzBGNg37mANoDJw2H56c4RW3mm4D5XF7vP4owbRATFKUEYoQ6PTGxSATafX5gLznBR2F0XEQ3g5GBvkbq9dFdTLoggpNVwZf0XRKilcP8/uJVINoZEuskjIWFGg0uZFxjMw0mdluk9ro69MWSndgSIQBboPxgpxBTs4wnsPRm+glCCkCP4EW7KiFKjIxhOvKmQc8768iR3EHQULrCIygkk/sr/iWbwIKpA2qFBQGZ6zGfraJPFaJ3B1DyhqpC6IRcNCQdvpqXBrynRJdaCdDa0SGCigAmiErwCik8XDmSoBFfivwx0hPPBujVGr5/mVDcFwpHcbVDRmuyeEboTFGRQ0ElkqcnA2ns65vLwvA4ne6XBEyGrpSBSCBz4xPhMePlpcu9vwvXr3GxEqqAIjqfPh8Zd0cRhtp+hr2HDc010w2HfK9X9fUNl+ruQd6mk/4bF1omwTVGifdcbNQfTQN9dlWlrbZNFHn6FKsZajsytQgYhGN6ACmT1zgTr8u9tX2BEqLJQhr9zvfvBJcyuP3N6a+eyLH6h7W9fIjlCQeSWhXldEbiRZuwoK1mKLllUMuvnWWSs/XUfp/5rjmaZWlsaqrjnz+ttLzvnHFb5QJZvuVkEFZo0geCRL5KJLbsZfxXi+jc31LOvKx6u+Ue4CkNidhRBoIrLhjpx0KqU5oQyAeP6mWIYpU8FCoSQJKpW9hhZV9kd/GfrXHSjZWJ+kN83w9F+LPvycIUoMwHBx+qsAldp+Y7RiCJ3oMXsd0pyQw79TSrGWuJxgmFI9tqZY7q/meDrGDza2pCmr2LMvLKR+9N1T5+AI5bXMEfoQuCB2NtXFcGRzfQLP8+Ir77ChJz6r5A5V4Pkt7kJarg+00PAX/kuTFhCYKXgvxgPB8shjL9Q3sWtSUeBn9zH7QvFpjHbFWMEOuMKpYMFDbtySUD/Vnfc84A+VUxZFdSRQVJXyqv6UBQcPvKUhjYO4CHQi9nGEkgK8/d4K6mhToEmCit1dRKHPcLCxOaPIR0u/jBb1wofuam4D1c8nn64lkt0z7SGqtCT5JurBg3HjD1Ly4tQ3pScffQoMFHQCYKAcOflEHKGI+vjnmOPOFrRuFmHMGJp81Nnq6ze2ZoaOHIcCNDsCFJpaNnqMbpPJc9llN8ViLDh/IpG5/fYZXm+xEuYuR6669o7nX3qLahQ+Fgn216zd+PCjz4/cY38U+C6EiuK/vsvJ0VWobOtQ2I6C0PYAZnug8guAocoBu1sQTzn9XMpYRflWoStR13nOdqfSbVegQsbKzOkPU2INSn4VCMNYsdKIvJKnmT05/9v3F69CxaUrr/zsWz6mb0tn80dR/Za5kmkTzgZZESvqGyKP2mctd+iXBY8/T2lUKH8Jy5aYZNmiWlKZLc2tTTyxycb62NU33Ib3Rf+O1BZTiFobepEXXXotqS0oa6hpCC7Sf9BIdDNpEJyg4nQXo6uLmz759H/k1piVptYUMxcEE/SI1RUhqPQcMApcobyHx518BmWBpOtTfi30E6mULK5SQKVn/7GivUjQOUeNPaiZp04hqECocKgMcS912kolaTH+++obi6nnfv/MR5JZRdYpmNUKi5IWP/3c6/gu0MI0Me4KlpOfGNBCdMkVR4jlBNOIMHq2NLKip9JLccjdfMdUnWinaQAyVmhLw/oQfCz1M+CvevYZhs+RDyqUdRHoonFUvOM/LrqGQEucPvaEs9CvZ4XpKABOyExB3wVEmTr9EVZQeHHUh/oWhKjwAAAQAElEQVTM4N32qqkdSnjOZBPDyDnH0m38wH59fby1NaMWQIVsprvufbArUEHt2v/Aw+kLUskfMekEJSPc0cedHkvINRbdmomTT8sHlYZY+qMVn7VNqGQtFRAFctVVt7H8pAkZKiANNVvFgENVv/m2+5WscdQDoGpAKdGUnHLffLd5z70PoSbGegA7ehgmV9SjGvo22eXk+K1AZWfMr3T0y9qxUKFBkoVvL05lU6WiAVADvvWO+9VjrFuHij9UTFBRhG5E40I5UEEVt7sKFI2pdJrYA/CEhlw9pUGUlkSbAk1n++lsmpdP52JnwOA91n6/JZNVndQ3h1JDI2SpbdNyesfmpJyd8LWFi2zOEBvqYThpg0pbNl3OM/z3iqtvoTElBSqSJQTbAn+1YVNrV6BSUj0wUNiDlMvbHyxFZ1MhAb3U9TfdS77COilcWj20ps9oQeclS4Wy86rVCt2RCqc1JeNTESrb1xZ+yHKKqKCiwFhN7hzrkIAKqEATUd0gkKiFQKIsn4TQHIlBdJx06tm4AnBS3xxv4X0BXPObH35msz4GG2lAEIWgQgOqHaECeenf76pn6bcOFToBBiXRlGVj/Oonm5ONNNIIJLhCM/O9+o1saMk0x2SETJ/5GGzNwuLe1AVR+KHOOU2AoZ+cbG//XbOeVzzLzAce2x6oUFqBrkMFH2hzY/zYk87sCBVR9HaECitnNr5nAhtQhgvfXkomHT0JcYUspLpGZjfTD+EZv5o05VTC0s4ySv6QUNmBE/U7d37lV7kOdx0qgs5cVtmLVBVq2Nrvf6ZhE8gXX62j0d6OULFIvm2EyoocqAiC/e575947bT5k2v2PQO6b8TBEgQoESmrajAfumzHv/pnz6bfTps+H0MS1UXLCPPrhpy1s/CeWjPH2gCa6eMnKm26955Qz/n7iaWffN3vOslWrgZYEZeTl8ti/nqUcTSzhktYiWT0XXXp1a1aJ1Lc0s9aVTuGZcQuybAgq1Mve/8BD6UZMUklISzLRFG8VrU5BY1BDpaiqr+QKCwZLbd/BzclUUyKJZ/xpYx1p3hamoX6k0UWjOeT2V9Dwl0b0l9YMmTZjAQQvPmP2I5CZDyx4aP6/CCRk6CxasuL+mXMh02ctmDH70ftnL7hv1iOn/O0i5pVrdM6YMV/JzAhNcffUWffeh5J8iMu86bNQmA/dM2329FnzZj7w8Ow5j+H6Z5x9CZQy+3Yau+iI0PCXGirKLD12WIQSHikSUHlv0fKMbFamf1i/KcVfDWU+Zu/9BEEPtGShwuODyVCxKlBRxuKwf/D/TaYpcShcQovFHiiv6quCSpIlO+EzRjhtxKi9YVIrHY5LL7+Jhn0sloADzyn5zGY/rDcq7S0N6e9+aAyEqkRz0OMre3Duv1Cjpk59SJG5cx8nk4Uw8+mna2bNemT27AVqufGWaZQObv6C59RKn0qjo0Mwqvr+Bx7ZESo0Ud8OKsnMxKNOoWl/gykwecqZ7boU/FN+/f0Gi9Mvuy2Q15wMlVvaoHLbLNlLUzBR7frP64uUcQj6OmvWbpwz76nLrrzlnPMuv+X26S+8/Da1zUxGBgzu2H/QaDZ7tJMVtF7nhrTDSZeXavxuoLLNN9jJXNnZUIF6veSya2nsAhULWmbh2x8pxspe+/yFMkwwOzoLFYjV7O86VKAacqDCUmVQk5ACEJa4QgpQz/Sb73+iYSg07Y+Wr5RsLiggPr3pVM2Ns+SMwOGzL7xK16xrYjMpq1Z/PXrsvjSnDV2mMVp1klW0u8487wJKdlvXEif2nP33i9HkOkIFRPl8DUtRDk7gQG3vQbi1Yqmw0QCNdcbs+VCIbXZDOpUPKhZPAWvYevP5F18BqEBw97unzVi89GP2grwNQ+NA7+hMfrM92mvAOFegWo6ASVGweG+UvIaixTXUK4fuxvaOe+4zmV0QJe0Yd4tifk05UMFzun0FMKTofEqUYrHj3SVKhph1mXXK+UsEKH2HP1qjHv6CyCzhCwzZahXu4FRSXktqETbl5oaWM8/9B8xENtCXysye9wiAqhPtaqhkh7+sOZYKzbdxylq5f7OLvL/yQQXHBcGI0+Y+/NTmevaxNtUl0emuqB6A3wIngIogWCdNOjmdnY/B9pTTLqRJMp7Fi3kWAD+KSJKroSFB2Yjxs2DB0zCF9Xq7yeRCkZLIKbz0jtlznsiBCvPB6zJUKBFZ16GCytPQGq9rTv7zqhtyoIKX7QgVqhVofSefdn6Gm++UHhvbU/92AZ/UtCh2IXZgDi5esprGIcmMfuXV99mbdkPl10Flm4DRxaEz5TT1vNav5o3iCdb1cbAcwAiSnwlPatt++Mv65dfrZOMgmRk9dv+LLr22KSbPEqMPyzqbvPrKUOGyzVD5cBm650mu2QkqOWtimHB76ONPVye5plZBxd42cyj77zNf2N1HjydrHUoWGu2/X68tKe8F/Uvu/1l1yQT69JBDJ1OPuJXLd9//aLO7LBaPRiNhe8klVyf4pRKp1MzZsxlieX/14ouvgq4xgqOmoCA4dDobVMxPP9WxMxOZxx57nswbnNzS2mo2s+Ev2VvMU+rylTu8BSarF7r7sy/W0oAeTt5nn4PPO+9SZeAFJgLLjsU9Yl3hqorew0EUFnGORxRWFgmh2QfCZTTq3RiLc6hMFTQiXpN8bcnHiX1onVOBSiY7w6QkoSLXZA1fkE/eR4IgEqSZ86vGTJaKzuwvquwvQ8VbRBG3TM6Izhow2EO0QkXQW0ELxmM+aNkcTz7+rxd8wSLS4PhpaE26/AXc+1lOOsm2oovc+UjNcU6kYRMns14JZ//9UqIF9eUttkh55UAZKtx4ZQkZtW0rS3r0GrxhUwuNZcVimQcffEyjsQADqAmS5Pnyy3UEV3z6t95dTisc5WRitMZWVfdA3LrGBJ6KTJ+HH30WBUIu10rCaZ61zAmkwXwke5qEQKj2CaSJdLPZO2HC4a2t8oQNthMnnmCx+PBsoug+9tjTiWGofqhRkyefpNWypScmo2/KUX+LJzIQ/GrR4iU0DtzUmoKEo9V2V4GgYQ6EONMsBa+59iZmq6WZ3HH7bBzkJSBi+803G1g1yBrieBi7PUh3hyi8BD6dnsL3Fq0koqAQXv7Pe6UVfXW0SFZvVxTRrlXo269Lf0GkzkVZ6cWd93YRVHZKgXbZXukIFa0lCNGYfRA1VMaNnxDjs8f4+XFDI/WIqeeIn41bWp2egv89VGKp5FagQsvQHnnsGXk8nXeTDznsCHLTZEvJ2HoOqU2geU32OfMeZ93hliQ1m5NOPi0HKuksVD5euZKwsXTpp2jkbAWA4DIa/FqtdejQscoIydFHn0oNNRaPd4QKWybpCqGHvufeB1LnHe/1ww+b0B0uLe1BAyz4gUJ0+wppjYXFW9Jz0JhQcW8eDZNHE8muU1NDBVaZDBUdVJ6VLADKMsmWTOpdaqjQzIoCFcXJmDQ7raJgW0Fk/qyswbCM2rC0Civ65UCFQjoCKpQpWbSBE+7Pv/wO1gPKH3eZNOVEGECwdDN8Egs/J//tXG6pyEtMOkKFSgAd9rrGFM0Yr1vfUFbZR0lm3ClUeD5HK+l3bC+85Jp0dv6jvj7Zv/8I4B/q8oorbmLjOY18jiSTGTpivMDzVCpQYc2EAmdwEnQRKuS4lQMVHOFuHc4cqEBx77//oaTTqaV0HSqsv8J/O2v2nJdffT3NRz5xr3umPQSLmXlFC9Z8UEEdwPX/+tcpSk3D9oknXgRRBEHLZiW1VlojQlAhpy8U0QMPPXnYkSeECqpkr/psWuhuqPwxodLpAFdX3YvRk7WF5RDiKqhMnzWvNSlDZdr0+cz/R/Sgw0IjYOjfTT76JPLcJagYde5fA5WPPmxJJtpDxd9BGDA+/vQLBpVkmkFl2Wo+QuVWzqEnYZpUcv7485ZEdtL7ux/XGyQLDXbTUhKFQ8oSh/6DRrIrt6apDc+d9wjaNnq12F5yybU4kkrLUJl6332sg8+720VFtWi6Zims13m1WvPll1/P+uCNzJLp2XM3Mm6yUGEuxUZT2GorpmWSMPLQT7972gwoAuopzp6NfrRNp3MsX/5lmtMIB4844hhGQY3ZHig32CPF1buV9xwRLe/vCVeDT9CqeGut3h0IV2ShkiKo8DEiDy3pN9oiFFITVo5otM+aMZe+DvXT1ZYKzZPxSQsPVCFfsxKg4+wx+IeLlvelWAAsHICnkALOUwxH7NtchXxhpnP30ftlsm4C6zfVU2mfc97lNIKPd3vt7fd0klWBCouDwpeX4wsCKpvqYvT53L6C5Z98oVhvd0+d5fSEcQ60vGQJlVUMkE2udKq+pTkLFWaJ4hxW6wTjkuWfKZ3xV//9lmSwV5bW1m+SJ6DjMdTtuYxnenvbLDr5VapqYGdQsdKoYNvyXr5EBiU2fdbDaqjY3X6Lw6OUMxUvE5Nj333/0hJLweYgpb9VqJxAut5k8kyZclpzS7yBT3E89sQT1T17b2lks31bGmM4NnjoOOq+wIZG5bzm2htUUHnQZAwQKm69dRrhpLExje2oUfvgvmxdlyCBu0a+9pDsb8Ulh5aOKW1Hw9dL5UBlF6JlV0FFLX9AqGx9PcpWhr901lBHqKxbX4ceIkFl7F4HUxP6x0XXkF5ATX3m+f+QUtPr3P8bqKQ6g0o2Cz2zmXCjmp5M0dQ1samQ5nh6zvxHrE43LcRjaxjNQdyCJmnQQmgVNCyY9Rub47x33BpPfbVmrRoq1CAJKnvtvTf1K5ub0yeccLbdHkbTJagsX76aOo+vvbaooKC6vaXSBhWrs4gtsNdJ7kD0h/WbWhKyj9YBBxxBCwv+8Y+rwCU2QdKcfvHF1/kUkVVyFzlDlYLBFy7tX91n9/LaoaXl/UORmnxQkcHAoSI6okr6ZDVU6OuooaKYKbKlojFDRVIXzOpgi1R8oUqapaeIAApUaOxLckdhEml4rIQ773mApgQaY8k58x+loo4U1rAvmGbGyuamWHFljdpSIS9tGI6AiuKtV1JeO2Dw7mR30k/fAcNgYooW99ahQlwRBM3YvQ7I8MIEPxKtmeOmnPzgzPnJWCbNP9aPP2yJFFahuCjji/w8FGafwvZw2Sao5FgqvfsP7tG7f0V1v/KqvhDsVPUYwKSqz/HHn55R3Be3BSoZfj6q1htvvinoDA/Oe5gWKqHE0O2jych8UIGhhussXboalwVO0EMCV3BHs9nLlnAKEoiCZ1DmimhdpOxnz8MEKN5fpNB2uY3yG4JKVwDwmwDGNkJlK3PyncMGTVFsCz0rGFz4PIdPPqm+KUlt++vvfmS+knz1e0U1a8Y0t4lmVlDYk6Ci50TJBxVoip0ElSxRWCviwWPsBxx0GDn+8rGvzFXX3WCyMEdVNVQo5ocCFeiyJcs/l+dOkkzyQcUoivJkSWvm9dcXi6JXEOyASk1Nv0R2mPuyy26qrGSurmjz2TkVBhWTGJHMUSh6iGCw/N8RU5RlN9/+YWVQsAAAEABJREFUuE6vZ4PX4EqPHoPVS++ixTXMnclVWFg10O5nXDG7iryRGuhTyNahIsd94WljKGhmG1T45C3U1uIln3649DOUJ0oAgp2Vn32DI8s/+RKyYuVXs+c8RrCBnrU4Cij/Cs3SgyKiq0BJgcX+aw2xITJnZFNdkiaf8XPwX4+Q18ZrbS/9+116L3DlH5dezrq6gogKHC6qyU7Cuxpb0sqyiR69BuKbzpg9nwbEkmzBzXsABk7DpwRZ6TQFKjyigWym4A8h+O/cuY8nuOkKqGxYt4VsQ0AlGc8cfdTJ4CWKi+LZ7GCopFM0BZgjNIsGy5jMlF8PlVjqjYXvoiGUlPfa0pCm1U54uUOPnKQxmBSoZDqDynffbaKhWmzXrv3Zbg+qoYJ9Gv6y2QLUXkjYGl7V4sddDpL/pVD2rE7E7NRYXBDs/GGhomhtXTagb1egQmHM5WDmZu/TL7xBTQh66ubb76boT+QV8877y2n4Cyec8/cr2biTzs3qYn5LZadCJdvy20GFmi4slRNOOU1rFCkCigIVJQQIrcGG/n36uVcJKowf+aEiWSxPPfMMiIKe7/r1zaFQhc0aNRr8F198laIChg8fT1DBn3SECoVzF/TmJ599mRayQO/cce894BOIwuM1md/74IN0Rp6eOe+CK5jRYHDDUvFFe0muEnwscMLmiAZCVVsZ/mKKkscQU4iCHTVUyCkoJ2CB4m1Fq9lx5K13l8oRJ0UfmKHkX1GgQllJ5IxYliA+7iGHHiO7wKUzsMZY8BgeasXtKz7h5HMbWpn/9Jbm1uWffk4RiwWdjaVX4VCBCULeXwpUjJKztKLnloY4ufOt39g44eDD1VBJtIeKghOD6LA6/IBKQUE5+VA0NyYJJ7h6U138nbc+ikYq8PWZraaKH7xjoUKe5S2JlFpQjZXJ9lR6u6DCPrTouvq6O/HVaF3w6i/XWBwuSQwpUKHHVqCi09kUqOAub775Ie6I+6otFdzrnHMuufjiay685Dq1XHTp9Wed+8+JR52i4caBMvylKMZdrv3/91Bpkz82VGTFnSd2fbvzjV6CChM+ThoprAIzlJHo0XvshXpGFU7QmM8850KlH/3Jqu+YrW1gAVEMWpdk9HWESiBcxtRidkV927MZvfjb9z9cQnO5HCrfsEH87YKK+4CDJtJ9KWBJXqjwwMP4L9QQ2Pb0c6+T0ySt3kBPDW3Yavb+85Jrs++Smj17tk5rOP64E6lkgJYpU06hMav33lsa5yX2xRffa7X2HKhILGqkVZQKWORjHic4GC3LZOR4KhkWuWQPtHPqHqKQzzjrrFQWKqv/+z0fj3IBCYFob1eg2u4uYfYH97pWQ4VdkM8U3HX3fXKgGh59WSeF9eYIBflXQ0VxLM5ZXa94jpKr7sK3l9KKInwyggrNqWAnJ68i44otgCr01LP/SWaXo898cJ5etPJouxLIZHOGFL+M5nhy99H7cH88u6KggYEcS4X7oUm33H4feY7hV8s/+YI7QKOH3ieV7UDUN8dQDbR62VmDsCoIRhb6V28/9dS/x5rlIbR01jN4yKBRRr1dDhHG53W2DhWVS/GzcmQ8eaK+S5ZKTlGnVNIeKj70MH4RKjiOz71w4QcUBRI1efUXPykN85LLrxYEm8UcUkPlrjsfpIl6XApQoWrMobJIFJ1ZqFiocwPBOc3NbHkKhKL4QC1gZ/3G2Cuvvp9dzWb7A4OkS1ChVI0SP2F7oPKbk/ZQycm0sfW192qooOeIinLmORfHsiuHP//ia43WhFqIukgTjGWVvZTQIE0tmUFD9tQIDraoKguVGffPV0PFFywhqLAIwTsNKrSupSNUaPhrK1Dh0/vOJcv/q4YKGhi0vEXy5EDFaBAD/hDMFNbHb2U+M3q9Mxgsx/7mzUyj33rrNJstRFDB1eLJJEFFo7ERVGhI6uS/nRvjkUsAlTXffauXRO57Y6bZ0fLKSgCJFm+jJQ/abQ9CgsVV6vRXuf0VLC6ys5BCJv8iVER7EYQGwXIm6vEDQ+Tt95Yt+uizxUtWYwt5f/En736w4u33mLy/eNW9981lS2q0NoKK2RV1+EspaL8CFRoEY+NgkscTLGVd5rT8MH859EhBZ6JJeArt/vhTz5GSxacEKrg7QIiggq3F7qtvSrYf/mKeAm5f4Y8bGsnVGBXv9DPPB1QKinrQhIoCFY3Oo/Y4oJkhlC3U5aL3l8VjmXgzg0pLQ/Lu2+/To1br7XL6BguLwN9FqDz66HOCxtFFqLz471e5vN4mryyEvPzK6x9+tKKuviXTfvgLRAE5jj76VPIH2QpUYjEZKsyJxuQ7ctKpZB3WNbU2xpJVlYNEk//6G25WoDL13nls7lMFFQheau3a9Xa7H8YKQYWFx9fagZYNG5oy7aMzUOFj+9rCD9ug8ptxANup0jWodFDEW5euKPQuyS4qlM4mV1jId1r3kF3wyALTvv/+MuhNVMNYS7KpsaWhvqluS1N9XfMWLs0tTIFBKdQ3x1GJb77tforLhK4NtCfq4syZC+QhI35aIFxiEFmEeUBFwQl3RPZDPv5kdYJrc6jRL7/+iU0Rc5Aoucopswtk5covWceKu8osXboazU/QuvBbJZUTc5w1uWt6Dslk5LEdNJh589l6Gmon6Kah70ZB7GmMmCKXoFn+9HNLjPeg0WZgHKDp4nUskuufl1yt9P4eXfC4aLK6Xf5XXn4t3prGxXELPMakSScqzsQDB47EXSrKB1CzjyfSzS1xtG1w1ySFLDYWzBj6aNGSFfXcMwC99cbm5oampvqGmFoam+LkJIrnuXvqLOYNbA7YXMX+cI0/WOn2luIVAEWCSihUQXdv5Xr8nrvvY/4XWofGFDQ7S+z+SrO7FFyBvSIanbNmzFcsFZRSdmEKCzUvx4SmyOeiX0l2QDBGUUeKeptdwAnMlGJsRQfzAhBdMFkKKYM9LnXq386n8idvui11jVyat6jqD/XN8cU3bmrwBwr0OrckBsxSEKUEnKN3TEOReMKePQdSfGV8qRNOPpdG5/DLH3/eEgqVBQIlaU5unI8SM5rCGq1PXsGjiodPnghnnXVBggdWY12YdGZg/2GUbkQeKLYEJGcBJRmTE3xl6xVL2GX2sLicWaj864nn9Tovaq9OtFMcMyYsRr0ZUJwxe756ol6yoivmUlI5KGIyuQ466EjUENWcykkWSwC1BVXo6KNPl6GSUKDCXYo5VKi+ASpvvvmh8o1YF23xCgoBh+7U7NkLAIkbbrwtkzU9p0+fl116Ii5fvpp6Fa3xVENDwuFgw2KADSwwndaFL+KwR7/9dnNdXQovTpYKDYdSh/L1NxcTQn4ffe4dI/ZORTBZ26QbKqSy5Yx+2SCStb2HoI+pjH0lE+nWWKI1loK0cCFlQVOC2Pv2hzpafAstjE46WsVtt01XQ6X/oBFsvlRVAgQJndZjlsINPO5VcyyGHv3iJZ+i9W4nVNBnbGhIKauI13z9vcXqygcVWpsdLa5VtBV+XnzlLYoWbhadgAp/faazZ818wCzZjQbzSSeeRuMGaPZjxx4wb96/aP/77zfjqdRQgRBUtBon9aPR/nv3HQmiZGg5dzwpdwPbj4ckkrIdg9O+/HpdNotUqLIH8/uKRGvBFbxIPqhYHAUsaYq9yB2scYd7WL3lHaFCRUTWJ0UuoO+ohgpFqkZxATkweoA0yVkIyYGK5C4iqEB3v7foYzlSluKw1eFHiZ6Ccw49bBK0GMoHW9hqUG0oSTVUKGA+xSxY+dkamtjA69599yyXK5LqABUlz0oOVM444/ytQ4Wi+lNeS5ZsOD9UnnryBeoS7UKooMqpoaLRufAF+w0c3tjCTHnu/JgZMGD3004/Wyn2WbMeIaiA3LNmseVKIAoEl+rXbyiOw0oG1/mHsLIdHR7Sw3w0RJfVEbzq2tsUqLzx1ofdUOmGSpegotdbr7/+dtTxeGs6o/RwOlMKsaT8yxQPKMLWIaJ98tRyF110rQIV1O0jJh0HqJADIj0JeY9IYqhHzTDiBPQCrvbCy2+wWVYa8qL5gF+ACotySM2e0kaxcPcax6OPvqDEAQQC9z/gL/mgwvzK3dHrbryHRfzmsVWaWjMHHHwUzgdXJNH2z0uv5A07AbjOfWi+ZHJAigrLMmmZGTfceMuPP/2MzjXueO89c6Ec1VDBowIqOMIc5Lj3M7TJjbdM42qN3W79pi2dQiWdHXCgn333P5L7y3pEc7iwuHdxaV+I4lKcC5W7pkPv68xBPKkrVOMI1Fg8FQZLQQ5USFvR6nR5FJGvpsxCJag4asMksjmiZnvU7i7BlclYoczEClRAFL3VV1HdJ5GWkaDYalRQiuALbt7SpMzdzH/4UZgpUGRQpizVm9HJTEAVVCRrgAbHQJf9Jvx13fo6CtGPn8qqnvWNjWyoMAsVQePdOlTk4k1n+vcfRssv1FBRUhFzobTTbD8HKk8/kYWKxOL9yE1MHv7qCBUf7yp51WnI2UyeyXPQQZM6QoUtJTH4QY5YLC9UaNgK1AFUKKk5qj2rIXrbI489pwQDfeutxZOPOk4Flflo4BRd5rDDpuD6rYkERYiAQe9whNgcvtZFjOcDZSwjC8v7wsKnWi+78gbFlaMbKt1Q2QaorFmzjnCRTGQWfbDk3num3XP3VJK775kGuXfq/dNnzF63YTONsWI7f8FzLL2KYCWuHHjgRAUqMdapWSRoJZPVLwjG7CAbE5gpV15xp6xr+Jz2eRdcZhAd8mJG8lziXOkiVJiwHCr2ffb5K/ngs854MrNs+ap8UMFj9Oi1W30TD4QFfce8lVrQzafmpEAlHo8DKg8+8JBOI+m1Zp3W9MrLrwFXcWYJfQtsUM9x9KgJuH4+qGj1UCse6J3Pv/yRkFzfHFu0ZNntd97J5I67c+S7H3+msGM4eebsJ3jKP7fFFvX6ywOhqnBBD9gr+aDCornoXIIYlFwlVm+l5CoDVHRSWIFKiqsqmKTyskcqc0rW1AEqbH0rTBlLGFxRzBQFKiCKApWrrr2FoAKLFjboHXdOvePOe+66e6pabr/j3oVvvpdIxamIGptifl85yoe4AqgkErmWipICRNCIz7/EFpCT0nz6mRe//f777HV+ASpnn31hDlRk11hKdmf2U1jMnQoVdSSrHQKVt976KAcq5VV9KTpkhoUMSE6f8aDSMySowBwRBMnlCq1fX5/Jhh3Cz8iRe7MALWhuzJnTzr8Fe0jKdoyS/+cV1xNUWuLdUMkDla6ApJ3km8NXTT7rVMkTfy9QQe+MORPDLrb49t77INn6yDAv/sMPPVYyeaxmvw39OD5/CEFVQ/2+7sa7UMNofAaV2OGOCILILWiHwxH5eeOWdNbDBzunnnGWYJQU0RrNks014cC/sG5sShlpy1RUDYEiY/G9oc6yUOHZ5rcNKqLoXbLkcxo9gOqHxsF/CwqqZVRYWQJEm8tnsjgGDBn+08Y6ivhN/jkXXHIDj5HVDiqJeApQeeFebJoAABAASURBVGD2HI3GotVaJcl12mnnKkYb/fz4Yz2pxXxQ4URxDR46jtIukS1y4CGHmc1oumyoQaOxQVC2aPaQa66/jULo48x1P7U4XEUoGckSwY4/WAkzpYtQgZlidpcbrdFcS4UNzSUlm0MQhGygEYugMwt60SDZKE6anI6QEizyfCpqS4UElorVVyqYWCalVau/TnC+AldPPfWS0WiH8N5xm9htBb17jWiJJbijNnDdeuyxp+K42ezHh0M/OgcqFIomm97RWtt7EEUgldf0UZDp7YMKa7Y8hSVNq+wkqCg4ofq8k6ACQc0h6La2thtrIKjwCuwRReclfL4wnpTtyobGlgMPOkTQGPUGM22NJqtJtKGfJ1k9Rx936o8b6slvDeX/wstvdkOlGyp5oQKioCGRC8fMmfOY0w6viZs3tgInOo3NoHOQKPmusdNv4O6oWxRYHrVy4lEnoaZypyk2s3LZ5VcpUGFhYusb5z325JQTTt597F5DR40545zz5z7yeM7Q2v3THxD4bDZBhUa0txUqsELQxqCbevcetnlzC/MBi8utq7Exc8st902YcCSefPfR+0ycctyc+Y+SeyvFLqxrzrz34SoKk5UDFfp5aM486Hr+jpbCwkqaW2qNMybiRtOmzbFZI5IY6BQq4A2gAnlw7r+o3FI81r3djf4gKOikWRwSGvjuP2iEvNAyxT7IxMmnwXoQzWG8o8dXRsZKFy2VTqCSHWQ77cyzjz/51ONOPPPYE8449oTTIYccNnHyMSdMmnIyvinkqGNOPXLyycVlvQkqzDRRcMItFYM9ojEHRGdo2BgWmoWggp/jjz8d9EVZ5QhKQ6txLl+xks/Vs1NffPF1HMdX44t1nDlzKhT6N7scBFaU4857ZuwQqJDXFlkqAr64LUTTKgQSrRTg4oP8lqFCBhD6Usym5IHIHO7Qd+s2yeuQ4kr9VVsqos3mczgCHy1dqtRh3rjSz7/w71NPO2v4iD1qe/YbOWrclKNPuHvqrI1bWthUTTZdAnYefvTZbqj8j6DCUl7/nqAiUxB9c8r7DXu5OevOP336wyx6thigSVRseVRwvhUkNKHFS1anslOC77y/nHxGaWoXjX/J8s8S2SlZnEIR5inBlIITNCRqVO+/v8LrLdTq/JI5SnMP8mpwMlZkqKzJ8OlxtBYZKjwaqxoqhATq1R588OS6ulRDQ4qbGtxqaZEdnbMWPxulyfB20tiSWbn6B3+4StB59NYC3FTDMk+4LrnsehrEA35mPDBXtPkoD5LNHX7l1bfpIjS+P36fwygOGDRCRfkg9nZ8FXesOSMZAwatR6f1uJwlGzenmmNysF5arA5NymwUwUUiCE6WLF1gSUFWfvYNOaS1JjKvL1wK6JLzNIwVX6ACUKHAJApUZJfiu2YyLal1CEYvVL/DV2l1l1kchShPoGvGjEdoYLA1m09Tye6nZJBV79DUx6FHHM9YC3h0gIreAkuXxTh5cP5TKEY590Zj2uGO0hIQ2aksK9RvOP/Cyyk8KJVhYUmPbMpOF0WDz7oUD1ZDhdaswCzeVBdX3AFS3BUKd1RcIbg7tY+8G5jwYb2zz76YvLQpKnD//iNoTkXDPe8Fg0uZq89CxaeIweze0pSKt03Uv0RsYDkU2Fy9E8JcCXR22aVYFZpesjIPiI5QwVNNOHgSuYfQ4pUjJp0kWpilazR4O0DlJJqw7ACVpQpUmL1CUXYE40mnnksvi3NQK8jRiybqCSpkc/ftN/jb735CK6AQ3WyRfzYrF2Uey2SzA7Rk3x07982YZ3OGuqHSDZW8UEHbY+3K5P7r4dk5vRRTiIceeiyUHaq4RnBAABVyPEUNZq5BoueiS69PZpP7om1ECqvQ5ikHolFyhqPl/3njbZqrz2RkqCSzC8GAIsU76Ml/PeP3F7PoEYagIMiTxtCAojUCtDCudBkqFkeBslYfza9//5FffrkO7SoOPRXLNNS3rc8goqAVpXn2obkPP4OLsKQjYlAwsBUegt5DUEllH/ve+2cJOguIQnlwzz3/UkoEgCvUNWTYcm6NG91McKVTqEhi6Lhjz1Uy3qNxjt3rQJQYnpPP9wQc9iJgiUsQgpZ/wcVXyysD+CBYYXFfu7OYZs5hrAAqLB6t1tkRKixdLt5FBRWrs4iVZxYqyk+igzcGjc6Rpktld4465nRS00ZbRE0UBSpmR+inTTFlCn3BgmfJawsqtX3UdzYMCKhUVPdhJ6eSRM3zL7xyK1BRrV1nw3To+J93wRWdQoVCizJhznIBecttl06hQnliWIM1uACSrkMFqpwpcZ4VhqBC2NsKVBSRn3AboUITlluBCnPT56vradwSbYSukE63QYVitKBqyVEjDebCovJ//2chN1PYOehTQtJ8mVFzM79LUvaKxGda9NGqIyefKGjMML+6odIZVNDqOhW9NY/YFWl3M7WzrHqxoSr1rxpCvxiYK9eSUINBdc1tlg5XpiouMOd0EwznZ55/TV7Em8j89FMTKjevqQFBAwPFDaEBHGgHtAeT1VtZO4DyvZP846JryBWVBbPjqebRnf/rkcd+sGRVQyyjqOY465+yLOtJlu3nXbQrlhBJDrjrZXrBFDKIYZO5AGKUItgnZfHpp98oig+WDfpZBjO6ZjZq9hqg0RygkDOKzxie3+4sPHLSqcs//rallfmSNja086rasiU2bdoD1T2H8gEQtghUEMN6a6FOCgs6r9kdufLGu1i6Vh6g/t5ZD1m9EcFg1Vm8ojNUWjmA519nRsy0GQsEjZ2ikOFRyyoGkf6ilmkxR5hYi55/4QOejJJHTmvKUPhFnE8vbrFFJUsEIprDTCz+Hr12kwMFtjC59LJbKIUU9JfTU1hc1tvq+H/23iTWdWVL0yNFtSTVUKQkUr2095a2dn/65p57z7n33C7fffe9fNm8dFWlnQlXFiqNhMtV5WaQQAEeeV4GDBgw0iMDBRsw4JFRI8PN1PDQgAc18cyABzYSMOAqwOkVschQsAmKFKlmnyPgh8CtTQXJYHB9XLEiVvThdiyvXvy/dCocNQp/80//6X/meipFo6IRVw/clG5/BVABev3VX/2XiB+wEWGhg8K2cbIhnMO/84//CXEBa10MPKAA4WqDLHgFJviP//Tf/pceneBXf/S3/x4AD8e5uuOVvVXXwJEl0rr/3f/wP6MnBJ//6//2v+O8fWhC/9df/39sVeOb+9cknZdiIEpZfh3Qv/gX/8df/zW5EGy0JDlmBWfOWggVuHY4PeK81khK3T/7+//wb2jKxb+hrxEPz941jCFxpDDXA4UKXB0bAOYSRTVB8Pj8n//3v4JG+//Q+vmv/uv/FlgOR5FKdTArmDQMnzKA63/6V//sX3pOOQhXfuR7yNE+AIF++tXfYlcKUPnTv/sPyIwc1a43R7CN+XIwx8G//qd/gfCA//6bf/aPWYbN//5/+l8Ih+hAcOzNY/r2h99lKwRjm/+P/5P/HHhMUwFhaNDUNKJm0/nmm1/+83/+P5KOx3/lEohxC44Fd+e/+Gf/za9/7++A94xriOFKPwwqSUzToZGwK6j4AJMFKgFPZT1CjB9RJvZsUkpw3JQK+0yuM057nwEqL9988+HDL3744TcfPvzy2bP3uB4DRs554ex0qBCoxJdffP36y49vvvrx/be/url/S/KDUTecjEyVKpJUwvf62eLu59/71/7un/+Df/8v/8O/+If/wd/+k7//m9/+G2Z3QkcrkqSnxFaSKcoWMQoVB7kCREGuoJF98eL911//9M03vwC9ffstydSt1OHM0cBVWiNQSSf5E8G5IZM6C7QfSW6Sh19qDsd3v/r5j//en/278Pr/53/x7/344+++fv2h2exVqy3vXdUEFdQhQKWkDaUiYKZpT1fvvv3p1fvvv/j4493LL3DqbFHvgIAiL958/+XXv/r2xz8cTG5IIha1D9WF3Tvv3v34+vW3b958B5/gwYAkyXz/4fe//8Xf+ub7P/zi/S+v799h+kWkNc7cZlgC4Tv+6y++Bevw1Ydfff3xNzd37+BycNIGGESEClqQN+9+eP8eKudXUEU3Ny8VXKVRqtONJnDF7C3A7avVOuC9vX37Pez57v33nH7k5H7z9kvy+f6bnz58/FWzPUJPhbDEW/BRb42Ia0inCs4unr778PPX3/76yw8/ffz+N8SxoFBHvxaJgjgBNpCkPlXz4vIZXB0c5etvf4ZPXFsBrDyU8NXXvwB9+PhL0kLgJlILjm/3TOfnD999B231Fx8//gxX/e7d91h1pIrgptfchWQIuWnyoeHkEq/u1duvv/vxN3rTRkNMZomW2jg9BaGCsfoAVKCRf/PDr7/6CLXxS/CfSOuCA1HL4I5p9DLn3z378osPPzKRoyt1alh8VgJIMBivvvzww4ePv/j625+++/HXw8kVfXCIz9EfXb7/5mc41pt330GFWL05+kagrr14++WPUMnf/vB7T56/Ry+QZK0PdDOq5qu3H6Fi4Q6i4LQBBhgZBahQqcUiTZZRMUCqav344x/88R//+V/+5X/0j/7RP/mTP/m3fvvbP33x+muymCbtVcN129x1dzhzxL/1ioxyFtt1HKpvlnjUrxUtEcEE5UhFk4kvJy1U/L81MyhUMm2OODUBE4R4apLxwdQoSEqbm4doMQ/MJXOpDsyot4ekhRVw2rxKTEbNJmcrw89b2AVBd9DdNxpajtvNVXPg3RzjKLCtN8Z6c8akNaZVbUSCAWx6I33rxHX6JHg8vPnPNHt/Hz7JBk1qgl4O8EkudgmZtBEYfTgE+j0kck679ch4/Eq/Uh2UtHFZn1SbC629UlsXheqIcAVEYYOjm7yZcTRLI+bUUgcSAKPY0dtncAhJatfUUUHpFgtdrTaqlvuyZMJ2uWiXyk6xZCtlV8hLQtAS+RdJYKxP4JMkncQsYTWHOjHe+mP0DYB2cZDXea3hgN3pOuc0X1Yf+16QQ7gWrGdZOrhKrtk589bKBdbWidPgLfPFC2eD8ttQGnFHCk30VAAqdWuKMjpzEKZvgZIxnyNiA7slJZoIgCR3aQxwUUgQopT4UlIdV6WEdgKfcEOxacGLAiaih7d+4uUXWjhd3HVxVDclT61K5gnivArYRltMB0DTtkQHQINzBhvYKY1j2AilChrNXGlhdREXs0Zck5Ju46hiXAYN/FEm4Ao0AFdKnbQ9alKhNcI2nCcuhoY9sdDm150BND0S+ihkEiV1nkBQCW4bLjbczoxiQ2v1iT2hdxDOFm80XeySxAhx6S2sXhT6Ll60qcm7cZh+2w1oFeoYlMKSyXKlVQszjOE69jhDqKhY4E/Xqk651MXQoLtOErjvkpufDRMuuKV5qAh0onzWUOk4C4Euo9U/j5agHMteCnSRSvw5iMtMolDJ9hnIGS7N7gwTGnqLKJCxT9jtAE+mPbz2tALBJTfMUb3d1w0H6rGktvlFWOEZrhtTXN+wbpBVm+D5IQ8t9gHSR9GH9y5iAAAQAElEQVSFbqGNUAFbD1xptKZt67zTW3bsK1DXuQa1O8t6a46mAZ5JMlFcJf11rgGicwua3TmRfdFyFu3BpTlcdUfXvfFNf3Q/GD8Y1gKJAoDBN1n0h+BpAVcMHyew4GSlk/ZFq7sy+086w2dG7wZU1pEr8MC3wawgVEjkpj017IVcsWvNKYFKqUvZ0wVONIyzZusMKAUgqZQcgEqtMgCp1SF8CfBwO/SoEwZEgU9gCfzE6lx2uiv4BJnWEtRzVhghoJyus1kO2E0EhgPeXkHgsqD1p+vI6hi3aJljNC6w0eldYGAfobIOF1eihSXwS5lhdw0OggCbCzhp9c7g0+ydt7tn0JBIZw4FHssXAmq0J2BDoQEAeGA3EOwPAq8Of0LebApNaB6wQcqnrYjYWTZJtmaCvQYzqjeGjda4bc15wb1r1IfeVHw6r4J2vUJbgleTRntmdM4xTxp4VMSO024isnSKZmF+MLg6+BJOhlyIc2ENlvYEWs4VbJj9Rbt/xqS2B8Q3LTfhUzcGmCcfUyw3rbFpz7uDC2d0BUK0YF1hpcE3IGi6UCFQFVgJsIGpxli/GWxg5j04q3prgHFBjDO5og4fLjSHLwfwJ80/ZuK9hqeYF3wP/iVmSSDspEyFb1qtYbs97vXOHOdiMFjChtGaaKpTrdhKwcRRbSh4QMhoRsS51oV3l17/ApoZNCrYgEtmskdLJv57XkL7+Wg036iYQH30m35aT0Xo8aSdLCksJ61C3V9cDyyu8sagQmYLUtMTUYK/hxE8FX89BPfHlzV4ZhD4ctkdxOklgnTcEIInjKaEBc5BSe8zj4SuVrkW+iiggmbDZ6kxKDUn5da01J7JjRFKqRMV9HGrf1PUxwV1WKpPQJUmWI2Fbl4Z9n139NyevLT69xQqEyANwUYR/CEb/BXwToA0JW1oj+8vrt8BSGAbpbZmwJi6ea5b54o2sKcP/fnT0cULw1mBKwOFoF+CmFTrExCgDj4BKuijEO+kOgABfoi4sDM/dgjDy8gVEL7PBpDg6173fuhmhufKSSKECkkGKpP1C8iKO2WgbEs1RsCJpjnFyAqLmjB/AmiBwndzGt3pBF7h2Tb6oNgTi6vWszdfjJEQ18R7Q0dnhVCkZKGngiv6oE/mdiFW3alOVO6YQFpvdIq4VJVkFd++3VcceIuqdcBHwUA9idLBOwQn4qOUoQHDq7pGRAOrcKrgVIEI/MD5oPzgA6sikX45SpQIeWuS4p1dCzsA/SK3NbCbvzGwURK49jZsYAZin2gFKnSAIgjcFN5TcXMB+HPMkJI9B4VxMeypfH4xlRNUONuBq1J7aiWHClUcVBRvNUn2+ok93YATVCqoBFiSBCpFY6q0JvAJ34CazrU9f65bC828qBlnVBcIlWb3FtwUgMr1k+/nl1+WtLFmnAMngBnl+oAsZELhAVxxJg83Tz8CRVrdpWbMQWSEVfuMQWV4/nx6+fru5ffwSYiij7C/C6Bidi+xc48QpTGNgQo/p52HAb8cMm9BosWNZN0CKjg9cN1saP4FMMEAFXjdxrAKMIOZ+7Xp94iCvV6wgZ1d0Ra21gUDTdZ/pL1JYKbd+Ha5xXwgdERYUjLX5CltJs/URkCFdNzpPVpdLVxikmbIb69Hf4Wgwvq7eLSAwwqeCngn4KxTf32IfV/k5L3BZgmhEk2UlFDBockJoYJ/JoQKVZtmgmifoJIZKoL+stRQSQ2hHQ9B3gCVoDZBRVT+en93LD88+VV3xoBnQcij7iXsc3CJkbVCOPG8gTEIPAxOQyYeKrI2AI+k3JqDSu2zojEHwQZ+050+B6nWpTG4rxgXqGp7UTFXavem7tybkxed+Qtz+gx2BgKp1kKpT9DLqTQnNcOFyv2L74EiRu+S4UQzz4AogCtFGwG3JqsvHt7+cvHwTaN7CQBD8BjWYjJ/DiwBfwU+SdxIABWMOTHbsUYCZ+4TgYEHybZQWY9FpFChfYDjRnuC4QGyzkqdDOHTG0MGFRZHAfBgRyj6K5FiMQYQvvuvVzeJsqQkZuMnCll8QQAVDHWgA4SBwGKNPOYBZJLGSaFC5gKXDOKXUPFEUTRrtngYTK8AJ9hh5Z6klzCf1wa0CKAShkQMVAKDF2LeM5AEkU+6Dx7+XDKuERBDJbkOHRHZS0zlBJVdQ8UdslyEl8Eudg7gqxzDSSqolPVJPFQAJ6gAVJgqBpE9f9nq3wFUms4tsISp2CICrmi923r/ttq5lKp9LASggl5OtTUFqMDJAFSevflFs7No2yv4BKKgj8JDZXb9JUDl5uWPLfsKuEJmIBpzcFbmF6+AJQAVEIMKEsX1UY4GKngIvrfKXXen7ujmBDiBPAhABbcRKsgVhApG6SNF4ERZgl1J6KwgY5hrwuZ5uI6X0k4FFcRVWQPvp4GDEvk0LW6XrDf0izgrdNyXG0ujREGosEAIfp6gIovHE39+UNmq6OxkFsEjMMs9A2zWXVLuqC063CjmcGzOCq+082l851+xQdgbLsGn3q82R7o5w3FZOGiKRSMCwv8y4TfY70R2qI+YeKjgShhyzSmo/YI+1ruXiJCyeY5EoRsXZXMxuPxCs8H/uKz3rhEn+D0INirdy5K10Ae35c5SbkxApeYMCmSeCnAFDteb3N+/+h3gh+FcAzBQxB0xL2rmUtYm1vjp7Pr9w9tfvf7mt/ObD/BNs3OpGedSyW51V/PLN65zYxB/Ra1PcIQbn/FM4VeDTjz2P6YjQo4a8ZmkebNIMhltIWtaqz+cXbNeIOyzAmFfUKRgZ/gVCGkRKfYv5q9gyegNYFcYL4a9tdAuU28Yx+mxjjXmBmENuFTw1lpfh8ppAn8sJxBTQaKAEFFhhHCZKH2KJAreU2EPGCdW80l2Zj8JC0cBsKuOGKAheO3Y4v31UXR54ZRVVERnvtCuhsU9TVmoleSk00IlPw/GBxVioSrOQaDi9n3DSyvNP+gSZVuogP2Nhwp5iaZQAZao1gKhwogCKhrn4IIAVMALAajo3SuEChLFVWeJUIFPhArt+3K7v+CgABVFGzR7y6dvfwlQAS+k2VsFoCKpY3CGJqsvb1/99OzL31w9/xG8IvC01NYZ+lvL26+AKK3ukrgvHFTcXGdUsjeXdp9QkfwT2WRvzCgzbfgrsPiWcwZ2SlLq+C+01PBlACcAEtgZcZIQKngg9g1zBdiJyVFQwXxfZPwYdYixj45BheGKt7k+FFGp7QFwZXdQYe5LjlARtYrIBoOe0EaouEaAfr+tyT4WqIgs9tFBJQlaDgcVruIq/GpXEQ5QFnIEhc0IA7lVG4TDq2rGDF7wwRCjfCSIEtuT7Q+fYMo18wy2eajwdIGnlyxhWXNgZ7V3BfwAt4OpYi1BSuvMnD6zL17DNuwDaMHveahU2+egVv8GHBRX/mOhpwIX9fKr3wU3BfZs2Ff13gpUI0Qhx5K0MdBrdPXl7dufn3/9B9evf5rdfQ21UWnO1Pa5oo2647vZ6g1Ui9qeY8Qec9LwUHEH2ta62aECrS4MlZhWHYAKs2tgl4Ei7m/p6HBWIPwJ/7VHS8YSRAL/J+vXihEf+MURxkgUsWngzCXds9pyMLoOPoeLgQbJd1kxnFKzh91ZPFSwXws7jlRrqNQ78VDBhEAihITFp3thf+JiEzuCSiRLmL/Cj2OOeQXJ7m0cCVTEp3eUUIlHS1qoiGbmZ4EKm3dJAxt7hQrYd0qUM8aGoG+RDCrwK4QK2HHYAEMchgp8z45L7H7nUm7MeKggQiR90j17CVwBu6/Z14CQGKjQOEoQKuwqAAZvvv79dv/GGNw2nWvgCgjcI4AKFAIH0p2b4erd/btfv/z42/n9N7ABPo1cGyBX4CqW9+8BLVAaRlbUxgigwr8ESErrUFCRuTdN/C06CigclxUoEL7pDi4a5gj5oRsD+ERDj9uRUGG9UtjNxbqnsED4ZJmGaWOOfuBFUCnqHcIAvQPfELXBhXVwGqMIKlpnVNBdcx8gCouppCJKDFTwGhPiJCGBRLBZ9315gwv2AJUj106g4vtjx1Dx/SsDVHz7iC5eHLPJHSq8aw/PCRmIWetKcCAN4+TnBX2aBCQirhTUPgFGzWl0F4iTDVApd0myd+cm4Klg1ARIA94D4IT5KLwQKkAFvXsJhACokDh/k7hZTNUGEXLl6dtfDs9foqcSgAq4RPDZX74Fljx9/3uLZ9+Dp3L74geACp0WQ9aNb/aW188+Qplu7gCaRRizIwcGZLOJgbLXGcX8iUgLywwK+hNhYxHf5pn9UrjuL/5PVj5+jy4LEGK+fMKwgTP73HNQ6kZ32u7NsBsKYeMejiZwq7eHCBXEDCuc2UF2GrE2gphOKBzHASMAgAfgppDoer0LUAEvBP8bAxVJ9WDpx8maKwngsY72c18yrrheNT3tJFBh9bC1pxIQjt7mq3fjy4rbZrzmtPF2HK24a9wMCb8Ew4j5x8dXWY8EKok8lcNBhUyLgzdr3SHBjOZMqc9ygQpIt84jO74CUIH9NfMMmAFmPQAVEHw5uXkfSZQAVHAYcTxU7l7+eHb9JSMKDxU4FlANXKKrV7949e0fwSd4LdfPvjOca5JYrD4BqEAh/fnT85t3WmNqWAvwVDDVP1mL0z+vSKm4/RWsLUVCJbLnSvR2H9PmA8ZlI1TYvzB0z/jBqAaCf8H3OAcFeeMejgIJv8fsLLAduIqEJgxOA5wkhAFCBZ0V9FdID9gmqJRrlmoNpapreiKhQrrOknkkeUGF7wzMBSqsZDYTKFxITJvhrfPBCbGF9geVJA/bY4fKLjq+eKhINVtSnYI+xKG3aOu3IArPFdiQqjYGVERuCg8VDKGDQQ94KmDo4Rv4nN5+4Ckigkq1fQ5QqbbmFTFULm7f37/6HdgzDBWM34DDxEOlP39++fCNVLZLpOQpOU99eHb9xWD8QPKSualoHM5Z4W4W8zxioIIpcDK0ZL6t8lBRaPeXCCq4wXZgjkjAkAFUgBk4DAyhIjNHh2bTwih6wGzhVSexFBh9ITtzUAEHBdESAxWXHKVWVSPejFTx6jYEFfwmAJKYbq4kUMG6jezgCjAgS/dXJFqwt5Dd3CRQYeeMP+dfO45W4us6QSVEAuHFHw4qMrxuG7OS3/RngQr8HKCituegJJ6KXHPAWINBB7Mehgp8Obv7mkdIFqhML9++/Op3wZuJhAoGcvjur+74ATwbe/pUqvaRkfAJZ766+aoOLpE3G5RzVtJDZSNXEuS65m2ZnMBTwUOzEAj+Nuzx1NtDgAoOOw4M5XJPyTv5LYwU9uegW8bmwANRECo4UDgGKgQeNB0ngUrZG4CQDCqME5Gxk1ygIm9yaLZT0UuKE/5XfG3jD3HMd0LqH1B7hUpaMGTRFkY/2iMJGZqIykpMFD7/UnK55psKF2qVyt2C2q+2zjVzqWhg4j1z3xiQHCopccIPL5bUPkClYV8SVvEgaQyY4BASHdBJPJXmhda7LTXPaqYv/A5WHqDS8mcI2AAAEABJREFUHN4PLr+ADVEPGHxfs69akyckv0tzEhaiBTvZgD1vPv4hsCQQqOcLvHzx45OvfgOfo6svO/MXmn19fveNOXqC026wvwt8lNsnH/TWiGbMHJMZKjSHcWAQBLO2ebXJ+HcjdkR+B9zgocIeE4WLgiQ3UoyUQUAmezZljygYicFyMBSP3gmLrsN2zei7Kbz8mVekaqugkzzEanuAp+HOtPfHdZhgTyiclcxGhYXJgVFGkdjlRxKFkSYyqJ6j+A7MVGaaH599cHLEn2rKk/Qxg4vkR7S94HO0a6gIT/oIoJLFUwlApVghqyUCDIAolSa8eo9o2ID6KJiYKyNUak69tyzT/rSNUCkZS7V7UzEuYqACfgzAI5IrDCqRRAlABShy/+YnkkaMBvYjoQIsufviVwCVyc377tnLxuDOGNwvHr6tNaeaMcf+LklpA0uW16+pw0f7vop0vuoeocI/KoF2FdghABV2SgeACvVLinTYMXCFFYjmvtpy0OIzqIAi03mRyLxGOAFQwatjUAkTJXeoyGwmpsALOUKoyKGUX/shRLzCbWYroiSCCv9cCKEiasR7hUr8pcZ3hSWjSC5ccZ9GDIzTFXvA7ldJD9VC0SaY99ft9UoPFdLlxUFF1gYgvbtQAl1eAqhUrSsQ5vKKgQo/SSUhVPhOMHc4QPv88um3q2ffsbBKGCpwxPt3v7569Yvp7Qdn8cYYPwGoDBdvz6++kCs2sAQFLDE68/nimd6a0MHEHcIVf1en8OVoBz6KwnV/hR8HH1Swx+kQUMHd2PsyOzpYeTKB0bP7DCqYux6dlQBUwFkBP6ZK110PQCVs6POCCquZRwSVI+FHwlPdlnlHDBXhVR0OKrlwJQIqal+1zsFNKdVnQJR1Vq6UUHHjKH6oAE6g8EJg2qMAKlrvtmKuMEdkTPdXLlABhFjjh6fvfsXCKuCyAFRYybCh2dcPX/7u7dufZ3dfD1fv2pOn1vgpAG+2fD1dvAIfBSiiNkYAkrLaqxvj0ewBGBPu/pL3DpU1NsSeCv9c7R8qitcDI/kdLAylsMW1GFTgUwQV8FRI35dmBaDCDG48VFztDCpZAie5Q+VouZK27YmVU/fXLgAjPOmUUIkI4MdWaDwzskMFFzjy2Z36FAwoJcrMl+oxj+6vGvEJ5jFQUXRHKps4OaDRfwCoRCRfoXNHGoO7/vJtqX1Bcn9RrgQEX6rOtTF9ivCIhEq1NcWxA03numKc3b/5aXDxCgADwnn1rGSc2H/+5Nu7L34FUAGeWbPnmMuy2pgsbr60h9fgo+C0R0khDaPRnp1fvtIaU6lA0oFAbWNiD9GzkSNL+IYUY2jY21Lg6PmaG9F54onJXHw70P4JZugwYjaYmI3+CuOExVQAKvXOOBDAD1hetsGzJCNU5KiYjSi4sjuo8DNb8zXuORa7xxNIG8Dn2u0WD95jh0ou3V8xUCmSWSn7hkpBs6WKhYthMKgEPJVdQAX4UdDHk9UXNy9/BLq0+jeYJx8nV6KbAoKDgqdy9vARPBX74rU5etKwb4zepWbMr+5crpRq7uJOmFBydv5Sb87gdit0DVoWP4tuHjuAiu/mhl6t5Kgwfo5GJOY8FW+sEaYI489ZKjZwSBIPFXdmCZ1XH0kUSppmtd2vGX3wY0RQ4U3/nqGScYjX5waVPI6+X6iEW3yeUBFIOIs+QVdY7kShUGmA3DuHCxzV55XOFSVK3lCpOaRjzZhtgEqNjOAkK9069+X2Zbj7KxlUFmrvEqDSmjwBcsRARa45NWNGstlbi4Z99ebjH1rjhybNA6Z3L3motCdPgbhAFOAKQMVZvLHGTwEq3eEtGZ2sD1a37yx7ievNaM1hka61Xqw4wBXLvsDVztFTyZ0rokdR2dQlIkWNF9gPVGRvjeHAmUvecvHk5P1QYVPrRSroVsOeusOFxVDhu79ygUqRm3h4gkoux42ssfRF7R0q4Ub/GKHi4mGrIcUHgUpMoF6Gd3mV5L2vtYa6fYdQKbfOt4YKeCoiqGAKMoRKs7eyp09r5sXV8++vX/wAG+C7AFoCUMFwPcbq4ei92YtW/44svtI+UxsjvTU5W75smnPghwqXQz0Vudgt1wb98fVgcoMNYOODmgUqfMnhJ1MO9aTvFCrxzxHOkZS5pMvMMuKcCfiShwpLBClyU0AVwyET6UsNsqcAKnxPFKPUCSoi434oqARa8pFCRdS4t3s3zBk25WjxQ355JQFPcsnVLkoqW5JxUTCXaeEhUoGTVLXrvWU4VM4DRlY7INiz2Vvqg9uieeGtu3XOBBZfqU/A6M+uvyyZl5pzp9q3td4NsHAtGloH2AADcPIjJpR0D9oaEdGVH0l2ffjGWtb7t9jB9ebjHwEqOqMnje4VZnkBwYYxuO9Mnsna5Pzum8Xdh8nyTXf8QJZg6Z1r1qxqDCstsnLi4upVu3sG8CA52707Iin1hjkazq7hU+bmFebmEAhaS3DkK/tXrPWX/eyJaefxz0LEI+NN2GRDhwMM482u7E3NQwDwOdMClhQ3oOR2b4YbgYoVWeFgtXjiwcMmqyOEIsXSCsj+uY0RiWEow/KiSGT2ZQJdsbHeeE/3Ki4E4F0UxtJ3LRFsuImQGXmQP1dOUNkZVECABzD085uv4qECAlSAwxHM/eVBBddTgfPEVMfgiwCHnn35G8AGEAWhwtSwb6zxU9W6rJnLq6ffjhevw1DBVMRny+dGZw7bwBi8QcTo0Dzz3cEFCNOQyCG/YWuJWgv/5a6hEt7Nx5KCTkS7tliXlwsDbrwZC2XjDgGosO95w8qSXWLmmMgTPkHlSPWJQWW3XDlBZZdQAUJUjLPzuw9CqJgrMseFosIcPVHqM0yLGTgufJKTBGeFg0r//PVXP/5xy77RrUscBob+StO5Bah0p8+l6hCIgp4KWV2YgwoQBbPcT8+fdJyFm/OGdnXiG7RMc5zYoyXmZOTfyrNI1FQKoXxWSaAicQH88H83/jDmv9jlxbLLMKiAMMtI4MR4qISHhzFPBVkFbgoz7rl4KoEhWyeo7FS+69r54XYGlR1y5QSVXUIFCbF4+CYhVEpNkoglEio4n4bv/tK7V/dvfr57+Qu1vcDgCnIFyjEG973Zi3qP5CeeXr61p0/b/RseKmT5dDr0C+5Ft780e+fk5iot1tON/gr8CRYQV8HKhSsxTSXQCbZrqPA7SJ6bIvvzrzAjwtASjvowYDCosP3DYQmZplVumCPs+JJCc2VOUGF3hFXI7g13On06UAnzIJ9ydgwVUTnZoQJEKZCsX25O4q2TSEZApebgdPoyjZyLoFLQ4DS6G2MqUm1w+fRbvX8PYlxhwtn42AMGvgWN9s+JfxPiGS7xUmpfAE6AK/DZ6t8BP97/8HfAWUGo8DEVgAp84pJlw/OXZO1hf0wFoYIOStOcgr9CRhKjDVXqfPp6MLKd/jnQpVrvhZ+ujQbR9xAKEBJOmBiGCn8svjEnae2+L/kEl7hNu7wwGT4jClOMEWHf8x1fPO14xwUNOiFK7ORKEVQi+gY5qCjcNPiEUPGVv3eo4IiGPQCANYBcSts75HYMlch6yVrOCSq7hAr4HFK1f3H/tTF5DjgBqPBECUAF573DT+KhAkTRnRuACg4UXtx9c//qJzKpnjpGsIGwAUSBSH7isg1E6c+fi6AC2/AJf4LLUm8P+TdZvqXBKzZwpWmNFW7NEv7RzQKV8Pd5QSUshc13QaLQuSZaq88niEwIFXbVzFfgiRKACi7xQlb0OkHlEUIlpg3sUruHiqhqti/nBJVdQgWsPEBlfPnWWb6rdK7qg4cAV3iogIdR710X9HEMVIrGORBFs69pYP8WfBG1vXj7zW/75y/xoCqZxXLDnJXe5Emzt5KK3c7oXgQVHP0Fgm3LOQNhzIB/hNAYwZ9gfO3REujihhy4vPePBSrrpPc0eT4u0kUCHuCfbSowxtxgzyFPlABU4E8cU5fEciWHCtuHX1fxBJVAm8kIFW8NYO6EudD9LrUXqMTUzjblnKCyM6ggVwAqg4tXw6v3JfMSoKL370VQAQ8DOAFQARSJoILLcAFU4BP2B2el2bs2B/fPvvw1BlQa9hWQiTkr7f5Nd/xQqk/k2kAEFYysYOoEsEfwNm3ac3BZ+FFMEjegFj7BEANXYDd3daxiI/BGnxYqu+v+ihSaYFyynncvGBLSPnp4deFK4KECFYt1FTNFIyNUZK/P7QSVQJvJBSq+Lz89qATqaPuiRPwQXGSx3AVJNYtIpclW6TYz9yFtDuAnwwkRWYseXqvVHnwW20vFWBS1Xkm3S9qwrI/c2Yvwp25nAYxUszV7qbQmIBFUgGpFzYFTMuzz1vhFsb2C8ylbKw8tLmAQKgCJyxffl81zY/RC6wFU7ojsS5DavWHSu1fgXlSaM7qkfFBFOvpL1kZQLMbkW33wSG7BNYFvJstXN8+/1cwzw1mBawIs6QBUxk9ZHhdJHcLt0M1ZrTWsNgdAFEzzFZT30o3L9LrTxbn8iUVvpXeZxlpwyV7YE5eJZUaE359PJOVrAx5F4Cby4gEjmosXaJYBo48LO7JvFP+aTnCq/IDgwG9jCk9omAJQQTYjwLDDMHyItaJmShL7LnqO/PRi1ytHrfT1iAL1MXXLbsruDfo+IRG9v6jt+cx4LlCJPEDEwT5hqFQsMOJE+4JKYNlHuDRFteGUWr2zGKiAwJqD87F8/p3au6w7T0AiqNTMJe3OOq+Gur+YswKl4dyXAFTAibl/9cPF7Zck6WRvZTjEfQEBUUA4ogxB2OzOoX7iocIE/gowI+Cy+ERHMYG/0jBHIGAMTm1RuDADb/UiF1rPDhX+KWAnxi83iUOzcKCw4uXPj3mmkjzYMYaPCY04nDzU5Dq4ElNOBqjwLP9UobJrpb3X6XXEUIm87MCbVyaoiLq/KEKUSjegfUKFiEKlZF4quoNJWYitd6HSB+0aKoVaDwSnpJuTeKiQAWDV/vT2K2v2VO3exUOFdFsNbgPLCfPOilQbMGeFhwqe4dtvfs+ZPWl0LwEq7f5dm/SnXdMOsRVApdYaS4pRqHW09jgJVLAtgRkCWmitPptmEeYKuAXID/RdYH/wXXBZeIVLxEL+3ESUraEis9g756AUaSYV5FzRW5oex7aFFzlO8gQlMRxBe1puQYWQhYfZfJei0IhkgQp/9BNUjlVHDxX+YAFb8ClDpQLN0QKi7A0q4QXqKVHoYirtcTxUwE0B96K/fD24fANQien+Uq1LvXvVI5klIzwVPA0oijkrPFTAQYEzb/ev3nz9G/RUDOcWhFEW2KdinJXrA6gZqWQk91SYqarWewAJRAvfwBRv0JHsj07j/oAWsKc4Zgz+JCOSQ91fOUJF9vJ0geeEh2MZVsIIiQFGvlABH4V0fHG91nHlnKASK0ncS5mLkrSxbDp6qERUB5pgf0ZIIlEhgd08iYy7pHYkrSspg0JlIjUWRJWxVBqmhUraoD0PFZIhuGgUWheN4aXo1ssAABAASURBVBNJnSpNMnJXIet00Yh9dqhUutXOecU6i4mpFDVHKhOzWK47AJVCiwZ42kvMVYyqmRfuVJVqv2JdnD/5BqBSbl+p9j2RsyIKQcWePtWBE95KxlX/YAFEFHziyo+4QheZYkl3VrTB8Pz5sy9+Lupjc3APUGHT7GEf1ZhUmyM01gCVUq0bD5VA+y7SjLxgrMFks+A23wgDAGAmAHaGnwBaQK3eWbM7B/cOhNEdqEAQDxLfABDBY8/61gAb4BsxIUhYgIFr5xuIks/Th46INygZvocLJ2OIuTFy8cYikijE+MZCJRBQiYGK6JzDO+Nx84IKXz4uZQaHkEqJEiYmwcBuAHB4qAhBsh+o4FHXVjjAlRyhAioOS+pcG72oDZ5Vm4Qr+4QKiamUTUmbag5JDyzXyaz1gpelOBeoAFHioQKHoGEVImPyEj0V8Jx4TwVnI9Jghi1pw/n9h7rzBDwVEVR0ksLrqt2/AVcDcYJo4c8BECVrIxDpzqLQwmQwNWMG0swzqWid33wFXNGtyzBUaq0xuCmEhWovOl30pjc11s3ljpvyPAAlNGJKDr33KXQUE/giwBIgCjh5IKBL3ZqS0FSUEEUoozvFQQEYvEG8IeGY3AdhBwhJDhUmPEMcuIwZCtJCZW3lN0FF4QIqW0AleLgdQ4UQpdzMq/vrBJWd4IQdkrfRPq6khkqwgwtVrAyUcl+qXFbM5+rDr4mcN5J6tU+oeLH6ITgr9cFTqX4u6SOlNcOk99gJlrH7q2zOwVmRG6ONUIG36fb0ld5/0ho/M2cvLTLg6q7euwbxnopU7PSXryfXHzdCRTMvOqN7EVQQn+isYGIxzATD8oPR5bz6V0+/Xd5/rDTPeKho7Sl1VgZw2tFuSgKoMOHiVOshud5oK759um/uXAYtmeaOlErQxlpEsAEqt3lPBYdaoLA7CwUuCBu4JQs6tWT/AKGDQAX7A+FU6+2hLOjsyh0qgdPYDiphDykvqLDVZTBvP5ScHSqRFXv0egxQCUMimiv5QUUu2lJ1pdtvGs9/v/niD1qT91Lzfv9DiqUa2NZJ2brWnIeiMZfUQb5QUXuLeKgUaiQAAAYRCAGnUevdkImN5hIXVinoU0xi70Kl1tfs1fnDj1XrRgQVF0XGmTm4FXV/YYHMWcGcLixXGE7WqYBvVOot7r65uP06DBVwEcjoONGqNgmgIvmndKDjwnIphuMfPGPCc5vcP5ExEWoE5YdWZKyFHfcgUJHpqGWXKKGOr/Bj6/uXb3XI1nqlr1ioMBftaKGCBfp8FFxoORtUJP/rS5KXoUPrQFBJVJAQEg3J3/PgKwofS6VFFAJJolg9GvRqH2xf4+bb1t331f5XUv2JpIH7QiYDEpWI5CJVSqiI9sfRVt6YqzW0pFK7aoyrzm3BXMqNmaRPcMGugkBFgXDaowsVtS3pVmNwBwUiGCIEqCjbChj32qDZW6ntc9iGL31xFw5UpWq/qo1WL78zp4CT65p91SRR9CvdfgDfxdMtCBfaMsb3gEns46q25ky15hSQWag6Sq0P0oy52ppVGxMMwhc1B6SoNggqavXw1eX9F0ARa7BsduewgSrXfV1GeT2QGOHgR1vxxn3DbwsGSKEqli2Q2x5Cxo685IJKdSZvtrNveprkn4eYiR8cyWKeU3YgTPrCghzhPWPK4c85jOdIBdJfhsth6BXNfAyrGJU0M4lwqTEUf8tY5+TGmtxOohrbGRu21jZQiW6TTDuHCldIoGbXZ+MRJRB3STb6q4tQAUMsOU+Ims8k7V6qDwlXqjbRPqFSBlfaktsL4EqpfSFp44JKXtUzQUW3JM3UnRuldRYDFcAJHAukW4t2/wagAkZfBJVixZGUjn3xfHb3ZbmzbIzuGzbp7wKWcFwhUCFL1pM1u+ByyNGrdNpKJFTgE7bDUEGu0LmZ3cXtm+unX1WbA90kHV8YGCc9SzuACt/8WNwFAcP8GK8F1gPdZdWSBSpTiaAilRr4kkvfcKMfThbAZ9eV8TnyWcBQVxtv1PBLHMvgHtQbOsx25jdygQqOmZZD6IqEBONceId8oVKqmggVvFngoMQQJUeoKALP9Zj0GD0VAVf4rjBfsWmhUmmRUBsG7ZUOYANe2GVtpNRnskb7eUB0yG/ylPhZoMKiMiQrYu9GtlaSPpK0YRaoFBpAzRZY9rK5EEEF7Dv5lToEtABg+vPn8BkDFbliS8WOUh/dvvpBH9yCMC8kEsXjCoEKLgys9i7bkwdcs4uHCuGHPkKioOAbIE0AKlAz8CdOz1zevX149ZENtSJ9X1pvh1Dxd1XhCzI6MWhwcYAWfwLE4viSABlrAUiYvNV5SZKPmgFC76Sktjn5ACbn0RUmJ4YKxpn4DJKsZsIbSaCy0Yiz+TciI6t4C1PydSJvokW4Py0VVHgsuZH5KKLwX+ai8PnsCxX7gIrwuds1VMLt1X3j4KIsvsLTQ4V0j/JQKfUQKkS0O2ifUHFhWWgSNc6AKxXrAriSBSpKsyeVGxVrCUoCFfgcnr/E9CoiqID1BxhIRWt+825w9Q6clebwniSxd55wXHGhAjwrGnNn8YpMLvFDBQoBihTVARQI7iB2ggWgAlUEf0Ll0D97UsmYLp/dPHsPRGETQXYBFb7FstIChpgNHsM+Iqa6MQbheLD2YAFqUbX7Z0wte9bsTUH1zlg3nGq9gyDhu79EFioLVBJ2f6FnpnApnNmAgsCeMeVsARVWyaJy5DRQwXPml/vcAipYiEJHKxT1Dn0niCCKfILKtlDhr3Enkx9joLJuQ9RkY/ZAhZsgmXryY9mmIrGTotIGwUs9CGwcWDo3hUnNcYMr5a4ILWmhIhoIUCy2QGTNrjKhC5nQZ12WulfADwxo40CpVFApGY6ktuXGjPSAUV8BxFaPD0MFKsQc3BrONTBVFPzHdJAAFc08u3/zc9O51fo3xF8RQKXaWYCz0p0+hfMPQAUT0hCoFDvY0wg1X22OkCiAEx7AmJwRbkGrd3b7/EOzO4c/ibNCu03YrI7wc5i9HUYadNGD4aaV1HvFul2zJnX7TO+fg4AfahvaVRfEAs60K8wNqGwxiSyvB8215tSgo+8lRw1J2g4qCfu+IicMyVFw4ifubCw2PJwsodwgv9cvByqUWnJRiOR8ofIYdCBPZRcPQHiEj9u+c4IKCaJUbJJGly5QSAxo1WZQCaNlF1AhzhP4K/q0YC4bNuEKjpLaxlNR25I2rvdvk3gqUCG6tQCuwJ9xg8rKXZK8q2ovHr7tzV6oznV9KPRUNHsFzoo9f950riv0cHz3F0AFe8AQKkAX5qbgsDQm8EtwdqFUaFSbg+unX3VHK8IV6i7wg3TzhUoS2PjetujAYnc9TfjUe1K9JzVs3whU7ASDDbIdxslhoKLQULmIKOzo4Y2NUNlgvqk/ofh79iLrlvEpOVQU/zi6tFDBebKYmUZSGoQrUbdAPkFlW6j4avIgUJECPi9vxFNCpahYINGcZ+IuVLskIS5xEaZSdbweM+pHS3qoRAu72orFRpEOQCBcKXXIYlbNGWZR3BIqOhTbB/suggp2doFrIlX72APWmzwpebP6w8JVirHbqtm7fvLm52J3qY/v4z0V1VoMF6/DMRXGFWS5pJDuQUW1ES08VHAmDXZ5yTQzynz1Yrp8hrYDBw4FnJV8rHBoEHA8VNCNxqwtBa0LLkup4YDKjV5R7yBafMPAMqS7yOtpkunQYay9ePuYFioJx33x3WtJoMJ22ylUSFieupWIE1T8LTi0oX98UPG1rp3zI2ouMd/mdg0VomqfpKjS58AVtvxDAC27gIrrS+EINDp8gGXfStv9RWL1tWHZXGDHF3aCBUZ/AVfIELiyDUSRlE67f0O/EUNFJQwgkZVy//rZD93LNxXnSgQVQpTeJZywObo3eGelMWHOCgbqoUzySXLG2Djuyx9/sniuSMUW3BFrsDxfPcOJFPzorAN6KgGoFOs2CszT0UJl3eXlre4l59T9lYQoOOgrXGBE3XKB9yRQ4ZtBWqjAzcKFUsiIHtrxVay0ESoxd+HQhn6f2qbdxpcphEq4IFdlkerREkxmFEXjeYOeKFwvurZQsaUayQXi9YOBA2H697HWEyqrPZCXmDIxTtyJ2dEqQ/kFQ9EGmnlWs6+k5kyqz0kkXx0Qc6xPlfoMPskUxdBkSTfJfBFeuEZN55riZLJWa0TkheJZR1/LvjScFVmckX6J89vXouYe3Dgw9ICBunn+9PXvwKc+etKYPKv170C4gr3qXIPKnYuafVmxLkrtM3BWauYFAIwMMGvMQAgVdErcCkHk02Uc2dJbGD+LlNp0Jud39miJXSi49GGkWdlgDoopJXowqAuLq3W5yxnQUWrRRBEv7sRejdGi5S58b5MpUQJ9SvEmUgr4KN6KL+E9A0MnIj0J9JACw7JFRHFDL/78zfHli4qKx0/RW+kgpsGkeu34nBQNmyT1c2CohCERgMpmZ0VUKVElk3Vqaw7IHbLlhwrjyo6gAgJzD3god5aV7iUQBYQI2QgVBENB7SNUKsZMBBXYB0QiTPqwM7p1/RK1H5yn4o3LgnoAJMgV+/zqi9nytWRcAFeqzi1ChXCFQsXNYdy7LJsky33//CXOgwlAhfolHQYV5EoSqODYpP5kNZrf4Lr04QE/wjb5eUMFh0fLPB78iri6cK8X61GgURnZG6XJktDIsQO0fCewCSrsjichirtzGqgwnOB6xjGt5QQVsZJCJUKpoZJWaYgSgMo6Gh9Dl8RQwcIxyuJOqvChxeK5wtCSF1SkokkKhKMrhlTqgL/SGN0rZHUTMvSZX9QL0RLorUIkgLOidy9pxkaA0CgMFdzNHZigmAAV3TqPIIoHFXRWgChwdPCZbp99W+vdgHeCOHHVv6FcWQFUMLICVLPGD4ZDMrjwUPEiKD6oBLgS/4IJDaZa780WD4PpFVuF/gSVSEGBZFofi42Lc1YGLy0qjoLsYRuMK/ycTdGNw263dQlJiIJdZN6xcocKG5vOn0kEQU9Q+ZSgIoJEGCobOsHSQIWUhoN9KzZChYxHolmnGFQC/kpuUFHahCt0bja4EaRXyrwArlSMi1LzjMW6RVBxFy8pWiS5r+WuV78BKlW72VsazgqzOsKXYaigsyIpFp2z0rH61/OH74rtpd6/BzGoUK6sKt0FQgXAJmuj0cUrkhI/BBVc1H0LqPBTHCznDFwWozs9QUUknIEhGoAQbxYZh2QPJJF7Mjcl3oJX9G7MceOhkhASqaASHoSWRYc27p8QVPK6DWmhEgZMjp5KAC3MXyEuSwletUwUDxg+sJ8ILSKo0PS3QJRCsV0owqeLFsy4xTwVMjud5gIIeyrAFdJ3p41a/Zs1UaKggkMDsLusP3/KojK8eKiwyfCg89tvB+dfqN0bY/SMj6kwT0WzV5gOslSfTJZvECpqa7ZejgxXteIzJnBciXFT1m2GtiIwDe3ezBlf6sYAvy9yy8uH998dVHwfOSo9AAAQAElEQVRcSQAV/nyyQIX9RFIa7BtQqWqCYAO+T2sTJczNHJoEKvsD+Fj/CTN9RSy+GQUVxid2LEkcope57JwbEcX/BM9HzvgqfIIKBxKawg6JEoyZ7Q8qPqWBSuD7ROPBMkCF91dI+MTjCg+V1KO/EkBFVkyQOxmzNmrYN6ZDuFJUBwgVUBgqbri+1Gs619X2PMZTwbgROivt/hX4K+imJIGKop/dvvxZt++03i04KzxUiOgYMPBUACok8ZdxZo+fFFUyqZ5whYOK5/8FuZIEKrxpBtNm2nNAi9bq4xIgfNg2bMTTGm7hy5AfKowr0UQRQyVjB1fYOynXLCAKI812BjFyXDW/v8J1fMXcMha3SAIV3u1gygsqEk2OgEPSlY1xlFP3Vxqo7NxTET4DisEkFVprJYZKktB9BGa2ggpDC4koUPvrhuUpV3YBFbeWsJeMogsz4OIsdNW6BJcFE9RjV1h4EDA6KwCVcmve6l/FeCpkdWEarse5n+isJISKVBz0xi9WL34qty+xB4wF6rW+O7C43lvVzItG97KgDpudy+7wHvNIYmoWt5sIERLiSnKorA10saE2nU7/HOgCGzKXwyq7ERdZkED3FyoAFTc/sZtQMn+oMNcEwyfuWFh25uCmxHoqwirlTKocNeZYCU0V2q6jSYQB3qzHFM6v9BVZTmBnNztyKLSTUYc27scFFVE73zlUfIBJBpXI7yX/Wiy7gAqdxWIzqCBXeLFeL9YPli9UyLT/ig3+SsW4AJcFuIKDjCOhQlLOaCOpbBuD65hAfbU1BaIgPMAZsqcPanuesPurpJ/J1cn5w/ej1fta74Y4KxxUNHsFwkXmASogcFOM3lVvdAfnTJdxdKHCRhIHuLIFVNBSMLSA14JoycWIi1ZG4aGCKVtc8alZEkAlY0wlQBQECV9aaqL495H83gn+yYgSwxXZi7hsNMf8T1xOcLWdF1SAKPzlRJyP/xafoLJJvHdS5/rB4lqUK8s5Ox6ByegOLuzRMkLDFVPHWTB1+8tI8fvvVdw5g/ljir6o9XVdg7rOLcgePHGGT5vOCsjRGd12x3ddB/513bOJnP59f/Bg9a9BXeuq1yH/sge3+A1Td0i+adur7ujasBf25LbVu7AGK7N/CYINqOe1+Kob3tvjJyDYAFn9W9O5advX5uA+pFumzui+3b+BYuFYUIjZO+/CRpTgFucjZ2HZFyDcwDtOzt85B/X6F87Q3XbFXy+nTfeFyBldMYnK4RU4z43ij4Vn27HPQHAVG5XkfHgJixpfgcz+ojuCRrJg4q8FnlBwFvECRY9wojrhJKp/9qtAmb3+GS9nCDc6+GXXmXM6T6eU9XlS+P4eLE1LzBtB9MuIwFNxF/gKK3Z+zA4lusDwioH8AmVKm6jQrWqTrnNvdm8K+lDxnI+qRlRTUZOCQkJBpnNV12ZabaI1pnpzhp1mbtcZjc3gFHe6xrDdG9+AG4FT3HEksS/Te63LVNYnheoABBsPL38HcNLqrsAXafauQ1qBqq25bi3k2qA3eeJM70hCYrrafKmyls95zelNSm0M6sa4aU4b7QmZ04otgXmEYSV4c+fFtzffVBtuNUmR/Pc9XfuR2VhhGjhJ2323+SkTFUX9bJI+gHfLar7rlT1Xg82HDyutJyqqQz404nNfKi2mcq1d1Sz4lIv1QqnBBH9ySukdHt5FeJTyNbODs0SElqASdGfFR2L2JMGDJIYNZ1MKliSbSrlvWJeavZIbk6IxV1ozpTEAlaik+lgq93D4LybVdweGNUa8isZUaU0kfYC5A7T2FFyWJFDBHMMg2IBDPLz8odVdNjuLSpfXJZPaPtdofEWq9uEQQC+wROW6U9FspkTQTd9O0NyUtU7DHIHUpkMmdXNdUrzSGruAbeW7vwJr4rI8uBvL9Ms3uoaJBU7YiK/9QEUqGQiVYGY8fxtmvViil6R9QqWmd0pVAyiCnyeoHFAnqBwpVORit1hx5KINLgsAA7gCRAGK8FAB0pAvi51qY9IY3JTaZzVjprbnQBEmwIkLlfoQiEJmohTbCBUvq6MQKizTMNkomIPZ09X9Bx2OQmfUe7piwsgKOCvgtQCuACpt54Ksj8KVyb/p59aIuRngaHeq9Z5uDHRrVDP667XHPYnKERpBLk6Gg4lRuLA5W948EirJmvp6+WF+US8+lJJEaetNVA7csmpzgJ6KCCpJQimJjA6neAjh/fWf/xoexUorsHGCyqH0SUFFGMDPSWmhkvah8iwLDxicLmMBLeq9ZalJHA4gBPofUmMswTc1B6SPb2VzDuSA//LiXRaECsnFUh8AV+BPd9UsmqzJTTXPQwUIhJN46K8kxZgsnq8evipZ83LnzAeV3g2J5HfJCOOaeaFai6oxrrRGTfvM6F8AP8pqL4AWNrAivBJipkbMGynNKjd6mjlU2wMQbLsuRehXsmclI8V7J2xUMQnaJ/BUJC62LLPZhV7GFLz2ar1T0S1QsWb4RtekHWiQ9vny/5wssksZhktwuhNXOaDyYXOJ5jsAxdV/So8tiWfj+75YB7+koprorDCESIouUCOdDm0Aj1wnqDxmqJQ6kmICUVpkIO9CUh0XEkCUxljWBgCVgnVWcS4BKuiXRELFZQOFRNtZYmQFlAQq2F0myc356tXixUfgita/ioGKak5r7Ump4eidacdZYAZP+KxoNnxicCLCTIiX/dgCKhLYF7puPNKl2nLAcQG6gBOjNh0+/3G8UcsClfUZet1BOG0TzqHeHoJgIwIne4cKm0pZbw0iicKggiDEdCxK7CyQXUOlqlkAFamg8R5JyDs5eSr71gkqRwUVjYqihesKKxTbRbLMF1jkfrO3IkGL2kjWJnSJlDGhi+pIxV6ru6pYZwASTEHPEtGvVXfDKpiL3p7cotcihorb+8GWaMR+9vObd9PL15p50bKvGp0bJpy5glDRO3PNmlWNYUHr6uak7Vysp3d4A3P52sgGlXqkWECCpDAp1HEALpkz6K1ID2gBwes2/MnmykV0W8HPmWrWWrgEHKrSXIv7LU4JxPLVZg+ktWzdgOOCg2i685NFTW6PUGEDlLWGE0kUhAoSBS+KFEKnoB4QKswv4ePzJ6gcVieoPA6o0GmkBpkrUyVcaTq3NH0LSThPgiX6QCp0qo1ZY3AVA5Vqc0Q8FSgNPktmq3dh2AvClQRQwSwAOGMDPCfgymT5pmacxUCl0TvXLOKsAEhUY9Tszt25kN6qXG5teJMG5O27v6Khwt7B2eRzDzNuXndm+NBQImNQ/Br1qjlmgitiUq0hU80cMJFwjiceXSUVDmR469Vz6w0fAVTQTcG6Ek3DYkRZZ2aLnV24a6iAj8I6vsRxlBNU9q2jhkraobrC6+Qe1JhJl3uDSqKbIaqHAhnh2mhPnNGVZFxL9WXROJfqU5Ljq9Sp91bV9jm/wopSHzHhLHfWqQXqjq7Jl1yog4cKBvPZ6sjMy8GZgOCsjBcva+YSCNfoPajmTaO7AGnmmW6dwydIbc/J2AFjAjyDA9VaY1xUGEtbX3KIK5F52lO3HxacDwwAS/BbfvSR1hxCheM8mOH0djS7m5w9TM+f8HMy6u0hxYZvSbGESnuNSYxgkmfEdQ3BKKsmOJRkseQafPYiEs946WfA34qPoyR6Hv3nIFJgwiOKLYtC6yEaHqKYygkq+5GvGRyeIieobKoHvASFrgejjV4VrDtJHQFXSHavolXQxw37ik8xGYAK4wqiBYy7NVhhwCNAFIRKJFdwoDAcDrjSP38NXNE7d/XuvQgqcNC6NUeuwOd65Uf+qjmuoM8ke6sWsjubuv2I1vtJW4431YlUfqHJTX4KrlOi+NPCx9zrY4CKjHNNaLIZqWxUWgN7dkdGFQqgwpZ2T3qeCdr8FlBZV/UJKkcpXzPYKzCS6ASVcD3IDde6KS1c0LfSuZLUiVw/k8pDqdhu9S5q5lkMVBhXABhSoaWbs6Y5BaiAkFUBqIS5ghERKAe+n16+7c+fl5pnqnUZ46ngYi1wLPgVLjFJTiCwPDBLnqHUFW9ljrhq2agMUAm3H6wchVuFIWwBk/f2HANUwEcp1bvwfkAmNmq9/uy2aZ8Rl0UAFfBRWCGp6zBBPYTrM+YxOUHlaOVrBgfARrxOUImsB/amXLalah+gUuvdKM0LSZvhKOF6b8mclUiogNjkR0kxOs6iqjs4dyQSKkGulAzKFTqWrNidLN9c3H8k+coEUIHdsNcL0UJgRjvfeJPqXanHFW/GCTMu27SfnDwVvg3wGcyyPHjHAJVqyyG0qFq11tCZ3sAnGX1QNmK6v1Dxab42P4+CeuDF3ieC9UOdV/fLE1SOUr5msFdgpHyYfUp7nTsI2idSlpsRAxUGRZoEWq45YLtb/TtZm6AnAZ5K01nxOAlDhS31CBwCH8UergJ9XzFQkaktcEdwUbfDmT1Z3H0FLAE1e0tkCW4X1D4eDj0kvqiwVQ1bJV9gFgxKmkTlu4BKloEY/D5J3BrhKfmnU8jegOCExh2/IWAoG1KlbfYX9uRaNydk9ATNjMmDJG0sKtU1xvd9sVMVShiQPwXqDylfkzg4RWIe5hNUIiQ1CsU2LsNVap4Zg3viedDVJI3BNZkpqfaTQAXso9Ycgr+C00c2QsW1EVXsB6MrZupDc3ANXAFPBXCCbgpsK9oANqrNES6vgstBesvX90QWJ94gxq9s6NMnChXe8LEsxTGT9QJlrg+qdszhsjta1a0pjsdzsyzvBSobBy9IHvyEj8wJKkcpX5M4OEViHuYTVCI8lVKbhFgktUzGd5pkFsvwXm7MyDqS2gCcFcxEuREqwA8oyuydA1r4MWDxUHFfJ721AKSSAa7J7YvvuuO7lk3iK0Aa+AYYU2uNeWeFZdoP25FwPfD1k7of7BOFSkSClsRQ4WM/3cmNPburtAZSzV0Yxj2f3UMlnigsPr8hQHWCylHK1yQOTpGYh/kElQgVyL8UpS7LmqS0ySyW+rQxuCM+ClnBftbqXyWECoagLfuC50oMVBhXpEIDF4Yh48HoosjnN+8MZwVEAbSAm1JpTrT2lHdW1i5L1NDbQFUE6kfmDM0JKriqSqruL/ym3h72JyuASqU1KmhdIpoXwM1AvGOobCSK4l9wRfjInKBylPI1iYNTJOlDnvY6RUbBtwYXh4GcoCKajBkd1ff+mzyDr+hhADtOluQqWp3RbbO3xNTF5LM1wkyUxXofpOhOQbPJ1ATP1YBPe3INeGBTFNcpSfhUJQkmmQ4mN+D6VDQbKAVEAbHZKmu01NyVhkVVIQcGVoS6fcKrXQmTLXL7pK3PVAkcE7bVJIY13NEXcQh+H36hMA4McJfhXsONlsomfDbti/7ZA3wqmsXvyX4YmD+4jnUnfh4lmkpAuE+AVXSiDJwMzlF1J2ByyBRLEKgXTYYN1V7kLRP9l924jfUQ+WcOdiwnxXiHudvkE1SOAiquMU1SD4KHTSp1cP1gAElvco+LP4ahS0LWBgAAEABJREFUwrhCJ8kbyBVgCXAFM9RmgUpZ7XX7S2d0RZJ96X10VoArfA8YTo7ZDioiWx+IYAvqJ119JodK8raa24OdDCqy2oN7DXfcHK7s2V3VGMOf/HLIviRmIZx4xnrz84iXEL4WXy2FFiNw58GoHUwVg3P7EyT8zwcq8QrvnNqw5mXHdgCVJOeZxT5/ulARVa63bDBdOTj/7q8sUElym4VGs0A9fTqXpWZedCZPJG0sN2ZhqCBXWJJzpAt4KmZ/gUm6toYKGfRcaDbNqT1cAUuQK+isIFQU1cbkkmGuJIRKpMWXi8HBUWHApK3PhFDJxdBkeSJ8aer5Za1LBtxN3ZzA60JvfAXb+MbAHJTg0GGKE54rMs2sleR5ZD1XMZXAjshvEMLR24fJkpMtIZMOKhEmbytrk9Yu7dqOpdfmNeeztNUTVI4aKhsaZewj585lqfYb9pU5fQZciYQKyF0dRPX6wYqtanMAXMkKFSq1MWg7y7o1x6kqOKkeuYIzLjNCJSC2hHuM15K2PpNAJS9DExNeImJz+KN+JYIKvDR0R6vB/K7VO0OXlGVZ5n0U128oNxlRQsY6gRGhHV9y1Av+WhxR3GXTcM0bepsSrkiWI1Ti71Eq8xpZyOHg8Uigst1h9qMkleKHytqQFas9jy7WdlMjkwMmbr5kFFREFS562BSlTqL3aEBp8LzVv2k619gBAqJJ6QdMGEFBYdQdTA9whaUW5ukC4hfaSgIDnLdvDVaYbB9DLEAX8FREXImGVgJDwweu+ZUTebr4FihMUJ9poRJ347isAWt5+WkkDirRJXDn7GvJuMYJZQlL0Y9LigFI+rNbgIrWHgdh418eeG1GOQON8ZVwTEVkfPmOr/CTyEaX8URBtkklcXel8OUghh878VS2MEFb2Ku0Sl/m5wAVwUOe5WKSyG+/9ue1JEJLglubCCqlDnBFKvXAX+lNb4EoVWPMEyUMFdZnohojXLoxwJW0UMHUyOCamP1Lw164ARUPKiyX5UaohMPyMQZIpt2ALN09+y35r2D52yTxmESeiqh8Dx4B8aPg1j9P085dY+0RBaGimxPwToAodWuKPZzluhNOZb8OfnjjrCIT/SaBSiCUEnmSZAcujuI6Sbgi54Ggsp353h0k0upRQiX7YfajLSvRNfpdTq45y9FfSQUVoqiRpgmhEhh27C6zWGq3nEVnTPwV1g8WhgqumOL6K8UW2CP0VzJ5KpjeWIHtNrgsbWeJaSXZyl04gnlj0D5yuNdGAxT4M2bordB4JQn+J1hJMGBbg8H5xO9V4S4y3F5n6qx2u6Pr0fnTVu+CJMXxlnUJHJdfDkD2DagTdSttftZE+/jOma1m5uaydIcY7Boq25rgYFfe44fK9uU/GqjkVbK4UviGFQ0VueQ6K8Vqz5ff6XBQiZzEkBYqspfVmGyUTb0zN4crEkcRQAVzC7rOCuUK81e2hoqbbL9k4prEJb0PXLEGKwzU8ysNx8dXRMOIkxh3H11Ez08GYPDivRmM8aBEo7xExlc0pFgEFTLliNatPbkFpxC2cQFpxIkUSnvjhp2oP+eXHg6rBAL1garDM4k824hz9nyU9dhiypVjg0o4rBVvowIP6S7s+0ajv+vyM0ElS6G5KWVvWGRdbFGJzLTtoh9M5pISxuDH96XgHm/sCwo+nPTpBUhYg2XFmBX0YdGYS/UxH7QvaDZKwkW66MJc8JPuaIV9YgwtpP8kNoAfP7+kpvfM/kI3J2yYAJZG1pcUQSunRi8yUiIY8IJXeyY+JiGSEpinGdUnJrxlIaPsAps6Ky6Pq31QsTJQyn3gdG98g7ErlmaNZA7lzl80d8dvrNM9aPw1Rt6dwFVg7QVOQHQ+MW5iFtuSxFDE26XdWchdQ4XfM7wdcz7bXE58pR+/8oKKMFCct9cS+F7oGImaRUqouCN8ym0w4g37stqeS+pAac0CI4wRKmSxJs9fgU/kCmIGiYIOTVqo8LYbisLuNSicXwFeBJXILsFtmqjYm4lUEqgITyYqrBJQzEAA5o54RZEW4i5URStZKdsVdWgP7ifzl/3ZvW7OcJkclgQB/twpVALUjHusvNHGpOoq6SJkO4XKdo3qeKCyHYS2gMo2V7qfKtuddgGVHQFmI1c2vqFLW3gqiu72M9TawAyjv9TMsyL4K/4RxsxZYcvK4ngwQBFwBYO9SJQYT4XnSjThKFRwrWKtPTbscygfB7zGQCUXrsSYrY2w8f0rJiAviNJHKrAaLpNU7LgqdREV7u2odSWo21q31p44syejixed0X2pPuGXAXYTRNLhxflCJYYokc+g7I1EYIyMTnMQZsYm5OdoK7K0qPD18sYn5lhZzm07kMScdlq7mlTbHfJ4lBdUmE2PiRnkwhUWQo8Hj9CSpoVKsc7lcWpLFatlX5I8XX6oMGcFXQe2Uj3OtweugGOBZisLVKhRMFBQGrBKNyeganMQD5XsXElkWJOET1LCQ3w+AqgASzyoeBF40gNZaY1azqJ/9uDM7+H2VZoTqdqXa4P1yD1utgqB9G6gEiZK2G7wtwwXWsb6Zy8Wyet/n1BJ8tvI0qRDQEU0Qz4vqIhMayJluUlHrsAt3+6GJUEL2yEhhCKhhf7Kxjf0JB0IvofQTafYIMM3XYtvlmp2e3AJdgpYEkgLxgfn0ZxJxRZsW4Nl3ZoibHioiGCQyJAV6hhoaZnjpjnFRcNY6N6tDXHywVTNPS2MtzO+KZ7Smi92vQ5iK8ADR6n15QpZjU3RRnr3yho/HVy8ssYPNfNC1kZkvHjNkdQeOC5otXmfAP9kLMnrutZV7Ydo2PSwG1TWOoQodOckQ/j2Wv8CE5wcPJFQSWtqRCWzz+hbkOBUE15XqhpLWtVZbtIulJqK4nJSVX0WqMiRkfZkUAn/yvWWBK8hqSzFGiood2yYBVwBhBj9JRKF5wo/ktj1V4otFEAFxPLeZ4cKvkejNQGW1I2x0ZlXtHUqF1IbsUltkzf3Y4OKm8bRS73FNghRynZRHWjGvDO6d2bPOpNnTedWqU8kdegKiFK1CVQ0G2MtKH6MQOqXjwSnTf70e2YiO6XQlaHRR5ETdNvGx7f2A5UtTH+OijRf8XvuASrhHyaq6oy2O3elvgBxObnc+11DJdzbhl/yk+P480kyxFYEFVkhC0cqBSICmFq35SwCeVxKus1m1Lv5waizgpEP3ZwY9jkfrs8CFd8rKs3ygmgBoddCqiuM+a24cnRQKZlS2cKRWjhRFP4keQc6i8bgpjd71p0+bfZWleaMuCylrqT0lHLfHfeFFY7jBSqtUtUo19rwyc+Ez/G61nUb6usLPixeWD6whiPZOcF0n+OHSrilyQJPJe05RNZ5PCQSlpn8WnKzyVlu0i6UF1Qi7/SOoJKl+yuAE1YCG5wasJ7JjfUGqGBXWMXSO3M2357lBOPR4naCUeEMbdUYMa5k7P6SvAwrbtYy+gk/L6s9vTUCVfQuG2eVhSvHDJVaa9zqXfTGN93RdXN4C1whfVzVvlSmPWC1fqHqlGsjOobYJsLFOtFBqRrAFV9ilVyh4qvY2BwBiBMyRM2bH8NKIN942GBNIvlIvN3Uf/Cb7biS1lgn2Z9ZrZh7wd+UXUNFSgBLn/K6YSkkCGzmcvEJS0sLlXBvVepgvugQaSAULmdjrYrvwnqiotGZN80p2HFMWU9mOWgOn1qYruvl+isYrm925yA2vwQ8DPhtkgmSgTfTtU0JtBB6B8taR2v1QdV6D62VHLUyYEzQMpcWm6VM14Zi2MxN7GirxkTr39SHd+3ZM+vsRWN0X+leFowzqTnjZuP6hPBAp6SimuiaxCxCFZ+2ZOP18hfua2BiouCNKJL5jPXIqZQRi7WI4Ze72QneQUEPXvTOUZe80dpElhO/f3iHjG018kKSVlE6cW3sBJW0UOG9ij1DJXKocXytiu+CL62L1hzi+lokkwpdTQtsH1uukXLFHWRMPhXwe9q11hC4AijCGkgOlXCnRwRUOPsF77/gr6Cwpz5sy+JHwmRssVnK9EFFaWrt8ej8KTglrckTfXBbshaEJeCXqEPimqjDMFTwG4YTpMvGbq4sUJHCpmdTKIV51TiGLX41xv1DJblxj9l/YxsIN8uIhzTB0fn/5tJW5dAQtVS1lExcG/MVun/AJKiOI4RKfKR9p1CJtJvbVHggrYvSquoOcIWt0gh0wcT13vpaPZwS4aKFOi7lutPunvGjtpJDJYAWUU89S+hLZmXTZFaMLhiaDqxPnPC27q0t8eeGSMalTdDtcyHNZRoOTM5nl1z2FmdEonC2e/dQSeCjrGHvT3V8DFAJ33c55EYkbCFJ9kzb9mL+m6Pdkz5VqCS/pOx2M4sh8BmFEEI2GM0dQEVOMNQ49e3goMKugsTJrXm1OUI3BfvBkCvAD0ysgqF7dxUWhQTYG+0JoRHNZp8WKmu0CF6Ew40HLTVYMRR2i6WFSqpKy9R++HOjeenZTCDcCCTuxEgJUKRa7+EFIl34FbT4BbV22v3lNRUvtYzgGnExFVcJ1o3fJ1TCt3vj/drOTGU0aJme5WQHjb65uZ3D3qGS5ESzP/9ZHn6h4jujkiFhC6iIjpJf8CDa6ICD0uye4yIobA1gurFOQMnPjsRTVRsD4Ap8MuiyOZ4AqiQBfHJKm/pYRNfChtUG8m6JjLuonJjhyxvHCIiO5abm9R2X1HOx2CjDCz7srNRrNVNVrUbDrtd71TqABChigMieRd2VEq0sUAnU6tqkRt0FZo9k2tklc0OHfYUkAgn/rz1BJaGJ2AiV+EIClckaiei3omLzuvxUhT9KqMSf62OBipxyAHG+UOFt1i6ggvnqtfYU120s1wciqLhdYXSpRzxhozMHAUXA+2EdYswTCkOF58r6xLaaoy57i1bhJ/YaieonLTyyQMVN8M59j/VcqRjAEk3rAEiaTQc2qmCgyXnW1yxhN6XoM8d5QYV/atY4Kflzl3H78AOFJZpaHxSMExwlVBLah4SWKomxirdgon/tjit7hcp+4ihpLym5spewQX5DH2n99wwVWcCVlE1BYHTKFpkzoRiqMQGXBSMrGFPhocI6cNw+NLo6vSQ3KpoNLoveGrnDXkOZ7SNSKEa2vVSpUPgduK5/URZh0b3YBVTYwr0gcD5Karumd/SmDYINfn5J9PK966zGabuP0kGFHEWpS/7uEb5RyX6orH2vo4dKQuOQr70K7xbvtaQ69Hb1kOqK0h/ioFARnfF2Rj97CRsU66DsLqYSDxU5B64IjI5iEGcFVGgBS8BfQWclDBU3BuC5I7wa7QlLu7IRKu6shciTTJ9fS2YDRhWfAeUNPZuCHlBMKvuM3V8ogIpSbbGICLCkWGlh4H1tfAXXuwuo+BoMQ7ISsY8c6v4S1v+RQSWhZYjZf7tiw92wgWYTWcOpjr51DWTZRywBVPYDmJ02joPIZ0RS9Ymlhw0/ZItZavJn6CHZsnH4hxqX1R7ggXgearfaHJTrDh29PLAAABAASURBVMaWmdigLwY//C18UzfGQBf8V4AuEeDM6fkRtWeRSlWzXLMqagdU1bpMemvCVDemTFrDYeL354Vp3rF8oAiT2NBzYkEUvvsrMsC+wXszosU9SqJHLOaJwyBKTFwqGUiiV5ZMch+TWIZdWJu0Fmnr/VOVlv260pcf3W599/QElXyhsutYS2D9lTVXuCpyt9OnzqW/8tsghYx/A6g0u3McrcQm2zOosAUcfWihc+OBSYAWtTHAf7GFhCNGZicIkCZqISmhwqZ5YxYyboizycQvO502owG/6mjOUEl1H9m7SAKrJ3ri3HFodBiYuP4/HagESk6yz9ZKUk7uV3SCSj43bw9QyWdUWGLYhOevhF3sFAqbIXqUWmtYt6buglpRUAmgBcP14OvAbwEqgKWq7qAHw09qCQ+VztpCUkKFKdQjl667SfwcJQDJLqAS+wTF7yB64tywfKyH9OlBJWG9SdmsU/Kf53UtJ6jkcNv2CZUUXMkMFdmfIh53i1jUNqFCa92js8KWPwG6xECFX3aeAQlLqGg2oIU5K8EwPnf+mVrItlAJSTTN4nFDZTMVBFChc2U2n8anChUpGVekfdmo7BdygkqiG7bPmyoEzHazWDJ3i8lRsUEpdq5TOpXbUqEBaAF/BdDCusIQEjFoWceB6MhjrTkEAWDYTFKXMTFrvKdqIaL2nDJxISbfjFBaqPCQEAIjibI+NWmfLP5fJIiSZPQdifProemZcUp9H7e6uryU/FhHzpUMOkElVPs7v9lbz47MDBWZ6/jKvf2xBbtwJWBcYR48FcBDDFfYsihrtBSaOFkS89uzigoPvtpuYFsSqCTiyiOHSkS9hUeUefMcIxuMzCexj42jHBAq+7ewCQ+XFzaOjysnqBwCKrlxJbEUL9EkTv3jlwLMq/25Ux1xwa6SUW0OwGUBqGBu441cCdQDzojEWAtmohQN6g0M4d18nsmgspEriqJF6rFAJaJLLVyOh5MAV9iTktRlPBBUDmVbkxw0F6IkKW3P136CyiEUiJ/nzZXIiTIYk2DXzgdXcuMKyyPpCYjS7M7B22BcEaElkBBM5gZGw59QAilEi+ZKeGrIhhaSGCrxXHn0UAkdyxuBtvnJkui0HlrIOo/kEXZ/HciqZjr0FkTZ+Nv9XnsCqKS9qZGT12K0n7t7REoJiUIxWuWSxVRU2kzwL+yHkQotfv+05YvuV1qjySegxLn3sA0qqw5TqWavc7mXu6BC0ZIVEyQV4HJM+LNYtiq1XlW14RO2S5UOL/iGCWsgt/aT8npTQ2XH55N+iHNKw7ReRS1ZLConlaomgh82krRVkU04Nvuz6/M5CqVt3CeoHBwqkkx6/MvV7jFARSq2tfZUN2deijCXKzxUeK6UKmuuAFEYVJCUiBatPqhpDlxggC4+ruT0AD92qKTWVlCRi3HrAe+q6vyLRZ6g8miUtnGfoLIfqMhViwnzAXsaSrWJVBtJJUcuWaBisQU6HFTgjbJd0fqN9qyqD2AjgJMAVwo1IrnaBblrSmK2MbnJnDDC1GoXuAJ0AcbAdpgrCXNzbW4/jxwqqUe1pTR2ewYJd111L+d/nT/PE1QegdI2phNUDguVcvuy0X9QrctjgYrSJucALkjNVhujjVxBqDCusD8BGMQJK7QYVxAeABUUQ0tyqGSJwZygsp/6EV5XsVElCwH0AoMITlB5BCITmpgSNKYTVPKFCh8t4MV3f4FkqQkqKm1j9Kw9fl5tLySl5yYRUZogYVqOlENjIwPasWozKZUukAOgAoyJiKZQVcrR4ru5AC1MPGOAK0z8mGPJG6oUk+RRpLTteddQ4es2yXFT3y/RcSPTQhfTNobUEl0XNGl4VSqX25WK28Lddi74rehadm30T1CJUKd/ztQdXDD1+tFyhksm0fe8+DJ3IXu0PC4NV6nUc5aRcuy1Bv2V3VuAYLvu3IOnYo6eNJ3bbn8FcpwLULe/jJSofNH97TrnqdRxLpns4TWcD27jucGGZS/5fRx7FSnheWJtDFYB4a13xpdM8Cd8ybfnJPdL1G5FEtWbsD5Ttue0x0p7v0TH5evNZxPSlp9SQjvjXAwGS9BweIkt3G3ngt+KriXt87tr+7Nre3gM8nd/JXhDEXktMW7sbnVwLAckyg4rkLD7i/NmMGUWDtjFXiAMYvOKSNGIU9YFnlCx0o5U2jf3QtFiKpa7GHUvV22tOUZPpaoPeIEfw8T3jLFuLhwDxuTWhjfgbe3BcJNy+FXrH7un4vPyE7zRf6qeCqvqoEdy8lSOX3wHtK+yEnR/JekW2/UF7KQLK4vyiqlw+wBLcDoIbGPnD0Yg+O6sg3V/0RFcbBwX2ZDB+sM524gN7BNbw4ODCuzD5Ova4uCHQZSI+mHrpnBzKUAIGFSSoIsIrnlBN3X7SdntnBZyaY1d6vJTSnRdWNXYIJPYHNG1JIy9bVwjR6Rdl/8YlTpQn1bHBpWDQUsAFf/IrqBwdUVeGxfvCuhQb+IyTfKhNh0w7jirETwJkLeO5Fo4r4Vf+IsXf+384AXmw+F6xq7868r44CGapZ/gLThTHXKnEZmHJuFzJzpWWqOW9lqSXGMmiO5A+zTijwUq+3wRP0HlWKFSMhAqYFh5Y/pYoCJ5wfMAV8JQ8biSDiqBFVzWdBHcO/7B5ld7LNfWKlVNJt47SfvGzf+WNyXRw9KCKzwK6jltd5ZIO+i28v1rn93dWfY5VPf7rs/nGOrkBJXjhIrvrfxxQkXysn1gZ5SbhSUKKpQrqaESSADjoiXl/eWvnYcKD5skEgIpptVFPfAnqORgHPdpQNPW/67P5xjqRGhMT1DZqvy8oIJLwWNiYP77xwUVqaBLFC2MK3lBha8ElkWfJdaMuNeiB2DHAee0RjCJJ3Tq/orXqfsrrJ3YNNGxTlA5LFR8kxwpQshruG4LPRhROYLjHhgqXDUWayZ2f2E2F0W100JFFFsKLEu8Ub5zywkqPhXqRIk9Cd8tS/uIpW2HOT3Xh3rekzybx2wf9lk/B5Owsh5JIzu2RpMJKtRBKdfByPY+Maiwyqw2RwAVnEt/KKj4AvgJRnm5V5oYKiyyUqqaQpiJ2tgJKpmfzWO2D/usn4NJWFmPpJEdW6PJApWNRHnsUCH1We2is3IkUOFjIbwqaocJwyTJ6wRxgkrdlk5QyfxsHrN92Gf9HEzCynokjezYGk0WqJR0m/grdBWsTxUqkkwSGwNUVGNyDN1fonrgvRYWh99iLgt/LxL1s5+gkvnZPGb7sM/6OZh8f3gxw0d08btuHEn2SSKl0pVLljshEUP0bp230EcJOChCeKSESurzrMYOWArX2xZGh2aZK6mW1upz81d6TMnRkgI2OXk2edXzLqTQqTCBkwzeMrqIVnLtHCpFd+Iqg/3WxjcwVvsRGTG3HrYeUZZB6W1mggXlDl+b+VXKMUOFEsXkMYBPERnIRO1mUo9kx1BJW43bGB0y5opwBSygbgwwvUo8VJKj5XOGiszl1lzfu4CROlaobP3ksmeTbShs2cpDW6fjV/qaP0El13JyeNp9Q4EtkqFEt8EUhvu7DgWVtE1tS6ODXKFrZjTMUbXeSwKVJGhhixZ/hlDhG6pbyeE332ODSuj52vq3bCOtt/05a+dQkUVvN0esJDDIq5wcnnzmppB5FSQ/PE6Ydxd+PxqohC9WWG9pjQ7XtJilrujd5FCJR8vnDBU54KNE6jihwsFvax6wH8pe+Org1mk7+3Pcx/2EPJUkRn/XlZvEHG942mlABWwZyTesOsCVqLUdjwIqCaslL6MDHptqjIAWCbkSA5V0XEkJlSPEjORfTmZDUz9OqISU6FrEz6kUgtOejfVjlOhh939/gkrmCk1yDkmg4jb0NVHIilUk0JJ2lNdeYirJayY/o2MAErT2OGMn2P6hcliuSKmIUno0UNn66eZ/hSMX3KIeT+/LoXSCyhFBJf6/rnDp32oHk1axhCLHCZVwJQi/zw8qktIEKlSbA/BakveDBcRnA9s1VGRulPABuZKuq0cIj7pAh4EK3+pS7R/4LUtKne+JfZJKZgpOUNmq/O3OYcOTX+nShUOI1ZNp6sMjh4qvKvxDdHx1kpfRwcTMShPn6zCupEXLnqEib7uM8WGIUnp8UEl3dVGTImRvsHW+5/bp6QSVTFDJXo7wfLiZKPxYL34JDd/+gszEUpmI39OdTJceKmnfpvkLZNvhLzfUTxZjVGyUVKta75W1josKrQeY2W7mypZDjY8ssM8qP8CzRHWbKBumCCrpYLOLZ38NzvRdWHwdQqNyCzl1hW2vE1RSlpbCaG6CCk8U4qBwizIlgYpc7eYFFTnN2zR/dWSb81HYvxLVT+Y3XKgx4Aq6LAwtiBPY+NygEnlDE9ZzsvzKxwuVYJvM8KSvubJf8/XoJLaHJ6ikLC0XqCBRmLl3e2P8c303QqVcbpXJDjoIV4CXyw2iPQ4pDlxs+PLj6icDVGQvrEqWYPHHV9jGZwgVlyLcNtRSRqhwux0xVLhZ92kf+UDbXnPlpDT1xukElcSl5XU+vKHHgV4YRIkkykaoKNVGXlCJO2cxV2IqJ77eMnoqMvOTyu1qc1CuO2y0MbopueUKeyRQYUTxBVGyQcW/2xFDhWuKabkSbtgnrmTTY4RKqL/leCQCg+/h95YgZERxvRaRBRcs+FgotmXFkCpDqTzAkWMKXYcqi6dCbJD3WMYYPv56DwWVtWi1AFRqrWHGSZGpdGxQibxBMfW8cZXG0E+OGip8q0vFFVG9sbtzcKuS6toPfg6PEyrHVYMRZyXHv/V7Pgq/zG1yqDCuAFQqtV7ZWpXMSwYVJbDaY/ruL7yKGMMn+VkS2E5+j3KDirfwZUm3kSuYf/MzhIprBGnaNFb520El6iePAypSSq6IoCJxbt9xmppj1SOEyjHfYDmBp8L7KEmMfvR44qolVfoVa1k7+7E4/ijX2iC3EywDVBQuEWw8VMIRoMDlb66rvKCCCWxoDhu23sxnCBUlNPzJ/Vd6qAh+chioxBj9+F8lhMHG8rc4+uetxwkVmRt3dGwKv8IHH362WDq19Wx4cSqoEFX6au8KoCIPPhRUMxeorB/FYmOjpxK8HSkHFufZ/UVXWUa0ADZYiOWzgkoYJ/H1LI6diPSYoCIl5kqS8h8dVw56qo8QKseg+IYY+J786XZ5kemNqe2FABKS0pGLXb050xpTXIvFVRbDJLjGmOtN9bCt9/S/EISNThbYyDTQmiU/mAg2kRQJfr9jqETeGlpjKSx+zKxGoSEo6rghlxtRO/C3IPxNPs9awjYZ/Zx6sdjtTmM9/MGf2jKvy8xXcto5oXnqBJWttNHI+l4VKRhol5dN0nnlBBUgCkgp22SDEWUvUPHtnIe/mC9UUMAMnA65xUiwJFAROiu791TYLeAt3RY4SQeVDeIr/xihkh0AMt/HeJTdJOFrP8ShT1DZSikMMReW5zN6ZYcKC8tvU2YGqETun7H57gIqUsk/O65hAAAGxUlEQVTAafZslbNPBio+ongGbgucRCZf2RYn8d+I8JPuWUsLFV4KN7N4m1ZKK5ndr8AZ7tTabCk6kvMQ53aCylZKboiZAcKwfI5QgQIlxVvUa79QidwhUdUJ+g12BBWp2AIqbBFfOebuL0YUORBHSYmTtFBZ93p5/WCPCyrStrMjw1o7iEevQ3DlBJWcFPHMh6Y3hndLCxXeeLnfuIapwSkfwMTAJvKqU9dYfFwkF6hQFWhiYwyxBAItuUAlR08lBjbsy2KlDSqUWizATnLzRAXSE2StjyJQTjDI+ByJnqzo9pkyyJGFLoHbkeq4B9HeuXKCSh6Kfv4DvV6ltfedL1TobnuFSvhfxwwVHG0M/kog4+Qjggr7EzaAKOFKoFxJR5RPCiopj6JwQ+e3Ps8AV45ZrJb2crYnqOR0wyLsQgUclB5LwcJ36eYEFfhc42qnClxvpOFLXW/7hQrOjnykngpf7WGchD2VrYmyFVTC/90eQvuBipTNWZFC/srxo2WPJ3mCSk53K2wUcKxXDkY/Fir5JotMCJUIS3fkUPG48kg9FdlbS4rl8mLzSxAqAU/lc4PKev80g7LkbcfdypyDLvNj8I5bRwSV44fwMdwqt3m5kdveNkOHBQp3eW0UGxewU6hs8dtEwuFMIeuQHDPxsAHrXNY6ZCIL3UBjDZ+HgooIJDihlf2LnDyliDj5YyKWZIDKbrvFAnCNbGy7eH6VjKPC/Oe/izPMV7uuz5OnkvNN8gZ69YgPcTiorHd+jFAR1XNOUJGoHWFcIcnz6caxQQVT7/BvwbyPEqW0a8ufoOI7RC7l8H/u4mzzrefdHGIXUCkLdOja3PVNonEUzvRnAQlva9JDZb245COEivC4eUHFc4MqepfnyrFBRaoQZ4XvV/l8oCL7+5d2bARz5srR4mRfSgOVpJX1WULFNQpeLi8l29yRrFBRWqATVKLFpesAljCX5digomgWcIVf6IFcVKH+yUNF4kzNHqDCjphLXCSvch6zTt1fGeQ2R667iX2/0chuhMp6z00eSRA2fFEpE0oGri53IGWq7fy6v3gBTsBlAbSQ1QRqHXdZgT1CBU6ASfFWsiGLRIVexbbzVDbOtD8qqIi+zx4M5x890T4R/uJWx1Ie1VDjvIF9gkrmu8L7EFICW5xkHx9+YqHCDwk7QWULqEgeV0q6jRQJjArbs6eCmCEG9DODSswjxriSS1FJ9lGyDRT2Nf4jzj75aKCS/SE/fsmcy4wZgvkYRviGpaWLr4RNAXmFy6JPTuMElTTtTfbegqu6ozYGFc32RlukSXefE1TQX5FxivgJKqHWuPNC+M7GrY7I/+Sx+Ct56wSVbbV+nXHTA/sMt5StE8x3iNhxw2DF1iuynDyVlO1N5t8liwbUJ0BFaw73CRW++4tV2slTCd+pjG2Jf6w2t4c8sjEGn4KjT2yck07dXyHlZTTzMsoJg/OblVP56RtTPo1SbAfTQSUJkDC/lit/zGPdVVWLVlqQlKom5vJKCsu0gfqjhMRJYj3u+yVuutyLy8HPct+VcoLKZw8VXjjgGFXWOkxFPVr8PiKxAsmos8Q4OUHl89Djvl8nqERVygkqnz1UfMZ6B/c07fmcoPI56XHfrxNUoirlBJXPHio+JbjXmdrYCSon+fT/t3dGywnCQBTtAPosTisFtC+tg/7/D7ZTOzEoa/dK1hC5M+cRw5pNctgIkna+KJUYnW4gldN9X+cH6SmVcFJB24HHAygSzaSd/g/vRCbtfFEqMTrduFJB70oKVvH03uly//tdrKXi/tZXCTp54PFAqZAeaeeLUonR6QZSGXOrK6VCqUx5kZofaeeLUonR6cZS4fbX7cVds4iPaQceD5QK6ZF2vlRSCTV58CDIL3n5L1mxdiwXr44iXzv8Y3qAV+6aeMZgPU7yHMM6v2g8KGh+xXFCHoI/NjT5Koph4Lyj64AQpxSPD6USG1AqeVY6KJVrKBVKZcr4Y+NppfL2/nlBVZ2pR3Nq5/osQdjUX1Wzr7ddwrRHiKruHKqPgPH47VuwafeD/OQxCHWNEeq8oeJpBaTjd22H0RxJRD62B4cmX61AqPVHar/ZHRya430GKhX/OmgxGuvrQWtjm6O5uhGqFlVxAPbnS7ayxb1O+ALx+QyMLMMIdd5Q8RQC0vHwlMxKEpFlsXLo10+7CltTAaOVd/LbX2PKuknIzLriRvtnZttfU5CKZrEQ40enpPfME4kAmC9rqaDzkVKhVCgVSoVSmRJzlgo6Oa2/PKXyt+Ul3ApMqTyHVFC4/ZUYd/188Ph1lVKhVCgVSoVSSYEZSOUbEDe61r7BlskAAAAASUVORK5CYII="}}], "tool_call_id": "call_YPL167UBBYnDfNjebMDWuAKk", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": "**Preparing for rendering**\n\nIt looks okay, but I need to render it in 1080p. I might need to check the CPU memory, too. I should use a preview scale of 1.0 and output the files to either data/final_exports or previews v7 in 1080p. I’m planning to render the frames at that resolution. Also, I need to make sure that the playback resolution matches the settings. This could take a while!", "finish_reason": "tool_calls", "reasoning_content": "**Preparing for rendering**\n\nIt looks okay, but I need to render it in 1080p. I might need to check the CPU memory, too. I should use a preview scale of 1.0 and output the files to either data/final_exports or previews v7 in 1080p. I’m planning to render the frames at that resolution. Also, I need to make sure that the playback resolution matches the settings. This could take a while!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE33Cvb6US42TsCiztidBX53cYWSrTtaObx0zBNn3Epoc3x3xwQIJgOcF7VYfK5qlTeHVPBUQ68jty22hiqBu1IDWQOxM68pvJPgonia-5TXcRprzPZK8AEJy5KQb6FyEwL2bSDCbOYFNI9dO2UeBrdcj36qk3fJXsDdyki-3OY2oTopJ0YHzd3Bplyepxlvm3bx96a3ir8ld0u6IUjgeDL9TxqSCsJjF5ZFsWO5LIcG6UkHoiKXlz1fnNwZTMcAW0zJvWblrBI0iPVgTAaeB15Qg5QvNfO9dAzD40zsOTNzEh9u9SQl-BSRxRaCLhBwrrmxDzau5RzXU71q9_0Z68FZ7zN_iVYiGocHAs3YoqCxmoDiE1JZGWfgyd0LtV3xZcHykrJch15w2SB2DKA3ad0ySDpM8VQqFDjNrSsFiBReTwcFMe_nJBHQ2hFKEWQAzjQeDKdE_oUBrjYeyb4oR9ep5-ZK1-0jxPOzazTuH-dWqm3W9avJmHRHRvzQZ_lWkMtJPDbI1tDsbdbWX7wcOvg3z8Xvx-0O5zeT8i0Ri5QOHUWxS3FzRPA7XwtEmt8z5Og6cQyt9NgOeX2fFLq6HOa04Wpua7He9zvrwRg6Gvz9IWD_b0OPgrBEcOA4zgcquM1SlpcscNnzoLTCEyf_igtBiMD0SvrznFVKGjRQ1wHHfOf6n9msSu6212-9AXZY7-eFcz3LZWReeFEQpTG_8DbB5Yk6NwtOfDIx_kHW0bvMgmhbmht8pJ6kXSQCNXwuNSd1eHHrkTULmtaYKbCuaW9sH0zDGHHctBLpvvvnh7tWUZuJcMmuBQRfcqxVSvNcqWONY2DX50ZZhcfrleAeEy-9LZRwvm0IlEgSniYFrng_b7dGXdAzhHq8IeM4-O6nGg7PZV5hk0pa7s_UP811QKBHS1EkKNutTiBrObbsIJS80wAYJrA2JOJ46MUl_jHSd3kbTUTxIlG8a1GLJ0ULN7QNbsAlSBosKIT1xOcjNAruquGvV-iTqHdfA9WZFjX68m0pJqOjqXP316gqqqwAqegMQ8hJ0iGweq-CIwE8tW5z9BmRMgHwekKr6aDRrUQL1FEahwGcijcxWSaadd8aRQTpSHHxIdDJZJkn6mIINdbCiQEg0avSZQwFKcdOwr7aC9aleU2zH_REGOSgWwhR3CJoE-w==", "id": "rs_0dc9f371a6d55e3f016a137dbf95b08191bfa0e35267f0abcc", "summary": [{"type": "summary_text", "text": "**Preparing for rendering**\n\nIt looks okay, but I need to render it in 1080p. I might need to check the CPU memory, too. I should use a preview scale of 1.0 and output the files to either data/final_exports or previews v7 in 1080p. I’m planning to render the frames at that resolution. Also, I need to make sure that the playback resolution matches the settings. This could take a while!"}]}], "tool_calls": [{"id": "call_zF0n6xBbiJy769f09fo2cRFc", "call_id": "call_zF0n6xBbiJy769f09fo2cRFc", "response_item_id": "fc_0dc9f371a6d55e3f016a137dc245c88191bab9bf57a9ead54b", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nfrom pathlib import Path\\nfrom math import ceil\\nfrom autoshorts.audio.voiceover import build_truetrace_final_voiceover\\nfrom autoshorts.audio.tts_plan import build_default_truetrace_tts_plan\\nfrom autoshorts.audio.edge_tts_adapter import EdgeTTSRequest, synthesize_edge_tts\\nfrom autoshorts.audio.probe import probe_media_duration_seconds\\nfrom autoshorts.audio.subtitles import build_final_motion_subtitle_track\\nfrom autoshorts.audio.final_preview import build_audio_caption_preview_plan, render_audio_caption_preview\\nfrom autoshorts.rendering.final_video_plan import build_truetrace_weird_email_final_video_plan\\nfrom autoshorts.rendering.scene_backgrounds import build_chatgpt_image_scene_background_plan\\nfrom autoshorts.rendering.motion_renderer import build_motion_render_plan, render_motion_preview\\ncandidate_id='truetrace-ai-automation-quiet-rot-38s'\\noutput_dir=Path('data/final_exports/truetrace-final-motion-v7-1080')/candidate_id\\nvoiceover=build_truetrace_final_voiceover(candidate_id)\\nfinal_plan=build_truetrace_weird_email_final_video_plan(voiceover)\\nbg_plan=build_chatgpt_image_scene_background_plan(final_plan, output_dir='data/generated_backgrounds/truetrace-weird-email-v1')\\nbackground_paths={asset.scene_id: asset.output_path for asset in bg_plan.assets}\\nmotion=render_motion_preview(build_motion_render_plan(final_plan, output_dir=output_dir, preview_scale=1.0, background_paths=background_paths))\\nif motion.returncode: raise SystemExit(motion.stderr)\\nvoice=synthesize_edge_tts(EdgeTTSRequest(text=voiceover.text, tts_plan=build_default_truetrace_tts_plan(), output_path=str(output_dir/'voice.mp3')))\\naudio_duration=probe_media_duration_seconds(voice.output_path)\\nsubtitles=build_final_motion_subtitle_track(voiceover.text, total_duration_seconds=ceil(audio_duration))\\nfinal=render_audio_caption_preview(build_audio_caption_preview_plan(video_path=motion.output_path,audio_path=voice.output_path,subtitle_track=subtitles,output_path=output_dir/'final-motion-audio-caption-1080.mp4',duration_mode='trim_to_audio'))\\nif final.returncode: raise SystemExit(final.stderr)\\nprint('final', final.output_path)\\nprint('frames', len(motion.frame_paths))\\nprint('cues', len(subtitles.cues))\\nprint('style', subtitles.style.name, subtitles.style.font_size, subtitles.style.margin_v)\\nprint('audio_duration', f'{audio_duration:.3f}')\\nPY\\nffprobe -v error -show_entries stream=codec_type,codec_name,width,height,duration -of default=noprint_wrappers=1 data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\\nsha256sum data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\",\"timeout\":600,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"final data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\\nframes 1110\\ncues 26\\nstyle truetrace_final_motion_compact 72 320\\naudio_duration 36.864\\ncodec_name=h264\\ncodec_type=video\\nwidth=1080\\nheight=1920\\nduration=36.833333\\ncodec_name=aac\\ncodec_type=audio\\nduration=36.864000\\n2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_zF0n6xBbiJy769f09fo2cRFc", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3-gC6VbhAbS-uUw4tQS6T8PLMX9GAZ9fIuBBUjWhw4hlGw3zb_Zc7oY3suiQ9Y9neWpV5DJFLAy-S8KEik3F3L-jm_sOS_96YqRxOLcwJXo4Bw6rt2UshRf3l1OACWqXQglPkegj_s1CQqz3dYqq-a-bbDrozB9P5VE55E8Skl1ahBiqDItCGykfUVQCnwukdWqvW2FNxKocwKU9cIVVMedCldKOQmpOvhTO9IitF8NTyyhsnKB5-JIRzIZ3cbcItRAiktLskHPPZp1lNc2dj5B7L7PWQx2ob1e49rbHy5U10ctPG58kByxV3P8VKwS3ymryW0NVQ7T07ajFFh37lx49butRqEhNSAcUepV9LbyaLbUrouxnNAg4_5W5tiMLFUn6aNUeBbweyhgrHLnBAYrsBI0qY5ClpZW7heSJ7_GOvBI8EE85GOa19JzrXmO6ENsEcWXTmZ9WKuC-vmVu1XkqJuygXTaG6Agnx7LDq53dJj54u06jmK3mvQAXUkDoZ8_afp6FkZkuUTiBoqjqMrBXDdZ_jXlweFUcYaGjvROUmiu-oBlAKh7-6Y9ayaNpVf-zKs7WPq98OPtgfHw6UfeYlxHuuDaPf5GgYWRKOyyQe3mQh9rtCZYVtxxBgao1PFsTwv_DjFcFj1fVqwQGaBgUDyoFISXChVBuCHiwTuX-8mbVqLyo1JAPDjwCWLp1Qrwh7ISFSWYgkIkXNcllSCHXdDE5nXSZnsVuKtcbhrSHDiiWeM8NXvmXOlDWwjNMmZEs9D53JmjHcBGw_Air9ZvMCFs35sTPLQ4KRddN7609gYVTAXf1ZQaQWYScH8_KFo-kT_OW0ZwS3jyFKgGCdL5uLVOnYKhRt_Lt5SlbbLC_6po9oWuzzm8_P8ZC3VTveZF-22dl12Mff-_S0Z7Tf7Js0ipJPVMTzQMbTDDLvnRKtwr5UO2dhEzU5zp1hXygl8Ka4zHVK0F44S_cTlcIXrnrg==", "id": "rs_0dc9f371a6d55e3f016a137f9f9dbc8191be0c3b97f86d7015", "summary": []}], "tool_calls": [{"id": "call_6T4ud8HPCOvUpz2w4ogwBFhP", "call_id": "call_6T4ud8HPCOvUpz2w4ogwBFhP", "response_item_id": "fc_0dc9f371a6d55e3f016a137fa029b081919cc1fd9d981770cb", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"rm -rf /tmp/truetrace_final_1080_v7 && mkdir -p /tmp/truetrace_final_1080_v7 && ffmpeg -y -i data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4 -vf \\\"select='eq(n,650)'\\\" -vsync 0 /tmp/truetrace_final_1080_v7/three_way.png >/dev/null 2>&1 && file /tmp/truetrace_final_1080_v7/three_way.png\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"/tmp/truetrace_final_1080_v7/three_way.png: PNG image data, 1080 x 1920, 8-bit/color RGB, non-interlaced\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_6T4ud8HPCOvUpz2w4ogwBFhP", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_cHiFDCCBSSkUc9hyhbnFGCsg", "call_id": "call_cHiFDCCBSSkUc9hyhbnFGCsg", "response_item_id": "fc_0dc9f371a6d55e3f016a137fad8c308191b4448b3717e548c3", "type": "function", "function": {"name": "vision_analyze", "arguments": "{\"image_url\":\"/tmp/truetrace_final_1080_v7/three_way.png\",\"question\":\"Final 1080 QA frame check: mobile readability, subtitle placement, clipping, and whether the 3-way split remains clear in the 1080 export.\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "vision_analyze", "content": [{"type": "text", "text": "Image loaded into your context — you can see it natively now. Use your built-in vision to answer the user.\n\nQuestion: Final 1080 QA frame check: mobile readability, subtitle placement, clipping, and whether the 3-way split remains clear in the 1080 export."}, {"type": "image_url", "image_url": {"url": 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"}}], "tool_call_id": "call_cHiFDCCBSSkUc9hyhbnFGCsg", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": "**Updating tests and documentation**\n\nI need to run full tests and patch the documentation. It looks like the 1080 QA is okay, but I wonder if the subtitles are still too large. I think I should run those tests. And maybe I need to check if the git status includes the documentation updates for version 7/1080. It seems like that could be important to make sure everything's in sync!", "finish_reason": "tool_calls", "reasoning_content": "**Updating tests and documentation**\n\nI need to run full tests and patch the documentation. It looks like the 1080 QA is okay, but I wonder if the subtitles are still too large. I think I should run those tests. And maybe I need to check if the git status includes the documentation updates for version 7/1080. It seems like that could be important to make sure everything's in sync!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3-5pVjtgQOdyfJNGJgKO4aHGQ8dxfq9AcQ5QhSRsufvyesqASPEdfpfxfqK-4AGgxXqIprNIrSn_0mtNP392J0Dev8PyBgwffZ1WEx4pkVT-8r9necS0RL5SBc7TymXaxdabnFCPYJpp4FEhh2ortX1C60pT4MR-WR1GQn-d8i4ztt4Li3SApPbBzUu3gs0j8uslctH__vVQaNEZ_KZmxSXPIcQhkx-ZnNeKG2_-abBTpQm_bM5oPh9eCQwZWd26n2tPbQDdb80J57aQjv62mPdKUWaTs7bfynPAo0HYCO7tRk95IN_r2fOG89cKnjvb4cWuXGmV0982tJwV0VHA5bcahRrytNIS07dW9a-K8LARgPOfYnFbC1TJ-qIg0QBXOhNdwc0cWLYEjEVDpLAKRLeIid4aVbV0GVKIaZVPCNLbxUU_f6Jli1bCwNZpVV2Yw1eCdOl0ahWlP7Uv1mp0I-C2FWmyqM2UYoHGolwlVyZXV-f2X7layjwzxYI0plrKksU0Ctw6TNEWycUUrapkamzcftyzW4-y-Ru5rYojfguwuRnQaNKEFRXTsjAmkn7yWg2uGclcnWPm9JTtkzuu2nnRFxufHp_xTiEup3lPF-hr1JVwnYb_2NnzfcGRFy5mF6F3CSelSGf1xuD92KxS95RCIVw-5IuGlj8i9FUS1A9Ldg0a6aVig3N27LhvLLlpKXQN9urHna-ZZ6vzk_6cU4en2OMcGlg0rYACUzdzWP7rkTWakzUD4HfisOf2Bk5XZez3gTVWf_o2N2M7FYvp1XKJPp_EKqVETtCdrwScotmmTv2NUpo53Plt0oljryO01n9miLY--L64AYxodjGSd-uY1HhjJs5cKXvOBQhCqwaXd2Gomxyc6_V0wIRtY07dPtfOU87Mx72DZtOtic9lc8OuD66NJYn63N_pEjzL3sRg-jrCULXi58ojzjFBlnTTRN30kshbR_G5aHabFqFpyi8q4fytOHaPqz90GWoNqqkcdgfbGm4j_ChLbRX-_17tlxg02sHWlA0FvX-gjyNqwK0M1k6r2USXZVWgQcu3Jb5Dx8K4CFMx7Ha_iOf0_aL2NLAVlwgLuK_jy0sxVbJ-Gt6cxKpaoKu5CBQyK1cRxFXQQMgAr2HpSvUwT4SWrjR4Qn7", "id": "rs_0dc9f371a6d55e3f016a137fb7045081918466a5c6daf35214", "summary": [{"type": "summary_text", "text": "**Updating tests and documentation**\n\nI need to run full tests and patch the documentation. It looks like the 1080 QA is okay, but I wonder if the subtitles are still too large. I think I should run those tests. And maybe I need to check if the git status includes the documentation updates for version 7/1080. It seems like that could be important to make sure everything's in sync!"}]}], "tool_calls": [{"id": "call_eGPqHiiMvNGw3kMNLjQIN6uz", "call_id": "call_eGPqHiiMvNGw3kMNLjQIN6uz", "response_item_id": "fc_0dc9f371a6d55e3f016a137fb947ec8191a1360acb79049777", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"## V7 update\\n\\nThe subtitle layer now has a final-motion compact style via `build_final_motion_subtitle_track()`:\\n\\n```text\\n1-4 word semantic cues\\nphrase-boundary aware splitting\\n72px ASS font\\n320px bottom margin at 1080x1920 PlayRes\\n```\\n\\nThis prevents awkward cross-clause chunks such as `ANYTHING DECIDE THREE` and gives the three-way split diagram more breathing room.\\n\\nCurrent 540p review artifact:\\n\\n```text\\ndata/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\n```\\n\\nCurrent 1080x1920 export artifact:\\n\\n```text\\ndata/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\\n```\\n\\nThe 1080 three-way split frame was visually checked for mobile readability, subtitle placement, and clipping.\",\"old_string\":\"These media files remain ignored by Git.\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\\n@@ -82,4 +82,29 @@\\n data/generated_backgrounds/truetrace-weird-email-v1/\\n ```\\n \\n-These media files remain ignored by Git.\\n+## V7 update\\n+\\n+The subtitle layer now has a final-motion compact style via `build_final_motion_subtitle_track()`:\\n+\\n+```text\\n+1-4 word semantic cues\\n+phrase-boundary aware splitting\\n+72px ASS font\\n+320px bottom margin at 1080x1920 PlayRes\\n+```\\n+\\n+This prevents awkward cross-clause chunks such as `ANYTHING DECIDE THREE` and gives the three-way split diagram more breathing room.\\n+\\n+Current 540p review artifact:\\n+\\n+```text\\n+data/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\n+```\\n+\\n+Current 1080x1920 export artifact:\\n+\\n+```text\\n+data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\\n+```\\n+\\n+The 1080 three-way split frame was visually checked for mobile readability, subtitle placement, and clipping.\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .md files\"}}", "tool_call_id": "call_eGPqHiiMvNGw3kMNLjQIN6uz", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_L3fWwT4HEdOYRdGCR8fLJUXc", "call_id": "call_L3fWwT4HEdOYRdGCR8fLJUXc", "response_item_id": "fc_0dc9f371a6d55e3f016a137fc290808191bfe8d072206c8c65", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"Subtitle/TTS strategy is documented in `docs/subtitle_tts_strategy.md`: use deterministic Hormozi-inspired renderer-owned captions; final-motion videos use compact phrase-boundary subtitle cues; start TTS with EdgeTTS English baseline; A/B test NVIDIA Magpie later only after script/retention quality is proven.\",\"old_string\":\"Subtitle/TTS strategy is documented in `docs/subtitle_tts_strategy.md`: use deterministic Hormozi-inspired renderer-owned captions; start TTS with EdgeTTS English baseline; A/B test NVIDIA Magpie later only after script/retention quality is proven.\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\\n@@ -83,7 +83,7 @@\\n \\n `autoshorts.demo.truetrace_preview_packages.build_top_truetrace_preview_packages()` turns the top three concepts into local German approval timing previews and side-effect-free approval/manual-upload packages. It writes PNG scene cards and MP4 timing previews under the selected output directory, then prepares `ContentPreviewApprovalPackage` and `ManualPostingPack` artifacts for each candidate. Each preview artifact also now carries a deterministic English subtitle cue track and the phase-1 EdgeTTS provider plan, so audio/caption decisions travel with the candidate before any real TTS call happens.\\n \\n-Subtitle/TTS strategy is documented in `docs/subtitle_tts_strategy.md`: use deterministic Hormozi-inspired renderer-owned captions; start TTS with EdgeTTS English baseline; A/B test NVIDIA Magpie later; use Whisper for alignment/QA, not voice generation.\\n+Subtitle/TTS strategy is documented in `docs/subtitle_tts_strategy.md`: use deterministic Hormozi-inspired renderer-owned captions; final-motion videos use compact phrase-boundary subtitle cues; start TTS with EdgeTTS English baseline; A/B test NVIDIA Magpie later only after script/retention quality is proven.\\n \\n The first public-facing audio/caption pilot now uses the accessible `weird email` framing: top card, scene captions, subtitles, and voiceover are derived from the final voiceover source instead of mixing old approval-card text with new spoken copy.\\n \\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .md files\"}}", "tool_call_id": "call_L3fWwT4HEdOYRdGCR8fLJUXc", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_rvL1agXzu6Ycl66zGvWUc0Cn", "call_id": "call_rvL1agXzu6Ycl66zGvWUc0Cn", "response_item_id": "fc_0dc9f371a6d55e3f016a137fca71688191a18a34945c6d0782", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/ -q\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"........................................................................ [ 42%]\\n........................................................................ [ 85%]\\n......................... [100%]\\n169 passed in 32.51s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_rvL1agXzu6Ycl66zGvWUc0Cn", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3_xoWvREWHuDB6QGU8NKlZ64T-LyonTz2q_HCuUpLyldbcdmkBG4DTE2FPTYK8TCn9TT_3ELPKtWa1XP68yILUI8kvhCEfHkDBNo1wpfBAIrq6KjB2GObd4gp_ImI8GJ8XQ-x4850SARoSUXPGtoW_xR11Bo4z4uNzAU-ZWLFr2DjoJkdaxhg0Gt6JzuaunCpOETdMedf-h2J6AkSz8mwG_4yrulDK_nQeFHzKTcjd0CnJdGqdz3th18LH9JiSSMA_a443lfvEAm1neQizIVTSWF4hWNy2D_pafHOKLV51LzmsJ1oYMFPJf9CppKPKFomVY8In4J_efBtFuSxkYzWmavQw-D4nWp-7DQlPBat-ZTfx6On4UYQKnVlaZT-L6FT9C1Cb9zsHCTFFgbke2XrxlCnuBK6ooNlSGaoMJ3MgsddSpyIQJDTdBl7wf-vm5h06zl4umF4VzB2K4FVi7pQbTuuORbWZ2ccszn0Rc1O50phI0OsJWM3_hl0iokNy44fWpknHUWmfcQ9bcmIONrJpMD0tPqhhsdSONiYp26ND5wjYwP7q1SQp5Umj9HNm7Nuck3eFf7wz3cTqGAKMJb_yeoRRD_Rt95WKbPgTVlpS-rpfnYnUK26d5KyswE7t0eKTNggSWTHOVXjM2GqqbmTrkvXC89HcZC_FigmyD7HJvZQzSb-0m3N5R9Cg7rziYCCBW17iXyPDreCqC_YmaY83QlQbN_wBFQl1T1m2DwKgoWW0Y5hkusEdWDBcvLbiW3iwRgJD-UkF9LW1FAzCviFcYsQYsDWc1rKT-lzTaQ5m4jtXxWwsptaUnAi2jPRriWRr4l2GzPfh209I---hZPIEajEYSxpHMVOi6WQbmYVjU3uhrFIu-OOEIJs-bZagW3WUppfWGEBMcNWU8m8AS0Zf5cJ3-gw6XmTVzE-JRR3BX4wlbQXRKT5BC2mouIWQPzzBaPLLSLIsQmuH-s4ihiVzShFQs1tehO5OZbY2OCtxQO4w=", "id": "rs_0dc9f371a6d55e3f016a137fefe8d88191bd594553b7a5c6c6", "summary": []}], "tool_calls": [{"id": "call_jZMvHEtCDm3sIIwodIS70vrC", "call_id": "call_jZMvHEtCDm3sIIwodIS70vrC", "response_item_id": "fc_0dc9f371a6d55e3f016a137ff1adb481919f47c194ce5c3c3e", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"git status --short && git check-ignore -v data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4 data/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4 || true && git add autoshorts/audio/subtitles.py autoshorts/audio/final_preview.py tests/test_audio_caption_preview.py README.md docs/final_motion_prototype.md && git commit -m \\\"feat: compact final motion subtitles\\\" && git status --short && git log --oneline -5\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"M README.md\\n M autoshorts/audio/final_preview.py\\n M autoshorts/audio/subtitles.py\\n M docs/final_motion_prototype.md\\n M tests/test_audio_caption_preview.py\\n?? data/\\n.gitignore:22:*.mp4\\tdata/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\\n.gitignore:20:data/previews/\\tdata/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\\n[feat/core-approval-quality-gates a061884] feat: compact final motion subtitles\\n 5 files changed, 112 insertions(+), 9 deletions(-)\\n?? data/\\na061884 feat: compact final motion subtitles\\ndb200ae feat: add scene-specific motion backgrounds\\n14310f9 feat: add TrueTrace final motion prototype\\n7375311 feat: make TrueTrace pilot beginner friendly\\nb9b6423 feat: align TrueTrace voiceover previews\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_jZMvHEtCDm3sIIwodIS70vrC", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": "**Investigating untracked data**\n\nI’m noticing some untracked data. It seems there are generated background PNG files being ignored, but I’m not sure why the directory is showing untracked. Running `git status` indicates there are files that might not be ignored, like .ass files? I might need to inspect or search through the files to understand better. Instead of using the terminal find command, I'll use the search_files tool as suggested. Let's clarify this!", "finish_reason": "tool_calls", "reasoning_content": "**Investigating untracked data**\n\nI’m noticing some untracked data. It seems there are generated background PNG files being ignored, but I’m not sure why the directory is showing untracked. Running `git status` indicates there are files that might not be ignored, like .ass files? I might need to inspect or search through the files to understand better. Instead of using the terminal find command, I'll use the search_files tool as suggested. Let's clarify this!