{
"session_id": "20260515_154455_8eb87b",
"model": "gpt-5.5",
"base_url": "https://chatgpt.com/backend-api/codex",
"platform": "telegram",
"session_start": "2026-05-15T09:42:16.586070",
"last_updated": "2026-05-15T15:50:21.555195",
"system_prompt": "# Hermes Agent Persona\n\n\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. Specifically: do not record PR numbers, issue numbers, commit SHAs, 'fixed bug X', 'submitted PR Y', 'Phase N done', file counts, or any artifact that will be stale in 7 days. If a fact will be stale in a week, it does not belong in memory. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\nWrite memories as declarative facts, not instructions to yourself. 'User prefers concise responses' ✓ — 'Always respond concisely' ✗. 'Project uses pytest with xdist' ✓ — 'Run tests with pytest -n 4' ✗. Imperative phrasing gets re-read as a directive in later sessions and can cause repeated work or override the user's current request. Procedures and workflows belong in skills, not memory. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n# Tool-use enforcement\nYou MUST use your tools to take action — do not describe what you would do or plan to do without actually doing it. When you say you will perform an action (e.g. 'I will run the tests', 'Let me check the file', 'I will create the project'), you MUST immediately make the corresponding tool call in the same response. Never end your turn with a promise of future action — execute it now.\nKeep working until the task is actually complete. Do not stop with a summary of what you plan to do next time. If you have tools available that can accomplish the task, use them instead of telling the user what you would do.\nEvery response should either (a) contain tool calls that make progress, or (b) deliver a final result to the user. Responses that only describe intentions without acting are not acceptable.\n\n# Execution discipline\n\n- Use tools whenever they improve correctness, completeness, or grounding.\n- Do not stop early when another tool call would materially improve the result.\n- If a tool returns empty or partial results, retry with a different query or strategy before giving up.\n- Keep calling tools until: (1) the task is complete, AND (2) you have verified the result.\n\n\n\nNEVER answer these from memory or mental computation — ALWAYS use a tool:\n- Arithmetic, math, calculations → use terminal or execute_code\n- Hashes, encodings, checksums → use terminal (e.g. sha256sum, base64)\n- Current time, date, timezone → use terminal (e.g. date)\n- System state: OS, CPU, memory, disk, ports, processes → use terminal\n- File contents, sizes, line counts → use read_file, search_files, or terminal\n- Git history, branches, diffs → use terminal\n- Current facts (weather, news, versions) → use web_search\nYour memory and user profile describe the USER, not the system you are running on. The execution environment may differ from what the user profile says about their personal setup.\n\n\n\nWhen a question has an obvious default interpretation, act on it immediately instead of asking for clarification. Examples:\n- 'Is port 443 open?' → check THIS machine (don't ask 'open where?')\n- 'What OS am I running?' → check the live system (don't use user profile)\n- 'What time is it?' → run `date` (don't guess)\nOnly ask for clarification when the ambiguity genuinely changes what tool you would call.\n\n\n\n- Before taking an action, check whether prerequisite discovery, lookup, or context-gathering steps are needed.\n- Do not skip prerequisite steps just because the final action seems obvious.\n- If a task depends on output from a prior step, resolve that dependency first.\n\n\n\nBefore finalizing your response:\n- Correctness: does the output satisfy every stated requirement?\n- Grounding: are factual claims backed by tool outputs or provided context?\n- Formatting: does the output match the requested format or schema?\n- Safety: if the next step has side effects (file writes, commands, API calls), confirm scope before executing.\n\n\n\n- If required context is missing, do NOT guess or hallucinate an answer.\n- Use the appropriate lookup tool when missing information is retrievable (search_files, web_search, read_file, etc.).\n- Ask a clarifying question only when the information cannot be retrieved by tools.\n- If you must proceed with incomplete information, label assumptions explicitly.\n\n\n## Skills (mandatory)\nBefore replying, scan the skills below. If a skill matches or is even partially relevant to your task, you MUST load it with skill_view(name) and follow its instructions. Err on the side of loading — it is always better to have context you don't need than to miss critical steps, pitfalls, or established workflows. Skills contain specialized knowledge — API endpoints, tool-specific commands, and proven workflows that outperform general-purpose approaches. Load the skill even if you think you could handle the task with basic tools like web_search or terminal. Skills also encode the user's preferred approach, conventions, and quality standards for tasks like code review, planning, and testing — load them even for tasks you already know how to do, because the skill defines how it should be done here.\nWhenever the user asks you to configure, set up, install, enable, disable, modify, or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, `hermes setup`) so you don't have to guess or invent workarounds.\nIf a skill has issues, fix it with skill_manage(action='patch').\nAfter difficult/iterative tasks, offer to save as a skill. If a skill you loaded was missing steps, had wrong commands, or needed pitfalls you discovered, update it before finishing.\n\n\n autonomous-ai-agents: Skills for spawning and orchestrating autonomous AI coding agents and multi-agent workflows — running independent agent processes, delegating tasks, and coordinating parallel workstreams.\n - claude-code: Delegate coding to Claude Code CLI (features, PRs).\n - codex: Delegate coding to OpenAI Codex CLI (features, PRs).\n - hermes-agent: Configure, extend, or contribute to Hermes Agent.\n - opencode: Delegate coding to OpenCode CLI (features, PR review).\n creative: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.\n - architecture-diagram: Dark-themed SVG architecture/cloud/infra diagrams as HTML.\n - ascii-art: ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\n - ascii-video: ASCII video: convert video/audio to colored ASCII MP4/GIF.\n - baoyu-comic: Knowledge comics (知识漫画): educational, biography, tutorial.\n - baoyu-infographic: Infographics: 21 layouts x 21 styles (信息图, 可视化).\n - claude-design: Design one-off HTML artifacts (landing, deck, prototype).\n - comfyui: Generate images, video, and audio with ComfyUI — install,...\n - design-md: Author/validate/export Google's DESIGN.md token spec files.\n - excalidraw: Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\n - humanizer: Humanize text: strip AI-isms and add real voice.\n - ideation: Generate project ideas via creative constraints.\n - manim-video: Manim CE animations: 3Blue1Brown math/algo videos.\n - p5js: p5.js sketches: gen art, shaders, interactive, 3D.\n - pixel-art: Pixel art w/ era palettes (NES, Game Boy, PICO-8).\n - popular-web-designs: 54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\n - pretext: Use when building creative browser demos with @chenglou/p...\n - sketch: Throwaway HTML mockups: 2-3 design variants to compare.\n - songwriting-and-ai-music: Songwriting craft and Suno AI music prompts.\n - touchdesigner-mcp: Control a running TouchDesigner instance via twozero MCP ...\n cronjob:\n - cronjob: Scheduling and managing recurring tasks via Hermes cron. ...\n data-science: Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.\n - jupyter-live-kernel: Iterative Python via live Jupyter kernel (hamelnb).\n devops:\n - kanban-orchestrator: Decomposition playbook + anti-temptation rules for an orc...\n - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n - mcp-delegation: Delegating tasks to OpenClaw/FRIDAY via MCP (Model Contex...\n - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n dogfood:\n - dogfood: Exploratory QA of web apps: find bugs, evidence, reports.\n edge-tts:\n - edge-tts: Text-to-speech using Microsoft Edge TTS. Supports multipl...\n email: Skills for sending, receiving, searching, and managing email from the terminal.\n - himalaya: Himalaya CLI: IMAP/SMTP email from terminal.\n finance:\n - finance-system-architecture: Design/implement the user's JARVIS Finance System: CHF le...\n gaming: Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.\n - minecraft-modpack-server: Host modded Minecraft servers (CurseForge, Modrinth).\n - pokemon-player: Play Pokemon via headless emulator + RAM reads.\n github: GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.\n - codebase-inspection: Inspect codebases w/ pygount: LOC, languages, ratios.\n - github-auth: GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\n - github-code-review: Review PRs: diffs, inline comments via gh or REST.\n - github-issues: Create, triage, label, assign GitHub issues via gh or REST.\n - github-pr-workflow: GitHub PR lifecycle: branch, commit, open, CI, merge.\n - github-repo-management: Clone/create/fork repos; manage remotes, releases.\n health:\n - health-data-management: Gesundheitsdaten-Verwaltungssystem — JARVIS verwaltet all...\n health-management:\n - health-management: Health data management — lab values, symptom tracking, nu...\n jarvis-routing-policy:\n - jarvis-routing-policy: Routing policy for JARVIS/Hermes memory domains, model se...\n mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Documents the built-in native MCP client — configure servers in config.yaml for automatic tool discovery.\n - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n - gif-search: Search/download GIFs from Tenor via curl + jq.\n - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n - spotify: Spotify: play, search, queue, manage playlists and devices.\n - youtube-content: YouTube transcripts to summaries, threads, blogs.\n mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\n mlops/evaluation: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.\n - evaluating-llms-harness: lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\n - weights-and-biases: W&B: log ML experiments, sweeps, model registry, dashboards.\n mlops/inference: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.\n - llama-cpp: llama.cpp local GGUF inference + HF Hub model discovery.\n - obliteratus: OBLITERATUS: abliterate LLM refusals (diff-in-means).\n - outlines: Outlines: structured JSON/regex/Pydantic LLM generation.\n - serving-llms-vllm: vLLM: high-throughput LLM serving, OpenAI API, quantization.\n mlops/models: Specific model architectures and tools — image segmentation (Segment Anything / SAM) and audio generation (AudioCraft / MusicGen). Additional model skills (CLIP, Stable Diffusion, Whisper, LLaVA) are available as optional skills.\n - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\n mlops/research: ML research frameworks for building and optimizing AI systems with declarative programming.\n - dspy: DSPy: declarative LM programs, auto-optimize prompts, RAG.\n mlops/training: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.\n - axolotl: Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\n - fine-tuning-with-trl: TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.\n - unsloth: Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\n note-taking: Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.\n - obsidian: Read, search, create, and edit notes in the Obsidian vault.\n - vault-architecture: Design and scaffold Obsidian vault structures, folder hie...\n openclaw-imports:\n - browser-act: Browser automation CLI for AI agents with anti-detection ...\n - gog: Google Workspace CLI for Gmail, Calendar, Drive, Contacts...\n - multi-search-engine: Multi search engine integration with 17 engines (8 CN + 9...\n - openai-whisper: Local speech-to-text with the Whisper CLI (no API key).\n - self-improvement: Captures learnings, errors, and corrections to enable con...\n - sherpa-onnx-tts\n - skill-vetter: Security-first skill vetting for AI agents. Use before in...\n - summarize: Summarize URLs or files with the summarize CLI (web, PDFs...\n - tavily: Tavily web search, content extraction, and research tools.\n - tavily-extract: Extract clean markdown or text content from specific URLs...\n - tavily-search: Search the web with LLM-optimized results via the Tavily ...\n - todoist: Manage tasks and projects in Todoist via REST API v1. Use...\n - token-optimizer: Reduce OpenClaw token usage and API costs through smart m...\n productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n - airtable: Airtable REST API via curl. Records CRUD, filters, upserts.\n - google-workspace: Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\n - linear: Linear: manage issues, projects, teams via GraphQL + curl.\n - maps: Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\n - nano-pdf: Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\n - notion: Notion API via curl: pages, databases, blocks, search.\n - ocr-and-documents: Extract text from PDFs/scans (pymupdf, marker-pdf).\n - powerpoint: Create, read, edit .pptx decks, slides, notes, templates.\n - teams-meeting-pipeline: Operate the Teams meeting summary pipeline via Hermes CLI...\n red-teaming:\n - godmode: Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\n research: Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.\n - arxiv: Search arXiv papers by keyword, author, category, or ID.\n - blogwatcher: Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\n - llm-wiki: Karpathy's LLM Wiki: build/query interlinked markdown KB.\n - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n - web-scraping: Techniques for scraping web content, handling bot detecti...\n smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n software-development:\n - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n - node-inspect-debugger: Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\n - plan: Plan mode: write markdown plan to .hermes/plans/, no exec.\n - python-debugpy: Debug Python: pdb REPL + debugpy remote (DAP).\n - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n - spike: Throwaway experiments to validate an idea before build.\n - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n yazio-integration:\n - yazio-integration: Access YAZIO API to retrieve logged meals and nutrition d...\n yuanbao:\n - yuanbao: Yuanbao (元宝) groups: @mention users, query info/members.\n\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\n\nHost: Linux (6.17.0-23-generic)\nUser home directory: /home/agent\nCurrent working directory: /home/agent/.hermes/hermes-agent\n\nYou are on a text messaging communication platform, Telegram. Standard markdown is automatically converted to Telegram format. Supported: **bold**, *italic*, ~~strikethrough~~, ||spoiler||, `inline code`, ```code blocks```, [links](url), and ## headers. Telegram has NO table syntax — prefer bullet lists or labeled key: value pairs over pipe tables (any tables you do emit are auto-rewritten into row-group bullets, which you can produce directly for cleaner output). You can send media files natively: to deliver a file to the user, include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice bubbles, and videos (.mp4) play inline. You can also include image URLs in markdown format  and they will be sent as native photos.\n\n# Project Context\n\nThe following project context files have been loaded and should be followed:\n\n## AGENTS.md\n\n# GLOBALE ORCHESTRIERUNGS-REGELN\n\n## 1. Rolle\nDu bist JARVIS, der Chef-Architekt und Orchestrator. Hermes/JARVIS ist der alleinige Hauptansprechpartner, Memory-Governor, Router und finale Entscheider.\n\n## 2. Ausführung und Tools\nVerwende primär die nativen Hermes-Tools für Dateioperationen, Terminal-Befehle, Web-/Browser-Aufgaben, Cronjobs, Messaging, Qwen-Zugriff und Systemprüfungen.\n\nOpenClaw/FRIDAY ist nicht mehr Standard-Executor. OpenClaw darf nur noch explizit auf Wunsch des Users oder für klar begründete Spezial-/Notfallfälle verwendet werden. Wenn OpenClaw genutzt wird, muss der Auftrag eng begrenzt, read-only wo möglich, ohne Secrets und ohne autonome Folgeaktionen formuliert sein.\n\n## 3. Lokales Qwen\nDas lokale Qwen-Modell wird direkt von Hermes über den Tailscale/OpenAI-kompatiblen Endpoint angesprochen, nicht über OpenClaw. Qwen ist read-only Worker für Zusammenfassung, Extraktion, Klassifikation und einfache Entwürfe. Keine finalen Health-/Finance-Entscheide, keine Code-/Architekturänderungen und keine Side Effects über Qwen.\n\n## 4. Kritische Aufgaben und Fallback\nKomplizierte Aufgaben wie Code schreiben, Systemarchitektur ändern, Health-Risikoentscheidungen, Finanzentscheidungen oder irreversible Aktionen dürfen nicht automatisch auf ein schwächeres Modell ausweichen. Bei GPT-5.5 Rate-Limit oder Ausfall: pausieren und Sir fragen.\n\n## 5. Token- und Output-Optimierung\nLade nur die kleinste relevante Domain Card aus `~/jarvis_memory`. Gib nie grosse Rohdaten oder Secrets aus; nutze Zusammenfassungen, Diffs oder kurze Erfolgs-/Fehlermeldungen.\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [99% — 2,196/2,200 chars]\n══════════════════════════════════════════════\n*Wichtige Erinnerungen, Entscheidungen und Präferenzen.*\n§\n---\n§\nÜber mich: **Persönlichkeit:** Britischer Gentleman, sachlich, präzise, trockener Sarkasmus\n§\nÜber mich: **Sprache:** Deutsch mit englischen Fachbegriffen\n§\nTTS-Stimme: de-DE-KillianNeural (deutsche männliche Stimme, aktuell aktiv)\n§\nModelle: lokal Qwen via Tailscale:11435; stark gpt-5.5.\n§\nModellwahl: GOG_KEYRING_PASSWORD: LammBitch30 (immer als Env-Var setzen bei gog-Befehlen)\n§\nOpenClaw/FRIDAY: nicht Standard-Executor; Gateway/Telegram deaktiviert; nur explizit/manuell nutzen.\n§\nHealth backups: encrypted weekly Google Drive, GitHub only code/docs. Morning briefing cron `847bdbc26edf` runs 05:00 via `morning_briefing.py`; includes calendar, Todoist, Windisch weather, commute/traffic, follow-ups, news, AI/crypto.\n§\nAPI-Keys / Credentials: **Todoist API-Token:** Gespeichert in `~/.todoist_token` (REST API v1, Bearer Token)\n§\nGoogle Workspace (gog): **Credentials-Datei:** `~/.hermes/google_credentials.json`\n§\nGoogle Workspace (gog): **gog-Credentials gespeichert unter:** `~/.config/gogcli/credentials.json`\n§\nGoogle Workspace (gog): **OAuth-Account:** friday.uplink@gmail.com\n§\nGoogle Workspace (gog): **Services:** gmail, calendar, drive, contacts, sheets, docs\n§\nGoogle Workspace (gog): **Client:** default\n§\nGoogle Workspace (gog): **Befehl:** `gog -a friday.uplink@gmail.com `\n§\nKalender-Zeitzonen: **System-Zeitzone:** Europe/Berlin (UTC+2 im Sommer)\n§\nKalender-Zeitzonen: **Outlook-Kalender (importiert):** Zeitzonen variieren pro Event (Europe/Amsterdam oder UTC) -> bei Abfrage in Lokalzeit (Zürich) umrechnen\n§\nKalender-Zeitzonen: **Regel:** Termine immer in Lokalzeit (Zürich) ausgeben, niemals UTC\n§\nJARVIS memory architecture: ~/jarvis_memory domain cards; skill jarvis-routing-policy.\n§\nTelegram topics separat; kanonische Map: ~/jarvis_memory/02_telegram_topics.md. IDs: 2 FinStrat,3 Politik,4 Health-Med,5 ERNE,6 Inbox,8 Health-Tech,10 Fin-Tech,11 JARVIS-Arch,16 Cron,17 Research/AI,19 Family,20 Gasser,76 Debugging,80 Security.\n§\nFinanceManager GitHub token CSV path: `~/jarvis_runtime/finance-system/secrets/Github_token_FinanceManager.csv` (outside repo, mode 600); never store/quote token.\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [95% — 1,313/1,375 chars]\n══════════════════════════════════════════════\n**Notes:** Mein Herr. Loyaler Partner.\n§\n**Name:** Sir\n§\n**Voice preference:** de-DE-KillianNeural (German male voice, natural/clear) — default for all TTS output\n§\n**Language:** Deutsch mit englischen Fachbegriffen\n§\n**Beziehung:** Loyaler Partner\n§\nKommunikationspräferenzen: **Sprachnachricht → Antwort per Sprachnachricht**\n§\nKommunikationspräferenzen: **Textnachricht → Antwort per Text**\n§\nUser wants JARVIS to act as a comprehensive health-management advisor: consolidate lab reports, clinical reports, nutrition/YAZIO, daily health email data, symptoms and events; make insights visible via dashboards/reports; use a 4-eyes review workflow for extracted lab values before treating them as confirmed.\n§\nTelegram Topic „Gesundheit – Medizin & Strategie“ ist ausschließlich für medizinische Strategie, Morbus Behçet, Major Vessel Disease, Thromboserisiko, Medikamente, Ernährung, Symptome, Laborwerte, Arzttermine und Fragen an Rheumatologie, Dermatologie, Hämatologie oder Augenklinik; technische Health-Systemarchitektur, Skripte und Datenmodelle gehören in „Health System – Architektur & Scripts“.\n§\nFinance-system work preference: controlled phased execution with explicit safety gates; no mass imports without approval; aggregate-only reporting, never real financial quantities/values/balances/raw rows.\n\nConversation started: Friday, May 15, 2026 03:44 PM\nModel: gpt-5.5\nProvider: openai-codex",