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE3_86Q0wIirZd1gSrnpgrhjtNcX5MkSFJENWBQLcnDC9GYXuf0olgba9pMQftSg7KfjemF-hFzGQ2CCQLFmkUU7SR2CastDJdldC9OJ29sWWxPjsOG-an-OZKL8Mwhki8L3faXYBcUghk-LjL_OwRrLt4V_wywy9TDs9u1Y327jMuYxJpVRsfsCJ2ICtfSlNJ7xoFFsuP5hs0eBAjXYSKRkw8MKb4FXkdHQXcuYLyAtoPGpQgSJ2vssAAFx0Gt-tkpJizpsuwerVH4-OZU2WBw5LSlomqVVySC3tVwQTsAXl1eItpGJv64BPRHhkQ12g4gBuE1Cpi_fpO0Vk31cRC_sQu5zBilKbVB9Xh1fRsfzsmDw5PrY8I5vsTX0sndta_MNrAgcLx3UBwAWt1NSPSo95SYsSbMw0S6SfngTgUs6mk9vok0DfI3UnuPNwqfJcKHjLcYxgkLAH04Sz5eAGQj8Fr3QOiJmjXpk8OQhzY3S3Va5_iYkZazX3NVWPb1j9SqCss6nOWbAayK3-Runhh-Ub0rPIB-xVCMg6JtdCmmaEEPpQ0dUs3_aoFh-xs-gCKFB2qnK1M9P51zVxsCeaxUVJjR-gr737lYZ1hFhtlULyx5m_zBX_yKy8KQcSoy0jKudTMW45mWhgkjZrhQpWwEXHZ_VRTsJ2Y50x3xvNJMJWzlH2jRd2FdqmjE3aCn0tIhgeAEEXeQ9rKxooh4l5O7N4z1qawxiBt_Bcns24TD1L9fmtNP0WPct4qiqYoGfzeZnQWaPcO2_uadmhui-q-jEFjFDhYViRvTm26EvLWVFznkxufHBdzAevSPwPYnR56O5JjRwD--IfdNpVR3E8EQUGEz62xvKOdsnlBg-aHa3VMKMUmxZnqNNslkGFs1Awp0kD6yLrkY-_rgGN8r_LpsqbhCXaEnWMfrx2a6a6a_nlc8b0kxWIFut45u5xsFBjh9kDVz8ytCJqY-NGkrrM_glvMaESTebTdKoSe0cZteyAPVEh1zeNTiUF_WhkYopIiawM1VkeeZJ4MyzDfItJpbWpCgpGXdzaXc6yl0ySADS9PqqRDVRoP58hx2btGwAMCxMHLoO5i5RxdMbZADzc5IzPP_ldKTe4SKoZZcrFVEg9I98iIZQY9G8Ak3VV9s_q8tbUTVhSIeLzX7cBoxU4iIcBZpNz9NytzPZUoFl_3pmZE0fHbjL7_iGe92o-SX-ZvIM0mnb_VCw8EmtVc_TeLGwnUg==", "id": "rs_0dc9f371a6d55e3f016a137ff928a88191ace21b0aef47d721", "summary": [{"type": "summary_text", "text": "**Investigating untracked data**\n\nI’m noticing some untracked data. It seems there are generated background PNG files being ignored, but I’m not sure why the directory is showing untracked. Running `git status` indicates there are files that might not be ignored, like .ass files? I might need to inspect or search through the files to understand better. Instead of using the terminal find command, I'll use the search_files tool as suggested. Let's clarify this!"}]}], "tool_calls": [{"id": "call_zcezlZl67zhb2bms96TpqnHt", "call_id": "call_zcezlZl67zhb2bms96TpqnHt", "response_item_id": "fc_0dc9f371a6d55e3f016a137ffcbefc8191962f5061dc8c87c4", "type": "function", "function": {"name": "search_files", "arguments": "{\"target\":\"files\",\"pattern\":\"*\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data\",\"limit\":100}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "search_files", "content": "{\"total_count\": 100, \"files\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.ass\", 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I think I’ll need to check the ignore list to see if that's the case. I want to ensure that I'm not overlooking anything important in the process. The representative aspect has me wondering whether I'm considering all relevant files. I need to clarify this to keep everything organized!", "finish_reason": "tool_calls", "reasoning_content": "**Checking for untracked data**\n\nI’m questioning if untracked data like files with extensions .ass, .mp3, and .txt is being ignored in my checks. I think I’ll need to check the ignore list to see if that's the case. I want to ensure that I'm not overlooking anything important in the process. The representative aspect has me wondering whether I'm considering all relevant files. I need to clarify this to keep everything organized!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE4AF62EM8jEFMAPMW1clMeKypfr9T4mOuH7fn57xDIMtO7SnKPE_Nm9m_FFcBW6pc0ORmQK6H16FRfXFPMCTTwFpGOuLN0RTqBth8-RyKBzgUqabBqpFeOdE6fMBYK8C-p0VMLrSDjQwrRFQ84b4jv1VGJCnbJwqteiHMK-ByfKiQHHrWojPSwZarjc_lY6gonRijGhOD-qYKputfs6JSqhU_IjXYuRX1U7QoFr4bPLBVUvVK3C15Ig2pRvQYeAbAnjWcoxtFiK7x4Bw2hAdUyJ8xOorwXFTlLETjRqfbSqsY-R_WZ4QCOqLqwuSlK66d7mS7ExO9accEQjkoglXI3jJ3uhg1PxxLgAcd9S4lClnukXUnUFLF2oBwBCmhZ6vUEK3M6pDWiOv5gdX3rJygjEUhiJW2vzq3IEMETqnB52N6x2E8_8P0enQnHiDplevD9BrlwlMHZ1yS6E-E980WC0TY4QXHQDsKh3b1Da5_49ertqMCCBPuM7h8b6uJeyi11PMmcdgDNcO8-_0aVd4aqJdrkQ7vUsPLp3g4O927J-oBuO8ndk3mYleEkclqavWdROG9F7CGCX2a-gSovLN2lU-wGHxviDGGdIVisTzG2OgMAdp3C09YWKYD7jJrzQ1P0IuTD84104R14rSH_26jwEdc1c7cZBubGd4nlF0kblCCwZP39k4SasfDmn4LlmLlIYv_wzM8a498PQM0r2VB9l7p4GUSVDlPrVNr_M9FeMmO_8CTGaOc_WF1WEn2R41b7HZWp7qML1hqYoXmZbSQhaATmDlmBWoIbkZ-JnkY9Nyx3ocwFK_8O6Jdh5cKVkE0PFINL2Q7iNQXQJ2LqxbyHL2TSMtxnrVZ7iTZzDRGQYutl-Hk1T8Wr6LOWF1lhtTlUU106MqtmhA7lFzaZILeUu6qyO_JcUJP-J_S2JlbsskCSN_Lz50kS0gOVXdb7BEChWK81lO87UXzNVImfRe_RUMIL-xce9Y2CmvFxokouVj6D2VwWXp7BlfC23W3JMPLXbW", "id": "rs_0dc9f371a6d55e3f016a138003fa908191abfe639ebfdac19d", "summary": [{"type": "summary_text", "text": "**Checking for untracked data**\n\nI’m questioning if untracked data like files with extensions .ass, .mp3, and .txt is being ignored in my checks. I think I’ll need to check the ignore list to see if that's the case. I want to ensure that I'm not overlooking anything important in the process. The representative aspect has me wondering whether I'm considering all relevant files. I need to clarify this to keep everything organized!"}]}], "tool_calls": [{"id": "call_kPz3gMHQxctfoxak7tDJHIeO", "call_id": "call_kPz3gMHQxctfoxak7tDJHIeO", "response_item_id": "fc_0dc9f371a6d55e3f016a138005c52481918722c0c7b24cd7f6", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"git check-ignore -v data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.ass data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/voice.mp3 data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/frames.txt || true\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \".gitignore:26:*.mp3\\tdata/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/voice.mp3\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_kPz3gMHQxctfoxak7tDJHIeO", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE4AMqdEnNJP_ZCQIshU3B_68KQTZTNo3KBzEaC-xbstM5L9RUJd2Npd0dmeIGIJZFgYJRiTSOgvmsJxkt1_3PLbuwbUwBURV-WrPiYfLCizIqgFzKegWelrqP7wqAv1iYtobdksaPGPXQFJ8c80BmhDBeVosx5I12oZ4hL-mfqaaL-quSvtq1rpz3s1dP_-QSVK8F-V59lGoPMetBNQRoPjf7DuvKlrfyCoIG5Oiv7u0AI0F5qoW_OV_sHhcyeUZur-QamScXdvX4TM6mGqMhwLsQntAy28PAZvMfZ6J3sIBMGAhJn-CsZMydL3Y6qgBoon28NrO13ag56_hG2M8s6fdx9-ClTDnCm1PdZVfNQPPYQYREAQG0C_YoXr6q-wKmyrfeeKwCnBU74CwsI3O64wJSnGRK8swHCba8Byf13yP5Txn1K3tJbGtO9w7aa0E4XJTkWR-56ERcr1G26HoSBSeyu3kzavlKuZb8XzSDDBWFEliUPaOFqlu0Ja2Pq4a175HcF2lZASbueIREaft3CUD587rS_IgT-offJFp9A8lT1FUj_M0omDN_ngEfeQFk_8mboRPe8gC8otssIcnjNKlJfukhEGgnpRd_Z8PA50lZHUrPGw90wODYTwTVEAkSL0ACeIQAavfEGaeHGrSWK6MoBwSZNXkQQ074VBZ6Oama4fFQsMLSsvHC7JKAx3X1E4YZk20umC_3cHIvEsAy_f3PuoApAynNnfqYq-7DX3ctnTEizOGcnOYZyIxIuU6e9CaArHs4R4HR7tREZqxkODq1GnehYCtzvKOEaBvSdXPEynjv_jcTkEs6Ghq0zvq18t5zKAdxV2kDaBdiNeooCi9eJctHIqrhH2SuVwfGhLDBnAwB_7QXDLtCXC1Z0sgAs0tPNaWWhAruejUoIRp_joNAjkC2LuxakMfGbiNFCq0_o0USwJsigj4xLPs9GMkTN9syehgbvcz_jOEJ4bDXgqhT8hM2pRwB78X_zMscygKjsE=", "id": "rs_0dc9f371a6d55e3f016a13800b6de481918ef4b4fd8ea7332d", "summary": []}], "tool_calls": [{"id": "call_q2CwJuQPi4w35179tLKCXauo", "call_id": "call_q2CwJuQPi4w35179tLKCXauo", "response_item_id": "fc_0dc9f371a6d55e3f016a13800c2ba48191844e63c45caf1c3f", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\":80,\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/.gitignore\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "read_file", "content": "{\"content\": \" 1|# Secrets / local config\\n 2|.env\\n 3|.env.*\\n 4|*.token\\n 5|*secret*\\n 6|\\n 7|# Python\\n 8|__pycache__/\\n 9|*.py[cod]\\n 10|.pytest_cache/\\n 11|.ruff_cache/\\n 12|.mypy_cache/\\n 13|.venv/\\n 14|venv/\\n 15|\\n 16|# Generated media and runtime data\\n 17|data/local_motion_renders/\\n 18|data/imported_ai_clips/\\n 19|data/generated/\\n 20|data/previews/\\n 21|outputs/\\n 22|*.mp4\\n 23|*.mov\\n 24|*.webm\\n 25|*.wav\\n 26|*.mp3\\n 27|*.png\\n 28|*.jpg\\n 29|*.jpeg\\n 30|*.webp\\n 31|\\n 32|# OS/editor\\n 33|.DS_Store\\n 34|.vscode/\\n 35|.idea/\\n 36|\", \"total_lines\": 35, \"file_size\": 364, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_q2CwJuQPi4w35179tLKCXauo", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": "**Considering data exports and configuration**\n\nI’m thinking about whether to add the data/final_exports/ directory and the frames.txt file. It seems like using *.ass might not be the best choice, so maybe I should just stick to text format. Also, should I include tests? I’m feeling a bit unsure about changing the .gitignore for this; it doesn’t seem like a TDD approach. I guess a simple configuration patch is worth considering too. Let’s see where this goes!", "finish_reason": "tool_calls", "reasoning_content": "**Considering data exports and configuration**\n\nI’m thinking about whether to add the data/final_exports/ directory and the frames.txt file. It seems like using *.ass might not be the best choice, so maybe I should just stick to text format. Also, should I include tests? I’m feeling a bit unsure about changing the .gitignore for this; it doesn’t seem like a TDD approach. I guess a simple configuration patch is worth considering too. Let’s see where this goes!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE4AVs0Ls0NU9rNtvPzsV8QgDG5bic_h-DZ2ZCuQcaXfZSJQLFmZJsQM3esFIJEA0UKuhoEHx_wGGTbX-4HPmrZMTYa3g4_MUcpkTJcVk55PVeomAC9YymLuFu2dE52c8wvvYD1H-53DoSUMflpj9Lb4kkggXZ2tPmP7MjkHV9uVW2f6n5d_IARfH7JZ9SghOOuo8kUtQmN9OyCA7PN58KHU1ySRMO0ure5nuiQTNa-_zGkSvfFxleFyTBnmaKyYyzBMRS5tnznd1sbRebusTQc7Cr1ldhrduLG1En4zfl99LUA-eAxynvtUeVpP5IPlWM3CM_fSYZqswg4mE4mV1BJeXusCKSLdrTnrfQf1MnQ_S6EEAU0l56ohA-FB4M5joBenDs3MdJWumfnvFfIouq8Xyb4MAZTX7WtfdNT8mslHtc0Gch5k9wjtM7KCWKgznxpPEcK0lEvOC1H77HjqigAApla7QLwWnWmAmuXJQOI4XkF4IkQ4KMiT64jD-p2AwkOlLJyiSLCSzZYzqJ2pJ9nH4ki3nxeYgdZWvHi-vwYECMIi2gvXx47NCZQ5BoYrjPVEKQi_cPJplKQizdgqRqTDDIl8pTMh1XMRmxcpQxZgHNbomSgcNGVVZe1Jwe_jwWDGy-TN_JczkeM1SYBtJih4Bmm8Fg1QWHSBJjf8Se_m_NiPi4wseUP5jJY9_qK27iAkCYvYZebOBEZGPP-T9J0Cp-C-lWmq2T2bYopqutDaKOZWN3bxfy_S_yMoxZOaOlb-_PnjAFM_zzquHfJvJswgoRWc6kiOme6C7qq8eWTV-u34ZvkYpz1d7TbME5r7eccR03JnYo5vAhI7GNNUDbBGqZDFR4JsLdYX2arHod384Zfw29k-Iy82lBSn-1Bpwyf77nrA7cnnw4i6HoTNYnGzZ_pM7kQvgExmr-3CHw8vh9_DOVAHBSP0gk1oxd9hyqamimj5Vw9NlhjVIAByKU1-o77DHdTlt41-6KsvTmyEPnHhjnWOYwDyhFsb78IwpRHbGSjfQ9YnSKVvKLTOEgXtZzESM5wJd7mVm8W5h-r6QTv8pnUAtrH1nlcu-UChQZIezYkcGrTk4bGhEY7dO_-lXPQ==", "id": "rs_0dc9f371a6d55e3f016a138012fedc8191b042ce51c185f982", "summary": [{"type": "summary_text", "text": "**Considering data exports and configuration**\n\nI’m thinking about whether to add the data/final_exports/ directory and the frames.txt file. It seems like using *.ass might not be the best choice, so maybe I should just stick to text format. Also, should I include tests? I’m feeling a bit unsure about changing the .gitignore for this; it doesn’t seem like a TDD approach. I guess a simple configuration patch is worth considering too. Let’s see where this goes!"}]}], "tool_calls": [{"id": "call_PAatW9gXW8oxbdnRy6uUlVVy", "call_id": "call_PAatW9gXW8oxbdnRy6uUlVVy", "response_item_id": "fc_0dc9f371a6d55e3f016a13801576188191a398430178eb577d", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"data/previews/\\ndata/final_exports/\\noutputs/\",\"old_string\":\"data/previews/\\noutputs/\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/.gitignore\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/.gitignore\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/.gitignore\\n@@ -18,6 +18,7 @@\\n data/imported_ai_clips/\\n data/generated/\\n data/previews/\\n+data/final_exports/\\n outputs/\\n *.mp4\\n *.mov\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/.gitignore\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for files\"}}", "tool_call_id": "call_PAatW9gXW8oxbdnRy6uUlVVy", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_Vwfj5xbbLJNrS2DH7QSTFa48", "call_id": "call_Vwfj5xbbLJNrS2DH7QSTFa48", "response_item_id": "fc_0dc9f371a6d55e3f016a13801a2ea48191b32f562df79e95f4", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"git status --short && git add .gitignore && git commit --amend --no-edit && git status --short && git log --oneline -5\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"M .gitignore\\n[feat/core-approval-quality-gates 033334c] feat: compact final motion subtitles\\n Date: Mon May 25 00:47:16 2026 +0200\\n 6 files changed, 113 insertions(+), 9 deletions(-)\\n033334c feat: compact final motion subtitles\\ndb200ae feat: add scene-specific motion backgrounds\\n14310f9 feat: add TrueTrace final motion prototype\\n7375311 feat: make TrueTrace pilot beginner friendly\\nb9b6423 feat: align TrueTrace voiceover previews\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_Vwfj5xbbLJNrS2DH7QSTFa48", "timestamp": "2026-05-25T00:48:19.126288"} {"role": "assistant", "content": "Erledigt, Sir.\n\n## Polishing-Slice abgeschlossen\n\nNeuer Commit:\n\n```text\n033334c feat: compact final motion subtitles\n```\n\n## Was verbessert wurde\n\n### 1. Compact Final-Motion Subtitles\n\nIch habe eine neue Subtitle-Variante gebaut:\n\n```python\nbuild_final_motion_subtitle_track()\n```\n\nEigenschaften:\n\n```text\n1–4 word cues\nphrase-boundary aware\nsmaller ASS font: 72px\nhigher bottom margin: 320px\nrenderer-owned\nside-effect-free\n```\n\nVorher gab es unschöne mechanische Chunks wie:\n\n```text\nANYTHING DECIDE THREE\n```\n\nDas ist grammatikalisch ungefähr so elegant wie ein Toaster im Ballett.\n\nJetzt werden Satz-/Phrasengrenzen respektiert, z. B.:\n\n```text\nBEFORE YOU\nAUTOMATE ANYTHING\n```\n\nstatt Wörter aus zwei Gedanken zusammenzukleben.\n\n---\n\n### 2. Subtitle/Layout-Konflikt reduziert\n\nBei der kritischen Szene:\n\n```text\nNormal → Go through\nUnclear → Review\nWeird/Risky → Stop\n```\n\nhabe ich geprüft:\n\n```text\nSubtitle konkurriert weniger mit Diagramm\nDiagramm bleibt lesbar\nkeine kritische Clipping-Probleme\nMobile readability ok\n```\n\n---\n\n### 3. 1080x1920 Export erzeugt\n\nNicht nur Preview — ich habe jetzt auch einen echten Full-HD Vertical Export gebaut:\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\n\n## Technische Daten\n\n```text\nResolution: 1080x1920\nVideo: h264\nAudio: aac\nVideo duration: 36.833s\nAudio duration: 36.864s\nFrames: 1110\nSubtitle cues: 26\n```\n\nSHA256:\n\n```text\n2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b\n```\n\n---\n\n## 4. Review Preview bleibt auch verfügbar\n\n540p Review-Version:\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\n\nSHA256:\n\n```text\n0a3cc3129cd09d4b2594f23ef2d35faf5b7d04e1e1f94c55a35b50d1f8034616\n```\n\n---\n\n## 5. Tests\n\nFull Suite:\n\n```text\n169 passed in 32.51s\n```\n\n## Aktueller Commit-Verlauf\n\n```text\n033334c feat: compact final motion subtitles\ndb200ae feat: add scene-specific motion backgrounds\n14310f9 feat: add TrueTrace final motion prototype\n7375311 feat: make TrueTrace pilot beginner friendly\nb9b6423 feat: align TrueTrace voiceover previews\n```\n\n## Einschätzung\n\nDer Clip ist jetzt kein bloßer technischer Prototyp mehr, sondern ein **brauchbarer First-Public-Candidate**:\n\n- beginner-friendly Thema\n- konkretes „weird email“-Problem\n- Voiceover/Subtitles/Top Text aus einer Linie\n- szenenspezifische ChatGPT Image Backgrounds\n- renderer-owned Texte und Pfeile\n- Mechanism Reveal statt Slideshow\n- 1080x1920 Export vorhanden\n\nNoch nicht perfekt, aber inzwischen klar genug, dass man ihn sinnvoll beurteilen kann — und nicht nur freundlich danebensteht, während die Maschine dekorativ dampft.", "reasoning": "**Finalizing media attachments**\n\nI need to finalize the media with a path of 1080, possibly attaching it. I should mention the tests that were conducted since “mach das” is done. Also, it looks like I need to include the commit hash for the changes made. I’ll make sure everything is in order before finalizing this. Let’s ensure that all necessary details are accounted for!", "finish_reason": "stop", "reasoning_content": "**Finalizing media attachments**\n\nI need to finalize the media with a path of 1080, possibly attaching it. I should mention the tests that were conducted since “mach das” is done. Also, it looks like I need to include the commit hash for the changes made. I’ll make sure everything is in order before finalizing this. Let’s ensure that all necessary details are accounted for!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE4AhecMuoGb8HMbHp3nHfFubSN6pycnEkYjjL6MLuAz5B1lbQ-AneeOAQBsrIEqD2C_Sk6NZQzgBumCpVzd7G4OpKuVt0ZTmD93Q97sWyM4n47ANSLYe1HGWlViXPr5RNkOzi3wFN3aDFZzpIitlFy0qOf6DLzkDfx6Lt_BFh0Yo6CW-PgyfrJm_D6cwD4Kv_nGNWyAn_RSh-WXDdJ_1RGdxPKK76VyBIM-MFyL3a8E77JSbX_fBUAjM8uY8b2I3OQldp1asVmqOL0S8xCcqMeK50ZTLRaieoWX5wpuCmZ0QDPVm0uodEn1ZwjBTCUUtgENc17qOPceyKojAf4NId7aije3Hp7JvzqrPphHUsaQycDXkVL3mNZrFkjODnXRQarf1FPOcwH6J9rZCljZyEHdmnv7HlpGVcez1c_EN_5jcRsdAor9q3qgXoId3J-M3S6E-amw1FNLm7ze2Tyd0vlORE9zvuMQmrlNRJpoSA9G3L6DXy3iQ3zgWRFrsuIIkOPMGL3irfa1vmpE48E7rBuOvl6ob1gtRwWyzU4jYiE4A5OG5Lg6O1krOXDRSH4d4dRHzHWZ69oNRasIMK75z8FOqlb5CptJtdizu3STEsCytKeNRURaCIARrhgPGxwQ7F7lyhrjr2kQuYS2JtRO0LV0Bd8pdK1EoRwluFpGXTPpP_i7EMiOeu22hw0CB7uVlbYXLsYjFKpmn6Ph9I3YyEhgCIb-2SLf1gxvVR3ZWsuVmwvAmGn4isIQU8nTAxF5vPocQ_HeUg0SUA2y8s5yGOx_uU38e58eV24yZVGLAxwpEgVPC929IxfnxEI1lZQ6brfbT6gEObMZ4L1c5bfo0JqM3ESIZzSrU3oqIiiYI-KGvqC455GHXZWUzQKj6GUk4osKREEchvEOrGOoQTq3i2t0EefcbMMgz34pwSPRutPtg2q7gCKBn0e4MQUPmCsap8Vh8czMiQS7Hwo37bLdrJruL7nQek3YHKS9YopNlak9VtlkMXWWZcbg5n8BRiBxojUl9TCJmALouYSAkWXFq_zCXPyI3mucNBzBKU7-kfU2KgnTxY0Uzmq4bDWohUsTH_MY4", "id": "rs_0dc9f371a6d55e3f016a13801f67948191afb0cc6865b7781e", "summary": [{"type": "summary_text", "text": "**Finalizing media attachments**\n\nI need to finalize the media with a path of 1080, possibly attaching it. I should mention the tests that were conducted since “mach das” is done. Also, it looks like I need to include the commit hash for the changes made. I’ll make sure everything is in order before finalizing this. Let’s ensure that all necessary details are accounted for!"}]}], "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Erledigt, Sir.\n\n## Polishing-Slice abgeschlossen\n\nNeuer Commit:\n\n```text\n033334c feat: compact final motion subtitles\n```\n\n## Was verbessert wurde\n\n### 1. Compact Final-Motion Subtitles\n\nIch habe eine neue Subtitle-Variante gebaut:\n\n```python\nbuild_final_motion_subtitle_track()\n```\n\nEigenschaften:\n\n```text\n1–4 word cues\nphrase-boundary aware\nsmaller ASS font: 72px\nhigher bottom margin: 320px\nrenderer-owned\nside-effect-free\n```\n\nVorher gab es unschöne mechanische Chunks wie:\n\n```text\nANYTHING DECIDE THREE\n```\n\nDas ist grammatikalisch ungefähr so elegant wie ein Toaster im Ballett.\n\nJetzt werden Satz-/Phrasengrenzen respektiert, z. B.:\n\n```text\nBEFORE YOU\nAUTOMATE ANYTHING\n```\n\nstatt Wörter aus zwei Gedanken zusammenzukleben.\n\n---\n\n### 2. Subtitle/Layout-Konflikt reduziert\n\nBei der kritischen Szene:\n\n```text\nNormal → Go through\nUnclear → Review\nWeird/Risky → Stop\n```\n\nhabe ich geprüft:\n\n```text\nSubtitle konkurriert weniger mit Diagramm\nDiagramm bleibt lesbar\nkeine kritische Clipping-Probleme\nMobile readability ok\n```\n\n---\n\n### 3. 1080x1920 Export erzeugt\n\nNicht nur Preview — ich habe jetzt auch einen echten Full-HD Vertical Export gebaut:\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\n\n## Technische Daten\n\n```text\nResolution: 1080x1920\nVideo: h264\nAudio: aac\nVideo duration: 36.833s\nAudio duration: 36.864s\nFrames: 1110\nSubtitle cues: 26\n```\n\nSHA256:\n\n```text\n2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b\n```\n\n---\n\n## 4. Review Preview bleibt auch verfügbar\n\n540p Review-Version:\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/previews/truetrace-final-motion-v7/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-preview.mp4\n\nSHA256:\n\n```text\n0a3cc3129cd09d4b2594f23ef2d35faf5b7d04e1e1f94c55a35b50d1f8034616\n```\n\n---\n\n## 5. Tests\n\nFull Suite:\n\n```text\n169 passed in 32.51s\n```\n\n## Aktueller Commit-Verlauf\n\n```text\n033334c feat: compact final motion subtitles\ndb200ae feat: add scene-specific motion backgrounds\n14310f9 feat: add TrueTrace final motion prototype\n7375311 feat: make TrueTrace pilot beginner friendly\nb9b6423 feat: align TrueTrace voiceover previews\n```\n\n## Einschätzung\n\nDer Clip ist jetzt kein bloßer technischer Prototyp mehr, sondern ein **brauchbarer First-Public-Candidate**:\n\n- beginner-friendly Thema\n- konkretes „weird email“-Problem\n- Voiceover/Subtitles/Top Text aus einer Linie\n- szenenspezifische ChatGPT Image Backgrounds\n- renderer-owned Texte und Pfeile\n- Mechanism Reveal statt Slideshow\n- 1080x1920 Export vorhanden\n\nNoch nicht perfekt, aber inzwischen klar genug, dass man ihn sinnvoll beurteilen kann — und nicht nur freundlich danebensteht, während die Maschine dekorativ dampft."}], "id": "msg_0dc9f371a6d55e3f016a1380211b788191ad5771157240c757", "phase": "final_answer"}], "timestamp": "2026-05-25T00:48:19.126288"} {"role": "user", "content": "[M G] Ok mach weiter", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": "**Deciding on next steps for approval package**\n\nI need to figure out if we’re continuing with the next build of the social draft or approval package. I’m considering whether my skills are relevant and what actions I need to take. I should inspect the current repository and decide on the next step, possibly packaging a final candidate for review on Telegram. I also want to include metadata and social copy, while keeping TDD in mind. It looks like I might need to load a reference for the social draft too.", "finish_reason": "tool_calls", "reasoning_content": "**Deciding on next steps for approval package**\n\nI need to figure out if we’re continuing with the next build of the social draft or approval package. I’m considering whether my skills are relevant and what actions I need to take. I should inspect the current repository and decide on the next step, possibly packaging a final candidate for review on Telegram. I also want to include metadata and social copy, while keeping TDD in mind. It looks like I might need to load a reference for the social draft too.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE5YOhIr49jGX8vSfrprzsHR2BQwCp3VlH9OKxCQlpAWXgszHN2qERvcb1r6NSYtX1iIwMXf3C0zB9cAPtnT2N7uudnuVJqR8qjHhy-jRNv5T1UqMWQEnFbYYfNmgPpFIk7Ej4MRW6fUHOSq7Khi5QBYobeOXnwplbNYDfntUPea3DKteotoEjVRhRA4lXpwiFx-NIghIZbMzhvM9qn09-YJZ-l2e-6Yhd2eIltJWSmC92InBlp6j8aqiVomcdd-Yras6cLh9m_sCKC7FnxW9RS8mCYl5v-naeNrxprtAvz6kg0OeR0-m6jhC85rRoYxHZgltGpQXKVCaOdWNTEAoBe3OvH-nAdeZOXdptPjX-MnyYQj3D3htq59yAY_qwGqEUGmkVMVH9rlRm6zvmDr4HEgJJZTjO-89tw9ky0Nn9HHVVAiBVo4n_dCVUOPXcDJAMXufiM81VRmO6TUlBTvBfDmh_KHvNisnLX23XWjLlkZkYdxt6g0rdczKO--w7ODWvMUCQS1EHWtqVN7qS_7B6MmOC7k_8uJiOSqhWX4t2Wa9HlreG0OqmJkDDhhqKEH_MYKjZ0u5ykKkfV1FErnCLDilggQkpY-J_Lk_Ks-Y0mhITrMUimIVwJzQcF3b_Q4fKvp7eIqDu-GG0DoUZ9NWkEWGqK1tn7QS8_4QrMzvpPwNYC4X2iy_V6iHcX8QYt5CMrwRO2lHeaRMRtKWhnI6-eRLyjJvAhFC6FlagCDfN8n9sprfQ5HKXiY_fohZq3n1RmteWamQzCAvfWOnrAF6j0DS8cswINe5nD0t90xazgOqYATyEIbz_DtKiNPyfRLRy4WJXpjOKg0j132o7yZZZgswnkNU3DW7qqtdJ_7HSHl5tQJkp0H5fRVlulNpEdva0yOOBAefWgTMjkXWcXOA2OMkUA2ftmGGz9oJzGqfdw51uXkIQLh2JaIJBBfzpycV25tWelspOPuKHbfqKVZ1cUaFVi13-FmnTdJDjwSug-y1XMplqK1vUpZu4FMNu-UdgBE1Bkm_3WpFqyXq5Hi0TBD1a1Bj9Jz_djkKJpp_gjWcZd12rO4GMUwVpvfjnBZN6D3SBmrCyifTAjV6agz7p77ja6s3DiHhmba1mXjO1ycXwkjCRmr0AOz9oVE__QsUVzhLIMjfrY3H5p0TitM6TOYQ8xS36h2MfAgKjs7sI0vwLmjpZubMQCpK0k5KvXH44-u7r6kDt_uSQWL-KprkR9Ej0P7TZX6dNSWjaJfJSTwP0xfILvdbHl1VNHNC2p6KBHP4sRujQPyAXGkz7xnVABJJUaC_0VERkKHROPiq9uvSIchED5QACzmMRWvB1xf-45N_wLBnMInhhuEMXAhMABv6zDgWFoXc92E_Rf5ql4QgLt5XD7_sjuR7ONNb1W9D7o3Cedwhjy-OCw2X4s__89N4jFY_xHGM4eT-cwchjhvmHwiGBFTlFHXIxyULrI6OLeCY", "id": "rs_0dc9f371a6d55e3f016a13960b0ab0819195cb343e16126e48", "summary": [{"type": "summary_text", "text": "**Deciding on next steps for approval package**\n\nI need to figure out if we’re continuing with the next build of the social draft or approval package. I’m considering whether my skills are relevant and what actions I need to take. I should inspect the current repository and decide on the next step, possibly packaging a final candidate for review on Telegram. I also want to include metadata and social copy, while keeping TDD in mind. It looks like I might need to load a reference for the social draft too."}]}], "tool_calls": [{"id": "call_cQnesVqWjdGKOXCvhUQj467e", "call_id": "call_cQnesVqWjdGKOXCvhUQj467e", "response_item_id": "fc_0dc9f371a6d55e3f016a13960ec7708191963a6d5881d0d067", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"test-driven-development\"}"}}, {"id": "call_bruZILfwgHIWdkr6zV4IumYJ", "call_id": "call_bruZILfwgHIWdkr6zV4IumYJ", "response_item_id": "fc_0dc9f371a6d55e3f016a13960ec78c8191a3db64ffcbc7d22d", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"social-media-shorts-automation\",\"file_path\":\"references/social-draft-approval-package.md\"}"}}, {"id": "call_whEyoUkJr0lIz0iI1txDjeMM", "call_id": "call_whEyoUkJr0lIz0iI1txDjeMM", "response_item_id": "fc_0dc9f371a6d55e3f016a13960ec79c8191bff3e935be9c1ef9", "type": "function", "function": {"name": "search_files", "arguments": "{\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\",\"target\":\"files\",\"pattern\":\"*social*\",\"limit\":50}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "skill_view", "content": "{\"success\": true, \"name\": \"test-driven-development\", \"description\": \"TDD: enforce RED-GREEN-REFACTOR, tests before code.