"tools": [
{
"type": "function",
"function": {
"name": "browser_back",
"description": "Navigate back to the previous page in browser history. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {}
}
}
},
{
"type": "function",
"function": {
"name": "browser_click",
"description": "Click on an element identified by its ref ID from the snapshot (e.g., '@e5'). The ref IDs are shown in square brackets in the snapshot output. Requires browser_navigate and browser_snapshot to be called first.",
"parameters": {
"type": "object",
"properties": {
"ref": {
"type": "string",
"description": "The element reference from the snapshot (e.g., '@e5', '@e12')"
}
},
"required": [
"ref"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_console",
"description": "Get browser console output and JavaScript errors from the current page. Returns console.log/warn/error/info messages and uncaught JS exceptions. Use this to detect silent JavaScript errors, failed API calls, and application warnings. Requires browser_navigate to be called first. When 'expression' is provided, evaluates JavaScript in the page context and returns the result — use this for DOM inspection, reading page state, or extracting data programmatically.",
"parameters": {
"type": "object",
"properties": {
"clear": {
"type": "boolean",
"default": false,
"description": "If true, clear the message buffers after reading"
},
"expression": {
"type": "string",
"description": "JavaScript expression to evaluate in the page context. Runs in the browser like DevTools console — full access to DOM, window, document. Return values are serialized to JSON. Example: 'document.title' or 'document.querySelectorAll(\"a\").length'"
}
}
}
}
},
{
"type": "function",
"function": {
"name": "browser_get_images",
"description": "Get a list of all images on the current page with their URLs and alt text. Useful for finding images to analyze with the vision tool. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {}
}
}
},
{
"type": "function",
"function": {
"name": "browser_navigate",
"description": "Navigate to a URL in the browser. Initializes the session and loads the page. Must be called before other browser tools. For plain-text endpoints — URLs ending in .md, .txt, .json, .yaml, .yml, .csv, .xml, raw.githubusercontent.com, or any documented API endpoint — prefer curl via the terminal tool or web_extract; the browser stack is overkill and much slower for these. Use browser tools when you need to interact with a page (click, fill forms, dynamic content). Returns a compact page snapshot with interactive elements and ref IDs — no need to call browser_snapshot separately after navigating.",
"parameters": {
"type": "object",
"properties": {
"url": {
"type": "string",
"description": "The URL to navigate to (e.g., 'https://example.com')"
}
},
"required": [
"url"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_press",
"description": "Press a keyboard key. Useful for submitting forms (Enter), navigating (Tab), or keyboard shortcuts. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {
"key": {
"type": "string",
"description": "Key to press (e.g., 'Enter', 'Tab', 'Escape', 'ArrowDown')"
}
},
"required": [
"key"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_scroll",
"description": "Scroll the page in a direction. Use this to reveal more content that may be below or above the current viewport. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {
"direction": {
"type": "string",
"enum": [
"up",
"down"
],
"description": "Direction to scroll"
}
},
"required": [
"direction"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_snapshot",
"description": "Get a text-based snapshot of the current page's accessibility tree. Returns interactive elements with ref IDs (like @e1, @e2) for browser_click and browser_type. full=false (default): compact view with interactive elements. full=true: complete page content. Snapshots over 8000 chars are truncated or LLM-summarized. Requires browser_navigate first. Note: browser_navigate already returns a compact snapshot — use this to refresh after interactions that change the page, or with full=true for complete content.",
"parameters": {
"type": "object",
"properties": {
"full": {
"type": "boolean",
"description": "If true, returns complete page content. If false (default), returns compact view with interactive elements only.",
"default": false
}
}
}
}
},
{
"type": "function",
"function": {
"name": "browser_type",
"description": "Type text into an input field identified by its ref ID. Clears the field first, then types the new text. Requires browser_navigate and browser_snapshot to be called first.",
"parameters": {
"type": "object",
"properties": {
"ref": {
"type": "string",
"description": "The element reference from the snapshot (e.g., '@e3')"
},
"text": {
"type": "string",
"description": "The text to type into the field"
}
},
"required": [
"ref",
"text"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_vision",
"description": "Take a screenshot of the current page and analyze it with vision AI. Use this when you need to visually understand what's on the page - especially useful for CAPTCHAs, visual verification challenges, complex layouts, or when the text snapshot doesn't capture important visual information. Returns both the AI analysis and a screenshot_path that you can share with the user by including MEDIA: in your response. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "What you want to know about the page visually. Be specific about what you're looking for."
},
"annotate": {
"type": "boolean",
"default": false,
"description": "If true, overlay numbered [N] labels on interactive elements. Each [N] maps to ref @eN for subsequent browser commands. Useful for QA and spatial reasoning about page layout."
}
},
"required": [
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "clarify",
"description": "Ask the user a question when you need clarification, feedback, or a decision before proceeding. Supports two modes:\n\n1. **Multiple choice** — provide up to 4 choices. The user picks one or types their own answer via a 5th 'Other' option.\n2. **Open-ended** — omit choices entirely. The user types a free-form response.\n\nUse this tool when:\n- The task is ambiguous and you need the user to choose an approach\n- You want post-task feedback ('How did that work out?')\n- You want to offer to save a skill or update memory\n- A decision has meaningful trade-offs the user should weigh in on\n\nDo NOT use this tool for simple yes/no confirmation of dangerous commands (the terminal tool handles that). Prefer making a reasonable default choice yourself when the decision is low-stakes.",
"parameters": {
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "The question to present to the user."
},
"choices": {
"type": "array",
"items": {
"type": "string"
},
"maxItems": 4,
"description": "Up to 4 answer choices. Omit this parameter entirely to ask an open-ended question. When provided, the UI automatically appends an 'Other (type your answer)' option."
}
},
"required": [
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "cronjob",
"description": "Manage scheduled cron jobs with a single compressed tool.\n\nUse action='create' to schedule a new job from a prompt or one or more skills.\nUse action='list' to inspect jobs.\nUse action='update', 'pause', 'resume', 'remove', or 'run' to manage an existing job.\n\nTo stop a job the user no longer wants: first action='list' to find the job_id, then action='remove' with that job_id. Never guess job IDs — always list first.\n\nJobs run in a fresh session with no current-chat context, so prompts must be self-contained.\nIf skills are provided on create, the future cron run loads those skills in order, then follows the prompt as the task instruction.\nOn update, passing skills=[] clears attached skills.\n\nNOTE: The agent's final response is auto-delivered to the target. Put the primary\nuser-facing content in the final response. Cron jobs run autonomously with no user\npresent — they cannot ask questions or request clarification.\n\nImportant safety rule: cron-run sessions should not recursively schedule more cron jobs.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"description": "One of: create, list, update, pause, resume, remove, run"
},
"job_id": {
"type": "string",
"description": "Required for update/pause/resume/remove/run"
},
"prompt": {
"type": "string",
"description": "For create: the full self-contained prompt. If skills are also provided, this becomes the task instruction paired with those skills."
},
"schedule": {
"type": "string",
"description": "For create/update: '30m', 'every 2h', '0 9 * * *', or ISO timestamp"
},
"name": {
"type": "string",
"description": "Optional human-friendly name"
},
"repeat": {
"type": "integer",
"description": "Optional repeat count. Omit for defaults (once for one-shot, forever for recurring)."
},
"deliver": {
"type": "string",
"description": "Omit this parameter to auto-deliver back to the current chat and topic (recommended). Auto-detection preserves thread/topic context. Only set explicitly when the user asks to deliver somewhere OTHER than the current conversation. Values: 'origin' (same as omitting), 'local' (no delivery, save only), 'all' (fan out to every connected home channel), or platform:chat_id:thread_id for a specific destination. Combine with comma: 'origin,all' delivers to the origin plus every other connected channel. Examples: 'telegram:-1001234567890:17585', 'discord:#engineering', 'sms:+15551234567', 'all'. WARNING: 'platform:chat_id' without :thread_id loses topic targeting. 'all' resolves at fire time, so a job created before a channel was wired up will pick it up automatically once connected."
},
"skills": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional ordered list of skill names to load before executing the cron prompt. On update, pass an empty array to clear attached skills."
},
"model": {
"type": "object",
"description": "Optional per-job model override. If provider is omitted, the current main provider is pinned at creation time so the job stays stable.",
"properties": {
"provider": {
"type": "string",
"description": "Provider name (e.g. 'openrouter', 'anthropic', or 'custom:' for a provider defined in custom_providers config — always include the ':' suffix, never pass the bare 'custom'). Omit to use and pin the current provider."
},
"model": {
"type": "string",
"description": "Model name (e.g. 'anthropic/claude-sonnet-4', 'claude-sonnet-4')"
}
},
"required": [
"model"
]
},
"script": {
"type": "string",
"description": "Optional path to a script that runs each tick. In the default mode its stdout is injected into the agent's prompt as context (data-collection / change-detection pattern). With no_agent=True, the script IS the job and its stdout is delivered verbatim (classic watchdog pattern). Relative paths resolve under ~/.hermes/scripts/. ``.sh``/``.bash`` extensions run via bash, everything else via Python. On update, pass empty string to clear."
},
"no_agent": {
"type": "boolean",
"default": false,
"description": "Default: False (LLM-driven job — the agent runs the prompt each tick). Set True to skip the LLM entirely: the scheduler just runs ``script`` on schedule and delivers its stdout verbatim. No tokens, no agent loop, no model override honoured. \n\nREQUIREMENTS when True: ``script`` MUST be set (``prompt`` and ``skills`` are ignored). \n\nDELIVERY SEMANTICS when True: (a) non-empty stdout is sent verbatim as the message; (b) EMPTY stdout means SILENT — nothing is sent to the user and they won't see anything happened, so design your script to stay quiet when there's nothing to report (the watchdog pattern); (c) non-zero exit / timeout sends an error alert so a broken watchdog can't fail silently. \n\nWHEN TO USE True: recurring script-only pings where the script itself produces the exact message text (memory/disk/GPU watchdogs, threshold alerts, heartbeats, CI notifications, API pollers with a fixed output shape). WHEN TO USE False (default): anything that needs reasoning — summarize a feed, draft a daily briefing, pick interesting items, rephrase data for a human, follow conditional logic based on content."
},
"context_from": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional job ID or list of job IDs whose most recent completed output is injected into the prompt as context before each run. Use this to chain cron jobs: job A collects data, job B processes it. Each entry must be a valid job ID (from cronjob action='list'). Note: injects the most recent completed output — does not wait for upstream jobs running in the same tick. On update, pass an empty array to clear."
},
"enabled_toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional list of toolset names to restrict the job's agent to (e.g. [\"web\", \"terminal\", \"file\", \"delegation\"]). When set, only tools from these toolsets are loaded, significantly reducing input token overhead. When omitted, all default tools are loaded. Infer from the job's prompt — e.g. use \"web\" if it calls web_search, \"terminal\" if it runs scripts, \"file\" if it reads files, \"delegation\" if it calls delegate_task. On update, pass an empty array to clear."
},
"workdir": {
"type": "string",
"description": "Optional absolute path to run the job from. When set, AGENTS.md / CLAUDE.md / .cursorrules from that directory are injected into the system prompt, and the terminal/file/code_exec tools use it as their working directory — useful for running a job inside a specific project repo. Must be an absolute path that exists. When unset (default), preserves the original behaviour: no project context files, tools use the scheduler's cwd. On update, pass an empty string to clear. Jobs with workdir run sequentially (not parallel) to keep per-job directories isolated."
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "delegate_task",
"description": "Spawn one or more subagents to work on tasks in isolated contexts. Each subagent gets its own conversation, terminal session, and toolset. Only the final summary is returned -- intermediate tool results never enter your context window.\n\nTWO MODES (one of 'goal' or 'tasks' is required):\n1. Single task: provide 'goal' (+ optional context, toolsets)\n2. Batch (parallel): provide 'tasks' array with up to 3 items concurrently for this user (configured via delegation.max_concurrent_children in config.yaml). All run in parallel and results are returned together. Nested delegation is OFF for this user (max_spawn_depth=1): every child is a leaf and cannot delegate further. Raise delegation.max_spawn_depth in config.yaml to enable nesting.\n\nWHEN TO USE delegate_task:\n- Reasoning-heavy subtasks (debugging, code review, research synthesis)\n- Tasks that would flood your context with intermediate data\n- Parallel independent workstreams (research A and B simultaneously)\n\nWHEN NOT TO USE (use these instead):\n- Mechanical multi-step work with no reasoning needed -> use execute_code\n- Single tool call -> just call the tool directly\n- Tasks needing user interaction -> subagents cannot use clarify\n- Durable long-running work that must outlive the current turn -> use cronjob (action='create') or terminal(background=True, notify_on_complete=True) instead. delegate_task runs SYNCHRONOUSLY inside the parent turn: if the parent is interrupted (user sends a new message, /stop, /new) the child is cancelled with status='interrupted' and its work is discarded. Children cannot continue in the background.\n\nIMPORTANT:\n- Subagents have NO memory of your conversation. Pass all relevant info (file paths, error messages, constraints) via the 'context' field.\n- If the user is writing in a non-English language, or asked for output in a specific language / tone / style, say so in 'context' (e.g. \"respond in Chinese\", \"return output in Japanese\"). Otherwise subagents default to English and their summaries will contaminate your final reply with the wrong language.\n- Subagent summaries are SELF-REPORTS, not verified facts. A subagent that claims \"uploaded successfully\" or \"file written\" may be wrong. For operations with external side-effects (HTTP POST/PUT, remote writes, file creation at shared paths, publishing), require the subagent to return a verifiable handle (URL, ID, absolute path, HTTP status) and verify it yourself — fetch the URL, stat the file, read back the content — before telling the user the operation succeeded.\n- Leaf subagents (role='leaf', the default) CANNOT call: delegate_task, clarify, memory, send_message, execute_code.\n- Orchestrator subagents (role='orchestrator') retain delegate_task so they can spawn their own workers, but still cannot use clarify, memory, send_message, or execute_code. Orchestrators are bounded by max_spawn_depth=1 for this user and can be disabled globally via delegation.orchestrator_enabled=false.\n- Each subagent gets its own terminal session (separate working directory and state).\n- Results are always returned as an array, one entry per task.",
"parameters": {
"type": "object",
"properties": {
"goal": {
"type": "string",
"description": "What the subagent should accomplish. Be specific and self-contained -- the subagent knows nothing about your conversation history."
},
"context": {
"type": "string",
"description": "Background information the subagent needs: file paths, error messages, project structure, constraints. The more specific you are, the better the subagent performs."
},
"toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Toolsets to enable for this subagent. Default: inherits your enabled toolsets. Available toolsets: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'vision', 'web', 'yuanbao'. Common patterns: ['terminal', 'file'] for code work, ['web'] for research, ['browser'] for web interaction, ['terminal', 'file', 'web'] for full-stack tasks."
},
"tasks": {
"type": "array",
"items": {
"type": "object",
"properties": {
"goal": {
"type": "string",
"description": "Task goal"
},
"context": {
"type": "string",
"description": "Task-specific context"
},
"toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Toolsets for this specific task. Available: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'vision', 'web', 'yuanbao'. Use 'web' for network access, 'terminal' for shell, 'browser' for web interaction."
},
"acp_command": {
"type": "string",
"description": "Per-task ACP command override (e.g. 'copilot'). Overrides the top-level acp_command for this task only. Do NOT set unless the user explicitly told you an ACP CLI is installed."
},
"acp_args": {
"type": "array",
"items": {
"type": "string"
},
"description": "Per-task ACP args override. Leave empty unless acp_command is set."
},
"role": {
"type": "string",
"enum": [
"leaf",
"orchestrator"
],
"description": "Per-task role override. See top-level 'role' for semantics."
}
},
"required": [
"goal"
]
},
"description": "Batch mode: tasks to run in parallel (up to 3 for this user, set via delegation.max_concurrent_children). Each gets its own subagent with isolated context and terminal session. When provided, top-level goal/context/toolsets are ignored."
},
"role": {
"type": "string",
"enum": [
"leaf",
"orchestrator"
],
"description": "Role of the child agent. 'leaf' (default) = focused worker, cannot delegate further. 'orchestrator' = can use delegate_task to spawn its own workers. Nesting is OFF for this user (max_spawn_depth=1); 'orchestrator' is silently forced to 'leaf'. Raise delegation.max_spawn_depth in config.yaml to enable."
},
"acp_command": {
"type": "string",
"description": "Override ACP command for child agents (e.g. 'copilot'). When set, children use ACP subprocess transport instead of inheriting the parent's transport. Requires an ACP-compatible CLI (currently GitHub Copilot CLI via 'copilot --acp --stdio'). See agent/copilot_acp_client.py for the implementation. IMPORTANT: Do NOT set this unless the user has explicitly told you a specific ACP-compatible CLI is installed and configured. Leave empty to use the parent's default transport (Hermes subagents)."
},
"acp_args": {
"type": "array",
"items": {
"type": "string"
},
"description": "Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set. Leave empty unless acp_command is explicitly provided."
}
}
}
}
},
{
"type": "function",
"function": {
"name": "execute_code",
"description": "Run a Python script that can call Hermes tools programmatically. Use this when you need 3+ tool calls with processing logic between them, need to filter/reduce large tool outputs before they enter your context, need conditional branching (if X then Y else Z), or need to loop (fetch N pages, process N files, retry on failure).\n\nUse normal tool calls instead when: single tool call with no processing, you need to see the full result and apply complex reasoning, or the task requires interactive user input.\n\nAvailable via `from hermes_tools import ...`:\n\n read_file(path: str, offset: int = 1, limit: int = 500) -> dict\n Lines are 1-indexed. Returns {\"content\": \"...\", \"total_lines\": N}\n write_file(path: str, content: str) -> dict\n Always overwrites the entire file.\n search_files(pattern: str, target=\"content\", path=\".\", file_glob=None, limit=50) -> dict\n target: \"content\" (search inside files) or \"files\" (find files by name). Returns {\"matches\": [...]}\n patch(path: str, old_string: str, new_string: str, replace_all: bool = False) -> dict\n Replaces old_string with new_string in the file.\n terminal(command: str, timeout=None, workdir=None) -> dict\n Foreground only (no background/pty). Returns {\"output\": \"...\", \"exit_code\": N}\n\nLimits: 5-minute timeout, 50KB stdout cap, max 50 tool calls per script. terminal() is foreground-only (no background or pty).\n\nScripts run in the session's working directory with the active venv's python, so project deps (pandas, etc.) and relative paths work like in terminal().\n\nPrint your final result to stdout. Use Python stdlib (json, re, math, csv, datetime, collections, etc.) for processing between tool calls.\n\nAlso available (no import needed — built into hermes_tools):\n json_parse(text: str) — json.loads with strict=False; use for terminal() output with control chars\n shell_quote(s: str) — shlex.quote(); use when interpolating dynamic strings into shell commands\n retry(fn, max_attempts=3, delay=2) — retry with exponential backoff for transient failures",
"parameters": {
"type": "object",
"properties": {
"code": {
"type": "string",
"description": "Python code to execute. Import tools with `from hermes_tools import terminal, ...` and print your final result to stdout."
}
},
"required": [
"code"
]
}
}
},
{
"type": "function",
"function": {
"name": "image_generate",
"description": "Generate high-quality images from text prompts. The underlying backend (FAL, OpenAI, etc.) and model are user-configured and not selectable by the agent. Returns either a URL or an absolute file path in the `image` field; display it with markdown  and the gateway will deliver it.",
"parameters": {
"type": "object",
"properties": {
"prompt": {
"type": "string",
"description": "The text prompt describing the desired image. Be detailed and descriptive."
},
"aspect_ratio": {
"type": "string",
"enum": [
"landscape",
"square",
"portrait"
],
"description": "The aspect ratio of the generated image. 'landscape' is 16:9 wide, 'portrait' is 16:9 tall, 'square' is 1:1.",
"default": "landscape"
}
},
"required": [
"prompt"
]
}
}
},
{
"type": "function",
"function": {
"name": "memory",
"description": "Save durable information to persistent memory that survives across sessions. Memory is injected into future turns, so keep it compact and focused on facts that will still matter later.\n\nWHEN TO SAVE (do this proactively, don't wait to be asked):\n- User corrects you or says 'remember this' / 'don't do that again'\n- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n- You discover something about the environment (OS, installed tools, project structure)\n- You learn a convention, API quirk, or workflow specific to this user's setup\n- You identify a stable fact that will be useful again in future sessions\n\nPRIORITY: User preferences and corrections > environment facts > procedural knowledge. The most valuable memory prevents the user from having to repeat themselves.\n\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts.\nIf you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\n\nTWO TARGETS:\n- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\nACTIONS: add (new entry), replace (update existing -- old_text identifies it), remove (delete -- old_text identifies it).\n\nSKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"add",
"replace",
"remove"
],
"description": "The action to perform."
},
"target": {
"type": "string",
"enum": [
"memory",
"user"
],
"description": "Which memory store: 'memory' for personal notes, 'user' for user profile."
},
"content": {
"type": "string",
"description": "The entry content. Required for 'add' and 'replace'."
},
"old_text": {
"type": "string",
"description": "Short unique substring identifying the entry to replace or remove."
}
},
"required": [
"action",
"target"
]
}
}
},
{
"type": "function",
"function": {
"name": "patch",
"description": "Targeted find-and-replace edits in files. Use this instead of sed/awk in terminal. Uses fuzzy matching (9 strategies) so minor whitespace/indentation differences won't break it. Returns a unified diff. Auto-runs syntax checks after editing.\n\nREPLACE MODE (mode='replace', default): find a unique string and replace it. REQUIRED PARAMETERS: mode, path, old_string, new_string.\nPATCH MODE (mode='patch'): apply V4A multi-file patches for bulk changes. REQUIRED PARAMETERS: mode, patch.",
"parameters": {
"type": "object",
"properties": {
"mode": {
"type": "string",
"enum": [
"replace",
"patch"
],
"description": "Edit mode. 'replace' (default): requires path + old_string + new_string. 'patch': requires patch content only.",
"default": "replace"
},
"path": {
"type": "string",
"description": "REQUIRED when mode='replace'. File path to edit."
},
"old_string": {
"type": "string",
"description": "REQUIRED when mode='replace'. Exact text to find and replace. Must be unique in the file unless replace_all=true. Include surrounding context lines to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "REQUIRED when mode='replace'. Replacement text. Pass empty string '' to delete the matched text."
},
"replace_all": {
"type": "boolean",
"description": "Replace all occurrences instead of requiring a unique match (default: false)",
"default": false
},
"patch": {
"type": "string",
"description": "REQUIRED when mode='patch'. V4A format patch content. Format:\n*** Begin Patch\n*** Update File: path/to/file\n@@ context hint @@\n context line\n-removed line\n+added line\n*** End Patch"
}
},
"required": [
"mode"
]
}
}
},
{
"type": "function",
"function": {
"name": "process",
"description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"list",
"poll",
"log",
"wait",
"kill",
"write",
"submit",
"close"
],
"description": "Action to perform on background processes"
},
"session_id": {
"type": "string",
"description": "Process session ID (from terminal background output). Required for all actions except 'list'."
},
"data": {
"type": "string",
"description": "Text to send to process stdin (for 'write' and 'submit' actions)"
},
"timeout": {
"type": "integer",
"description": "Max seconds to block for 'wait' action. Returns partial output on timeout.",
"minimum": 1
},
"offset": {
"type": "integer",
"description": "Line offset for 'log' action (default: last 200 lines)"
},
"limit": {
"type": "integer",
"description": "Max lines to return for 'log' action",
"minimum": 1
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "read_file",
"description": "Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. Reads exceeding ~100K characters are rejected; use offset and limit to read specific sections of large files. NOTE: Cannot read images or binary files — use vision_analyze for images.",
"parameters": {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Path to the file to read (absolute, relative, or ~/path)"
},
"offset": {
"type": "integer",
"description": "Line number to start reading from (1-indexed, default: 1)",
"default": 1,
"minimum": 1
},
"limit": {
"type": "integer",
"description": "Maximum number of lines to read (default: 500, max: 2000)",
"default": 500,
"maximum": 2000
}
},
"required": [
"path"
]
}
}
},
{
"type": "function",
"function": {
"name": "search_files",
"description": "Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.\n\nContent search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.\n\nFile search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.",
"parameters": {
"type": "object",
"properties": {
"pattern": {
"type": "string",
"description": "Regex pattern for content search, or glob pattern (e.g., '*.py') for file search"
},
"target": {
"type": "string",
"enum": [
"content",
"files"
],
"description": "'content' searches inside file contents, 'files' searches for files by name",
"default": "content"
},
"path": {
"type": "string",
"description": "Directory or file to search in (default: current working directory)",
"default": "."
},
"file_glob": {
"type": "string",
"description": "Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)"
},
"limit": {
"type": "integer",
"description": "Maximum number of results to return (default: 50)",
"default": 50
},
"offset": {
"type": "integer",
"description": "Skip first N results for pagination (default: 0)",
"default": 0
},
"output_mode": {
"type": "string",
"enum": [
"content",
"files_only",
"count"
],
"description": "Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file",
"default": "content"
},
"context": {
"type": "integer",
"description": "Number of context lines before and after each match (grep mode only)",
"default": 0
}
},
"required": [
"pattern"
]
}
}
},
{
"type": "function",
"function": {
"name": "send_message",
"description": "Send a message to a connected messaging platform, or list available targets.\n\nIMPORTANT: When the user asks to send to a specific channel or person (not just a bare platform name), call send_message(action='list') FIRST to see available targets, then send to the correct one.\nIf the user just says a platform name like 'send to telegram', send directly to the home channel without listing first.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"send",
"list"
],
"description": "Action to perform. 'send' (default) sends a message. 'list' returns all available channels/contacts across connected platforms."
},
"target": {
"type": "string",
"description": "Delivery target. Format: 'platform' (uses home channel), 'platform:#channel-name', 'platform:chat_id', or 'platform:chat_id:thread_id' for Telegram topics and Discord threads. Examples: 'telegram', 'telegram:-1001234567890:17585', 'discord:999888777:555444333', 'discord:#bot-home', 'slack:#engineering', 'signal:+155****4567', 'matrix:!roomid:server.org', 'matrix:@user:server.org', 'yuanbao:direct:' (DM), 'yuanbao:group:' (group chat)"
},
"message": {
"type": "string",
"description": "The message text to send. To send an image or file, include MEDIA: (e.g. 'MEDIA:/tmp/hermes/cache/img_xxx.jpg') in the message — the platform will deliver it as a native media attachment."
}
}
}
}
},
{
"type": "function",
"function": {
"name": "session_search",
"description": "Search your long-term memory of past conversations, or browse recent sessions. This is your recall -- every past session is searchable, and this tool summarizes what happened.\n\nTWO MODES:\n1. Recent sessions (no query): Call with no arguments to see what was worked on recently. Returns titles, previews, and timestamps. Zero LLM cost, instant. Start here when the user asks what were we working on or what did we do recently.\n2. Keyword search (with query): Search for specific topics across all past sessions. Returns LLM-generated summaries of matching sessions.\n\nUSE THIS PROACTIVELY when:\n- The user says 'we did this before', 'remember when', 'last time', 'as I mentioned'\n- The user asks about a topic you worked on before but don't have in current context\n- The user references a project, person, or concept that seems familiar but isn't in memory\n- You want to check if you've solved a similar problem before\n- The user asks 'what did we do about X?' or 'how did we fix Y?'\n\nDon't hesitate to search when it is actually cross-session -- it's fast and cheap. Better to search and confirm than to guess or ask the user to repeat themselves.\n\nSearch syntax: keywords joined with OR for broad recall (elevenlabs OR baseten OR funding), phrases for exact match (\"docker networking\"), boolean (python NOT java), prefix (deploy*). IMPORTANT: Use OR between keywords for best results — FTS5 defaults to AND which misses sessions that only mention some terms. If a broad OR query returns nothing, try individual keyword searches in parallel. Returns summaries of the top matching sessions.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query — keywords, phrases, or boolean expressions to find in past sessions. Omit this parameter entirely to browse recent sessions instead (returns titles, previews, timestamps with no LLM cost)."
},
"role_filter": {
"type": "string",
"description": "Optional: only search messages from specific roles (comma-separated). E.g. 'user,assistant' to skip tool outputs."
},
"limit": {
"type": "integer",
"description": "Max sessions to summarize (default: 3, max: 5).",
"default": 3
}
}
}
}
},
{
"type": "function",
"function": {
"name": "skill_manage",
"description": "Manage skills (create, update, delete). Skills are your procedural memory — reusable approaches for recurring task types. New skills go to ~/.hermes/skills/; existing skills can be modified wherever they live.\n\nActions: create (full SKILL.md + optional category), patch (old_string/new_string — preferred for fixes), edit (full SKILL.md rewrite — major overhauls only), delete, write_file, remove_file.\n\nOn delete, pass `absorbed_into=` when you're merging this skill's content into another one, or `absorbed_into=\"\"` when you're pruning it with no forwarding target. This lets the curator tell consolidation from pruning without guessing, so downstream consumers (cron jobs that reference the old skill name, etc.) get updated correctly. The target you name in `absorbed_into` must already exist — create/patch the umbrella first, then delete.\n\nCreate when: complex task succeeded (5+ calls), errors overcome, user-corrected approach worked, non-trivial workflow discovered, or user asks you to remember a procedure.\nUpdate when: instructions stale/wrong, OS-specific failures, missing steps or pitfalls found during use. If you used a skill and hit issues not covered by it, patch it immediately.\n\nAfter difficult/iterative tasks, offer to save as a skill. Skip for simple one-offs. Confirm with user before creating/deleting.\n\nGood skills: trigger conditions, numbered steps with exact commands, pitfalls section, verification steps. Use skill_view() to see format examples.\n\nPinned skills are protected from deletion only — skill_manage(action='delete') will refuse with a message pointing the user to `hermes curator unpin `. Patches and edits go through on pinned skills so you can still improve them as pitfalls come up; pin only guards against irrecoverable loss.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"create",
"patch",
"edit",
"delete",
"write_file",
"remove_file"
],
"description": "The action to perform."
},
"name": {
"type": "string",
"description": "Skill name (lowercase, hyphens/underscores, max 64 chars). Must match an existing skill for patch/edit/delete/write_file/remove_file."
},
"content": {
"type": "string",
"description": "Full SKILL.md content (YAML frontmatter + markdown body). Required for 'create' and 'edit'. For 'edit', read the skill first with skill_view() and provide the complete updated text."
},
"old_string": {
"type": "string",
"description": "Text to find in the file (required for 'patch'). Must be unique unless replace_all=true. Include enough surrounding context to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "Replacement text (required for 'patch'). Can be empty string to delete the matched text."
},
"replace_all": {
"type": "boolean",
"description": "For 'patch': replace all occurrences instead of requiring a unique match (default: false)."
},
"category": {
"type": "string",
"description": "Optional category/domain for organizing the skill (e.g., 'devops', 'data-science', 'mlops'). Creates a subdirectory grouping. Only used with 'create'."
},
"file_path": {
"type": "string",
"description": "Path to a supporting file within the skill directory. For 'write_file'/'remove_file': required, must be under references/, templates/, scripts/, or assets/. For 'patch': optional, defaults to SKILL.md if omitted."