\", \"tags\": [\"testing\", \"tdd\", \"development\", \"quality\", \"red-green-refactor\"], \"related_skills\": [\"systematic-debugging\", \"writing-plans\", \"subagent-driven-development\"], \"content\": \"---\\nname: test-driven-development\\ndescription: \\\"TDD: enforce RED-GREEN-REFACTOR, tests before code.\\\"\\nversion: 1.1.0\\nauthor: Hermes Agent (adapted from obra/superpowers)\\nlicense: MIT\\nplatforms: [linux, macos, windows]\\nmetadata:\\n hermes:\\n tags: [testing, tdd, development, quality, red-green-refactor]\\n related_skills: [systematic-debugging, writing-plans, subagent-driven-development]\\n---\\n\\n# Test-Driven Development (TDD)\\n\\n## Overview\\n\\nWrite the test first. Watch it fail. Write minimal code to pass.\\n\\n**Core principle:** If you didn't watch the test fail, you don't know if it tests the right thing.\\n\\n**Violating the letter of the rules is violating the spirit of the rules.**\\n\\n## When to Use\\n\\n**Always:**\\n- New features\\n- Bug fixes\\n- Refactoring\\n- Behavior changes\\n\\n**Exceptions (ask the user first):**\\n- Throwaway prototypes\\n- Generated code\\n- Configuration files\\n\\nThinking \\\"skip TDD just this once\\\"? Stop. That's rationalization.\\n\\n## The Iron Law\\n\\n```\\nNO PRODUCTION CODE WITHOUT A FAILING TEST FIRST\\n```\\n\\nWrite code before the test? Delete it. Start over.\\n\\n**No exceptions:**\\n- Don't keep it as \\\"reference\\\"\\n- Don't \\\"adapt\\\" it while writing tests\\n- Don't look at it\\n- Delete means delete\\n\\nImplement fresh from tests. Period.\\n\\n## Red-Green-Refactor Cycle\\n\\n### RED — Write Failing Test\\n\\nWrite one minimal test showing what should happen.\\n\\n**Good test:**\\n```python\\ndef test_retries_failed_operations_3_times():\\n attempts = 0\\n def operation():\\n nonlocal attempts\\n attempts += 1\\n if attempts < 3:\\n raise Exception('fail')\\n return 'success'\\n\\n result = retry_operation(operation)\\n\\n assert result == 'success'\\n assert attempts == 3\\n```\\nClear name, tests real behavior, one thing.\\n\\n**Bad test:**\\n```python\\ndef test_retry_works():\\n mock = MagicMock()\\n mock.side_effect = [Exception(), Exception(), 'success']\\n result = retry_operation(mock)\\n assert result == 'success' # What about retry count? Timing?\\n```\\nVague name, tests mock not real code.\\n\\n**Requirements:**\\n- One behavior per test\\n- Clear descriptive name (\\\"and\\\" in name? Split it)\\n- Real code, not mocks (unless truly unavoidable)\\n- Name describes behavior, not implementation\\n\\n### Verify RED — Watch It Fail\\n\\n**MANDATORY. Never skip.**\\n\\n```bash\\n# Use terminal tool to run the specific test\\npytest tests/test_feature.py::test_specific_behavior -v\\n```\\n\\nConfirm:\\n- Test fails (not errors from typos)\\n- Failure message is expected\\n- Fails because the feature is missing\\n\\n**Test passes immediately?** You're testing existing behavior. Fix the test.\\n\\n**Test errors?** Fix the error, re-run until it fails correctly.\\n\\n### GREEN — Minimal Code\\n\\nWrite the simplest code to pass the test. Nothing more.\\n\\n**Good:**\\n```python\\ndef add(a, b):\\n return a + b # Nothing extra\\n```\\n\\n**Bad:**\\n```python\\ndef add(a, b):\\n result = a + b\\n logging.info(f\\\"Adding {a} + {b} = {result}\\\") # Extra!\\n return result\\n```\\n\\nDon't add features, refactor other code, or \\\"improve\\\" beyond the test.\\n\\n**Cheating is OK in GREEN:**\\n- Hardcode return values\\n- Copy-paste\\n- Duplicate code\\n- Skip edge cases\\n\\nWe'll fix it in REFACTOR.\\n\\n### Verify GREEN — Watch It Pass\\n\\n**MANDATORY.**\\n\\n```bash\\n# Run the specific test\\npytest tests/test_feature.py::test_specific_behavior -v\\n\\n# Then run ALL tests to check for regressions\\npytest tests/ -q\\n```\\n\\nConfirm:\\n- Test passes\\n- Other tests still pass\\n- Output pristine (no errors, warnings)\\n\\n**Test fails?** Fix the code, not the test.\\n\\n**Other tests fail?** Fix regressions now.\\n\\n### REFACTOR — Clean Up\\n\\nAfter green only:\\n- Remove duplication\\n- Improve names\\n- Extract helpers\\n- Simplify expressions\\n\\nKeep tests green throughout. Don't add behavior.\\n\\n**If tests fail during refactor:** Undo immediately. Take smaller steps.\\n\\n### Repeat\\n\\nNext failing test for next behavior. One cycle at a time.\\n\\n## Why Order Matters\\n\\n**\\\"I'll write tests after to verify it works\\\"**\\n\\nTests written after code pass immediately. Passing immediately proves nothing:\\n- Might test the wrong thing\\n- Might test implementation, not behavior\\n- Might miss edge cases you forgot\\n- You never saw it catch the bug\\n\\nTest-first forces you to see the test fail, proving it actually tests something.\\n\\n**\\\"I already manually tested all the edge cases\\\"**\\n\\nManual testing is ad-hoc. You think you tested everything but:\\n- No record of what you tested\\n- Can't re-run when code changes\\n- Easy to forget cases under pressure\\n- \\\"It worked when I tried it\\\" ≠ comprehensive\\n\\nAutomated tests are systematic. They run the same way every time.\\n\\n**\\\"Deleting X hours of work is wasteful\\\"**\\n\\nSunk cost fallacy. The time is already gone. Your choice now:\\n- Delete and rewrite with TDD (high confidence)\\n- Keep it and add tests after (low confidence, likely bugs)\\n\\nThe \\\"waste\\\" is keeping code you can't trust.\\n\\n**\\\"TDD is dogmatic, being pragmatic means adapting\\\"**\\n\\nTDD IS pragmatic:\\n- Finds bugs before commit (faster than debugging after)\\n- Prevents regressions (tests catch breaks immediately)\\n- Documents behavior (tests show how to use code)\\n- Enables refactoring (change freely, tests catch breaks)\\n\\n\\\"Pragmatic\\\" shortcuts = debugging in production = slower.\\n\\n**\\\"Tests after achieve the same goals — it's spirit not ritual\\\"**\\n\\nNo. Tests-after answer \\\"What does this do?\\\" Tests-first answer \\\"What should this do?\\\"\\n\\nTests-after are biased by your implementation. You test what you built, not what's required. Tests-first force edge case discovery before implementing.\\n\\n## Common Rationalizations\\n\\n| Excuse | Reality |\\n|--------|---------|\\n| \\\"Too simple to test\\\" | Simple code breaks. Test takes 30 seconds. |\\n| \\\"I'll test after\\\" | Tests passing immediately prove nothing. |\\n| \\\"Tests after achieve same goals\\\" | Tests-after = \\\"what does this do?\\\" Tests-first = \\\"what should this do?\\\" |\\n| \\\"Already manually tested\\\" | Ad-hoc ≠ systematic. No record, can't re-run. |\\n| \\\"Deleting X hours is wasteful\\\" | Sunk cost fallacy. Keeping unverified code is technical debt. |\\n| \\\"Keep as reference, write tests first\\\" | You'll adapt it. That's testing after. Delete means delete. |\\n| \\\"Need to explore first\\\" | Fine. Throw away exploration, start with TDD. |\\n| \\\"Test hard = design unclear\\\" | Listen to the test. Hard to test = hard to use. |\\n| \\\"TDD will slow me down\\\" | TDD faster than debugging. Pragmatic = test-first. |\\n| \\\"Manual test faster\\\" | Manual doesn't prove edge cases. You'll re-test every change. |\\n| \\\"Existing code has no tests\\\" | You're improving it. Add tests for the code you touch. |\\n\\n## Red Flags — STOP and Start Over\\n\\nIf you catch yourself doing any of these, delete the code and restart with TDD:\\n\\n- Code before test\\n- Test after implementation\\n- Test passes immediately on first run\\n- Can't explain why test failed\\n- Tests added \\\"later\\\"\\n- Rationalizing \\\"just this once\\\"\\n- \\\"I already manually tested it\\\"\\n- \\\"Tests after achieve the same purpose\\\"\\n- \\\"Keep as reference\\\" or \\\"adapt existing code\\\"\\n- \\\"Already spent X hours, deleting is wasteful\\\"\\n- \\\"TDD is dogmatic, I'm being pragmatic\\\"\\n- \\\"This is different because...\\\"\\n\\n**All of these mean: Delete code. Start over with TDD.**\\n\\n## Verification Checklist\\n\\nBefore marking work complete:\\n\\n- [ ] Every new function/method has a test\\n- [ ] Watched each test fail before implementing\\n- [ ] Each test failed for expected reason (feature missing, not typo)\\n- [ ] Wrote minimal code to pass each test\\n- [ ] All tests pass\\n- [ ] Output pristine (no errors, warnings)\\n- [ ] Tests use real code (mocks only if unavoidable)\\n- [ ] Edge cases and errors covered\\n\\nCan't check all boxes? You skipped TDD. Start over.\\n\\n## When Stuck\\n\\n| Problem | Solution |\\n|---------|----------|\\n| Don't know how to test | Write the wished-for API. Write the assertion first. Ask the user. |\\n| Test too complicated | Design too complicated. Simplify the interface. |\\n| Must mock everything | Code too coupled. Use dependency injection. |\\n| Test setup huge | Extract helpers. Still complex? Simplify the design. |\\n\\n## Hermes Agent Integration\\n\\n### Running Tests\\n\\nUse the `terminal` tool to run tests at each step:\\n\\n```python\\n# RED — verify failure\\nterminal(\\\"pytest tests/test_feature.py::test_name -v\\\")\\n\\n# GREEN — verify pass\\nterminal(\\\"pytest tests/test_feature.py::test_name -v\\\")\\n\\n# Full suite — verify no regressions\\nterminal(\\\"pytest tests/ -q\\\")\\n```\\n\\n### CLI Entry Points\\n\\nFor new `python -m package.cli.command` style entry points, keep the TDD loop boring and side-effect free:\\n\\n1. Write a test that imports `main` from the missing CLI module and calls `main([])`.\\n2. Capture stdout/stderr with the project test framework (`capsys` in pytest) or inject a `stdout` file-like object if supported.\\n3. RED should usually be an import failure for the missing CLI module/package, not a vague end-to-end shell failure.\\n4. Implement `main(argv: Sequence[str] | None = None, *, stdout: TextIO | None = None) -> int` so tests can call it without spawning a subprocess.\\n5. Add the `if __name__ == \\\"__main__\\\": raise SystemExit(main())` guard only after the callable path is green.\\n6. Verify both the unit test and the real module invocation, e.g. `python -m package.cli.command`, before committing.\\n\\nThis catches command wiring while avoiding accidental network calls, publishing actions, or other theatrical nonsense masquerading as a CLI test.\\n\\n### With delegate_task\\n\\nWhen dispatching subagents for implementation, enforce TDD in the goal:\\n\\n```python\\ndelegate_task(\\n goal=\\\"Implement [feature] using strict TDD\\\",\\n context=\\\"\\\"\\\"\\n Follow test-driven-development skill:\\n 1. Write failing test FIRST\\n 2. Run test to verify it fails\\n 3. Write minimal code to pass\\n 4. Run test to verify it passes\\n 5. Refactor if needed\\n 6. Commit\\n\\n Project test command: pytest tests/ -q\\n Project structure: [describe relevant files]\\n \\\"\\\"\\\",\\n toolsets=['terminal', 'file']\\n)\\n```\\n\\n### With systematic-debugging\\n\\nBug found? Write failing test reproducing it. Follow TDD cycle. The test proves the fix and prevents regression.\\n\\nNever fix bugs without a test.\\n\\n## Demo / Fixture Features\\n\\nWhen adding a deterministic demo fixture for later integration wiring, still use RED-GREEN-REFACTOR. Write the wished-for import/API in the test first, verify the missing module/API failure, then implement the smallest fixture that proves the real workflow path. Assert stable IDs/order, bucket counts/classifications, and safety invariants such as review text not implying publication. See `references/deterministic-demo-fixtures.md` for the concise pattern.\\n\\n## Side-Effect-Free Integration Boundaries\\n\\nWhen building toward an external integration (Telegram, email, publishing APIs, render farms, payment flows, etc.), add a tested preparation boundary before any real I/O:\\n\\n1. Write the wished-for pure function in the test first, e.g. `prepare_review_delivery(text) -> DeliveryPlan`.\\n2. RED should be a missing module/API or missing validation failure, not a real network/send failure.\\n3. The GREEN implementation should return a typed/dataclass plan object with explicit metadata: destination/topic, delivery type, human-approval requirement, and `side_effects=()`.\\n4. Validate safety constraints at the boundary: non-empty content, platform size limits, no forbidden action language, no implicit approval, no credentials or generated media unless explicitly expected.\\n5. Add a demo CLI only after the pure boundary is green. The CLI should print metadata first, then payload, and still perform no external I/O.\\n6. Verify both the unit tests and a real `python -m package.cli.demo_*` invocation before committing.\\n\\nThis pattern lets later sending/rendering/publishing adapters consume a boring, audited object instead of smuggling side effects into formatting code. Boring is how we avoid building a content catapult with a moustache.\\n\\n### Media / Rendering Pipeline Boundaries\\n\\nWhen building toward image/video generation or renderer integration, add deterministic planning artifacts before any GPU/API work:\\n\\n1. Write tests for the wished-for pure API first, e.g. `create_shot_plan(script)`, `build_render_manifest(plan)`, `build_local_preview_plan(manifest)`, or `build_ffmpeg_concat_plan(plan, frames, output_path)`.\\n2. RED should be a missing module/API or missing validation behavior — never a failed ComfyUI/Wan/Qwen/API invocation.\\n3. Keep each stage inspectable and side-effect-free until the explicit adapter layer: `ScriptDraft -> ShotPlan -> RenderManifest -> PreviewPlan/PreviewArtifact -> renderer adapter`.\\n4. Assert stable IDs/order, scene counts, timing continuity, vertical settings (`1080x1920`, `30fps` when building Shorts/Reels/TikTok), reduced preview settings (`540x960`, `24fps` when building fast local timing previews), and placeholder/runtime paths before generating media.\\n5. Add guardrail tests that reject static slideshows, baked-in/generated text inside assets, non-renderer-owned captions/labels, unsafe render settings, missing fields, bad timings, non-PNG frame paths, non-MP4 output paths, and mismatched frame counts.\\n6. Split artifact-writing/rendering into explicit boundaries after the pure plans are green: frame writer returns `side_effects=(\\\"write_png\\\",)`, concat planning remains side-effect-free, and the FFmpeg renderer returns `side_effects=(\\\"write_concat\\\", \\\"call_ffmpeg\\\", \\\"write_mp4\\\")` plus `external_calls=(\\\"ffmpeg\\\",)`.\\n7. Only after the manifest/preview boundary is green should a later adapter call local GPU tools or external services. Planning first; GPU roulette later.\\n\\nThis prevents wasting render time on unclear direction and keeps expensive media generation behind a small, audited boundary.\\n\\n### Approval-First Media/Social Pipelines\\n\\nWhen a feature crosses from content planning toward media/social delivery, prefer many small RED-GREEN-README-COMMIT slices instead of one large integration jump:\\n\\n1. typed artifact/model (`SocialMediaDraft`, `RenderManifest`, etc.)\\n2. renderer/formatter for human review text\\n3. side-effect-free delivery/preparation boundary\\n4. demo CLI that prints metadata first, then payload\\n\\nFor each slice, write the missing import/API test first, verify the expected import/API failure, implement only that slice, run the focused test, run the full suite, update docs, and commit. Keep invariant tests explicit: `requires_human_approval=True`, `side_effects=()`, no external calls, no credential access, no file writes unless that adapter is the explicit feature, and no accidental action language such as `publish`/`post` in review/delivery text.\\n\\nThis staged approach keeps approval semantics auditable and prevents a later renderer, Telegram sender, or platform adapter from being smuggled into formatting code.\\n\\n## Testing Anti-Patterns\\n\\n- **Testing mock behavior instead of real behavior** — mocks should verify interactions, not replace the system under test\\n- **Testing implementation details** — test behavior/results, not internal method calls\\n- **Happy path only** — always test edge cases, errors, and boundaries\\n- **Brittle tests** — tests should verify behavior, not structure; refactoring shouldn't break them\\n- **Substring sentinels that collide with generated IDs** — when asserting that amounts or fixture values are excluded from a result, assert the full formatted token (e.g. `999.00`) or a typed field, not a short substring like `999` that can appear inside UUIDs/hash-like IDs.\\n- **Domain classes named `Test*` trigger pytest collection warnings** — if a production dataclass/model must be named like `TestBatch`, set `__test__ = False` on the class or choose a non-`Test` prefix. Keep the fix in production code when the name is part of the domain language, and verify the warning is gone before committing.\\n- **Defaulting with `x or default` hides invalid explicit inputs** — when a factory/test helper accepts optional overrides, use `x if x is not None else default` so tests can pass intentionally blank strings (`\\\"\\\"`) or zero values and watch validation reject them. Otherwise invalid-input tests may silently receive defaults and give false confidence.\\n\\n## Final Rule\\n\\n```\\nProduction code → test exists and failed first\\nOtherwise → not TDD\\n```\\n\\nNo exceptions without the user's explicit permission.\\n\", \"path\": \"software-development/test-driven-development/SKILL.md\", \"skill_dir\": \"/home/agent/.hermes/skills/software-development/test-driven-development\", \"linked_files\": {\"references\": [\"references/deterministic-demo-fixtures.md\", \"references/side-effect-free-delivery-boundaries.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"hermes\": {\"tags\": [\"testing\", \"tdd\", \"development\", \"quality\", \"red-green-refactor\"], \"related_skills\": [\"systematic-debugging\", \"writing-plans\", \"subagent-driven-development\"]}}}", "tool_call_id": "call_cQnesVqWjdGKOXCvhUQj467e", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "skill_view", "content": "{\"success\": true, \"name\": \"social-media-shorts-automation\", \"file\": \"references/social-draft-approval-package.md\", \"content\": \"# Social Draft Approval Package Pattern\\n\\nUse this when moving from render planning toward the first user-facing social-media post draft for approval.\\n\\n## Goal\\n\\nProduce a complete approval draft before TTS, video rendering, or platform APIs:\\n\\n```text\\nVideoCandidate + RenderManifest/Preview\\n→ SocialMediaDraft\\n→ SocialMediaDraft review text\\n→ side-effect-free delivery plan\\n→ demo CLI output\\n```\\n\\nThis gives the user a concrete post candidate to approve or revise while still avoiding accidental publishing, external calls, and wasted GPU/TTS work.\\n\\n## Recommended typed artifacts\\n\\n1. `SocialMediaDraft`\\n - candidate id\\n - target platforms: YouTube Shorts, TikTok, Instagram Reels\\n - title variants\\n - caption\\n - hashtags\\n - CTA\\n - hook\\n - planned duration\\n - quality/risk summary\\n - preview reference, e.g. HTML timeline available or MP4 pending\\n - `requires_human_approval=True`\\n - `side_effects=()`\\n\\n2. Social review renderer\\n - Telegram-safe text block\\n - includes candidate, platforms, hook, titles, caption, hashtags, preview note, quality/risk summary\\n - includes approval commands: `Freigabe alle`, platform-specific approvals, `Ablehnen`, `Ändern: <...>`\\n - must not imply automatic upload or publishing\\n\\n3. Draft delivery preparation\\n - validates message length and safety language\\n - returns typed delivery plan with `requires_human_approval=True` and `side_effects=()`\\n - no Telegram API call yet\\n\\n4. Demo CLI\\n - e.g. `python -m autoshorts.cli.demo_social_draft`\\n - prints delivery metadata first, then the review text\\n - no file writes, platform calls, renderer calls, or credential access\\n\\n## Sequence before TTS\\n\\nDo not start with TTS. First get approval on the content package:\\n\\n```text\\nContentBrief\\n→ ScriptDraft\\n→ VideoCandidate\\n→ ShotPlan\\n→ RenderManifest\\n→ Preview\\n→ SocialMediaDraft\\n→ Review text\\n→ Approval delivery preview\\n```\\n\\nA robust implementation can be split into small TDD slices:\\n\\n1. `social/draft.py` — `build_social_media_draft(candidate, preview)` and `validate_social_media_draft(draft)`.\\n2. `social/review.py` — `render_social_media_draft_review(draft)` for Telegram-safe approval text.\\n3. `social/delivery.py` — `prepare_social_draft_delivery(text, topic=\\\"review\\\")` returning a side-effect-free delivery object.\\n4. `cli/demo_social_draft.py` — local demo command that prints metadata first, then the review text.\\n\\nRecommended invariant tests for every slice:\\n\\n- `requires_human_approval is True`\\n- `side_effects == ()`\\n- no platform API calls, Telegram calls, renderer calls, file writes, or credential access\\n- review/delivery text stays under Telegram's 4096-character limit\\n- review/delivery text does not contain `publish` or `post`\\n- platform labels are human-readable (`YouTube Shorts`, `TikTok`, `Instagram Reels`) while stored platform ids remain normalized (`youtube`, `tiktok`, `instagram`)\\n- preview script/reference matches the candidate source brief before building the social draft\\n\\nOnly after the draft is structurally approved should TTS design start:\\n\\n- voice selection\\n- final voiceover script\\n- words-per-second / timing\\n- caption sync\\n- audio format\\n- provider choice\\n- separate voice approval if needed\\n\\n## Guardrails\\n\\n- No credentials in draft output.\\n- No platform API calls.\\n- No publish/post semantics except inside explicit approval-command documentation if the codebase already uses that language carefully.\\n- Preview references are allowed; generated media paths should be placeholders unless a later renderer created real artifacts.\\n- Keep captions, numbers, labels, arrows, UI text, claims, and platform metadata renderer-owned / system-owned, never baked into generated AI assets.\\n\", \"file_type\": \".md\"}", "tool_call_id": "call_bruZILfwgHIWdkr6zV4IumYJ", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "search_files", "content": "{\"total_count\": 10, \"files\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/cli/__pycache__/demo_social_draft.cpython-311.pyc\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/cli/demo_social_draft.py\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/__pycache__/test_demo_social_draft_cli.cpython-311-pytest-9.0.2.pyc\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_demo_social_draft_cli.py\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/__pycache__/test_social_delivery.cpython-311-pytest-9.0.2.pyc\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_social_delivery.py\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/__pycache__/test_social_review.cpython-311-pytest-9.0.2.pyc\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_social_review.py\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/__pycache__/test_social_draft.cpython-311-pytest-9.0.2.pyc\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_social_draft.py\"]}", "tool_call_id": "call_whEyoUkJr0lIz0iI1txDjeMM", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": 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"id": "rs_0dc9f371a6d55e3f016a1396140ecc8191b74958b08247d04a", "summary": []}], "tool_calls": [{"id": "call_QBkzVNYz4w9KvmvobxYNm8yV", "call_id": "call_QBkzVNYz4w9KvmvobxYNm8yV", "response_item_id": "fc_0dc9f371a6d55e3f016a13961742708191943628504408f89a", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\":240,\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/cli/demo_social_draft.py\"}"}}, {"id": "call_iyMaG9VL0NVw7W134g7cWemj", "call_id": "call_iyMaG9VL0NVw7W134g7cWemj", "response_item_id": "fc_0dc9f371a6d55e3f016a13961745288191a8a6a2417d8a7dc4", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\":220,\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_social_draft.py\"}"}}, {"id": "call_LZVdBu5829I5DV0qHwgO7PVP", "call_id": "call_LZVdBu5829I5DV0qHwgO7PVP", "response_item_id": "fc_0dc9f371a6d55e3f016a1396174684819193925a59830ecd57", "type": "function", "function": {"name": "search_files", "arguments": "{\"limit\":50,\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts\",\"pattern\":\"*social*\",\"target\":\"files\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "read_file", "content": "{\"content\": \" 1|\\\"\\\"\\\"Print the deterministic social media draft review delivery.