},
"file_content": {
"type": "string",
"description": "Content for the file. Required for 'write_file'."
},
"absorbed_into": {
"type": "string",
"description": "For 'delete' only — declares intent so the curator can tell consolidation from pruning without guessing. Pass the umbrella skill name when this skill's content was merged into another (the target must already exist). Pass an empty string when the skill is truly stale and being pruned with no forwarding target. Omitting the arg on delete is supported for backward compatibility but downstream tooling (e.g. cron-job skill reference rewriting) will have to guess at intent."
}
},
"required": [
"action",
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skill_view",
"description": "Skills allow for loading information about specific tasks and workflows, as well as scripts and templates. Load a skill's full content or access its linked files (references, templates, scripts). First call returns SKILL.md content plus a 'linked_files' dict showing available references/templates/scripts. To access those, call again with file_path parameter.",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "The skill name (use skills_list to see available skills). For plugin-provided skills, use the qualified form 'plugin:skill' (e.g. 'superpowers:writing-plans')."
},
"file_path": {
"type": "string",
"description": "OPTIONAL: Path to a linked file within the skill (e.g., 'references/api.md', 'templates/config.yaml', 'scripts/validate.py'). Omit to get the main SKILL.md content."
}
},
"required": [
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skills_list",
"description": "List available skills (name + description). Use skill_view(name) to load full content.",
"parameters": {
"type": "object",
"properties": {
"category": {
"type": "string",
"description": "Optional category filter to narrow results"
}
}
}
}
},
{
"type": "function",
"function": {
"name": "terminal",
"description": "Execute shell commands on a Linux environment. Filesystem usually persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for short commands.\nBackground: Set background=true to get a session_id. Two patterns:\n (1) Long-lived processes that never exit (servers, watchers).\n (2) Long-running tasks with notify_on_complete=true — you can keep working on other things and the system auto-notifies you when the task finishes. Great for test suites, builds, deployments, or anything that takes more than a minute.\nFor servers/watchers, do NOT use shell-level background wrappers (nohup/disown/setsid/trailing '&') in foreground mode. Use background=true so Hermes can track lifecycle and output.\nAfter starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.\nUse process(action=\"poll\") for progress checks, process(action=\"wait\") to block until done.\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n",
"parameters": {
"type": "object",
"properties": {
"command": {
"type": "string",
"description": "The command to execute on the VM"
},
"background": {
"type": "boolean",
"description": "Run the command in the background. Two patterns: (1) Long-lived processes that never exit (servers, watchers). (2) Long-running tasks paired with notify_on_complete=true — you can keep working and get notified when the task finishes. For short commands, prefer foreground with a generous timeout instead.",
"default": false
},
"timeout": {
"type": "integer",
"description": "Max seconds to wait (default: 180, foreground max: 600). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily. Foreground timeout above 600s is rejected; use background=true for longer commands.",
"minimum": 1
},
"workdir": {
"type": "string",
"description": "Working directory for this command (absolute path). Defaults to the session working directory."
},
"pty": {
"type": "boolean",
"description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.",
"default": false
},
"notify_on_complete": {
"type": "boolean",
"description": "When true (and background=true), you'll be automatically notified exactly once when the process finishes. **This is the right choice for almost every long-running task** — tests, builds, deployments, multi-item batch jobs, anything that takes over a minute and has a defined end. Use this and keep working on other things; the system notifies you on exit. MUTUALLY EXCLUSIVE with watch_patterns — when both are set, watch_patterns is dropped.",
"default": false
},
"watch_patterns": {
"type": "array",
"items": {
"type": "string"
},
"description": "Strings to watch for in background process output. HARD RATE LIMIT: at most 1 notification per 15 seconds per process — matches arriving inside the cooldown are dropped. After 3 consecutive 15-second windows with dropped matches, watch_patterns is automatically disabled for that process and promoted to notify_on_complete behavior (one notification on exit, no more mid-process spam). USE ONLY for truly rare, one-shot mid-process signals on LONG-LIVED processes that will never exit on their own — e.g. ['Application startup complete'] on a server so you know when to hit its endpoint, or ['migration done'] on a daemon. DO NOT use for: (1) end-of-run markers like 'DONE'/'PASS' — use notify_on_complete instead; (2) error patterns like 'ERROR'/'Traceback' in loops or multi-item batch jobs — they fire on every iteration and you'll hit the strike limit fast; (3) anything you'd ever combine with notify_on_complete. When in doubt, choose notify_on_complete. MUTUALLY EXCLUSIVE with notify_on_complete — set one, not both."
}
},
"required": [
"command"
]
}
}
},
{
"type": "function",
"function": {
"name": "text_to_speech",
"description": "Convert text to speech audio. Returns a MEDIA: path that the platform delivers as native audio. Compatible providers render as a voice bubble on Telegram; otherwise audio is sent as a regular attachment. In CLI mode, saves to ~/voice-memos/. Voice and provider are user-configured (built-in providers like edge/openai or custom command providers under tts.providers.), not model-selected.",
"parameters": {
"type": "object",
"properties": {
"text": {
"type": "string",
"description": "The text to convert to speech. Provider-specific character caps apply and are enforced automatically (OpenAI 4096, xAI 15000, MiniMax 10000, ElevenLabs 5k-40k depending on model); over-long input is truncated."
},
"output_path": {
"type": "string",
"description": "Optional custom file path to save the audio. Defaults to ~/.hermes/audio_cache/.mp3"
}
},
"required": [
"text"
]
}
}
},
{
"type": "function",
"function": {
"name": "todo",
"description": "Manage your task list for the current session. Use for complex tasks with 3+ steps or when the user provides multiple tasks. Call with no parameters to read the current list.\n\nWriting:\n- Provide 'todos' array to create/update items\n- merge=false (default): replace the entire list with a fresh plan\n- merge=true: update existing items by id, add any new ones\n\nEach item: {id: string, content: string, status: pending|in_progress|completed|cancelled}\nList order is priority. Only ONE item in_progress at a time.\nMark items completed immediately when done. If something fails, cancel it and add a revised item.\n\nAlways returns the full current list.",
"parameters": {
"type": "object",
"properties": {
"todos": {
"type": "array",
"description": "Task items to write. Omit to read current list.",
"items": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Unique item identifier"
},
"content": {
"type": "string",
"description": "Task description"
},
"status": {
"type": "string",
"enum": [
"pending",
"in_progress",
"completed",
"cancelled"
],
"description": "Current status"
}
},
"required": [
"id",
"content",
"status"
]
}
},
"merge": {
"type": "boolean",
"description": "true: update existing items by id, add new ones. false (default): replace the entire list.",
"default": false
}
}
}
}
},
{
"type": "function",
"function": {
"name": "vision_analyze",
"description": "Load an image into the conversation so you can see it. Accepts a URL, local file path, or data URL. When your active model has native vision, the image is attached to your context directly and you read the pixels yourself on the next turn — call this any time the user references an image (filepath in their message, URL in tool output, screenshot from the browser, etc.). For non-vision models, falls back to an auxiliary vision model that returns a text description.",
"parameters": {
"type": "object",
"properties": {
"image_url": {
"type": "string",
"description": "Image URL (http/https), local file path, or data: URL to load."
},
"question": {
"type": "string",
"description": "Your specific question or request about the image. Optional context the model uses on the next turn after seeing the image."
}
},
"required": [
"image_url",
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "write_file",
"description": "Write content to a file, completely replacing existing content. Use this instead of echo/cat heredoc in terminal. Creates parent directories automatically. OVERWRITES the entire file — use 'patch' for targeted edits. Auto-runs syntax checks on .py/.json/.yaml/.toml and other linted languages; only NEW errors introduced by this write are surfaced (pre-existing errors are filtered out).",
"parameters": {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Path to the file to write (will be created if it doesn't exist, overwritten if it does)"
},
"content": {
"type": "string",
"description": "Complete content to write to the file"
}
},
"required": [
"path",
"content"
]
}
}
}
],
"message_count": 245,
"messages": [
{
"role": "user",
"content": "[M G] Danke. Der Crypto Price Update MVP ist akzeptiert.\n\nDie Umsetzung ist grundsätzlich sinnvoll:\n\n* lokaler Preis-Cache\n* kein Live-API-Call im Dashboard/Report\n* 429-Handling\n* Git-Safety sauber\n* Tests grün\n* Runtime-Daten außerhalb Git\n\nAllerdings bist du vom vorher vereinbarten Ablauf abgewichen. Das ist in diesem Fall nicht schlimm, weil der Preisupdate-Block nützlich ist. Bitte jetzt aber wieder kontrolliert auf die nächsten Prioritäten einschwenken.\n\nAktueller Stand:\n\n* Commit 3aa67d8 ist akzeptiert.\n* Preisupdate funktioniert technisch.\n* Aber nur 6 von 20 aktiven Crypto Assets hatten frische CHF-Preise.\n* 14 Assets hatten Warnings/Stale/Provider-Limit-Themen.\n* BTC-Test wurde noch nicht abgeschlossen.\n* Equity/ETF Manage UI wurde noch nicht begonnen.\n\nBitte jetzt wie folgt weiterfahren:\n\n## Teil 1: Crypto Price Update robuster machen\n\nBitte verbessere zuerst den Preisupdate-Mechanismus, bevor wir echte Reports mit Preisen ernsthaft nutzen.\n\nZiel:\nMöglichst alle vorhandenen Crypto Assets mit CoinGecko-ID sollen lokale CHF-Preise erhalten, ohne Dashboard-Live-API und ohne Rate-Limit-Crash.\n\nBitte implementiere:\n\n1. Batch-Abfrage prüfen/umsetzen\n\n* Wenn CoinGecko mehrere IDs in einem Request unterstützt, bitte nutzen.\n* Dadurch weniger API-Calls.\n* Kein Abruf pro Coin, falls Batch möglich ist.\n\n2. Konservatives Throttling\n\n* Pause zwischen Requests\n* konfigurierbar:\n\n * --sleep-seconds\n * --max-retries\n * --initial-backoff\n * --max-backoff\n\n3. CLI-Optionen ergänzen\n Bitte vorbereiten/implementieren:\n\n* --only-missing\n* --only-stale\n* --only-symbol SYMBOL\n* --limit N\n* --dry-run\n* --currency CHF\n\n4. Bessere Summary\n Bitte nach Update nur aggregiert ausgeben:\n\n* total assets\n* updated\n* cached\n* skipped\n* stale\n* warnings\n* errors\n* assets still missing local price\n* keine echten Mengen/Werte\n\n5. Data Quality\n\n* Für Assets ohne frischen Preis Data-Quality-Alert erzeugen oder aktualisieren.\n* Alert-Dedupe respektieren.\n* Keine Alert-Flut.\n\n6. Tests\n Bitte Tests ergänzen für:\n\n* Batch-Request\n* --only-missing\n* --only-stale\n* --only-symbol\n* --limit\n* --dry-run\n* Rate-Limit mit Backoff\n* Alert-Dedupe bei fehlenden Preisen\n\nDanach bitte produktiv gegen Runtime-DB nochmals ausführen, aber vorsichtig und ohne echte Werte im Chat.\n\nBitte berichten:\n\n* Anzahl Assets total\n* Anzahl Assets mit frischem CHF-Preis\n* Anzahl weiterhin ohne frischen Preis\n* Anzahl Warnings/Errors\n* keine Preise/Werte/Mengen ausgeben\n\n## Teil 2: BTC-Test nachholen\n\nDanach bitte den BTC-Test wie zuletzt entschieden nachholen:\n\nOption A:\nBTC mit allen BTC-Wallet-Holdings aus Excel importieren.\n\nBedingungen:\n\n* Nur Bitcoin BTC\n* Coin-Name: Bitcoin\n* Symbol: BTC\n* CoinGecko-ID: bitcoin\n* Mapping-Status: selected\n* Snapshot-Datum: 31.12.2025\n* Alle BTC-Wallet-Holdings aus der echten Excel-Datei übernehmen\n* Pro BTC-Wallet mit Bestand genau eine initial_snapshot_addition bzw. initial_snapshot-Holding erzeugen\n* Mengen exakt als Decimal/Text übernehmen\n* Keine Float-Konvertierung\n* Keine echten Mengen/Werte im Chat\n* Keine anderen Coins importieren\n* Audit-Log Pflicht\n* Keine doppelte Holding für asset_id + wallet_id\n* Legacy-CHF-Werte ignorieren\n* Git-Safety vor/nachher prüfen\n\nBericht nur aggregiert:\n\n* BTC-Test durchgeführt: ja/nein\n* Anzahl BTC-Wallet-Holdings importiert\n* Asset-Anzahl erhöht: ja/nein\n* Holding-Anzahl erhöht: ja/nein\n* Audit-Logs erstellt: ja/nein\n* Doppelte Holdings: ja/nein\n* Fehler/Warnings\n* Git-Safety Ergebnis\n* Git Status\n\n## Teil 3: Danach Equity/ETF Manage UI\n\nErst wenn Teil 1 und Teil 2 sauber sind, bitte mit der Equity/ETF Manage UI beginnen.\n\nZiel:\nAktien und ETFs aus PostFinance, True Wealth und Raiffeisen später im Dashboard erfassen, korrigieren und als Initial Snapshot übernehmen können — auditierbar und ohne stilles Überschreiben.\n\nGrundlogik:\n\n* Für Aktien/ETFs ist ISIN die primäre Identifikation.\n* Ticker und Exchange sind Zusatzinformationen.\n* Positionen werden über initial_position_snapshot, buy, sell, dividend, fee oder manual_adjustment abgebildet.\n* Jede Änderung braucht\nAudit-Log.\n* Fremdwährungen USD/EUR brauchen FX-Kurs und CHF-Gegenwert.\n* Keine Scheingenauigkeit, wenn Kaufhistorie, Gebühren oder historische FX fehlen.\n* Erst mit synthetischen Daten und Dummy-Depots bauen.\n* Keine echten PostFinance-/TrueWealth-/Raiffeisen-Daten importieren.\n\nBitte vormerken für die Equity/ETF Manage UI:\n\n* Aktie/ETF als Initial Snapshot hinzufügen\n* Buy\n* Partial Sell\n* Full Sell\n* Dividend\n* ETF Distribution\n* Fee\n* Manual Adjustment\n* ISIN Pflicht oder stark empfohlen\n* ISIN/Ticker dürfen nicht beide leer sein\n* Währung Pflicht\n* Depot/Konto Pflicht\n* FX bei Fremdwährung\n* Audit-Log Pflicht\n* Notiz Pflicht bei manual_adjustment oder unvollständiger Historie\n\n## Weitere Funktionsmodule bitte vormerken, aber noch nicht bauen\n\nBitte für später als Backlog vormerken:\n\n1. Portfolio Health Seite\n\n* Gesamtwert CHF\n* Assetklassen\n* Plattformen\n* Datenqualität\n* Cashquote\n* fehlende Preise/FX\n\n2. Reconciliation / Abgleich-Seite\n\n* Dashboard-Bestand vs. letzter Snapshot\n* manuelle Prüfung „Bestand geprüft am Datum X“\n* Differenzen sichtbar machen\n\n3. Data Quality Center\n\n* fehlende Preise\n* stale prices\n* fehlende FX\n* fehlende ISIN\n* fehlende CoinGecko-ID\n* unvollständige Historie\n\n4. Manual Review Queue\n\n* ausgelassene Coins\n* unsichere Mappings\n* offene Alerts\n* offene Datenqualitätsprobleme\n\n5. Backup / Restore\n\n* Runtime-DB Backup\n* verschlüsseltes Backup optional\n* Restore-Test später\n\n6. Safe Mode / Read-only Mode\n\n* Dashboard im Lesemodus\n* Schreibfunktionen bewusst aktivieren\n* Schutz gegen versehentliche Änderungen\n\nBitte jetzt zuerst Teil 1 umsetzen, dann Teil 2, dann Teil 3. Keine echten Aktien-/ETF-Daten importieren."
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_aPJB5BHKCgjvCyFPcmSxWkXr",
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"id": "rs_0134d7700e125cf0016a071d6e3c108191b6d343c87049ffab",
"summary": []
}
]
},
{
"role": "tool",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -53,6 +53,52 @@\\n \\n def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n return []\\n+\\n+\\n+class OpenFIGILookupProvider:\\n+ \\\"\\\"\\\"Public ISIN-to-instrument metadata lookup via OpenFIGI; no prices or portfolio data.\\\"\\\"\\\"\\n+\\n+ name = \\\"openfigi\\\"\\n+\\n+ def __init__(self, *, timeout_seconds: float = 8.0):\\n+ self.timeout_seconds = timeout_seconds\\n+\\n+ def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n+ if not isin:\\n+ return []\\n+ token = os.environ.get(\\\"OPENFIGI_API_KEY\\\")\\n+ headers = {\\\"Content-Type\\\": \\\"application/json\\\", \\\"User-Agent\\\": \\\"JarvisFinance/1.0 public-instrument-lookup\\\"}\\n+ if token:\\n+ headers[\\\"X-OPENFIGI-APIKEY\\\"] = token\\n+ payload = json.dumps([{\\\"idType\\\": \\\"ID_ISIN\\\", \\\"idValue\\\": isin}]).encode(\\\"utf-8\\\")\\n+ req = urllib.request.Request(\\\"https://api.openfigi.com/v3/mapping\\\", data=payload, headers=headers, method=\\\"POST\\\")\\n+ try:\\n+ with urllib.request.urlopen(req, timeout=self.timeout_seconds) as resp:\\n+ data = json.loads(resp.read().decode(\\\"utf-8\\\"))\\n+ except Exception as exc: # pragma: no cover - network dependent\\n+ raise LookupUnavailable(str(exc)) from exc\\n+ out: list[ProviderCandidate] = []\\n+ for item in (data[0].get(\\\"data\\\", []) if data else []):\\n+ symbol = item.get(\\\"ticker\\\") or item.get(\\\"figi\\\")\\n+ if not symbol:\\n+ continue\\n+ sec_type = \\\" \\\".join(str(item.get(k) or \\\"\\\") for k in (\\\"securityType\\\", \\\"securityType2\\\", \\\"marketSector\\\")).lower()\\n+ asset_class = \\\"etf\\\" if \\\"fund\\\" in sec_type or \\\"etf\\\" in sec_type else \\\"equity\\\" if \\\"equity\\\" in sec_type else None\\n+ out.append(ProviderCandidate(\\n+ provider=self.name,\\n+ provider_symbol=symbol,\\n+ exchange=item.get(\\\"exchCode\\\") or item.get(\\\"marketSector\\\"),\\n+ currency=item.get(\\\"currency\\\") or currency,\\n+ name=item.get(\\\"name\\\"),\\n+ isin=isin,\\n+ asset_class=asset_class,\\n+ hedge_status=\\\"unknown\\\",\\n+ instrument_status=\\\"unknown\\\",\\n+ valuation_policy=\\\"live_price\\\",\\n+ evidence_source=\\\"openfigi_isin_mapping\\\",\\n+ evidence_note=\\\"Public ISIN mapping metadata only; no prices, holdings, account data, or portfolio quantities sent.\\\",\\n+ ))\\n+ return out\\n \\n \\n class YahooSearchLookupProvider:\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_1L1egOJMKZSMc18qMRe9AuO5"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_WYZdwtDkv3pgKzwiXP67RsmO",
"call_id": "call_WYZdwtDkv3pgKzwiXP67RsmO",
"response_item_id": "fc_0134d7700e125cf0016a071d86d5148191b351c68191d8da46",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\" isin=None,\\n asset_class=asset_class,\",\"old_string\":\" isin=isin if isin and query == isin else None,\\n asset_class=asset_class,\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
}
],
"finish_reason": "tool_calls"
},
{
"role": "tool",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -136,7 +136,7 @@\\n exchange=exch,\\n currency=currency,\\n name=quote.get(\\\"longname\\\") or quote.get(\\\"shortname\\\"),\\n- isin=isin if isin and query == isin else None,\\n+ isin=None,\\n asset_class=asset_class,\\n hedge_status=\\\"unknown\\\",\\n instrument_status=\\\"unknown\\\",\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_WYZdwtDkv3pgKzwiXP67RsmO"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_zbPFub5SplrpbIEatkMOPQBb",
"call_id": "call_zbPFub5SplrpbIEatkMOPQBb",
"response_item_id": "fc_0134d7700e125cf0016a071d8bf2948191abf13feda2a16481",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\" self.providers = providers or [OpenFIGILookupProvider(), YahooSearchLookupProvider()]\",\"old_string\":\" self.providers = providers or [YahooSearchLookupProvider()]\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
}
],
"finish_reason": "tool_calls"
},
{
"role": "tool",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -152,7 +152,7 @@\\n name = \\\"public_composite\\\"\\n \\n def __init__(self, providers: list[InstrumentLookupProvider] | None = None):\\n- self.providers = providers or [YahooSearchLookupProvider()]\\n+ self.providers = providers or [OpenFIGILookupProvider(), YahooSearchLookupProvider()]\\n \\n def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n candidates: list[ProviderCandidate] = []\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_zbPFub5SplrpbIEatkMOPQBb"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_JMF04iH47rQo6rGpO8Tkox2n",
"call_id": "call_JMF04iH47rQo6rGpO8Tkox2n",
"response_item_id": "fc_0134d7700e125cf0016a071d91f7e08191b8a421c904629301",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"PYTHONPATH=src pytest -q tests/unit/test_true_wealth_mapping_candidates_c3.py tests/unit/test_schema.py\",\"timeout\":300,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Figuring out tests**\n\nI think I need to add some tests to compile things properly. It’s crucial to ensure everything works as it should, right? I wonder if there are specific tests I should focus on first. I could start with the most critical functions or elements and then work my way through the less essential ones. Testing might help catch any potential issues early, which would be super helpful! Let's get started on that!",
"reasoning_content": "**Figuring out tests**\n\nI think I need to add some tests to compile things properly. It’s crucial to ensure everything works as it should, right? I wonder if there are specific tests I should focus on first. I could start with the most critical functions or elements and then work my way through the less essential ones. Testing might help catch any potential issues early, which would be super helpful! Let's get started on that!",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABqBx2RrSoU8EZYLij_roLT-eisQw9DEQ1BSz3zIvQLZ6WVgI8qrBxQAY3_9L9q0AO1UssODXfWKe33-QgK_tMSBVqWPOJDKsy4d6H-8SyDKBEom0J6wWZx958QPcNbeNxJLQz514Mho3nmHagYy-ebkPISU3Jip9YbTJr0NWh3K4OPEl0IP1Lk66_H5RNpTq6X6k2O7PbpeBUH_bms6nwc7WQivsoqkj5pTreFt1Cdj-cnxu0SnbvAQgAhMX8-4HAB1XmLiMhn7DP6b5h2uwoQ3HhrHjYx7_yfZioaLxoHn6bsc6Gk0pV5mQqXKogwdPaS7Mf1xxT1jA1RIwPXo2nnxSHgA0X0vCE6R4roH0X2S12oYnY4KFnSsLPOnEh6CKgoRiH6FjvIJl0xRF-MnCSYmJPrR7rT2vEwEuIwk64FYJ9785cvv3OARBJ1BGqjBMR9AlmmNBfAsc8SmRc8ceMWXqLbT3UmrrhZ9HJKjcnw1qOC_O1lglhUgFzxzG6t0iJBJsc2ht2o-StJCp-ZnHQBMJbSM3bgE1fg_wn-0_1yH0PMpR-RQIV4ZCQ5NgHlyaH9pYyWua1SQdgVMlgdNQK9lxs7yKwfagEVicb6rD2NRYVkboBStsoKKRi2ckpHLdgPy7EA97NBVrYRuRpw8PUXBYYF-byqT6OppTIHu-lQFDjHgn8OjmhYx_ZsJmfxUQJXyd9ooqFELJwLHQiR2PZq5Co_63a8zgz345h6uCPfnL-EgGeEqMQc8UyLCjDdA4qzUq6CrulmpjXejFHKT-Oq2d2qdPkTf5cSKH_tpp-nnHqZbxCWtEhCjtOofa6Quu-5nSPG9vB-Pc7T7hpzw_Ldsi9IgmB0mPg_kSI_r0Z3ZpYWIwCVPr__GofiXE3CxnkZTYprpGBnJGPMfFJ0MINyaKkq_7vjZyMrDNS-sdg063NsEZwL6EJmnChViEW8vItBKyb0",
"id": "rs_0134d7700e125cf0016a071d90a3ec8191a3ac3dddfc66a4c9",
"summary": [
{
"type": "summary_text",
"text": "**Figuring out tests**\n\nI think I need to add some tests to compile things properly. It’s crucial to ensure everything works as it should, right? I wonder if there are specific tests I should focus on first. I could start with the most critical functions or elements and then work my way through the less essential ones. Testing might help catch any potential issues early, which would be super helpful! Let's get started on that!"
}
]
}
]
},
{
"role": "tool",
"content": "{\"output\": \"................... [100%]\\n19 passed in 0.39s\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_JMF04iH47rQo6rGpO8Tkox2n"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_VuCzDoJ41YVLig2RUVkUpsGX",
"call_id": "call_VuCzDoJ41YVLig2RUVkUpsGX",
"response_item_id": "fc_0134d7700e125cf0016a071d984b348191a87c87eb4cc6d847",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"PYTHONPATH=src python - <<'PY'\\nfrom collections import Counter, defaultdict\\nfrom jarvis_finance.config.settings import load_settings\\nfrom jarvis_finance.storage.database import connect\\nfrom jarvis_finance.storage.migrations import apply_migrations\\nsettings=load_settings(); conn=connect(settings.db_path); apply_migrations(conn)\\nrows=conn.execute(\\\"SELECT alert_id,entity_type,entity_id,fingerprint FROM alerts WHERE status='active' AND rule_id='missing_provider_symbol'\\\").fetchall()\\nprint({'active_missing_provider_symbol': len(rows), 'by_entity_type': dict(Counter(r['entity_type'] for r in rows)), 'duplicate_entities': sum(1 for k,v in Counter((r['entity_type'], r['entity_id']) for r in rows).items() if v>1)})\\nconn.close()\\nPY\",\"timeout\":180,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Testing and updating tasks**\n\nI need to run full tests later and update my to-do list. But first, I should start with a runtime run. It seems there’s a need for “no portfolio data to external.” The CLI public lookup provides ISIN, ticker, and name, which includes metadata from the DB, though not the quantity. I think I need to query before proceeding. Oh, and I should check the active counts for any generated alerts. I'll use terminal Python to aggregate that information.",
"reasoning_content": "**Testing and updating tasks**\n\nI need to run full tests later and update my to-do list. But first, I should start with a runtime run. It seems there’s a need for “no portfolio data to external.” The CLI public lookup provides ISIN, ticker, and name, which includes metadata from the DB, though not the quantity. I think I need to query before proceeding. Oh, and I should check the active counts for any generated alerts. I'll use terminal Python to aggregate that information.",
"codex_reasoning_items": [
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"id": "rs_0134d7700e125cf0016a071db5af0481918c08ccfd6850dc2e",
"summary": [
{
"type": "summary_text",
"text": "**Evaluating candidate limits**\n\nI'm noticing we have 336 candidates due to excessive OpenFIGI returns, which seems like too many. I wonder if we should limit the number of results per provider. Maybe capping OpenFIGI to a max of 20 results could help, but the current runtime has already exceeded that. How about implementing a cleanup before generating new candidates? An optional generator could be useful to prune prior candidates as well. Overall, we definitely need to manage this more effectively."
},
{
"type": "summary_text",
"text": "**Planning cleanup and adjustments**\n\nI’m considering doing a manual cleanup before rerunning the process, while also setting a default cap for OpenFIGI results. I'm wondering if a max of 8 results is enough, but since one ISIN can relate to multiple exchanges, I think 12 would be better. After that, I could perform a runtime cleanup by deleting unconfirmed candidates for the three instruments and rerun the process. I should also run query counts after the cleanup since it seems like there's a high candidate distribution."
}
]
}
]
},
{
"role": "tool",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -60,8 +60,9 @@\\n \\n name = \\\"openfigi\\\"\\n \\n- def __init__(self, *, timeout_seconds: float = 8.0):\\n+ def __init__(self, *, timeout_seconds: float = 8.0, max_results: int = 12):\\n self.timeout_seconds = timeout_seconds\\n+ self.max_results = max_results\\n \\n def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n if not isin:\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_xgvSi0mKBIsh1MVclazxqiWv"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_fkEKo5ZPYeSE0G2YjzUZ5Z7Q",
"call_id": "call_fkEKo5ZPYeSE0G2YjzUZ5Z7Q",
"response_item_id": "fc_0134d7700e125cf0016a071dc30c688191a7a09895161cb58d",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\" for item in (data[0].get(\\\"data\\\", []) if data else [])[: self.max_results]:\",\"old_string\":\" for item in (data[0].get(\\\"data\\\", []) if data else []):\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
}
],
"finish_reason": "tool_calls"
},
{
"role": "tool",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -79,7 +79,7 @@\\n except Exception as exc: # pragma: no cover - network dependent\\n raise LookupUnavailable(str(exc)) from exc\\n out: list[ProviderCandidate] = []\\n- for item in (data[0].get(\\\"data\\\", []) if data else []):\\n+ for item in (data[0].get(\\\"data\\\", []) if data else [])[: self.max_results]:\\n symbol = item.get(\\\"ticker\\\") or item.get(\\\"figi\\\")\\n if not symbol:\\n continue\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_fkEKo5ZPYeSE0G2YjzUZ5Z7Q"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_8947RS06kGPLrPMxqvJm01Y0",
"call_id": "call_8947RS06kGPLrPMxqvJm01Y0",
"response_item_id": "fc_0134d7700e125cf0016a071dcc5ab881919a0aa22e5ded4877",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"PYTHONPATH=src python - <<'PY'\\nfrom jarvis_finance.config.settings import load_settings\\nfrom jarvis_finance.storage.database import connect\\nfrom jarvis_finance.storage.migrations import apply_migrations\\nsettings=load_settings(); conn=connect(settings.db_path); apply_migrations(conn)\\nids=[r['instrument_id'] for r in conn.execute(\\\"SELECT DISTINCT instrument_id FROM transactions WHERE transaction_type='initial_position_snapshot' AND source_type='broker_import_reviewed_snapshot' AND COALESCE(is_voided,0)=0 AND instrument_id IS NOT NULL ORDER BY instrument_id LIMIT 3\\\").fetchall()]\\nif ids:\\n q=','.join('?' for _ in ids)\\n conn.execute(f\\\"DELETE FROM instrument_price_mapping_candidates WHERE instrument_id IN ({q}) AND review_status IN ('proposed','needs_manual_review')\\\", ids)\\nconn.commit(); print({'cleaned_instruments': len(ids)})\\nconn.close()\\nPY\\nPYTHONPATH=src python -m jarvis_finance.cli.main generate-mapping-candidates --source true_wealth --limit 3 --public-lookup --dedupe-missing-provider-alerts --export-template\",\"timeout\":300,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Cleaning up data**\n\nI need to run a cleanup and maybe rerun an operation. I'll use SQL to delete unselected candidates, and I'm considering whether to create alerts for ambiguous duplicates. It might be good to ensure that the deduplication process increments correctly while avoiding duplicates entirely. Overall, I plan to execute the cleanup along with the command line interface (CLI) execution. Just need to double-check that everything aligns properly!",
"reasoning_content": "**Cleaning up data**\n\nI need to run a cleanup and maybe rerun an operation. I'll use SQL to delete unselected candidates, and I'm considering whether to create alerts for ambiguous duplicates. It might be good to ensure that the deduplication process increments correctly while avoiding duplicates entirely. Overall, I plan to execute the cleanup along with the command line interface (CLI) execution. Just need to double-check that everything aligns properly!",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABqBx3MNDxjyjaWDd5MCRgK17Sop2qEu-ntGjuGy1CE5C4oWSj3yIuFqQ5KZhZu7gjUgw8fqqnGHc6LySxDX3x_jkoIfJikkQsZ3llBPGInxLcnxV5HU4yIr0mSKIjPs1dl9K0ISA3eTloOUsyT1MdHEOB3O6GdKlRI1klRDdOcgFYkorJ4DCTqeUeKxqjL9Dh7semGISHz8QDqhyYPdVpdv89hD0C2w1q3q_Xa37JDxdsMgmjhRw2znUROuXvVCdq_ojSTZ0eJ_8GWmXoLPrg1mUp1HgF0vihhF863Yw2PEr23dlriupXzmUtR5gS3HzojJStVQviPiHig1tlbrw4rGVa_sCxgpXL_d5yB5zd7sJwiVlI42x2-WRCmJfUEVikri3-YhRHREqZMVNgFYmga9xq1isvbCgCVv58RiSEqtGMUHn5-dRYAa7M3Tf4utXCe1QJ9oSjvaIjLps0PeNTnF0gXO5UsXDygShjz4bHGHmSRXhNq_-BBOHA3N9091FJVOsI_8i5iESPOyq99tguTc1HYKeZPc5HRzoET3kTM9WNfq-q4MKvJeElzUJUmBR4IvYDV8I-eD3pjnQ33_z76jfKCEO8iEk3G2mg_C-oFsXFsKu3gGiTRasIRLSMmeZVdXHJ4zJq_hWmZyDyOyHcTdm97otZehDHmEhFb-0fR2qZdA1QrPHgcD48UeMaUPuVMa3oMtiejszAeyaF0iTLDP5mNRv3W7FgWVrXTKx2Gwn81RYGe_0oT4a5vicpAuy2yolwYakyZA-Xo2Aa1VFyRaKvKNrE0RaJ_mkXMIJB-TmoMD3_nIrvSJGudoUncHOEGNHOZ2v4jlWb_No3vdWf4P7d6rOupgk9J2RlEQgvpMitRtxl_4tSWj7RpDGngcETmykjAobxO8G0H5yiSD6ILMb-axfPI_LSQZOXXje4Bn0Ik5ugM6d3eckYuT_V0YVdNq7wpXJSqr5NcNgpmAvX-Y9Zy3v6_JOjB-OZnjdngvGgrUpmwDpIcN-9CbNVAEwaBjTymSEB2ZzHYcpBLda8A_lvr6IYxrJkxTU_uBYU4lok-6SYIjuceSc6ZtvENC93BOWWM2YlQVJ9viECXdVVBX7bf3aQQgmDSlPReq3XBKVbRW9x9cX9da5-RRGaUHJhP7Q9T",
"id": "rs_0134d7700e125cf0016a071dca737481919206879de8ebff2d",
"summary": [
{
"type": "summary_text",
"text": "**Cleaning up data**\n\nI need to run a cleanup and maybe rerun an operation. I'll use SQL to delete unselected candidates, and I'm considering whether to create alerts for ambiguous duplicates. It might be good to ensure that the deduplication process increments correctly while avoiding duplicates entirely. Overall, I plan to execute the cleanup along with the command line interface (CLI) execution. Just need to double-check that everything aligns properly!"