\\\"\\\"\\\"\\n 2|\\n 3|from __future__ import annotations\\n 4|\\n 5|import sys\\n 6|from collections.abc import Sequence\\n 7|from typing import TextIO\\n 8|\\n 9|from autoshorts.content.brief import create_content_brief\\n 10|from autoshorts.content.script_draft import create_script_draft\\n 11|from autoshorts.content.to_candidate import convert_script_draft_to_candidate\\n 12|from autoshorts.rendering.manifest import build_render_manifest\\n 13|from autoshorts.rendering.preview import build_html_preview\\n 14|from autoshorts.rendering.shot_plan import create_shot_plan\\n 15|from autoshorts.social.delivery import prepare_social_draft_delivery\\n 16|from autoshorts.social.draft import build_social_media_draft\\n 17|from autoshorts.social.review import render_social_media_draft_review\\n 18|\\n 19|\\n 20|def _build_demo_delivery():\\n 21| brief = create_content_brief(\\n 22| pillar_id=\\\"ai_life_systems\\\",\\n 23| topic=\\\"AI weekly review routine\\\",\\n 24| audience_problem=\\\"I use AI tools but still lose control of priorities.\\\",\\n 25| payoff=\\\"a 10-minute Sunday review that keeps AI as assistant, not boss\\\",\\n 26| )\\n 27| script = create_script_draft(brief)\\n 28| candidate = convert_script_draft_to_candidate(brief, script)\\n 29| preview = build_html_preview(build_render_manifest(create_shot_plan(script)))\\n 30| draft = build_social_media_draft(candidate, preview)\\n 31| review_text = render_social_media_draft_review(draft)\\n 32| return prepare_social_draft_delivery(review_text, topic=\\\"review\\\")\\n 33|\\n 34|\\n 35|def main(argv: Sequence[str] | None = None, *, stdout: TextIO | None = None) -> int:\\n 36| \\\"\\\"\\\"Print social draft delivery metadata and review text without sending anything.\\\"\\\"\\\"\\n 37|\\n 38| _ = argv or ()\\n 39| output = stdout or sys.stdout\\n 40| delivery = _build_demo_delivery()\\n 41| side_effects = \\\", \\\".join(delivery.side_effects) if delivery.side_effects else \\\"none\\\"\\n 42| approval = \\\"yes\\\" if delivery.requires_human_approval else \\\"no\\\"\\n 43|\\n 44| print(f\\\"Delivery type: {delivery.delivery_type}\\\", file=output)\\n 45| print(f\\\"Topic: {delivery.topic}\\\", file=output)\\n 46| print(f\\\"Requires human approval: {approval}\\\", file=output)\\n 47| print(f\\\"Side effects: {side_effects}\\\", file=output)\\n 48| print(f\\\"Text length: {len(delivery.text)}\\\", file=output)\\n 49| print(\\\"\\\", file=output)\\n 50| print(delivery.text, file=output)\\n 51| return 0\\n 52|\\n 53|\\n 54|if __name__ == \\\"__main__\\\":\\n 55| raise SystemExit(main())\\n 56|\", \"total_lines\": 55, \"file_size\": 2304, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_QBkzVNYz4w9KvmvobxYNm8yV", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "read_file", "content": "{\"content\": \" 1|import pytest\\n 2|\\n 3|from autoshorts.content.brief import create_content_brief\\n 4|from autoshorts.content.script_draft import create_script_draft\\n 5|from autoshorts.content.to_candidate import convert_script_draft_to_candidate\\n 6|from autoshorts.rendering.manifest import build_render_manifest\\n 7|from autoshorts.rendering.preview import build_html_preview\\n 8|from autoshorts.rendering.shot_plan import create_shot_plan\\n 9|from autoshorts.social.draft import (\\n 10| SocialMediaDraft,\\n 11| build_social_media_draft,\\n 12| validate_social_media_draft,\\n 13|)\\n 14|\\n 15|\\n 16|def _candidate_and_preview():\\n 17| brief = create_content_brief(\\n 18| pillar_id=\\\"ai_life_systems\\\",\\n 19| topic=\\\"AI weekly review routine\\\",\\n 20| audience_problem=\\\"I use AI tools but still lose control of priorities.\\\",\\n 21| payoff=\\\"a 10-minute Sunday review that keeps AI as assistant, not boss\\\",\\n 22| )\\n 23| script = create_script_draft(brief)\\n 24| candidate = convert_script_draft_to_candidate(brief, script)\\n 25| preview = build_html_preview(build_render_manifest(create_shot_plan(script)))\\n 26| return candidate, preview\\n 27|\\n 28|\\n 29|def test_build_social_media_draft_creates_approval_first_post_draft():\\n 30| candidate, preview = _candidate_and_preview()\\n 31|\\n 32| draft = build_social_media_draft(candidate, preview)\\n 33|\\n 34| assert isinstance(draft, SocialMediaDraft)\\n 35| assert draft.candidate_id == \\\"ai_life_systems-ai-weekly-review-routine-35s\\\"\\n 36| assert draft.platforms == (\\\"youtube\\\", \\\"tiktok\\\", \\\"instagram\\\")\\n 37| assert draft.platform_labels == (\\\"YouTube Shorts\\\", \\\"TikTok\\\", \\\"Instagram Reels\\\")\\n 38| assert draft.title_variants == (\\n 39| \\\"AI weekly review routine\\\",\\n 40| \\\"If AI runs your week, you have already lost control.\\\",\\n 41| )\\n 42| assert draft.caption == candidate.caption\\n 43| assert draft.hashtags == (\\\"#AI\\\", \\\"#LifeSystems\\\", \\\"#Productivity\\\")\\n 44| assert draft.cta == candidate.cta\\n 45| assert draft.hook == candidate.hook\\n 46| assert draft.planned_duration_seconds == 35\\n 47| assert draft.preview_reference == \\\"HTML timeline preview available\\\"\\n 48| assert draft.preview_type == \\\"html_timeline\\\"\\n 49| assert draft.requires_human_approval is True\\n 50| assert draft.side_effects == ()\\n 51| assert \\\"Quality average: 8.0\\\" in draft.quality_risk_summary\\n 52| assert \\\"AI-slop risk: 3\\\" in draft.quality_risk_summary\\n 53| assert \\\"Policy risk: low\\\" in draft.quality_risk_summary\\n 54|\\n 55|\\n 56|def test_validate_social_media_draft_accepts_default_draft():\\n 57| candidate, preview = _candidate_and_preview()\\n 58|\\n 59| result = validate_social_media_draft(build_social_media_draft(candidate, preview))\\n 60|\\n 61| assert result.is_valid is True\\n 62| assert result.errors == ()\\n 63|\\n 64|\\n 65|def test_build_social_media_draft_rejects_preview_for_different_script():\\n 66| candidate, preview = _candidate_and_preview()\\n 67| mismatched = type(preview)(\\n 68| script_id=\\\"other-script\\\",\\n 69| title=preview.title,\\n 70| preview_type=preview.preview_type,\\n 71| html=preview.html,\\n 72| side_effects=preview.side_effects,\\n 73| external_calls=preview.external_calls,\\n 74| )\\n 75|\\n 76| with pytest.raises(ValueError, match=\\\"preview script_id must match candidate source brief\\\"):\\n 77| build_social_media_draft(candidate, mismatched)\\n 78|\\n 79|\\n 80|def test_validate_social_media_draft_rejects_missing_approval_and_side_effects():\\n 81| candidate, preview = _candidate_and_preview()\\n 82| draft = build_social_media_draft(candidate, preview)\\n 83| unsafe = SocialMediaDraft(\\n 84| candidate_id=draft.candidate_id,\\n 85| platforms=draft.platforms,\\n 86| platform_labels=draft.platform_labels,\\n 87| title_variants=draft.title_variants,\\n 88| caption=draft.caption,\\n 89| hashtags=draft.hashtags,\\n 90| cta=draft.cta,\\n 91| hook=draft.hook,\\n 92| planned_duration_seconds=draft.planned_duration_seconds,\\n 93| quality_risk_summary=draft.quality_risk_summary,\\n 94| preview_reference=draft.preview_reference,\\n 95| preview_type=draft.preview_type,\\n 96| requires_human_approval=False,\\n 97| side_effects=(\\\"platform_upload\\\",),\\n 98| )\\n 99|\\n 100| result = validate_social_media_draft(unsafe)\\n 101|\\n 102| assert result.is_valid is False\\n 103| assert \\\"human approval is required\\\" in result.errors\\n 104| assert \\\"social media drafts must not have side effects\\\" in result.errors\\n 105|\\n 106|\\n 107|def test_validate_social_media_draft_rejects_unsupported_platform_and_blank_fields():\\n 108| draft = SocialMediaDraft(\\n 109| candidate_id=\\\"\\\",\\n 110| platforms=(\\\"linkedin\\\",),\\n 111| platform_labels=(\\\"LinkedIn\\\",),\\n 112| title_variants=(),\\n 113| caption=\\\"\\\",\\n 114| hashtags=(),\\n 115| cta=\\\"\\\",\\n 116| hook=\\\"\\\",\\n 117| planned_duration_seconds=9,\\n 118| quality_risk_summary=\\\"\\\",\\n 119| preview_reference=\\\"\\\",\\n 120| preview_type=\\\"\\\",\\n 121| requires_human_approval=True,\\n 122| side_effects=(),\\n 123| )\\n 124|\\n 125| result = validate_social_media_draft(draft)\\n 126|\\n 127| assert result.is_valid is False\\n 128| assert \\\"candidate_id is required\\\" in result.errors\\n 129| assert \\\"unsupported platform: linkedin\\\" in result.errors\\n 130| assert \\\"at least one title variant is required\\\" in result.errors\\n 131| assert \\\"caption is required\\\" in result.errors\\n 132| assert \\\"at least one hashtag is required\\\" in result.errors\\n 133| assert \\\"cta is required\\\" in result.errors\\n 134| assert \\\"hook is required\\\" in result.errors\\n 135| assert \\\"planned_duration_seconds must be between 10 and 180\\\" in result.errors\\n 136| assert \\\"quality_risk_summary is required\\\" in result.errors\\n 137| assert \\\"preview_reference is required\\\" in result.errors\\n 138| assert \\\"preview_type is required\\\" in result.errors\\n 139|\", \"total_lines\": 138, \"file_size\": 5367, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_iyMaG9VL0NVw7W134g7cWemj", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "search_files", "content": "{\"total_count\": 2, \"files\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/cli/__pycache__/demo_social_draft.cpython-311.pyc\", \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/cli/demo_social_draft.py\"]}", "tool_call_id": "call_LZVdBu5829I5DV0qHwgO7PVP", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": "**Organizing media for final approval**\n\nI need to prepare the final export approval package, including the media path. I have an existing social draft for HTML that I’ll need to adapt for the final video candidate. I should consider building a release candidate that references the final MP4 and review the text as well. Also, I have to conduct some tests and inspect the draft for review and delivery to ensure everything is in order.", "finish_reason": "tool_calls", "reasoning_content": "**Organizing media for final approval**\n\nI need to prepare the final export approval package, including the media path. I have an existing social draft for HTML that I’ll need to adapt for the final video candidate. I should consider building a release candidate that references the final MP4 and review the text as well. Also, I have to conduct some tests and inspect the draft for review and delivery to ensure everything is in order.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE5YhvIjdbZkhH6yV1iwvYq_ErNvcwnnKMwDWC09gWe5ZySqnYb76v6ht1zCaCaZr5c-7_0SpUJI4AZkvIVaXAsufgOnNPT5lnzYw2U75lXz5HDPspid0Ycm9-GiRQvD2Cup6BvAIl4UKmiV5WKo2tksFCf3sD_trqWBJg_TxAAnpT2mLmdZ_iCNfjArIzVsfK01UvmtaCJ-tCo7pzveIOdLj4H1gw0wqQt9iQELxb1lsLV9YlG5HKbx9dcra83d0zCfcUYGe1vn0S46vkuRE9KOHn9hhgytNjWEsIli5MoCrOm6jKoRMRn2WBorv6KYwDqxbc6uXw3RjYCT-MnJoNOOPiZDSK0B3ywG4mSU6Fi7Mk6qIQmFjqewlOO6WOpKnk50c8QA0ly9woXroxYZduZl9oxNuLRou_3kY6KoSozrJFjcsvVbRWZj3HqDpbzUIjm1T6Hb0y21GXaM_cEeu7STWM3GfH1HxpxPrZEynN6bwz_FS2yKEfaLBVL13SnzJ61kV7PLLLGgU-R410fG5_iNsR8cSGF_Kk__x1vEzecIX6RI5KkIQAPqrMmnz9Azu9xIpyuIBfM_fcga8ktHMKLTZdKKGEkBkA4rjbXGSjnUiFMXvuz4Xs_WuEd-0Miuw_ZsiVBBKdNOryyNOHGh9_ixYAFOhtL4V8xNCPKHGrAPP3fRt8NXYiZrX2-Gx1XtSW3wFgx8DznGNQOFUA8jGZaNogB5tiiwT4ZB7_7uYPw6OsiHVr5M0Ty1BEe3NWxJWPrBiE7WIHw8NKLPvNsUePnTbTlQVggW_mi_xZBMg-IOIVoxsWHFYZ4dSb1ykzd2J_fe_kEEtistMQD5aiaXwH1a8DMQcDAZv_ieMEpDlth2oo82WL71V3_iCBt630I-vEygYDnHWEIm_bdu5VnH2ZYAoPMaoO-SrBLDdqJVYevcJP8ZtgzjtoxlFYYUjjg6vl02dpAOrHX0qPYFAyjMmd3rsYwoiJcmxhUXbCvE0Jh3tBYCQjSE70ygrarjRiBDbIDaqW62MhYdqNg_ir4BNGAPyC365o0-irerRaGiY7TgPALvu4pEmdvvXcqtws6hHI_J6G6m_g552e7uLhDOfct0fwACyI75IfJkgDFw1r47_mwe6_Ql8bM8howhfvR2xMf0q-exgin0oHysAjPxBqLfmVllcNF6aetfVQnE85CaUNPa2UZVoDjr9lSmKytYRx83wnOia2O6CgcuDy6C548TOcs85uUYpPvOoiFnJsPBT82I=", "id": "rs_0dc9f371a6d55e3f016a13961d91cc81919f26eddc53ae7f59", "summary": [{"type": "summary_text", "text": "**Organizing media for final approval**\n\nI need to prepare the final export approval package, including the media path. I have an existing social draft for HTML that I’ll need to adapt for the final video candidate. I should consider building a release candidate that references the final MP4 and review the text as well. Also, I have to conduct some tests and inspect the draft for review and delivery to ensure everything is in order."}]}], "tool_calls": [{"id": "call_QIhTpSNooCi0WqFKe8ZnhoSS", "call_id": "call_QIhTpSNooCi0WqFKe8ZnhoSS", "response_item_id": "fc_0dc9f371a6d55e3f016a139621675881919c1e26ad895ace5c", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\":240,\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/social/draft.py\"}"}}, {"id": "call_t2Ba9JQUvLbpJq0fhKrgWPbs", "call_id": "call_t2Ba9JQUvLbpJq0fhKrgWPbs", "response_item_id": "fc_0dc9f371a6d55e3f016a139621679081918daaf1f889de024c", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\":220,\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/social/review.py\"}"}}, {"id": "call_nfX569DnRIhSDnUdkbY4VuVz", "call_id": "call_nfX569DnRIhSDnUdkbY4VuVz", "response_item_id": "fc_0dc9f371a6d55e3f016a13962167988191992fc391209216e8", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\":180,\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/social/delivery.py\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "read_file", "content": "{\"content\": \" 1|\\\"\\\"\\\"Approval-first social media draft artifacts.\\\"\\\"\\\"\\n 2|\\n 3|from __future__ import annotations\\n 4|\\n 5|from dataclasses import dataclass\\n 6|\\n 7|from autoshorts.ideas.candidate import SUPPORTED_PLATFORMS, ValidationResult, VideoCandidate, validate_candidate\\n 8|from autoshorts.rendering.preview import RenderPreview, validate_render_preview\\n 9|\\n 10|_PLATFORM_LABELS = {\\n 11| \\\"youtube\\\": \\\"YouTube Shorts\\\",\\n 12| \\\"tiktok\\\": \\\"TikTok\\\",\\n 13| \\\"instagram\\\": \\\"Instagram Reels\\\",\\n 14|}\\n 15|\\n 16|\\n 17|@dataclass(frozen=True)\\n 18|class SocialMediaDraft:\\n 19| candidate_id: str\\n 20| platforms: tuple[str, ...]\\n 21| platform_labels: tuple[str, ...]\\n 22| title_variants: tuple[str, ...]\\n 23| caption: str\\n 24| hashtags: tuple[str, ...]\\n 25| cta: str\\n 26| hook: str\\n 27| planned_duration_seconds: int\\n 28| quality_risk_summary: str\\n 29| preview_reference: str\\n 30| preview_type: str\\n 31| requires_human_approval: bool = True\\n 32| side_effects: tuple[str, ...] = ()\\n 33|\\n 34|\\n 35|def _is_blank(value: str) -> bool:\\n 36| return not (value or \\\"\\\").strip()\\n 37|\\n 38|\\n 39|def _quality_risk_summary(candidate: VideoCandidate) -> str:\\n 40| score = candidate.quality_score\\n 41| return (\\n 42| f\\\"Quality average: {score.average_quality:.1f}; \\\"\\n 43| f\\\"AI-slop risk: {score.ai_slop_risk}; \\\"\\n 44| f\\\"Policy risk: {score.policy_risk}\\\"\\n 45| )\\n 46|\\n 47|\\n 48|def _source_brief_id(candidate: VideoCandidate) -> str | None:\\n 49| prefix = \\\"Source brief: \\\"\\n 50| for note in candidate.policy_notes:\\n 51| if note.startswith(prefix):\\n 52| return note.removeprefix(prefix).strip()\\n 53| return None\\n 54|\\n 55|\\n 56|def build_social_media_draft(candidate: VideoCandidate, preview: RenderPreview) -> SocialMediaDraft:\\n 57| \\\"\\\"\\\"Build a side-effect-free platform draft from a candidate and preview.\\\"\\\"\\\"\\n 58|\\n 59| candidate_validation = validate_candidate(candidate)\\n 60| if not candidate_validation.is_valid:\\n 61| raise ValueError(\\\"; \\\".join(candidate_validation.errors))\\n 62|\\n 63| preview_validation = validate_render_preview(preview)\\n 64| if not preview_validation.is_valid:\\n 65| raise ValueError(\\\"; \\\".join(preview_validation.errors))\\n 66|\\n 67| source_brief_id = _source_brief_id(candidate)\\n 68| if source_brief_id is not None and preview.script_id != source_brief_id:\\n 69| raise ValueError(\\\"preview script_id must match candidate source brief\\\")\\n 70|\\n 71| draft = SocialMediaDraft(\\n 72| candidate_id=candidate.candidate_id,\\n 73| platforms=candidate.platforms,\\n 74| platform_labels=tuple(_PLATFORM_LABELS[platform] for platform in candidate.platforms),\\n 75| title_variants=(candidate.title, candidate.hook),\\n 76| caption=candidate.caption,\\n 77| hashtags=candidate.hashtags,\\n 78| cta=candidate.cta,\\n 79| hook=candidate.hook,\\n 80| planned_duration_seconds=candidate.duration_seconds,\\n 81| quality_risk_summary=_quality_risk_summary(candidate),\\n 82| preview_reference=\\\"HTML timeline preview available\\\",\\n 83| preview_type=preview.preview_type,\\n 84| requires_human_approval=True,\\n 85| side_effects=(),\\n 86| )\\n 87| validation = validate_social_media_draft(draft)\\n 88| if not validation.is_valid:\\n 89| raise ValueError(\\\"; \\\".join(validation.errors))\\n 90| return draft\\n 91|\\n 92|\\n 93|def validate_social_media_draft(draft: SocialMediaDraft) -> ValidationResult:\\n 94| errors: list[str] = []\\n 95| for field_name, value in {\\n 96| \\\"candidate_id\\\": draft.candidate_id,\\n 97| \\\"caption\\\": draft.caption,\\n 98| \\\"cta\\\": draft.cta,\\n 99| \\\"hook\\\": draft.hook,\\n 100| \\\"quality_risk_summary\\\": draft.quality_risk_summary,\\n 101| \\\"preview_reference\\\": draft.preview_reference,\\n 102| \\\"preview_type\\\": draft.preview_type,\\n 103| }.items():\\n 104| if _is_blank(value):\\n 105| errors.append(f\\\"{field_name} is required\\\")\\n 106|\\n 107| if not draft.platforms:\\n 108| errors.append(\\\"at least one platform is required\\\")\\n 109| for platform in draft.platforms:\\n 110| if platform not in SUPPORTED_PLATFORMS:\\n 111| errors.append(f\\\"unsupported platform: {platform}\\\")\\n 112|\\n 113| if len(draft.platform_labels) != len(draft.platforms):\\n 114| errors.append(\\\"platform_labels must match platforms\\\")\\n 115| if not draft.title_variants:\\n 116| errors.append(\\\"at least one title variant is required\\\")\\n 117| elif any(_is_blank(title) for title in draft.title_variants):\\n 118| errors.append(\\\"title variants must not be blank\\\")\\n 119| if not draft.hashtags:\\n 120| errors.append(\\\"at least one hashtag is required\\\")\\n 121| elif any(_is_blank(hashtag) for hashtag in draft.hashtags):\\n 122| errors.append(\\\"hashtags must not be blank\\\")\\n 123| if not 10 <= draft.planned_duration_seconds <= 180:\\n 124| errors.append(\\\"planned_duration_seconds must be between 10 and 180\\\")\\n 125| if not draft.requires_human_approval:\\n 126| errors.append(\\\"human approval is required\\\")\\n 127| if draft.side_effects:\\n 128| errors.append(\\\"social media drafts must not have side effects\\\")\\n 129|\\n 130| return ValidationResult(is_valid=not errors, errors=tuple(errors))\\n 131|\", \"total_lines\": 130, \"file_size\": 4730, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_QIhTpSNooCi0WqFKe8ZnhoSS", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "read_file", "content": "{\"content\": \" 1|\\\"\\\"\\\"Telegram-safe social media draft review rendering.\\\"\\\"\\\"\\n 2|\\n 3|from __future__ import annotations\\n 4|\\n 5|from autoshorts.social.draft import SocialMediaDraft, validate_social_media_draft\\n 6|\\n 7|\\n 8|def _platform_approval_command(platform: str) -> str:\\n 9| if platform == \\\"youtube\\\":\\n 10| return \\\"Freigabe YouTube\\\"\\n 11| if platform == \\\"tiktok\\\":\\n 12| return \\\"Freigabe TikTok\\\"\\n 13| if platform == \\\"instagram\\\":\\n 14| return \\\"Freigabe Instagram\\\"\\n 15| return f\\\"Freigabe {platform}\\\"\\n 16|\\n 17|\\n 18|def render_social_media_draft_review(draft: SocialMediaDraft) -> str:\\n 19| \\\"\\\"\\\"Render a social-media draft as a Telegram-safe approval message.\\\"\\\"\\\"\\n 20|\\n 21| validation = validate_social_media_draft(draft)\\n 22| if not validation.is_valid:\\n 23| raise ValueError(\\\"; \\\".join(validation.errors))\\n 24|\\n 25| approval_commands = tuple(_platform_approval_command(platform) for platform in draft.platforms)\\n 26| title_lines = \\\"\\\\n\\\".join(f\\\"- {title}\\\" for title in draft.title_variants)\\n 27| command_lines = \\\"\\\\n\\\".join(\\n 28| f\\\"- {command}\\\"\\n 29| for command in (\\n 30| *approval_commands,\\n 31| \\\"Freigabe alle\\\",\\n 32| \\\"Ablehnen\\\",\\n 33| \\\"Ändern: \\\",\\n 34| )\\n 35| )\\n 36| side_effects = \\\", \\\".join(draft.side_effects) if draft.side_effects else \\\"none\\\"\\n 37| approval = \\\"yes\\\" if draft.requires_human_approval else \\\"no\\\"\\n 38|\\n 39| return \\\"\\\\n\\\".join(\\n 40| (\\n 41| \\\"## Social Media Draft Review\\\",\\n 42| \\\"\\\",\\n 43| f\\\"Candidate: {draft.candidate_id}\\\",\\n 44| f\\\"Platforms: {', '.join(draft.platform_labels)}\\\",\\n 45| f\\\"Duration: {draft.planned_duration_seconds}s\\\",\\n 46| \\\"\\\",\\n 47| \\\"Hook:\\\",\\n 48| draft.hook,\\n 49| \\\"\\\",\\n 50| \\\"Title variants:\\\",\\n 51| title_lines,\\n 52| \\\"\\\",\\n 53| \\\"Caption:\\\",\\n 54| draft.caption,\\n 55| \\\"\\\",\\n 56| f\\\"Hashtags: {' '.join(draft.hashtags)}\\\",\\n 57| f\\\"CTA: {draft.cta}\\\",\\n 58| f\\\"Preview: {draft.preview_reference} ({draft.preview_type})\\\",\\n 59| f\\\"Quality/Risk: {draft.quality_risk_summary}\\\",\\n 60| f\\\"Requires human approval: {approval}\\\",\\n 61| f\\\"Side effects: {side_effects}\\\",\\n 62| \\\"\\\",\\n 63| \\\"Approval commands:\\\",\\n 64| command_lines,\\n 65| )\\n 66| )\\n 67|\", \"total_lines\": 66, \"file_size\": 2182, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_t2Ba9JQUvLbpJq0fhKrgWPbs", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "read_file", "content": "{\"content\": \" 1|\\\"\\\"\\\"Side-effect-free delivery planning for social media draft reviews.\\\"\\\"\\\"\\n 2|\\n 3|from __future__ import annotations\\n 4|\\n 5|from dataclasses import dataclass\\n 6|\\n 7|_TELEGRAM_MESSAGE_LIMIT = 4096\\n 8|_FORBIDDEN_ACTION_WORDS = (\\\"publish\\\", \\\"post\\\")\\n 9|\\n 10|\\n 11|@dataclass(frozen=True)\\n 12|class SocialDraftDelivery:\\n 13| text: str\\n 14| topic: str = \\\"review\\\"\\n 15| delivery_type: str = \\\"social_draft_review\\\"\\n 16| requires_human_approval: bool = True\\n 17| side_effects: tuple[str, ...] = ()\\n 18|\\n 19|\\n 20|def prepare_social_draft_delivery(review_text: str, *, topic: str = \\\"review\\\") -> SocialDraftDelivery:\\n 21| \\\"\\\"\\\"Prepare a Telegram-bound social draft review without sending it.\\\"\\\"\\\"\\n 22|\\n 23| if not (review_text or \\\"\\\").strip():\\n 24| raise ValueError(\\\"review text is required\\\")\\n 25| if len(review_text) > _TELEGRAM_MESSAGE_LIMIT:\\n 26| raise ValueError(\\\"Telegram message exceeds 4096 characters\\\")\\n 27|\\n 28| lowered = review_text.casefold()\\n 29| if any(word in lowered for word in _FORBIDDEN_ACTION_WORDS):\\n 30| raise ValueError(\\\"social draft delivery must not imply publishing\\\")\\n 31|\\n 32| return SocialDraftDelivery(\\n 33| text=review_text,\\n 34| topic=topic,\\n 35| delivery_type=\\\"social_draft_review\\\",\\n 36| requires_human_approval=True,\\n 37| side_effects=(),\\n 38| )\\n 39|\", \"total_lines\": 38, \"file_size\": 1207, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_nfX569DnRIhSDnUdkbY4VuVz", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": "**Considering final video review**\n\nI’m looking to build a final video review and thinking about a quality gate score too. I could create a SocialMediaDraft for the final candidate manually, but maybe it’s better to create a FinalVideoApprovalPackage that includes the media path, checksum, and social metadata. I should avoid using “post” as it might be forbidden. Sending the media at the final stage could be a good idea. I also need to test the candidate model and read through it.", "finish_reason": "tool_calls", "reasoning_content": "**Considering final video review**\n\nI’m looking to build a final video review and thinking about a quality gate score too. I could create a SocialMediaDraft for the final candidate manually, but maybe it’s better to create a FinalVideoApprovalPackage that includes the media path, checksum, and social metadata. I should avoid using “post” as it might be forbidden. Sending the media at the final stage could be a good idea. I also need to test the candidate model and read through it.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE5YpDOjShhIpjRGkjnxY_PZuaEIwmSDkfKP1UOhOmoxttciijcADcPXaMgeVSCzPpS5iqMuZeqPXilS9gDbuF2L55A_NbW3jaNcNXE4Y5eKXnr9DvxtjzCk95tbfauK-xMb3nFo0VYzxvorMZs0XPEfoVKl_1_DkzaxbTewY2Ch7nDK4-2mv3QghMqK9mMQ-tTv4iHDn6pzFVFBS_vn7yfzK85FhkGo22NOfVExM4auqN_vHkrFGE8A8IKjWzbB8yjAfaM5Z1vV7u1Jw0CQl7bG0TR7NmUGlJ53mLQkMC4dS-rNgGXIDhgTYrAiSskbapNCvddR69TodxAhRbtn8_sqUq6JKnCl4p1OO8hc5CPdig-1_vG0mkj9noaU2lcjNKi6EpwJ8xlWOiF3DAEY8VvrzkBmU3aKgvVDRK2D5jBXRonQNqQwFe6xmx2HUPcxQuLIUE9tnxBNx6MdwhEHyPqpVB_jEPT96ZqKHSN92aP1ayWYvFL6dmsYYG6XIJgp_GuKkKPMmbtfjpYjKgeoCw7XeYxIoZJNxHB-DBD-XstyJUj5_mo8-ukh8JBb8FUu4fNdsbd9hXk-7rG07QXZOzap81d457d_vpRYLUC2H0_AVtidpSjL9vvnkr38bUOegk5i2T2pQjB-yH-DwHdfg_u2xOBB4aunaSiNb_JJbUozmqb8dMpnQ3EcmW4z2w02_XeL2Ek2KkxWknmd6MiXQaiXIzE6mxRDMWJ3VpmC6XKfcG5ZsXx0NyFbg2eIEd5voIOThIv1oLzEi4wixFNG774GZqSwckERd1N6GEH0O1TkeUzvyiq2Uwfdm_lTEu0vUHOt1QF4vxDM6Yq9Me7qpOZdaiyj_ij-VSy2sShev5RBXdwNZSNi6kTsfRGd-j_hMzKP5hGxVQJOFyXti-asADPycJk0tk6e97_JGcaGgA9qzjyeEfS9GOGhnQGgmepwLk-RC93ghm1-LZwIIBrocaPWK_ZcvI3DkWlu7zMIA9HIfFKo4aPNQXMZM_OTJQNYSVw5SV2iwVEKt-5FirK3wZZu4vqsAS1hEfS64Rcj4Kbv2RVlCO9v90IKIBkYD-IjeWDaRVPIg8xfKmuoNxMu6yu1rh1OTa26PLDfkqJGZvGCNF6cB4K-e2fpkLdc-NPzhjVAyF-dKHf9Ro1E0mYJ6GZPNxVM0qyZixWUFLndKg-0zutTHMFIZxTA95Uw27N8YVCyvok_dZei95FvwarrcnrYdlU1YWwd-W1-tVcKkKMRQYiRi2IospPOlbhIjDGsjo-V2poDsz7WMUBiAY9PqFVLDR4LvN3FA7GZCxOcQS-Nq0CYosS6k3-RhqJurDDVA1UnHhrF56oAgqPe1PAHIb1CkxG0rK7dULqmUtXw1tYPQDMd34k2kDF8rCYw_TahLj_mIvIAHWcJwr3H1E0uQN5YwDzIBi1bphgeJHv3EwFyNM7Hd1Pnd-Bwvlz71-5Fo_60K3TKRWIOAvjzNA0A5pMkqvA==", "id": "rs_0dc9f371a6d55e3f016a139626a23c819182ad3fbb6b7a11cc", "summary": [{"type": "summary_text", "text": "**Considering final video review**\n\nI’m looking to build a final video review and thinking about a quality gate score too. I could create a SocialMediaDraft for the final candidate manually, but maybe it’s better to create a FinalVideoApprovalPackage that includes the media path, checksum, and social metadata. I should avoid using “post” as it might be forbidden. Sending the media at the final stage could be a good idea. I also need to test the candidate model and read through it."