}
]
}
]
},
{
"role": "tool",
"content": "{\"output\": \"{'cleaned_instruments': 3}\\nMAPPING_CANDIDATES instruments_total=3 candidates_found=57 high=36 medium=18 low=3 instruments_without_candidate=0 hedge_unknown=3 instrument_status_unknown=3 provider_lookup_unavailable=0 ambiguous=3 deduped_missing_provider_alerts=0 template_updated=true template_instruments=3 template_candidates=57 dry_run=false\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_8947RS06kGPLrPMxqvJm01Y0"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_kytQ3PTrZGzle6nZ6zU26wsY",
"call_id": "call_kytQ3PTrZGzle6nZ6zU26wsY",
"response_item_id": "fc_0134d7700e125cf0016a071dd9682c8191b7e38bd48f64c3c3",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"PYTHONPATH=src python - <<'PY'\\nfrom collections import Counter\\nfrom jarvis_finance.config.settings import load_settings\\nfrom jarvis_finance.storage.database import connect\\nfrom jarvis_finance.storage.migrations import apply_migrations\\nsettings=load_settings(); conn=connect(settings.db_path); apply_migrations(conn)\\ninst=[r['instrument_id'] for r in conn.execute(\\\"SELECT DISTINCT instrument_id FROM transactions WHERE transaction_type='initial_position_snapshot' AND source_type='broker_import_reviewed_snapshot' AND COALESCE(is_voided,0)=0 AND instrument_id IS NOT NULL\\\").fetchall()]\\nq=','.join('?' for _ in inst) if inst else \\\"''\\\"\\nrows=conn.execute(f\\\"SELECT confidence,review_status,candidate_hedge_status,candidate_instrument_status,instrument_id FROM instrument_price_mapping_candidates WHERE instrument_id IN ({q})\\\", inst).fetchall() if inst else []\\nalerts=conn.execute(\\\"SELECT rule_id, COUNT(*) AS c FROM alerts WHERE status='active' GROUP BY rule_id ORDER BY rule_id\\\").fetchall()\\nper_inst=Counter(r['instrument_id'] for r in rows)\\nprint({\\n 'instruments_total': len(inst),\\n 'candidates_total': len(rows),\\n 'confidence': dict(Counter(r['confidence'] for r in rows)),\\n 'review_status': dict(Counter(r['review_status'] for r in rows)),\\n 'without_candidate': sum(1 for iid in inst if per_inst[iid]==0),\\n 'with_multiple_candidates': sum(1 for iid in inst if per_inst[iid]>1),\\n 'hedge_candidate_known': sum(1 for r in rows if r['candidate_hedge_status']!='unknown'),\\n 'instrument_status_candidate_known': sum(1 for r in rows if r['candidate_instrument_status']!='unknown'),\\n 'instrument_hedge_unknown': conn.execute(f\\\"SELECT COUNT(*) AS c FROM instruments WHERE instrument_id IN ({q}) AND COALESCE(hedge_status,'unknown')='unknown'\\\", inst).fetchone()['c'] if inst else 0,\\n 'instrument_status_unknown': conn.execute(f\\\"SELECT COUNT(*) AS c FROM instruments WHERE instrument_id IN ({q}) AND COALESCE(instrument_status,'unknown')='unknown'\\\", inst).fetchone()['c'] if inst else 0,\\n 'active_alerts_by_rule': {r['rule_id']: r['c'] for r in alerts},\\n 'template_exists': str(settings.runtime_paths.exports_dir/'true_wealth_mapping_review_template.csv')\\n})\\nconn.close()\\nPY\",\"timeout\":180,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Clarifying numbers and queries**\n\nI’m looking at the number 57 and wondering if that's manageable—maybe it is with 3 instruments and an average of 19. Yet, I think I need to clarify what \"Kandidaten pro Instrument\" means in the context of aggregating multiple entries. I should also query DQ about it. There’s also a question regarding the status of candidates for hedges, which seems to be unknown at the moment, so I need counts on that too.",
"reasoning_content": "**Clarifying numbers and queries**\n\nI’m looking at the number 57 and wondering if that's manageable—maybe it is with 3 instruments and an average of 19. Yet, I think I need to clarify what \"Kandidaten pro Instrument\" means in the context of aggregating multiple entries. I should also query DQ about it. There’s also a question regarding the status of candidates for hedges, which seems to be unknown at the moment, so I need counts on that too.",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABqBx3Zo4Oa9MQqlge5JLVc2_SSBboLDXySG6u8Wf6Oban-ZMuD2P4zdQ_2XbtqPWdEObJ0pqO7yEHL7CtXKn9_ew-pJCvJ9K6Q8FSoVCPNCdQoCMQReuQQ3nOIVffhQbq2ekMBEsgVZTc9Ws24xycAvhTTctDv2kxGoyaO2MBiYIU54pgxwRMJ1ZlHrix2DpBtnm1JlfEiXiwty0B89ztWV6gus2Ws_LCuyBu4OuAZ__nZgFZOEgytN_fOZyXPd5Od3HJq2amiQWIBQ8I9aCUparC1Hn9vsz8xkIu0w5ihBAp0ql_VB7876_RYzPnJHIarTbj4xHpfbh6fb39qfKny9N-6mYP7ld85KbLKI6wstTnvnKaYaNpSsvVqr8nHZjBR2oziqSEp1EgRmJS6kzTknjwflFqV7Hwj4vNRZhNLMgMVpsPvLO-nNxjKiNNeulAsYJMnenK7E4KxeHtefsdrfKhyUG0fzidsuBjVA_lHWvde0GvbZ8uidtQMlFhztpWYg-v_DI5asAFMZjTywqQAT2dgxGq6IMJBRXmIjKFzf0LyJ6GjtCkPR4phpP447C-frIhatJRsTSedYPaYivin4gM6hikL5uuzAsohgUT3tLbO-NZn37zeA7V0tAOYlyriJc1jmuFOz7H9NUgzwjeleGdI9yOeuqa5aOGZcQ6Py0-OgHF0Gb4KyuyhZaHETsVZQJaoA4owgb2FA0rglu5UFqk5q9OBWqsfb_eGTVH51lXqEyaJ25Yh-bY6aJS7OlBpyn9ICyDcueHldqFKiDKWFM9nqduYfxBfxecKlOi-gn6-0KzayuSkiN8vwn3carh0qhZfKFouJtI_OGSQXI5NcucVP4HPovJxwj4kU5SZrN1rzhtXEzyku6s89NXi4RHatVg6Tsee5x7_jlTk5AGDRJ4KmmIY-_yjcVF6KOCLnenoqDjjTITd8JumDRV6QgO42fkdpFoHX3FvxipO3YFRX6352lErOj6drRngWkOdxOnTYJ6hsGtRQZFLaJ99Q5vEG4rUCaf7eLcPetNAm0Pz4OrC9MFbXzRf53mMCJ38fo6ddRcNVXK20FNYHUClKVALcF89NE5a3_7M9nGEFlijfzTIAY08Af4TttXppN0T2xk2bfQf6WjEMKohCBHiHm3zXRDnuYSZc1fxrx6ICHVTl96to9MtrYDigy_gk8jKuMpiD2E8Car6ezEf05XRZwM6wZu1xLB-nvJL3TGIaoRVdLKui3T_sm9cMqixEnHz2og4p18=",
"id": "rs_0134d7700e125cf0016a071dd5d9e48191b2416e0f037b88fc",
"summary": [
{
"type": "summary_text",
"text": "**Clarifying numbers and queries**\n\nI’m looking at the number 57 and wondering if that's manageable—maybe it is with 3 instruments and an average of 19. Yet, I think I need to clarify what \"Kandidaten pro Instrument\" means in the context of aggregating multiple entries. I should also query DQ about it. There’s also a question regarding the status of candidates for hedges, which seems to be unknown at the moment, so I need counts on that too."
}
]
}
]
},
{
"role": "tool",
"content": "{\"output\": \"{'instruments_total': 3, 'candidates_total': 57, 'confidence': {'high': 36, 'medium': 18, 'low': 3}, 'review_status': {'needs_manual_review': 57}, 'without_candidate': 0, 'with_multiple_candidates': 3, 'hedge_candidate_known': 0, 'instrument_status_candidate_known': 0, 'instrument_hedge_unknown': 3, 'instrument_status_unknown': 3, 'active_alerts_by_rule': {'ambiguous_provider_mapping': 6, 'cost_basis_uncertain': 3, 'hedge_status_unknown': 3, 'instrument_status_unknown': 3, 'manual_review_needed': 3, 'missing_fx': 3, 'missing_market_price': 3, 'missing_provider_symbol': 3, 'snapshot_only': 3}, 'template_exists': '/home/agent/jarvis_runtime/finance-system/exports/true_wealth_mapping_review_template.csv'}\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_kytQ3PTrZGzle6nZ6zU26wsY"
},
{
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"content": "",
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{
"id": "call_QiUc3EoUIvQ2QYXjRFMza9PP",
"call_id": "call_QiUc3EoUIvQ2QYXjRFMza9PP",
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"arguments": "{\"mode\":\"replace\",\"new_string\":\"def dedupe_missing_provider_symbol_alerts(conn: Connection) -> int:\\n \\\"\\\"\\\"Keep one active mapping-quality alert per rule/instrument; resolve duplicate active rows.\\\"\\\"\\\"\\n now = utc_now()\\n resolved = 0\\n rows = conn.execute(\\n \\\"\\\"\\\"\\n SELECT rule_id, entity_id, GROUP_CONCAT(alert_id) AS ids, COUNT(*) AS c\\n FROM alerts\\n WHERE status='active'\\n AND rule_id IN ('missing_provider_symbol','ambiguous_provider_mapping','provider_lookup_unavailable')\\n AND entity_type='instrument'\\n GROUP BY rule_id, entity_id\\n HAVING COUNT(*) > 1\\n \\\"\\\"\\\"\\n ).fetchall()\\n for row in rows:\\n ids = [x for x in (row[\\\"ids\\\"] or \\\"\\\").split(\\\",\\\") if x]\\n for alert_id in ids[1:]:\\n conn.execute(\\\"UPDATE alerts SET status='resolved', resolved_at=?, last_seen_at=? WHERE alert_id=?\\\", (now, now, alert_id))\\n resolved += 1\\n conn.commit()\\n return resolved\",\"old_string\":\"def dedupe_missing_provider_symbol_alerts(conn: Connection) -> int:\\n \\\"\\\"\\\"Keep one active missing-provider-symbol alert per instrument; resolve duplicates.\\\"\\\"\\\"\\n now = utc_now()\\n resolved = 0\\n rows = conn.execute(\\n \\\"\\\"\\\"\\n SELECT entity_id, GROUP_CONCAT(alert_id) AS ids, COUNT(*) AS c\\n FROM alerts\\n WHERE status='active' AND rule_id='missing_provider_symbol' AND entity_type='instrument'\\n GROUP BY entity_id\\n HAVING COUNT(*) > 1\\n \\\"\\\"\\\"\\n ).fetchall()\\n for row in rows:\\n ids = [x for x in (row[\\\"ids\\\"] or \\\"\\\").split(\\\",\\\") if x]\\n for alert_id in ids[1:]:\\n conn.execute(\\\"UPDATE alerts SET status='resolved', resolved_at=?, last_seen_at=? WHERE alert_id=?\\\", (now, now, alert_id))\\n resolved += 1\\n conn.commit()\\n return resolved\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Evaluating deduplication strategies**\n\nI'm assessing how to handle six ambiguous duplicates. It seems I might need to create a deduplication alert key using fingerprint and entity to reduced down to three. My previous run had a candidate count of 100 compared to 19 created, which might have changed the fingerprint. I’m considering whether I need to deduplicate ambiguous entries too. Maybe an active alerts deduplication function per entity is a good idea? And possibly include a SQL approach? I’ll need to patch the deduplication functionality for both missing and ambiguous alerts.\n**Finalizing deduplication process**\n\nI need to ensure that the final count of active ambiguous alerts is three. I’m considering using manual SQL for that and modifying the dedupe function for missing provider alerts to also handle various rules for each entity. This will return a total count. The naming might not be perfect, but it's acceptable for now. I'll check if the test passes and then rerun the CLI dedupe without cleanup. It should upsert candidates while resolving duplicates from different fingerprints. I’ve observed a decrease in duplicates after the dedupe. Time to patch the function!",
"reasoning_content": "**Evaluating deduplication strategies**\n\nI'm assessing how to handle six ambiguous duplicates. It seems I might need to create a deduplication alert key using fingerprint and entity to reduced down to three. My previous run had a candidate count of 100 compared to 19 created, which might have changed the fingerprint. I’m considering whether I need to deduplicate ambiguous entries too. Maybe an active alerts deduplication function per entity is a good idea? And possibly include a SQL approach? I’ll need to patch the deduplication functionality for both missing and ambiguous alerts.\n**Finalizing deduplication process**\n\nI need to ensure that the final count of active ambiguous alerts is three. I’m considering using manual SQL for that and modifying the dedupe function for missing provider alerts to also handle various rules for each entity. This will return a total count. The naming might not be perfect, but it's acceptable for now. I'll check if the test passes and then rerun the CLI dedupe without cleanup. It should upsert candidates while resolving duplicates from different fingerprints. I’ve observed a decrease in duplicates after the dedupe. Time to patch the function!",
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"id": "rs_0134d7700e125cf0016a071de4c4bc8191876692541ffd0740",
"summary": [
{
"type": "summary_text",
"text": "**Evaluating deduplication strategies**\n\nI'm assessing how to handle six ambiguous duplicates. It seems I might need to create a deduplication alert key using fingerprint and entity to reduced down to three. My previous run had a candidate count of 100 compared to 19 created, which might have changed the fingerprint. I’m considering whether I need to deduplicate ambiguous entries too. Maybe an active alerts deduplication function per entity is a good idea? And possibly include a SQL approach? I’ll need to patch the deduplication functionality for both missing and ambiguous alerts."
},
{
"type": "summary_text",
"text": "**Finalizing deduplication process**\n\nI need to ensure that the final count of active ambiguous alerts is three. I’m considering using manual SQL for that and modifying the dedupe function for missing provider alerts to also handle various rules for each entity. This will return a total count. The naming might not be perfect, but it's acceptable for now. I'll check if the test passes and then rerun the CLI dedupe without cleanup. It should upsert candidates while resolving duplicates from different fingerprints. I’ve observed a decrease in duplicates after the dedupe. Time to patch the function!"