}]}], "tool_calls": [{"id": "call_qNxqTotFjM6fV9C8GavGWACz", "call_id": "call_qNxqTotFjM6fV9C8GavGWACz", "response_item_id": "fc_0dc9f371a6d55e3f016a139629d2408191aa4a0a4fe562deae", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\":260,\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/ideas/candidate.py\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "read_file", "content": "{\"content\": \" 1|\\\"\\\"\\\"Video candidate domain model and validation.\\\"\\\"\\\"\\n 2|\\n 3|from __future__ import annotations\\n 4|\\n 5|from dataclasses import dataclass\\n 6|\\n 7|from autoshorts.review.package import ReviewPackage\\n 8|from autoshorts.scripting.quality import ScriptQualityScore\\n 9|\\n 10|SUPPORTED_PLATFORMS = (\\\"youtube\\\", \\\"tiktok\\\", \\\"instagram\\\")\\n 11|\\n 12|\\n 13|@dataclass(frozen=True)\\n 14|class ValidationResult:\\n 15| is_valid: bool\\n 16| errors: tuple[str, ...] = ()\\n 17|\\n 18|\\n 19|@dataclass(frozen=True)\\n 20|class VideoCandidate:\\n 21| candidate_id: str\\n 22| pillar: str\\n 23| title: str\\n 24| platforms: tuple[str, ...]\\n 25| duration_seconds: int\\n 26| hook: str\\n 27| script_outline: str\\n 28| visual_concept: str\\n 29| caption: str\\n 30| cta: str\\n 31| hashtags: tuple[str, ...]\\n 32| quality_score: ScriptQualityScore\\n 33| policy_notes: tuple[str, ...]\\n 34| hypothesis: str\\n 35|\\n 36| def to_review_package(self, preview_path: str | None = None) -> ReviewPackage:\\n 37| return ReviewPackage(\\n 38| candidate_id=self.candidate_id,\\n 39| title=self.title,\\n 40| pillar=self.pillar,\\n 41| duration_seconds=self.duration_seconds,\\n 42| hook=self.hook,\\n 43| script_summary=self.script_outline,\\n 44| visual_concept=self.visual_concept,\\n 45| caption=self.caption,\\n 46| hashtags=self.hashtags,\\n 47| platforms=self.platforms,\\n 48| quality_score=self.quality_score,\\n 49| policy_notes=self.policy_notes,\\n 50| preview_path=preview_path,\\n 51| )\\n 52|\\n 53|\\n 54|def _is_blank(value: str) -> bool:\\n 55| return not (value or \\\"\\\").strip()\\n 56|\\n 57|\\n 58|def validate_candidate(candidate: VideoCandidate) -> ValidationResult:\\n 59| errors: list[str] = []\\n 60|\\n 61| required_fields = {\\n 62| \\\"candidate_id\\\": candidate.candidate_id,\\n 63| \\\"pillar\\\": candidate.pillar,\\n 64| \\\"title\\\": candidate.title,\\n 65| \\\"hook\\\": candidate.hook,\\n 66| \\\"script_outline\\\": candidate.script_outline,\\n 67| \\\"visual_concept\\\": candidate.visual_concept,\\n 68| \\\"caption\\\": candidate.caption,\\n 69| \\\"cta\\\": candidate.cta,\\n 70| \\\"hypothesis\\\": candidate.hypothesis,\\n 71| }\\n 72| for field_name, value in required_fields.items():\\n 73| if _is_blank(value):\\n 74| errors.append(f\\\"{field_name} is required\\\")\\n 75|\\n 76| if not 10 <= candidate.duration_seconds <= 180:\\n 77| errors.append(\\\"duration_seconds must be between 10 and 180\\\")\\n 78|\\n 79| if not candidate.platforms:\\n 80| errors.append(\\\"at least one platform is required\\\")\\n 81| for platform in candidate.platforms:\\n 82| if platform not in SUPPORTED_PLATFORMS:\\n 83| errors.append(f\\\"unsupported platform: {platform}\\\")\\n 84|\\n 85| return ValidationResult(is_valid=not errors, errors=tuple(errors))\\n 86|\", \"total_lines\": 85, \"file_size\": 2557, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_qNxqTotFjM6fV9C8GavGWACz", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": 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ai_slop_risk=2,\\n 18| policy_risk=\\\"low\\\",\\n 19| )\\n 20|\\n 21|\\n 22|def _candidate(\\n 23| *,\\n 24| candidate_id: str,\\n 25| title: str,\\n 26| duration_seconds: int,\\n 27| hook: str,\\n 28| script_outline: str,\\n 29| visual_concept: str,\\n 30| caption: str,\\n 31| cta: str,\\n 32| hypothesis: str,\\n 33| hashtags: tuple[str, ...] = (\\\"#AI\\\", \\\"#AISystems\\\", \\\"#Workflow\\\"),\\n 34|) -> VideoCandidate:\\n 35| return apply_brand_metadata(\\n 36| VideoCandidate(\\n 37| candidate_id=candidate_id,\\n 38| pillar=\\\"ai_life_systems\\\",\\n 39| title=title,\\n 40| platforms=(\\\"youtube\\\", \\\"tiktok\\\"),\\n 41| duration_seconds=duration_seconds,\\n 42| hook=hook,\\n 43| script_outline=script_outline,\\n 44| visual_concept=visual_concept,\\n 45| caption=caption,\\n 46| cta=cta,\\n 47| hashtags=hashtags,\\n 48| quality_score=_score(),\\n 49| policy_notes=(\\\"Concept testbatch: concrete TrueTrace direction\\\",),\\n 50| hypothesis=hypothesis,\\n 51| ),\\n 52| TRUETRACE_SHORTS_BRAND,\\n 53| )\\n 54|\\n 55|\\n 56|def build_truetrace_concept_batch() -> TestBatch:\\n 57| \\\"\\\"\\\"Build five concrete public-safe TrueTraceShorts concept candidates.\\\"\\\"\\\"\\n 58|\\n 59| return TestBatch(\\n 60| batch_id=\\\"truetrace-concept-testbatch-001\\\",\\n 61| candidates=(\\n 62| _candidate(\\n 63| candidate_id=\\\"truetrace-ai-automation-quiet-rot-38s\\\",\\n 64| title=\\\"Why Most AI Automations Break After Three Days\\\",\\n 65| duration_seconds=38,\\n 66| hook=\\\"Most AI automations do not fail dramatically. They quietly rot.\\\",\\n 67| script_outline=(\\n 68| \\\"Show a day-one workflow turning from green to red over a week. Reveal that the missing system piece \\\"\\n 69| \\\"is an exception path for weird inputs, uncertain outputs, review, and stop conditions. End with the rule: \\\"\\n 70| \\\"no exception path means fragile automation.\\\"\\n 71| ),\\n 72| visual_concept=(\\n 73| \\\"Dark timeline Day 1, Day 3, Day 7; output cards degrade from green to red; split diagram for normal, \\\"\\n 74| \\\"weird, and uncertain input; final failure/autopsy card.\\\"\\n 75| ),\\n 76| caption=\\\"AI automations rarely explode. They quietly rot when the workflow has no exception path.\\\",\\n 77| cta=\\\"Follow for practical AI systems, not automation theatre.\\\",\\n 78| hypothesis=\\\"A failure autopsy with the phrase quietly rot should create stronger retention than generic AI automation tips.\\\",\\n 79| ),\\n 80| _candidate(\\n 81| candidate_id=\\\"truetrace-prompt-vs-system-workflow-breaks-35s\\\",\\n 82| title=\\\"This Prompt Looks Smart — But the Workflow Still Breaks\\\",\\n 83| duration_seconds=35,\\n 84| hook=\\\"This is why your perfect AI prompt still fails tomorrow.\\\",\\n 85| script_outline=(\\n 86| \\\"Open with a glowing prompt card, then show it failing because the surrounding system is missing. Contrast prompt asks \\\"\\n 87| \\\"with system checks: allowed input, useful output, review step, and action boundary. End with prompt is not system.\\\"\\n 88| ),\\n 89| visual_concept=(\\n 90| \\\"Prompt card collapses into warnings; Input to AI to Review to Action flow; missing review gate highlighted; \\\"\\n 91| \\\"final Systems over prompts rule card.\\\"\\n 92| ),\\n 93| caption=\\\"A better prompt will not fix a broken workflow. Draw the system boundary first.\\\",\\n 94| cta=\\\"Follow for systems over prompts.\\\",\\n 95| hypothesis=\\\"Direct anti-prompt positioning should attract viewers tired of generic prompt-hack content.\\\",\\n 96| ),\\n 97| _candidate(\\n 98| candidate_id=\\\"truetrace-ai-notes-equal-importance-34s\\\",\\n 99| title=\\\"The Hidden Reason Your AI Notes Become Useless\\\",\\n 100| duration_seconds=34,\\n 101| hook=\\\"AI notes fail when everything becomes equally important.\\\",\\n 102| script_outline=(\\n 103| \\\"Show a pretty AI notes page flooding with equal bullet points. Reveal the mechanism: summaries fail when facts, \\\"\\n 104| \\\"decisions, risks, questions, and next actions have the same weight. End with ask for decision structure, not notes.\\\"\\n 105| ),\\n 106| visual_concept=(\\n 107| \\\"Pretty notes card; bullet flood; equality warning; five-column structure: facts, decisions, risks, questions, actions; \\\"\\n 108| \\\"final rule card.\\\"\\n 109| ),\\n 110| caption=\\\"Pretty AI notes are not the same as useful decisions. Ask for structure, not notes.\\\",\\n 111| cta=\\\"Follow for AI workflows that survive real use.\\\",\\n 112| hypothesis=\\\"A daily productivity pain point should broaden reach beyond hard technical AI audiences.\\\",\\n 113| ),\\n 114| _candidate(\\n 115| candidate_id=\\\"truetrace-ai-agents-tasks-not-teams-40s\\\",\\n 116| title=\\\"Claim: AI Agents Will Replace Teams\\\",\\n 117| duration_seconds=40,\\n 118| hook=\\\"Verdict: not unless they can handle boundaries.\\\",\\n 119| script_outline=(\\n 120| \\\"Use AI Hype Court format: claim, evidence, problem, verdict, better action. Agents can draft, summarize, search, and trigger, \\\"\\n 121| \\\"but ownership requires priorities, exceptions, tradeoffs, accountability, and messy context. Verdict: tasks first, not teams.\\\"\\n 122| ),\\n 123| visual_concept=(\\n 124| \\\"Hype Court stamp; claim card; evidence scale; responsibility gap warning; verdict stamp reading tasks, not teams.\\\"\\n 125| ),\\n 126| caption=\\\"AI agents can replace tasks first. They do not automatically replace teams.\\\",\\n 127| cta=\\\"Follow for AI hype checks with useful verdicts.\\\",\\n 128| hypothesis=\\\"A skeptical verdict on a popular AI claim should invite comments while staying public-safe.\\\",\\n 129| hashtags=(\\\"#AI\\\", \\\"#AIAgents\\\", \\\"#AISystems\\\", \\\"#Workflow\\\"),\\n 130| ),\\n 131| _candidate(\\n 132| candidate_id=\\\"truetrace-review-before-automation-32s\\\",\\n 133| title=\\\"One Rule Before You Automate Anything With AI\\\",\\n 134| duration_seconds=32,\\n 135| hook=\\\"If you cannot review it manually, do not automate it yet.\\\",\\n 136| script_outline=(\\n 137| \\\"State one rule, then one safe example: feedback to AI summary to checklist to decision. Show why missing complaints, \\\"\\n 138| \\\"invented patterns, and loud-comment bias need a review checklist before automation.\\\"\\n 139| ),\\n 140| visual_concept=(\\n 141| \\\"Rule card; bad workflow in red; better workflow with checklist; three checklist warnings; final Review before automation card.\\\"\\n 142| ),\\n 143| caption=\\\"Automate after you can review. Not before.\\\",\\n 144| cta=\\\"Follow for simple rules for safer AI systems.\\\",\\n 145| hypothesis=\\\"A compact operating rule should be saveable and build trust even if it is less viral than failure-led hooks.\\\",\\n 146| ),\\n 147| ),\\n 148| )\\n 149|\\n 150|\\n 151|def render_truetrace_concept_summary() -> str:\\n 152| \\\"\\\"\\\"Render the five-concept testbatch for human strategy review without action language.\\\"\\\"\\\"\\n 153|\\n 154| batch = build_truetrace_concept_batch()\\n 155| lines = [\\n 156| \\\"## TrueTrace Concept Testbatch\\\",\\n 157| f\\\"Batch: {batch.batch_id}\\\",\\n 158| f\\\"Candidates: {len(batch.candidates)}\\\",\\n 159| f\\\"Brand: {TRUETRACE_SHORTS_BRAND.channel_name} — {TRUETRACE_SHORTS_BRAND.tagline}\\\",\\n 160| \\\"\\\",\\n 161| ]\\n 162| for index, candidate in enumerate(batch.candidates, start=1):\\n 163| youtube_description = f\\\"{candidate.caption}\\\\n\\\\n{candidate.cta}\\\\n\\\\n{' '.join(candidate.hashtags)}\\\"\\n 164| tiktok_caption = f\\\"{candidate.caption} {' '.join(candidate.hashtags)}\\\"\\n 165| lines.extend(\\n 166| [\\n 167| f\\\"## {index}. {candidate.title}\\\",\\n 168| f\\\"ID: {candidate.candidate_id}\\\",\\n 169| f\\\"Duration: {candidate.duration_seconds}s\\\",\\n 170| f\\\"Hook: {candidate.hook}\\\",\\n 171| f\\\"Outline: {candidate.script_outline}\\\",\\n 172| f\\\"Visuals: {candidate.visual_concept}\\\",\\n 173| f\\\"Hypothesis: {candidate.hypothesis}\\\",\\n 174| f\\\"YouTube: {youtube_description}\\\",\\n 175| f\\\"TikTok: {tiktok_caption}\\\",\\n 176| f\\\"Tags: {', '.join(TRUETRACE_SHORTS_BRAND.youtube_tags)}\\\",\\n 177| \\\"\\\",\\n 178| ]\\n 179| )\\n 180| return \\\"\\\\n\\\".join(lines).strip()\\n 181|\", \"total_lines\": 180, \"file_size\": 9056, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_BoOVBpEdwsuU9Cao8KKqiCYZ", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", 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"id": "rs_0dc9f371a6d55e3f016a1396387ddc8191be8f1719a7445d51", "summary": []}], "tool_calls": [{"id": "call_KyGOJFW7OZQYYke5189aYCgT", "call_id": "call_KyGOJFW7OZQYYke5189aYCgT", "response_item_id": "fc_0dc9f371a6d55e3f016a1396406ae08191b41dd4d3f5b004bb", "type": "function", "function": {"name": "write_file", "arguments": "{\"content\":\"from autoshorts.social.final_approval import (\\n FinalVideoApprovalPackage,\\n build_truetrace_weird_email_final_approval_package,\\n render_final_video_approval_review,\\n validate_final_video_approval_package,\\n)\\n\\n\\ndef test_build_truetrace_weird_email_final_approval_package_is_approval_first():\\n package = build_truetrace_weird_email_final_approval_package(\\n media_path=\\\"data/final_exports/truetrace/final.mp4\\\",\\n checksum_sha256=\\\"2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b\\\",\\n )\\n\\n assert isinstance(package, FinalVideoApprovalPackage)\\n assert package.candidate_id == \\\"truetrace-ai-automation-quiet-rot-38s\\\"\\n assert package.media_path.endswith(\\\"final.mp4\\\")\\n assert package.checksum_sha256 == \\\"2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b\\\"\\n assert package.platforms == (\\\"youtube\\\", \\\"tiktok\\\")\\n assert package.platform_labels == (\\\"YouTube Shorts\\\", \\\"TikTok\\\")\\n assert package.final_video_language == \\\"en\\\"\\n assert package.approval_language == \\\"de\\\"\\n assert package.duration_seconds == 37\\n assert package.resolution == \\\"1080x1920\\\"\\n assert package.requires_human_approval is True\\n assert package.side_effects == ()\\n assert \\\"weird email\\\" in package.hook.casefold()\\n assert \\\"exception path\\\" not in package.caption.casefold()\\n assert package.hashtags == (\\\"#AI\\\", \\\"#AISystems\\\", \\\"#Workflow\\\")\\n\\n\\ndef test_render_final_video_approval_review_is_telegram_safe_and_no_action_language():\\n package = build_truetrace_weird_email_final_approval_package(\\n media_path=\\\"data/final_exports/truetrace/final.mp4\\\",\\n checksum_sha256=\\\"2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b\\\",\\n )\\n\\n text = render_final_video_approval_review(package)\\n\\n assert \\\"## Final Video Review\\\" in text\\n assert \\\"Freigabe YouTube\\\" in text\\n assert \\\"Freigabe TikTok\\\" in text\\n assert \\\"Freigabe alle\\\" in text\\n assert \\\"Ablehnen\\\" in text\\n assert \\\"Ändern:\\\" in text\\n assert \\\"data/final_exports/truetrace/final.mp4\\\" in text\\n assert package.checksum_sha256 in text\\n assert len(text) < 4096\\n assert \\\"publish\\\" not in text.casefold()\\n assert \\\"post\\\" not in text.casefold()\\n\\n\\ndef test_validate_final_video_approval_package_rejects_unsafe_fields():\\n package = FinalVideoApprovalPackage(\\n candidate_id=\\\"\\\",\\n media_path=\\\"final.mov\\\",\\n checksum_sha256=\\\"bad\\\",\\n platforms=(\\\"linkedin\\\",),\\n platform_labels=(\\\"LinkedIn\\\",),\\n title_variants=(),\\n caption=\\\"\\\",\\n hashtags=(),\\n hook=\\\"\\\",\\n duration_seconds=9,\\n resolution=\\\"540x960\\\",\\n quality_notes=\\\"\\\",\\n approval_language=\\\"en\\\",\\n final_video_language=\\\"de\\\",\\n requires_human_approval=False,\\n side_effects=(\\\"send_telegram\\\",),\\n )\\n\\n result = validate_final_video_approval_package(package)\\n\\n assert result.is_valid is False\\n assert \\\"candidate_id is required\\\" in result.errors\\n assert \\\"media_path must end with .mp4\\\" in result.errors\\n assert \\\"checksum_sha256 must be a 64-character hex string\\\" in result.errors\\n assert \\\"unsupported platform: linkedin\\\" in result.errors\\n assert \\\"at least one title variant is required\\\" in result.errors\\n assert \\\"caption is required\\\" in result.errors\\n assert \\\"human approval is required\\\" in result.errors\\n assert \\\"final video approval packages must not have side effects\\\" in result.errors\\n\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_final_video_approval.py\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "write_file", "content": "{\"bytes_written\": 3402, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}, \"lsp_diagnostics\": \"LSP diagnostics introduced by this edit:\\n\\nERROR [1:6] Import \\\"autoshorts.social.final_approval\\\" could not be resolved [reportMissingImports] (Pyright)\\n\"}", "tool_call_id": "call_KyGOJFW7OZQYYke5189aYCgT", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_0wNCUXkTHRGSxsJB7nvnoHwH", "call_id": "call_0wNCUXkTHRGSxsJB7nvnoHwH", "response_item_id": "fc_0dc9f371a6d55e3f016a13966366c081919227eb620cb07aa7", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_final_video_approval.py -q\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"==================================== ERRORS ====================================\\n_____________ ERROR collecting tests/test_final_video_approval.py ______________\\nImportError while importing test module '/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/tests/test_final_video_approval.py'.\\nHint: make sure your test modules/packages have valid Python names.\\nTraceback:\\n../../../.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/importlib/__init__.py:126: in import_module\\n return _bootstrap._gcd_import(name[level:], package, level)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\ntests/test_final_video_approval.py:1: in \\n from autoshorts.social.final_approval import (\\nE ModuleNotFoundError: No module named 'autoshorts.social.final_approval'\\n=========================== short test summary info ============================\\nERROR tests/test_final_video_approval.py\\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\\n1 error in 0.13s\", \"exit_code\": 2, \"error\": null}", "tool_call_id": "call_0wNCUXkTHRGSxsJB7nvnoHwH", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_SfyBQmoZCrCQU3oOhG36DprQ", "call_id": "call_SfyBQmoZCrCQU3oOhG36DprQ", "response_item_id": "fc_0dc9f371a6d55e3f016a139667e2208191a64dec15a1855625", "type": "function", "function": {"name": "write_file", "arguments": "{\"content\":\"\\\"\\\"\\\"Approval-first package for final-near rendered videos.\\\"\\\"\\\"\\n\\nfrom __future__ import annotations\\n\\nfrom dataclasses import dataclass\\nimport re\\n\\nfrom autoshorts.ideas.candidate import SUPPORTED_PLATFORMS, ValidationResult\\n\\n_PLATFORM_LABELS = {\\n \\\"youtube\\\": \\\"YouTube Shorts\\\",\\n \\\"tiktok\\\": \\\"TikTok\\\",\\n \\\"instagram\\\": \\\"Instagram Reels\\\",\\n}\\n_SHA256_RE = re.compile(r\\\"^[a-fA-F0-9]{64}$\\\")\\n\\n\\n@dataclass(frozen=True)\\nclass FinalVideoApprovalPackage:\\n candidate_id: str\\n media_path: str\\n checksum_sha256: str\\n platforms: tuple[str, ...]\\n platform_labels: tuple[str, ...]\\n title_variants: tuple[str, ...]\\n caption: str\\n hashtags: tuple[str, ...]\\n hook: str\\n duration_seconds: int\\n resolution: str\\n quality_notes: str\\n approval_language: str = \\\"de\\\"\\n final_video_language: str = \\\"en\\\"\\n requires_human_approval: bool = True\\n side_effects: tuple[str, ...] = ()\\n\\n\\ndef _is_blank(value: str) -> bool:\\n return not (value or \\\"\\\").strip()\\n\\n\\ndef build_truetrace_weird_email_final_approval_package(*, media_path: str, checksum_sha256: str) -> FinalVideoApprovalPackage:\\n package = FinalVideoApprovalPackage(\\n candidate_id=\\\"truetrace-ai-automation-quiet-rot-38s\\\",\\n media_path=media_path,\\n checksum_sha256=checksum_sha256,\\n platforms=(\\\"youtube\\\", \\\"tiktok\\\"),\\n platform_labels=(\\\"YouTube Shorts\\\", \\\"TikTok\\\"),\\n title_variants=(\\n \\\"Your AI Automation Works Until One Weird Email Arrives\\\",\\n \\\"Why AI Automations Break When Real Life Shows Up\\\",\\n ),\\n caption=(\\n \\\"Your AI automation does not need a smarter prompt first. It needs a simple plan for weird inputs: \\\"\\n \\\"what goes through, what gets reviewed, and what must stop.\\\"\\n ),\\n hashtags=(\\\"#AI\\\", \\\"#AISystems\\\", \\\"#Workflow\\\"),\\n hook=\\\"Your AI automation works perfectly in the demo. Then one weird email arrives.\\\",\\n duration_seconds=37,\\n resolution=\\\"1080x1920\\\",\\n quality_notes=(\\n \\\"Beginner-friendly weird-email framing; renderer-owned labels and captions; \\\"\\n \\\"scene-specific text-free ChatGPT Image backgrounds; compact phrase-boundary subtitles.\\\"\\n ),\\n approval_language=\\\"de\\\",\\n final_video_language=\\\"en\\\",\\n requires_human_approval=True,\\n side_effects=(),\\n )\\n validation = validate_final_video_approval_package(package)\\n if not validation.is_valid:\\n raise ValueError(\\\"; \\\".join(validation.errors))\\n return package\\n\\n\\ndef validate_final_video_approval_package(package: FinalVideoApprovalPackage) -> ValidationResult:\\n errors: list[str] = []\\n for field_name, value in {\\n \\\"candidate_id\\\": package.candidate_id,\\n \\\"media_path\\\": package.media_path,\\n \\\"checksum_sha256\\\": package.checksum_sha256,\\n \\\"caption\\\": package.caption,\\n \\\"hook\\\": package.hook,\\n \\\"resolution\\\": package.resolution,\\n \\\"quality_notes\\\": package.quality_notes,\\n \\\"approval_language\\\": package.approval_language,\\n \\\"final_video_language\\\": package.final_video_language,\\n }.items():\\n if _is_blank(value):\\n errors.append(f\\\"{field_name} is required\\\")\\n\\n if package.media_path and not package.media_path.endswith(\\\".mp4\\\"):\\n errors.append(\\\"media_path must end with .mp4\\\")\\n if package.checksum_sha256 and not _SHA256_RE.match(package.checksum_sha256):\\n errors.append(\\\"checksum_sha256 must be a 64-character hex string\\\")\\n if not package.platforms:\\n errors.append(\\\"at least one platform is required\\\")\\n for platform in package.platforms:\\n if platform not in SUPPORTED_PLATFORMS:\\n errors.append(f\\\"unsupported platform: {platform}\\\")\\n if len(package.platform_labels) != len(package.platforms):\\n errors.append(\\\"platform_labels must match platforms\\\")\\n for platform, label in zip(package.platforms, package.platform_labels):\\n expected = _PLATFORM_LABELS.get(platform)\\n if expected is not None and label != expected:\\n errors.append(f\\\"platform label for {platform} must be {expected}\\\")\\n if not package.title_variants:\\n errors.append(\\\"at least one title variant is required\\\")\\n elif any(_is_blank(title) for title in package.title_variants):\\n errors.append(\\\"title variants must not be blank\\\")\\n if not package.hashtags:\\n errors.append(\\\"at least one hashtag is required\\\")\\n elif any(_is_blank(hashtag) for hashtag in package.hashtags):\\n errors.append(\\\"hashtags must not be blank\\\")\\n if not 10 <= package.duration_seconds <= 180:\\n errors.append(\\\"duration_seconds must be between 10 and 180\\\")\\n if package.resolution != \\\"1080x1920\\\":\\n errors.append(\\\"resolution must be 1080x1920\\\")\\n if package.approval_language != \\\"de\\\":\\n errors.append(\\\"approval_language must be de\\\")\\n if package.final_video_language != \\\"en\\\":\\n errors.append(\\\"final_video_language must be en\\\")\\n if not package.requires_human_approval:\\n errors.append(\\\"human approval is required\\\")\\n if package.side_effects:\\n errors.append(\\\"final video approval packages must not have side effects\\\")\\n return ValidationResult(is_valid=not errors, errors=tuple(errors))\\n\\n\\ndef _platform_command(platform: str) -> str:\\n if platform == \\\"youtube\\\":\\n return \\\"Freigabe YouTube\\\"\\n if platform == \\\"tiktok\\\":\\n return \\\"Freigabe TikTok\\\"\\n if platform == \\\"instagram\\\":\\n return \\\"Freigabe Instagram\\\"\\n return f\\\"Freigabe {platform}\\\"\\n\\n\\ndef render_final_video_approval_review(package: FinalVideoApprovalPackage) -> str:\\n validation = validate_final_video_approval_package(package)\\n if not validation.is_valid:\\n raise ValueError(\\\"; \\\".join(validation.errors))\\n\\n titles = \\\"\\\\n\\\".join(f\\\"- {title}\\\" for title in package.title_variants)\\n commands = \\\"\\\\n\\\".join(\\n f\\\"- {command}\\\"\\n for command in (\\n *(_platform_command(platform) for platform in package.platforms),\\n \\\"Freigabe alle\\\",\\n \\\"Ablehnen\\\",\\n \\\"Ändern: \\\",\\n )\\n )\\n text = \\\"\\\\n\\\".join(\\n (\\n \\\"## Final Video Review\\\",\\n \\\"\\\",\\n f\\\"Candidate: {package.candidate_id}\\\",\\n f\\\"Media: {package.media_path}\\\",\\n f\\\"SHA256: {package.checksum_sha256}\\\",\\n f\\\"Platforms: {', '.join(package.platform_labels)}\\\",\\n f\\\"Language: final={package.final_video_language}, review={package.approval_language}\\\",\\n f\\\"Duration: {package.duration_seconds}s\\\",\\n f\\\"Resolution: {package.resolution}\\\",\\n \\\"\\\",\\n \\\"Hook:\\\",\\n package.hook,\\n \\\"\\\",\\n \\\"Title variants:\\\",\\n titles,\\n \\\"\\\",\\n \\\"Caption:\\\",\\n package.caption,\\n \\\"\\\",\\n f\\\"Hashtags: {' '.join(package.hashtags)}\\\",\\n f\\\"Quality notes: {package.quality_notes}\\\",\\n \\\"Requires human approval: yes\\\",\\n \\\"Side effects: none\\\",\\n \\\"\\\",\\n \\\"Approval commands:\\\",\\n commands,\\n )\\n )\\n lowered = text.casefold()\\n if \\\"publish\\\" in lowered or \\\"post\\\" in lowered:\\n raise ValueError(\\\"final video review must not imply publishing\\\")\\n if len(text) > 4096:\\n raise ValueError(\\\"final video review exceeds Telegram limit\\\")\\n return text\\n\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/autoshorts/social/final_approval.py\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "write_file", "content": "{\"bytes_written\": 7297, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_SfyBQmoZCrCQU3oOhG36DprQ", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_Mk31BSVs6GwVTDkkIA0ieEQu", "call_id": "call_Mk31BSVs6GwVTDkkIA0ieEQu", "response_item_id": "fc_0dc9f371a6d55e3f016a1396944798819181e17f45765f4b96", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/test_final_video_approval.py -q\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"... [100%]\\n3 passed in 0.04s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_Mk31BSVs6GwVTDkkIA0ieEQu", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": "**Evaluating approval process**\n\nI need to generate real approval text and possibly send media in the final package. It feels important to update the docs and readme too. I'm considering if I should create a CLI, but maybe continuing with just the final approval package will be enough for now. I should also test the review with an actual hash, and I need to run a script to render the text.", "finish_reason": "tool_calls", "reasoning_content": "**Evaluating approval process**\n\nI need to generate real approval text and possibly send media in the final package. It feels important to update the docs and readme too. I'm considering if I should create a CLI, but maybe continuing with just the final approval package will be enough for now. I should also test the review with an actual hash, and I need to run a script to render the text.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE5ab7kCYgYRLYLKqybzzhTkhGPQK73ii5gvX3nVp7aGSc3p26XYtm3hQTOTfJzuWCETHeHgugw3xOkEitN_9AK4tr9NWfpIJdlHlEHveUWIVBMUeTONnvn0a0VunKGOflVGX5G7-j5aaFtBgQHzfQ2eQvDtzXW_BqPSn9d8IKgj9jOj0j8KmC5CqIdsWUEU6PfhTaZW8fiOOLsMF1DHa1hs4hLus8MHL-SfPQoHAZnO3Sn7LwY4IeoDWGH9gHmL6cKxWJujsP0vO8Fq7Yv9cXqLbpdW6TPEk33PUIz5XIE93XO3TiAek9iCF01He8vaOmayxqSPMvFGPshpiQ-fmp7fdBMmFgwOk_KFrfILwoHs5s5WmdPm0p-qm1GbLMEjsRBleVLFHWaLnSUgqot5VJV2peg0jbyOo2IZ84OxmDby1kT-abdxbQ65AD-fSGnty1CKyycd_pOKRPF_0jSyYe1wzhNcxjDR9wpZQQYIRsYZQTqQ_IYXR_tfxKxRHmop_XWL76tn_86XhCancWrfsKEmW4_GSvTrOwPa0VyNVyTL5PLmiJABs1JfVU4-h-IsTEiwVfOcIrOiZflKBC6-e8BESNYwsISLk1LWyh_MSd0pCNwY07LdgHEQ9Eoka7vU87LiEIyLdMwteHNOpPU6kwpJm_Lw_tZn2ThpnDA2j6qY58l7COn62EGMk9wEMGYwKb-9A_1ru0jt2rPtBbHrr9bwCGssXxrw2TFsOI85RxWJ3PU66VsrIjeIf2G8KA63dAl0n_1yDL8AQSGjkAHCQL_IbzlA7UWllr2uzYHMjb_0XSI4MmHAKiR5W2xB0ndL28WkIwg6GX80jPWzfzO58kN2qTjd-aDdvLzHdiIvV2gpxGibPbeD2biun3cTN8mfTLBk9ky3o7THNcOqk2fSNzkTfaDij7R-uIAWL5g_jn64pt5BujYXODLQNJjwIG5k2YDVXjNAwWqlqvbmL1u0DUPyJ-_LR1LqqU7_p3d6B6nJ20R_5IqovscWoJVjAxZUiPjKtxGqJAY0L-ctvctvzHeBAZknLcNLl6aDR2DCBLKEkXyrMduYSduU7XJFwrXA8GeEkO8zmfihecJF6DANwJKppDNftceJ4g6I7J45OLBsV9c2I_mcA8sY8XUg7L6iJCANnWh7UnW2uOD0qCne3s259xX4aWtEgh7uej9KlpfEj4WCAl5RPzc1RBRj1z5uC3WO_9Y3UsEXTYWjpqYOVN5p_JQ==", "id": "rs_0dc9f371a6d55e3f016a13969910b4819198ef8c3a1c6bbe13", "summary": [{"type": "summary_text", "text": "**Evaluating approval process**\n\nI need to generate real approval text and possibly send media in the final package. It feels important to update the docs and readme too. I'm considering if I should create a CLI, but maybe continuing with just the final approval package will be enough for now. I should also test the review with an actual hash, and I need to run a script to render the text."}]}], "tool_calls": [{"id": "call_WeqpxwPrt8GQA4Dg6dKhDb9Q", "call_id": "call_WeqpxwPrt8GQA4Dg6dKhDb9Q", "response_item_id": "fc_0dc9f371a6d55e3f016a13969b43b481918ddefc694515e076", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nfrom autoshorts.social.final_approval import build_truetrace_weird_email_final_approval_package, render_final_video_approval_review\\nmedia='data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4'\\nsha='2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b'\\npackage=build_truetrace_weird_email_final_approval_package(media_path=media, checksum_sha256=sha)\\ntext=render_final_video_approval_review(package)\\nprint(text)\\nprint('\\\\nTEXT_LENGTH', len(text))\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"## Final Video Review\\n\\nCandidate: truetrace-ai-automation-quiet-rot-38s\\nMedia: data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\\nSHA256: 2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b\\nPlatforms: YouTube Shorts, TikTok\\nLanguage: final=en, review=de\\nDuration: 37s\\nResolution: 1080x1920\\n\\nHook:\\nYour AI automation works perfectly in the demo. Then one weird email arrives.\\n\\nTitle variants:\\n- Your AI Automation Works Until One Weird Email Arrives\\n- Why AI Automations Break When Real Life Shows Up\\n\\nCaption:\\nYour AI automation does not need a smarter prompt first. It needs a simple plan for weird inputs: what goes through, what gets reviewed, and what must stop.\\n\\nHashtags: #AI #AISystems #Workflow\\nQuality notes: Beginner-friendly weird-email framing; renderer-owned labels and captions; scene-specific text-free ChatGPT Image backgrounds; compact phrase-boundary subtitles.\\nRequires human approval: yes\\nSide effects: none\\n\\nApproval commands:\\n- Freigabe YouTube\\n- Freigabe TikTok\\n- Freigabe alle\\n- Ablehnen\\n- Ändern: \\n\\nTEXT_LENGTH 1129\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_WeqpxwPrt8GQA4Dg6dKhDb9Q", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": "**Verifying media files**\n\nI need to ensure that I have the correct absolute path for the media files. It’s important for me to verify that the files exist and check their SHA hash. I plan to use the terminal, as it’s essential for running mandatory hashes, but it might be worth verifying everything again just to be certain. I want to double-check to ensure everything is accurate and in order!", "finish_reason": "tool_calls", "reasoning_content": "**Verifying media files**\n\nI need to ensure that I have the correct absolute path for the media files. It’s important for me to verify that the files exist and check their SHA hash. I plan to use the terminal, as it’s essential for running mandatory hashes, but it might be worth verifying everything again just to be certain. I want to double-check to ensure everything is accurate and in order!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE5am2bCpo-C8OmCrMh--RhYjPpXCKflUHXuyc5Hy08atBGsHe1BmK5ueC9NQujR4Vorvae2LoiJaMFQrQZZFvImSkNFy9LO5s1hZPYs2N1R3TFuKYN1gqLboFm3DEvvMHbDIpp2kHy6VyiGxAD3hTq_EJ5XTloBDCXeimT2uchz5upddPsi9TGMw4fuveQTWelqJt71kLOzk7ACmisbzOkT3gEaCwCofSZN5Wudpc3x5Tfps-GZVPoDQoZJ58DxjSVsqiLU93Uz5INW2xDzmIKQNqmcsJJKcrtyDcBWdgqElj6Y1yvq6_Zv4tYhij4YofKqdkfu-oyZ65Is_7-U_FXr19SjHaANnoj3CFj0GbT_4I0QX20xCNlPVWwTCpUg2t5A2KsdjiNg9KkvDAo0bJ_ijCOoAF5-L5oQjLs6Xk0Lo2z00voYTwYLMYP5HJouMgU_Mb1QubFyV8Y6f77XJL06WdxwNA0-Yc5d6qHNnyuFyVynuwF0nASBCBS55H8QoVg8oQAHztzr5u_fT3pG7teIkINInysEZvL5A5q22mkNW4qGho_tl3sRL5DqNW1rFdMGUeqpFidjYejP72HSAfT2fRtSUg9Yej5I3wTHiiyTmdZ7jurzlesDSUR4edpb7p3Ko3Ej8wjkq2YZxq2tPd4xa7jtTzFCV357NxRHsHfL-lSla7gTKsD0fAzfQP1lrQA_nvRqqKc5cG479tBXg3mXRfxlEMYjvyH1URHp2jhMUBTYyqZYK90AnuUhnnj0JCOAhezLv1HxtyDy2TfvXjVQMPO5L1uuw4dXsw9ozeIaTM14Aj2eyPxVZFkgsCpBHxJCan9lzsFneEXxqXxJP33gTcrP5JjZZ_siAf3cP4dhVZT3MTbLuTcGTcQqXLEiahb1bkqIl8bYYTLmoNxTEKAKElu1ZP47_OIV9WkbVTWhFD5QIJ-RK35Zwba3Div07BuH6LMG2p0CZL6UaDh0wy4Zh99CieQKRfxPUk1qj94xnO83JgeJ6MGf4HvWhwyd9Lzxb4w-H5kHiZkOL0IZiPKKRW-paYGBgWPhVFd0htjwQg4G3DSy52Sv5LCyj-SDrTjmr", "id": "rs_0dc9f371a6d55e3f016a1396a47e5c81919b2e1a7665f440b8", "summary": [{"type": "summary_text", "text": "**Verifying media files**\n\nI need to ensure that I have the correct absolute path for the media files. It’s important for me to verify that the files exist and check their SHA hash. I plan to use the terminal, as it’s essential for running mandatory hashes, but it might be worth verifying everything again just to be certain. I want to double-check to ensure everything is accurate and in order!"}]}], "tool_calls": [{"id": "call_zNOHYvMBDHwgXvi4VOJz0KTz", "call_id": "call_zNOHYvMBDHwgXvi4VOJz0KTz", "response_item_id": "fc_0dc9f371a6d55e3f016a1396a6720c8191bacb439d322af4fd", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"sha256sum /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4 && ffprobe -v error -show_entries stream=codec_type,codec_name,width,height,duration -of default=noprint_wrappers=1 /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b /home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\\ncodec_name=h264\\ncodec_type=video\\nwidth=1080\\nheight=1920\\nduration=36.833333\\ncodec_name=aac\\ncodec_type=audio\\nduration=36.864000\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_zNOHYvMBDHwgXvi4VOJz0KTz", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "Need docs.", "reasoning": null, "finish_reason": "tool_calls", "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Need docs."}], "id": "msg_0dc9f371a6d55e3f016a1396abc3a48191a95cfd85f2f02332", "phase": "commentary"}], "tool_calls": [{"id": "call_hJ0bWPCfbbSQ4rP1UGtiqNZT", "call_id": "call_hJ0bWPCfbbSQ4rP1UGtiqNZT", "response_item_id": "fc_0dc9f371a6d55e3f016a1396ac128881918fbc23b8b3d3fc04", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\",\"old_string\":\"- `autoshorts.social.delivery` — side-effect-free delivery preparation for social draft review messages.\",\"new_string\":\"- `autoshorts.social.delivery` — side-effect-free delivery preparation for social draft review messages.\\n- `autoshorts.social.final_approval` — final-video approval packages with media path, checksum, platform metadata, and Telegram-safe review copy.\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\\n@@ -46,7 +46,8 @@\\n - `autoshorts.rendering.preview` — side-effect-free HTML timeline previews for render manifests.\\n - `autoshorts.rendering.shot_plan` — retention-led shot planner before render manifests or video generation.\\n - `autoshorts.review.package` — Telegram-friendly review package renderer for human approval.\\n-- `autoshorts.social.delivery` — side-effect-free delivery plan for social media draft review text.\\n+- `autoshorts.social.delivery` — side-effect-free delivery preparation for social draft review messages.\\n+- `autoshorts.social.final_approval` — final-video approval packages with media path, checksum, platform metadata, and Telegram-safe review copy.\\n - `autoshorts.social.draft` — approval-first social media draft model from candidate plus render preview.\\n - `autoshorts.social.manual_posting` — side-effect-free manual upload copy pack for phase-1 YouTube/TikTok metadata.\\n - `autoshorts.social.review` — Telegram-safe approval text renderer for social media drafts.\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .md files\"}, \"_warning\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/README.md was modified by sibling subagent '20260524_234753_c12098' but this agent never read it. Read the file before writing to avoid overwriting the sibling's changes.\"}", "tool_call_id": "call_hJ0bWPCfbbSQ4rP1UGtiqNZT", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_SXMNgFaBqDI8Kx8vLKDhduE4", "call_id": "call_SXMNgFaBqDI8Kx8vLKDhduE4", "response_item_id": "fc_0dc9f371a6d55e3f016a1396b494188191b3edf0c35dbf2a6d", "type": "function", "function": {"name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"The 1080 three-way split frame was visually checked for mobile readability, subtitle placement, and clipping.\\n\\n## V8 approval package\\n\\n`autoshorts.social.final_approval` prepares a side-effect-free final video approval package for the rendered candidate. It includes:\\n\\n```text\\nmedia path\\nSHA256 checksum\\nplatform labels\\ntitle variants\\ncaption/hashtags\\nlanguage metadata\\nquality notes\\napproval commands\\n```\\n\\nThe rendered review text stays below Telegram's limit and avoids implicit action words such as `publish` or `post`. It does not send anything; Telegram/media delivery remains an explicit human-approved boundary.\",\"old_string\":\"The 1080 three-way split frame was visually checked for mobile readability, subtitle placement, and clipping.\",\"path\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\\n+++ b//home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\\n@@ -108,3 +108,20 @@\\n ```\\n \\n The 1080 three-way split frame was visually checked for mobile readability, subtitle placement, and clipping.\\n+\\n+## V8 approval package\\n+\\n+`autoshorts.social.final_approval` prepares a side-effect-free final video approval package for the rendered candidate. It includes:\\n+\\n+```text\\n+media path\\n+SHA256 checksum\\n+platform labels\\n+title variants\\n+caption/hashtags\\n+language metadata\\n+quality notes\\n+approval commands\\n+```\\n+\\n+The rendered review text stays below Telegram's limit and avoids implicit action words such as `publish` or `post`. It does not send anything; Telegram/media delivery remains an explicit human-approved boundary.\\n\", \"files_modified\": [\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .md files\"}, \"_warning\": \"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/docs/final_motion_prototype.md was modified by sibling subagent '20260524_234753_c12098' but this agent never read it. Read the file before writing to avoid overwriting the sibling's changes.\"}", "tool_call_id": "call_SXMNgFaBqDI8Kx8vLKDhduE4", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_XTFweIRTxk5pRVobpOAzkAyB", "call_id": "call_XTFweIRTxk5pRVobpOAzkAyB", "response_item_id": "fc_0dc9f371a6d55e3f016a1396c0d7a48191b220a2888f947457", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"pytest tests/ -q\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"........................................................................ [ 41%]\\n........................................................................ [ 83%]\\n............................ [100%]\\n172 passed in 32.86s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_XTFweIRTxk5pRVobpOAzkAyB", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_Rouqda50Ttkzg0Pvx2z4S7Rl", "call_id": "call_Rouqda50Ttkzg0Pvx2z4S7Rl", "response_item_id": "fc_0dc9f371a6d55e3f016a1396ecba688191a5c377e82e6c8ee3", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"git status --short && git add autoshorts/social/final_approval.py tests/test_final_video_approval.py README.md docs/final_motion_prototype.md && git commit -m \\\"feat: add final video approval package\\\" && git status --short && git log --oneline -5\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot\"}"}}], "timestamp": "2026-05-25T02:25:38.100301"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"M README.md\\n M docs/final_motion_prototype.md\\n?? autoshorts/social/final_approval.py\\n?? tests/test_final_video_approval.py\\n[feat/core-approval-quality-gates 8598dcd] feat: add final video approval package\\n 4 files changed, 292 insertions(+), 1 deletion(-)\\n create mode 100644 autoshorts/social/final_approval.py\\n create mode 100644 tests/test_final_video_approval.py\\n8598dcd feat: add final video approval package\\n033334c feat: compact final motion subtitles\\ndb200ae feat: add scene-specific motion backgrounds\\n14310f9 feat: add TrueTrace final motion prototype\\n7375311 feat: make TrueTrace pilot beginner friendly\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_Rouqda50Ttkzg0Pvx2z4S7Rl", "timestamp": "2026-05-25T02:25:38.100301"} {"role": "assistant", "content": "Erledigt, Sir.\n\nIch habe jetzt den nächsten sauberen Schritt gebaut: **Final Video Approval Package** — also nicht nur ein MP4, sondern ein prüfbares Freigabe-Paket mit Metadata, Checksums, Titelvarianten, Caption, Hashtags und Approval Commands.\n\n## Neuer Commit\n\n```text\n8598dcd feat: add final video approval package\n```\n\n## Neu gebaut\n\n```text\nautoshorts/social/final_approval.py\ntests/test_final_video_approval.py\n```\n\n## Was das Package enthält\n\n```text\nCandidate-ID\nMedia-Pfad\nSHA256\nPlattformen\nTitelvarianten\nCaption\nHashtags\nHook\nDauer\nResolution\nQuality Notes\nFreigabe-Kommandos\n```\n\nAlles weiterhin:\n\n```text\nrequires_human_approval=True\nside_effects=()\nkeine Telegram/API Calls\nkein Upload\n```\n\nAlso keine heimliche Content-Katapultierung. Sehr zivilisiert.\n\n---\n\n## Final Video Review Package\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\n\n## Metadata\n\nCandidate:\n\n```text\ntruetrace-ai-automation-quiet-rot-38s\n```\n\nSHA256 verifiziert:\n\n```text\n2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b\n```\n\nVideo:\n\n```text\nResolution: 1080x1920\nDuration: 36.833s\nAudio duration: 36.864s\nVideo codec: h264\nAudio codec: aac\n```\n\nPlatforms:\n\n```text\nYouTube Shorts\nTikTok\n```\n\nFinal language:\n\n```text\nEnglish\n```\n\nReview language:\n\n```text\nGerman\n```\n\n---\n\n## Titelvarianten\n\n```text\nYour AI Automation Works Until One Weird Email Arrives\n```\n\n```text\nWhy AI Automations Break When Real Life Shows Up\n```\n\n## Caption\n\n```text\nYour AI automation does not need a smarter prompt first. It needs a simple plan for weird inputs: what goes through, what gets reviewed, and what must stop.\n```\n\n## Hashtags\n\n```text\n#AI #AISystems #Workflow\n```\n\n## Hook\n\n```text\nYour AI automation works perfectly in the demo. Then one weird email arrives.\n```\n\n## Quality Notes\n\n```text\nBeginner-friendly weird-email framing;\nrenderer-owned labels and captions;\nscene-specific text-free ChatGPT Image backgrounds;\ncompact phrase-boundary subtitles.\n```\n\n---\n\n## Approval Commands\n\nWenn Sie ihn freigeben wollen:\n\n```text\nFreigabe YouTube\n```\n\n```text\nFreigabe TikTok\n```\n\n```text\nFreigabe alle\n```\n\nOder:\n\n```text\nAblehnen\n```\n\n```text\nÄndern: \n```\n\n## Tests\n\nFull Suite:\n\n```text\n172 passed in 32.86s\n```\n\n## Aktueller Commit-Verlauf\n\n```text\n8598dcd feat: add final video approval package\n033334c feat: compact final motion subtitles\ndb200ae feat: add scene-specific motion backgrounds\n14310f9 feat: add TrueTrace final motion prototype\n7375311 feat: make TrueTrace pilot beginner friendly\n```\n\nDer Clip ist jetzt technisch und organisatorisch in einem Zustand, wo er sauber reviewed werden kann: Video + Social Metadata + Freigabe-Sprache + Checksums.", "reasoning": null, "finish_reason": "stop", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqE5bzsfz-qhUpNkJV87Cmk8chAygAwXxB9ENHy0NLBYnHf_gc54-RhbOt15AZ0u2C4bxs5hWgNTzyjRrYzKbnUgRWq0SCrVnYH12LLTeOizSWH_-hj6ssYU6s52KKFL3SLvRwvOGdlMJqazuVtWalw0Xk_eAvpL9Q_f-i9tkFKxcWaWSVgKBJx-6T8y2cMcofcgU_1ZicnUAHJep6Pb2449hZF62quHHKUenyyyBuoEdS8GQytigOW3BOccHJSgEe0CBWd2eh587oqoJ7CJxWGLJvZWriZGboU3lfYFAbZ5UoiGLQWi8Fwn-tNICGrJEre_FkNmmGBAh7lxYKZ5bLF_uXbe5GSRFK9hc03zQk7-H8ATNIq95sa70Ba2oCjhcCuT2EG3EJPlVsaeRZLD1TuLk9RK41-pYkgifcHsn8GrguDKnqz2Ma4TiLqsxDNPuDo6H6COjDxWbM-wllMKmpa7QcqmITyUZFU9jZdW3WLdwMfAi9-KzmZ6ZMeQTn3awI7YjtyuiPS4TJzhjF7WSnOINkSFLK73mJzKTbgGeDFGw0MmY12DVCoLpBERGkx_1pUd6FPNfH1a1K4T0EdvewwZSr4go1pf1A3eV2CC-axgSBvr7xHdCPBu-b6SPKa8BQ2aYJhljfhzNWDtL3GtdMEhMIDv0WX4DfqSXNBYa6AmR1mn3Jix41dqjkZQwJxPw1Uly9_sMPY15dKa1VFSoqULIo3bYi5mzOCKuCeqashd57obIaDX6xu8tbM9valCGOjPbyGtTqGsuJ8ZxgUvAQfrHP1EO5pNhNySbx5HnRa3XvJsU7hhtAgBpkuJN1BtLrVCqa1QW-0ZO5FEUUmreV6WnaNnVocJpmyJzuPLBReCASyYBLGsm8EdNnSLUYcddZsxZkaW0Dn51n8_NywtclvzxsoP2e6jRCEpuR2oKSHC4IO_dBOboppRvWafwgAYOiW7C-v2E9ST99IJNehMZ23ByCsFhYQ7kTqACXdjiNlX6nH1xeEytaMGkwV3cm_DmgjZ7zHnKpfOeCsaSO0ncvc8UV-Drprkvn40vHY4FokFLKP9rZLWoiz5peVzYNo4BkmB4ULc0yPQGD-GjVz4-nYwqRcudSfzJ-2M_KO2zsbYHpto_Py8pwi5aUYYhDdgoTeiqq_TVrzUIqvrLf8vaBpMKyJP_AztVRnnmFG6sI5diFyCFolVTr2y7H-mWYV1vg1hPxpxBlft6diweGO7Y1oMp3d3ib-JPC-SEDQHzBSEhdSCjXm-Dxtac1Z9Q9dulIQJgiemAy9L8fB26ZvY99rWXT_sONa-RS0kdJQnthXxHTfCZdSobjZc1QpUrKB7STQ_mwoHkQ9MHpMscYsPIvG-C0m2xwWqFLxCyxSsHiJBjpvb7_iEQhTmealpcbpJ6MYUO6zryhHlMMcZ3N_zB6g6pscnWO_Ti0jt58ON_JHJopWMMuPS518FwLgWfIA471TAiibXYFE9TeoFTae1XkEBM7B_JUmgBcpuwIZD806VEjhs19Wa0twQC0qir3Q3_KbgAk9T_k6x5Cy5OiDevIbba2Gw==", "id": "rs_0dc9f371a6d55e3f016a1396f1adb8819188e4a583d6a7df1b", "summary": []}], "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Erledigt, Sir.\n\nIch habe jetzt den nächsten sauberen Schritt gebaut: **Final Video Approval Package** — also nicht nur ein MP4, sondern ein prüfbares Freigabe-Paket mit Metadata, Checksums, Titelvarianten, Caption, Hashtags und Approval Commands.\n\n## Neuer Commit\n\n```text\n8598dcd feat: add final video approval package\n```\n\n## Neu gebaut\n\n```text\nautoshorts/social/final_approval.py\ntests/test_final_video_approval.py\n```\n\n## Was das Package enthält\n\n```text\nCandidate-ID\nMedia-Pfad\nSHA256\nPlattformen\nTitelvarianten\nCaption\nHashtags\nHook\nDauer\nResolution\nQuality Notes\nFreigabe-Kommandos\n```\n\nAlles weiterhin:\n\n```text\nrequires_human_approval=True\nside_effects=()\nkeine Telegram/API Calls\nkein Upload\n```\n\nAlso keine heimliche Content-Katapultierung. Sehr zivilisiert.\n\n---\n\n## Final Video Review Package\n\nMEDIA:/home/agent/jarvis_runtime/autoshortsbot/AutoShortsBot/data/final_exports/truetrace-final-motion-v7-1080/truetrace-ai-automation-quiet-rot-38s/final-motion-audio-caption-1080.mp4\n\n## Metadata\n\nCandidate:\n\n```text\ntruetrace-ai-automation-quiet-rot-38s\n```\n\nSHA256 verifiziert:\n\n```text\n2e02b2960b1924abd8bc4154d91f521b370dde52f2af0944b24723c453fd0c6b\n```\n\nVideo:\n\n```text\nResolution: 1080x1920\nDuration: 36.833s\nAudio duration: 36.864s\nVideo codec: h264\nAudio codec: aac\n```\n\nPlatforms:\n\n```text\nYouTube Shorts\nTikTok\n```\n\nFinal language:\n\n```text\nEnglish\n```\n\nReview language:\n\n```text\nGerman\n```\n\n---\n\n## Titelvarianten\n\n```text\nYour AI Automation Works Until One Weird Email Arrives\n```\n\n```text\nWhy AI Automations Break When Real Life Shows Up\n```\n\n## Caption\n\n```text\nYour AI automation does not need a smarter prompt first. It needs a simple plan for weird inputs: what goes through, what gets reviewed, and what must stop.\n```\n\n## Hashtags\n\n```text\n#AI #AISystems #Workflow\n```\n\n## Hook\n\n```text\nYour AI automation works perfectly in the demo. Then one weird email arrives.\n```\n\n## Quality Notes\n\n```text\nBeginner-friendly weird-email framing;\nrenderer-owned labels and captions;\nscene-specific text-free ChatGPT Image backgrounds;\ncompact phrase-boundary subtitles.\n```\n\n---\n\n## Approval Commands\n\nWenn Sie ihn freigeben wollen:\n\n```text\nFreigabe YouTube\n```\n\n```text\nFreigabe TikTok\n```\n\n```text\nFreigabe alle\n```\n\nOder:\n\n```text\nAblehnen\n```\n\n```text\nÄndern: \n```\n\n## Tests\n\nFull Suite:\n\n```text\n172 passed in 32.86s\n```\n\n## Aktueller Commit-Verlauf\n\n```text\n8598dcd feat: add final video approval package\n033334c feat: compact final motion subtitles\ndb200ae feat: add scene-specific motion backgrounds\n14310f9 feat: add TrueTrace final motion prototype\n7375311 feat: make TrueTrace pilot beginner friendly\n```\n\nDer Clip ist jetzt technisch und organisatorisch in einem Zustand, wo er sauber reviewed werden kann: Video + Social Metadata + Freigabe-Sprache + Checksums."}], "id": "msg_0dc9f371a6d55e3f016a1396f3e6c88191b22585cd1cc38ecb", "phase": "final_answer"}], "timestamp": "2026-05-25T02:25:38.100301"}