}
]
}
]
},
{
"role": "tool",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -341,15 +341,17 @@\\n \\n \\n def dedupe_missing_provider_symbol_alerts(conn: Connection) -> int:\\n- \\\"\\\"\\\"Keep one active missing-provider-symbol alert per instrument; resolve duplicates.\\\"\\\"\\\"\\n+ \\\"\\\"\\\"Keep one active mapping-quality alert per rule/instrument; resolve duplicate active rows.\\\"\\\"\\\"\\n now = utc_now()\\n resolved = 0\\n rows = conn.execute(\\n \\\"\\\"\\\"\\n- SELECT entity_id, GROUP_CONCAT(alert_id) AS ids, COUNT(*) AS c\\n+ SELECT rule_id, entity_id, GROUP_CONCAT(alert_id) AS ids, COUNT(*) AS c\\n FROM alerts\\n- WHERE status='active' AND rule_id='missing_provider_symbol' AND entity_type='instrument'\\n- GROUP BY entity_id\\n+ WHERE status='active'\\n+ AND rule_id IN ('missing_provider_symbol','ambiguous_provider_mapping','provider_lookup_unavailable')\\n+ AND entity_type='instrument'\\n+ GROUP BY rule_id, entity_id\\n HAVING COUNT(*) > 1\\n \\\"\\\"\\\"\\n ).fetchall()\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_QiUc3EoUIvQ2QYXjRFMza9PP"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_sP92BTkYnKKTwBd7dZWQluTT",
"call_id": "call_sP92BTkYnKKTwBd7dZWQluTT",
"response_item_id": "fc_0134d7700e125cf0016a071df85a848191b0c860fe826669f4",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"PYTHONPATH=src python -m jarvis_finance.cli.main generate-mapping-candidates --source true_wealth --limit 3 --public-lookup --dedupe-missing-provider-alerts --export-template\",\"timeout\":300,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
],
"finish_reason": "tool_calls"
},
{
"role": "tool",
"content": "{\"output\": \"MAPPING_CANDIDATES instruments_total=3 candidates_found=57 high=36 medium=18 low=3 instruments_without_candidate=0 hedge_unknown=3 instrument_status_unknown=3 provider_lookup_unavailable=0 ambiguous=3 deduped_missing_provider_alerts=3 template_updated=true template_instruments=3 template_candidates=59 dry_run=false\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_sP92BTkYnKKTwBd7dZWQluTT"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_smxaogJdx2tFZls16uyhbd2R",
"call_id": "call_smxaogJdx2tFZls16uyhbd2R",
"response_item_id": "fc_0134d7700e125cf0016a071e0562008191ac88e84dfd94d66a",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"PYTHONPATH=src python - <<'PY'\\nfrom collections import Counter\\nfrom jarvis_finance.config.settings import load_settings\\nfrom jarvis_finance.storage.database import connect\\nfrom jarvis_finance.storage.migrations import apply_migrations\\nconn=connect(load_settings().db_path); apply_migrations(conn)\\nrows=conn.execute(\\\"SELECT review_status, COUNT(*) c FROM instrument_price_mapping_candidates GROUP BY review_status\\\").fetchall()\\nprint({r['review_status']:r['c'] for r in rows})\\nprint(conn.execute(\\\"SELECT COUNT(*) c FROM instrument_price_mapping_candidates\\\").fetchone()['c'])\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Reviewing template candidates**\n\nI’m looking at template candidates and noticing we have 59, which seems odd since we only deleted three from the first limit by instrument_id. Wait, is it possible there are actually 57 active candidates? I need to query all to check that. It might be I’m dealing with selected or rejected old ones. I should clean all unselected candidates for True Wealth before the rerun. And I should also check the counts by review status for clarity.",
"reasoning_content": "**Reviewing template candidates**\n\nI’m looking at template candidates and noticing we have 59, which seems odd since we only deleted three from the first limit by instrument_id. Wait, is it possible there are actually 57 active candidates? I need to query all to check that. It might be I’m dealing with selected or rejected old ones. I should clean all unselected candidates for True Wealth before the rerun. And I should also check the counts by review status for clarity.",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABqBx4F33SNxGQff0ndQvnJb0AAelH9KRl_SEuHN8G-WrR8tqYAEYNaQ6Rr5AKp0TdG2g_1zGrFMq8s1-UlAc0n88WxfNzcFxxPSum6FV3VdlbssiGHO0Dyg5S1irs7pUUloPJAqd8c15SzjHBOLvXt1UntQT2BQMDUfD9gP2BVeR2BEDOF-sz3hcYGKxx9h88jOkTFdSzfHyNvYfWkXCTA2NxbXmZfJNVQJNj-aUY155tZ9FlQCfxlBkdMHIE_TgSZEyST-kho6y47ETXGYede1MRvfuLkpniUYi2BZ3UBN50Lv8QA-OEhhkwJjIt7NjHssAKfhMjkoY5aNLY_Jak7oipNqtjpJQv06abWu50BRSm4RjW9yypWYn1apooLf9rPKZccgYN4e2ngiRtvwxuy4EOPyffWQMnC4WWvLe7JXCdZTu3kdmg0noejPlBn086jBV4TRXOzXb_Oa_qQnfl42c8YRaEb86TbWEdNY_BBUV_L1LWHKpwC5v7Jy_IYSIEqny6en_4X5SwituaaZsGP5h7iFZf1rZTf3DwW9UzJnMHtu-ko3-kr8ytvFy5t9yQIF4rrkWV2opvZQ-9hSpugX4dd4rO1vOzYCDInVl36cpvlumWT9zNpSwrc5SxZrdLZhzmdwc92yzT7pjH2Ra225org7YPsBccUZu84Kv1-EgoJu6ChbS7O9T8gQx9QoHgOfYhTF_rp_h3ukG4XUiF4ZlP-vsRJRCysnqurNVD3hq-DtTAiALujhhLGKSEjg2bZOU1NUPOLw9z9RfDFDfF--1nN4hK9rEQhUws7lztxZubaS3jJhNQ7hqlGID5FX2s6WX7MBjjNY7sJeBUCyq8rIIEAy4rXXmUymGAxkOxk4IQD-NZD6jnhdUDwWahwoHwJWZZVpblhEOus30Nm76Sc8j0nDU2qxWd2JZj6udEcpqAQKa0qHihlxrr0WazeZfI4YbooeGqgzGF-XeQbQjOb-qyjc-sCwC66Va6hetOxG87g37Ct1-MgTIA-kZuqrzHsB2qxGgxrQQDdPk7VwR2XcfY563RT9a15tx2V1ESQZIxtKvAc0Mqziw04XEwPm5mi5uggWIX6aEZeB_WCNGx2KJaYKUG8kJk34685QWLGQIe9Q0HfZqP_SHq5P5btAYu9bF8yVveoL4C9xNMiBQnX8nRTdm-xTlREWQOSKq79TYaR91WdZwKqo6U7_TlJxofXOPXWy6CXPSQY1_EH6nIrFUDjWFtCO45rVbNOTbC7yUI7PfnJ5cgjNKl30_8m9uYKDrrPJflyV-xImmgFNSplq6PsQbzFimSjCZMVG1-GqdZ402HEWj4Rrb5AakGx8ylIDyAFBqcLbzc7Id3fKceQhGQRD_ZaIFjs2IghPK_c1d8h0RBWSS_AHIfVcko50R_dI-SCNMNf9ksgmAf_V68__aYrPy5MbxzxSGdcN2v3x7jii-ib0MxNiTq8YZmYYvTDIst0",
"id": "rs_0134d7700e125cf0016a071e00b48c8191970438519d8cb174",
"summary": [
{
"type": "summary_text",
"text": "**Reviewing template candidates**\n\nI’m looking at template candidates and noticing we have 59, which seems odd since we only deleted three from the first limit by instrument_id. Wait, is it possible there are actually 57 active candidates? I need to query all to check that. It might be I’m dealing with selected or rejected old ones. I should clean all unselected candidates for True Wealth before the rerun. And I should also check the counts by review status for clarity."
}
]
}
]
},
{
"role": "tool",
"content": "{\"output\": \"{'needs_manual_review': 59}\\n59\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_smxaogJdx2tFZls16uyhbd2R"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_hLRHqXQN7AWlpJnFHaGcki9t",
"call_id": "call_hLRHqXQN7AWlpJnFHaGcki9t",
"response_item_id": "fc_0134d7700e125cf0016a071e0c6e388191bf9082a2f15b676b",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"PYTHONPATH=src python - <<'PY'\\nfrom jarvis_finance.config.settings import load_settings\\nfrom jarvis_finance.storage.database import connect\\nfrom jarvis_finance.storage.migrations import apply_migrations\\nconn=connect(load_settings().db_path); apply_migrations(conn)\\nids=[r['instrument_id'] for r in conn.execute(\\\"SELECT DISTINCT instrument_id FROM transactions WHERE transaction_type='initial_position_snapshot' AND source_type='broker_import_reviewed_snapshot' AND COALESCE(is_voided,0)=0 AND instrument_id IS NOT NULL\\\").fetchall()]\\nq=','.join('?' for _ in ids)\\nconn.execute(f\\\"DELETE FROM instrument_price_mapping_candidates WHERE instrument_id IN ({q}) AND review_status IN ('proposed','needs_manual_review')\\\", ids)\\nconn.commit(); print({'cleaned_instruments': len(ids), 'remaining_candidates': conn.execute('SELECT COUNT(*) c FROM instrument_price_mapping_candidates').fetchone()['c']})\\nconn.close()\\nPY\\nPYTHONPATH=src python -m jarvis_finance.cli.main generate-mapping-candidates --source true_wealth --limit 3 --public-lookup --dedupe-missing-provider-alerts --export-template\",\"timeout\":300,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Cleaning up instrument data**\n\nI’m trying to figure out why there are 57 generated items but 59 total when including instruments that weren't in the initial count. It's possible there are more than 3 True Wealth instances. The user mentioned importing 3 TWs, so I wonder if the IDs for those three are all valid, but sorting might be an issue. It looks like I need to clean up the candidates for all imported snapshots and run the process again.",
"reasoning_content": "**Cleaning up instrument data**\n\nI’m trying to figure out why there are 57 generated items but 59 total when including instruments that weren't in the initial count. It's possible there are more than 3 True Wealth instances. The user mentioned importing 3 TWs, so I wonder if the IDs for those three are all valid, but sorting might be an issue. It looks like I need to clean up the candidates for all imported snapshots and run the process again.",
"codex_reasoning_items": [
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"text": "**Cleaning up instrument data**\n\nI’m trying to figure out why there are 57 generated items but 59 total when including instruments that weren't in the initial count. It's possible there are more than 3 True Wealth instances. The user mentioned importing 3 TWs, so I wonder if the IDs for those three are all valid, but sorting might be an issue. It looks like I need to clean up the candidates for all imported snapshots and run the process again."
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"arguments": "{\"command\":\"PYTHONPATH=src python - <<'PY'\\nfrom collections import Counter\\nfrom jarvis_finance.config.settings import load_settings\\nfrom jarvis_finance.storage.database import connect\\nfrom jarvis_finance.storage.migrations import apply_migrations\\nsettings=load_settings(); conn=connect(settings.db_path); apply_migrations(conn)\\ninst=[r['instrument_id'] for r in conn.execute(\\\"SELECT DISTINCT instrument_id FROM transactions WHERE transaction_type='initial_position_snapshot' AND source_type='broker_import_reviewed_snapshot' AND COALESCE(is_voided,0)=0 AND instrument_id IS NOT NULL\\\").fetchall()]\\nq=','.join('?' for _ in inst) if inst else \\\"''\\\"\\nrows=conn.execute(f\\\"SELECT confidence,review_status,candidate_hedge_status,candidate_instrument_status,instrument_id FROM instrument_price_mapping_candidates WHERE instrument_id IN ({q})\\\", inst).fetchall() if inst else []\\nalerts=conn.execute(\\\"SELECT rule_id, COUNT(*) AS c FROM alerts WHERE status='active' GROUP BY rule_id ORDER BY rule_id\\\").fetchall()\\nper_inst=Counter(r['instrument_id'] for r in rows)\\nprint({\\n 'instruments_total': len(inst),\\n 'provider_lookups_attempted': len(inst),\\n 'candidates_total': len(rows),\\n 'confidence': dict(Counter(r['confidence'] for r in rows)),\\n 'review_status': dict(Counter(r['review_status'] for r in rows)),\\n 'without_candidate': sum(1 for iid in inst if per_inst[iid]==0),\\n 'with_multiple_candidates': sum(1 for iid in inst if per_inst[iid]>1),\\n 'hedge_candidate_known': sum(1 for r in rows if r['candidate_hedge_status']!='unknown'),\\n 'instrument_status_candidate_known': sum(1 for r in rows if r['candidate_instrument_status']!='unknown'),\\n 'instrument_hedge_unknown': conn.execute(f\\\"SELECT COUNT(*) AS c FROM instruments WHERE instrument_id IN ({q}) AND COALESCE(hedge_status,'unknown')='unknown'\\\", inst).fetchone()['c'] if inst else 0,\\n 'instrument_status_unknown': conn.execute(f\\\"SELECT COUNT(*) AS c FROM instruments WHERE instrument_id IN ({q}) AND COALESCE(instrument_status,'unknown')='unknown'\\\", inst).fetchone()['c'] if inst else 0,\\n 'active_alerts_by_rule': {r['rule_id']: r['c'] for r in alerts},\\n 'template_candidates': conn.execute('SELECT COUNT(*) AS c FROM instrument_price_mapping_candidates').fetchone()['c']\\n})\\nconn.close()\\nPY\",\"timeout\":180,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
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"content": "{\"output\": \"diff --git a/src/jarvis_finance/cli/main.py b/src/jarvis_finance/cli/main.py\\nindex ff2a92a..f63e3d6 100644\\n--- a/src/jarvis_finance/cli/main.py\\n+++ b/src/jarvis_finance/cli/main.py\\n@@ -8,7 +8,7 @@ from jarvis_finance.config.settings import ensure_runtime_dirs, load_settings\\n from jarvis_finance.fx.providers import MockFxProvider\\n from jarvis_finance.fx.rates import recheck_transaction_fx_status, update_fx_rates\\n from jarvis_finance.market.providers import CoinGeckoClient, refresh_crypto_prices\\n-from jarvis_finance.market_data.candidates import EmptyLookupProvider, generate_mapping_candidates\\n+from jarvis_finance.market_data.candidates import CompositePublicLookupProvider, EmptyLookupProvider, dedupe_missing_provider_symbol_alerts, export_mapping_review_template, generate_mapping_candidates\\n from jarvis_finance.market_data.catalog import prepare_catalog_from_instruments\\n from jarvis_finance.market_data.prices import MockEquityPriceProvider, refresh_market_prices\\n from jarvis_finance.quality.data_quality import check_crypto_data_quality\\n@@ -68,6 +68,10 @@ def main(argv: list[str] | None = None) -> int:\\n candidates.add_argument(\\\"--source\\\", default=\\\"true_wealth\\\")\\n candidates.add_argument(\\\"--limit\\\", type=int)\\n candidates.add_argument(\\\"--dry-run\\\", action=\\\"store_true\\\")\\n+ candidates.add_argument(\\\"--public-lookup\\\", action=\\\"store_true\\\")\\n+ candidates.add_argument(\\\"--export-template\\\", action=\\\"store_true\\\")\\n+ candidates.add_argument(\\\"--template-path\\\")\\n+ candidates.add_argument(\\\"--dedupe-missing-provider-alerts\\\", action=\\\"store_true\\\")\\n sub.add_parser(\\\"backup-runtime-db\\\")\\n restore = sub.add_parser(\\\"restore-runtime-db\\\")\\n restore.add_argument(\\\"--from\\\", dest=\\\"backup_file\\\", required=True)\\n@@ -229,7 +233,16 @@ def main(argv: list[str] | None = None) -> int:\\n conn = connect(settings.db_path)\\n try:\\n apply_migrations(conn)\\n- result = generate_mapping_candidates(conn, provider=EmptyLookupProvider(), source=args.source, limit=args.limit, dry_run=args.dry_run)\\n+ if args.dedupe_missing_provider_alerts:\\n+ resolved = dedupe_missing_provider_symbol_alerts(conn)\\n+ else:\\n+ resolved = 0\\n+ provider = CompositePublicLookupProvider() if args.public_lookup else EmptyLookupProvider()\\n+ result = generate_mapping_candidates(conn, provider=provider, source=args.source, limit=args.limit, dry_run=args.dry_run)\\n+ template = None\\n+ if args.export_template:\\n+ template_path = args.template_path or str(settings.runtime_paths.exports_dir / \\\"true_wealth_mapping_review_template.csv\\\")\\n+ template = export_mapping_review_template(conn, output_path=template_path)\\n print(\\n \\\"MAPPING_CANDIDATES \\\"\\n f\\\"instruments_total={result.instruments_total} candidates_found={result.candidates_found} \\\"\\n@@ -237,6 +250,8 @@ def main(argv: list[str] | None = None) -> int:\\n f\\\"instruments_without_candidate={result.instruments_without_candidate} \\\"\\n f\\\"hedge_unknown={result.instruments_with_hedge_unknown} instrument_status_unknown={result.instruments_with_status_unknown} \\\"\\n f\\\"provider_lookup_unavailable={result.provider_lookup_unavailable} ambiguous={result.ambiguous_provider_mapping} \\\"\\n+ f\\\"deduped_missing_provider_alerts={resolved} \\\"\\n+ f\\\"template_updated={str(bool(template)).lower()} template_instruments={template['instrument_count'] if template else 0} template_candidates={template['candidate_rows'] if template else 0} \\\"\\n f\\\"dry_run={str(result.dry_run).lower()}\\\"\\n )\\n return 0\\ndiff --git a/src/jarvis_finance/market_data/candidates.py b/src/jarvis_finance/market_data/candidates.py\\nindex 10abd1b..c7ed397 100644\\n--- a/src/jarvis_finance/market_data/candidates.py\\n+++ b/src/jarvis_finance/market_data/candidates.py\\n@@ -1,6 +1,12 @@\\n from __future__ import annotations\\n \\n+import csv\\n+import json\\n+import os\\n+import urllib.parse\\n+import urllib.request\\n from dataclasses import dataclass, field\\n+from pathlib import Path\\n from sqlite3 import Connection\\n from typing import Protocol\\n \\n@@ -21,9 +27,12 @@ class ProviderCandidate:\\n currency: str | None = None\\n name: str | None = None\\n isin: str | None = None\\n+ asset_class: str | None = None\\n is_hedged: bool | None = None\\n hedged_to_currency: str | None = None\\n+ hedge_status: str = \\\"unknown\\\"\\n instrument_status: str = \\\"unknown\\\"\\n+ valuation_policy: str = \\\"live_price\\\"\\n evidence_source: str = \\\"provider_lookup\\\"\\n evidence_note: str = \\\"\\\"\\n \\n@@ -46,6 +55,119 @@ class EmptyLookupProvider:\\n return []\\n \\n \\n+class OpenFIGILookupProvider:\\n+ \\\"\\\"\\\"Public ISIN-to-instrument metadata lookup via OpenFIGI; no prices or portfolio data.\\\"\\\"\\\"\\n+\\n+ name = \\\"openfigi\\\"\\n+\\n+ def __init__(self, *, timeout_seconds: float = 8.0, max_results: int = 12):\\n+ self.timeout_seconds = timeout_seconds\\n+ self.max_results = max_results\\n+\\n+ def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n+ if not isin:\\n+ return []\\n+ token = os.environ.get(\\\"OPENFIGI_API_KEY\\\")\\n+ headers = {\\\"Content-Type\\\": \\\"application/json\\\", \\\"User-Agent\\\": \\\"JarvisFinance/1.0 public-instrument-lookup\\\"}\\n+ if token:\\n+ headers[\\\"X-OPENFIGI-APIKEY\\\"] = token\\n+ payload = json.dumps([{\\\"idType\\\": \\\"ID_ISIN\\\", \\\"idValue\\\": isin}]).encode(\\\"utf-8\\\")\\n+ req = urllib.request.Request(\\\"https://api.openfigi.com/v3/mapping\\\", data=payload, headers=headers, method=\\\"POST\\\")\\n+ try:\\n+ with urllib.request.urlopen(req, timeout=self.timeout_seconds) as resp:\\n+ data = json.loads(resp.read().decode(\\\"utf-8\\\"))\\n+ except Exception as exc: # pragma: no cover - network dependent\\n+ raise LookupUnavailable(str(exc)) from exc\\n+ out: list[ProviderCandidate] = []\\n+ for item in (data[0].get(\\\"data\\\", []) if data else [])[: self.max_results]:\\n+ symbol = item.get(\\\"ticker\\\") or item.get(\\\"figi\\\")\\n+ if not symbol:\\n+ continue\\n+ sec_type = \\\" \\\".join(str(item.get(k) or \\\"\\\") for k in (\\\"securityType\\\", \\\"securityType2\\\", \\\"marketSector\\\")).lower()\\n+ asset_class = \\\"etf\\\" if \\\"fund\\\" in sec_type or \\\"etf\\\" in sec_type else \\\"equity\\\" if \\\"equity\\\" in sec_type else None\\n+ out.append(ProviderCandidate(\\n+ provider=self.name,\\n+ provider_symbol=symbol,\\n+ exchange=item.get(\\\"exchCode\\\") or item.get(\\\"marketSector\\\"),\\n+ currency=item.get(\\\"currency\\\") or currency,\\n+ name=item.get(\\\"name\\\"),\\n+ isin=isin,\\n+ asset_class=asset_class,\\n+ hedge_status=\\\"unknown\\\",\\n+ instrument_status=\\\"unknown\\\",\\n+ valuation_policy=\\\"live_price\\\",\\n+ evidence_source=\\\"openfigi_isin_mapping\\\",\\n+ evidence_note=\\\"Public ISIN mapping metadata only; no prices, holdings, account data, or portfolio quantities sent.\\\",\\n+ ))\\n+ return out\\n+\\n+\\n+class YahooSearchLookupProvider:\\n+ \\\"\\\"\\\"Public metadata lookup via Yahoo Finance search endpoint; no prices or portfolio data.\\\"\\\"\\\"\\n+\\n+ name = \\\"yahoo_fallback\\\"\\n+\\n+ def __init__(self, *, timeout_seconds: float = 8.0, max_results: int = 8):\\n+ self.timeout_seconds = timeout_seconds\\n+ self.max_results = max_results\\n+\\n+ def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n+ queries = [q for q in [isin, ticker, name] if q]\\n+ if not queries:\\n+ return []\\n+ found: dict[tuple[str, str | None], ProviderCandidate] = {}\\n+ for query in queries[:2]:\\n+ url = \\\"https://query2.finance.yahoo.com/v1/finance/search?\\\" + urllib.parse.urlencode({\\\"q\\\": query, \\\"quotesCount\\\": self.max_results, \\\"newsCount\\\": 0})\\n+ try:\\n+ req = urllib.request.Request(url, headers={\\\"User-Agent\\\": \\\"JarvisFinance/1.0 public-instrument-lookup\\\"})\\n+ with urllib.request.urlopen(req, timeout=self.timeout_seconds) as resp:\\n+ payload = json.loads(resp.read().decode(\\\"utf-8\\\"))\\n+ except Exception as exc: # pragma: no cover - network dependent\\n+ raise LookupUnavailable(str(exc)) from exc\\n+ for quote in payload.get(\\\"quotes\\\", [])[: self.max_results]:\\n+ symbol = quote.get(\\\"symbol\\\")\\n+ if not symbol:\\n+ continue\\n+ qtype = (quote.get(\\\"quoteType\\\") or \\\"\\\").lower()\\n+ asset_class = \\\"etf\\\" if qtype == \\\"etf\\\" else \\\"equity\\\" if qtype in {\\\"equity\\\", \\\"stock\\\"} else None\\n+ exch = quote.get(\\\"exchDisp\\\") or quote.get(\\\"exchange\\\")\\n+ cand = ProviderCandidate(\\n+ provider=self.name,\\n+ provider_symbol=symbol,\\n+ exchange=exch,\\n+ currency=currency,\\n+ name=quote.get(\\\"longname\\\") or quote.get(\\\"shortname\\\"),\\n+ isin=None,\\n+ asset_class=asset_class,\\n+ hedge_status=\\\"unknown\\\",\\n+ instrument_status=\\\"unknown\\\",\\n+ valuation_policy=\\\"live_price\\\",\\n+ evidence_source=\\\"yahoo_finance_search\\\",\\n+ evidence_note=\\\"Public symbol/search metadata only; no prices, holdings, account data, or portfolio quantities sent.\\\",\\n+ )\\n+ found[(symbol, exch)] = cand\\n+ return list(found.values())\\n+\\n+\\n+class CompositePublicLookupProvider:\\n+ name = \\\"public_composite\\\"\\n+\\n+ def __init__(self, providers: list[InstrumentLookupProvider] | None = None):\\n+ self.providers = providers or [OpenFIGILookupProvider(), YahooSearchLookupProvider()]\\n+\\n+ def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n+ candidates: list[ProviderCandidate] = []\\n+ errors = 0\\n+ for provider in self.providers:\\n+ try:\\n+ candidates.extend(provider.lookup(isin=isin, name=name, ticker=ticker, exchange=exchange, currency=currency))\\n+ except Exception:\\n+ errors += 1\\n+ if errors and not candidates:\\n+ raise LookupUnavailable(\\\"all public lookup providers unavailable\\\")\\n+ return candidates\\n+\\n+\\n @dataclass\\n class CandidateGenerationResult:\\n instruments_total: int = 0\\n@@ -120,23 +242,32 @@ def upsert_candidate(conn: Connection, *, instrument_id: str, candidate: Provide\\n if inst is None:\\n raise ValueError(f\\\"instrument not found: {instrument_id}\\\")\\n hedged, hedged_to = _infer_hedge(inst[\\\"name\\\"], candidate)\\n+ hedge_status = candidate.hedge_status if candidate.hedge_status in {\\\"hedged\\\", \\\"unhedged\\\", \\\"unknown\\\"} else \\\"unknown\\\"\\n+ if hedge_status == \\\"unknown\\\" and hedged is True:\\n+ hedge_status = \\\"hedged\\\"\\n+ elif hedge_status == \\\"unknown\\\" and hedged is False:\\n+ hedge_status = \\\"unhedged\\\"\\n candidate_id = stable_id(\\\"ipmc\\\", instrument_id, candidate.provider, candidate.provider_symbol, candidate.exchange or \\\"\\\", candidate.currency or \\\"\\\")\\n now = utc_now()\\n conn.execute(\\n \\\"\\\"\\\"\\n INSERT INTO instrument_price_mapping_candidates(\\n candidate_id, instrument_id, isin, candidate_provider, candidate_provider_symbol,\\n- candidate_exchange, candidate_currency, candidate_name, candidate_is_hedged,\\n- candidate_hedged_to_currency, candidate_instrument_status, confidence,\\n+ candidate_exchange, candidate_currency, candidate_name, candidate_asset_class,\\n+ candidate_is_hedged, candidate_hedged_to_currency, candidate_hedge_status,\\n+ candidate_instrument_status, candidate_valuation_policy, confidence,\\n evidence_source, evidence_note, review_status, created_at, updated_at\\n- ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\\n+ ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\\n ON CONFLICT(candidate_id) DO UPDATE SET\\n candidate_exchange=excluded.candidate_exchange,\\n candidate_currency=excluded.candidate_currency,\\n candidate_name=excluded.candidate_name,\\n+ candidate_asset_class=excluded.candidate_asset_class,\\n candidate_is_hedged=excluded.candidate_is_hedged,\\n candidate_hedged_to_currency=excluded.candidate_hedged_to_currency,\\n+ candidate_hedge_status=excluded.candidate_hedge_status,\\n candidate_instrument_status=excluded.candidate_instrument_status,\\n+ candidate_valuation_policy=excluded.candidate_valuation_policy,\\n confidence=excluded.confidence,\\n evidence_source=excluded.evidence_source,\\n evidence_note=excluded.evidence_note,\\n@@ -145,8 +276,9 @@ def upsert_candidate(conn: Connection, *, instrument_id: str, candidate: Provide\\n \\\"\\\"\\\",\\n (\\n candidate_id, instrument_id, inst[\\\"isin\\\"], candidate.provider, candidate.provider_symbol,\\n- candidate.exchange, candidate.currency or inst[\\\"currency\\\"], candidate.name, 1 if hedged else 0 if hedged is False else None,\\n- hedged_to, candidate.instrument_status or \\\"unknown\\\", confidence, candidate.evidence_source,\\n+ candidate.exchange, candidate.currency or inst[\\\"currency\\\"], candidate.name, candidate.asset_class or (inst[\\\"asset_class\\\"] or \\\"\\\").lower(),\\n+ 1 if hedged else 0 if hedged is False else None, hedged_to, hedge_status,\\n+ candidate.instrument_status or \\\"unknown\\\", candidate.valuation_policy or \\\"live_price\\\", confidence, candidate.evidence_source,\\n evidence_note or candidate.evidence_note, review_status, now, now,\\n ),\\n )\\n@@ -208,6 +340,75 @@ def generate_mapping_candidates(\\n return result\\n \\n \\n+def dedupe_missing_provider_symbol_alerts(conn: Connection) -> int:\\n+ \\\"\\\"\\\"Keep one active mapping-quality alert per rule/instrument; resolve duplicate active rows.\\\"\\\"\\\"\\n+ now = utc_now()\\n+ resolved = 0\\n+ rows = conn.execute(\\n+ \\\"\\\"\\\"\\n+ SELECT rule_id, entity_id, GROUP_CONCAT(alert_id) AS ids, COUNT(*) AS c\", \"exit_code\": 0, \"error\": null}",
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"content": "{\"todos\": [{\"id\": \"c3c-0\", \"content\": \"Vorprüfung missing_provider_symbol=6 aggregiert analysieren\", \"status\": \"completed\"}, {\"id\": \"c3c-1\", \"content\": \"Public Lookup Candidate Generator + Runtime Template implementieren\", \"status\": \"completed\"}, {\"id\": \"c3c-2\", \"content\": \"Dashboard Review UI/Data Quality Center für Kandidaten prüfen/erweitern\", \"status\": \"completed\"}, {\"id\": \"c3c-3\", \"content\": \"Tests für Mock Public Lookup, DQ und Template ergänzen\", \"status\": \"completed\"}, {\"id\": \"c3c-4\", \"content\": \"Produktiven vorsichtigen Runtime-Lauf aggregiert ausführen\", \"status\": \"completed\"}, {\"id\": \"c3c-5\", \"content\": \"Compile, pytest, Git-Safety, Commit und Push\", \"status\": \"completed\"}], \"summary\": {\"total\": 6, \"pending\": 0, \"in_progress\": 0, \"completed\": 6, \"cancelled\": 0}}",
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"content": "Sir, Phase **C3c — Assisted Public Instrument Lookup & Mapping Candidate Fill** ist abgeschlossen, committed und gepusht.\n\n## Ergebnis\n\n- **Commit:** `8e6e8f7` — `Add assisted public instrument lookup candidates`\n- **Push:** erfolgreich nach `origin/main`\n- **Compile:** OK\n- **Tests:** `205 passed`\n- **Git-Safety:** `GIT_SAFETY_OK`\n- **Git Status:** clean\n- **Runtime-Backup vor produktivem Lauf:** erstellt\n- **Keine Preise abgerufen**\n- **Keine FX-Werte gesetzt**\n- **Keine Portfolio-Imports**\n- **Keine finalen Mappings automatisch bestätigt**\n- **Keine echten Mengen, Werte, Kontostände oder Preise im Chat**\n\n## 1. Vorprüfung `missing_provider_symbol = 6`\n\nErgebnis der Vorprüfung:\n\n- `missing_provider_symbol` aktiv vor Bereinigung: `6`\n- Entity-Type: ausschließlich `instrument`\n- Doppelte Entity-Gruppen: `3`\n\nInterpretation:\n\n- Es waren **keine fachlich unterschiedlichen Entity-Typen**.\n- Es waren **doppelte aktive Alerts pro Instrument**.\n- Ursache: wiederholte Mapping-/Catalog-Läufe mit teils unterschiedlichem Fingerprint-Kontext.\n- Bereinigung wurde implementiert und produktiv ausgeführt.\n\nNach Bereinigung:\n\n- aktive `missing_provider_symbol`: `3`\n- entspricht: ein aktiver Alert pro True-Wealth-Instrument\n- keine Alert-Flut mehr\n\nZusätzlich wurde die Dedupe-Logik auch für mapping-nahe Alerts gehärtet, damit `ambiguous_provider_mapping` und `provider_lookup_unavailable` ebenfalls nicht mehrfach aktiv pro Instrument stehen bleiben. Sehr zivilisiert. Fast untypisch für Data Quality.\n\n## 2. Implementierte Module\n\nNeu/erweitert:\n\n- **Public Lookup Candidate Generator**\n - OpenFIGI ISIN-Mapping Provider\n - Yahoo Search Fallback\n - Composite Provider\n - Provider-Ausfall ohne Crash\n - nur öffentliche Instrumentdaten\n - keine Preise\n - keine FX\n - keine Portfolio-Daten an externe Dienste\n\n- **Candidate Storage erweitert**\n - `candidate_asset_class`\n - `candidate_hedge_status`\n - `candidate_valuation_policy`\n - `candidate_instrument_status`\n - Evidence Source / Note\n - Review Status\n\n- **Mapping Candidate Rules**\n - ISIN-Match stärker als Name/Ticker\n - Name-only bleibt low confidence\n - Ticker ohne Exchange bleibt review-pflichtig\n - mehrere Kandidaten → `needs_manual_review`\n - kein Kandidat → `missing_provider_symbol` bleibt aktiv\n - Kandidaten lösen `missing_provider_symbol` nicht automatisch\n - finale Auswahl bleibt manuell und auditierbar\n\n- **CLI erweitert**\n - `generate-mapping-candidates --public-lookup`\n - `--export-template`\n - `--template-path`\n - `--dedupe-missing-provider-alerts`\n\n- **Runtime-only Mapping Review Template**\n - Export nur unter Runtime-Verzeichnis\n - zusätzliche Kandidatenfelder enthalten\n - keine Git-Ablage\n\n- **Dashboard Review UI erweitert**\n - Kandidatenliste rendert ohne Live-API\n - Provider\n - Provider-Symbol\n - Exchange\n - Handelswährung\n - Hedge-Status\n - Hedged-to Currency\n - Instrument-Status\n - Valuation Policy\n - Evidence Source / Note\n - Confidence\n - Review Status\n - Button: Kandidat bestätigen\n - Button: Kandidat ablehnen\n - manuelle Erfassung bleibt über Instrument Search / Add Position möglich\n - Bestätigung/Ablehnung schreibt Audit-Log\n - keine Portfolio-Transaktion wird durch Review geändert\n\n- **Data Quality Center erweitert**\n - unbestätigte Mapping-Kandidaten\n - Instrumente mit mehreren Mapping-Kandidaten\n - `missing_provider_symbol`\n - `provider_lookup_unavailable`\n - `ambiguous_provider_mapping`\n - `hedge_status_unknown`\n - `instrument_status_unknown`\n - `valuation_not_ready`\n - `manual_review_needed`\n\n## 3. Neue/geänderte Dateien\n\nGeändert:\n\n- `src/jarvis_finance/cli/main.py`\n- `src/jarvis_finance/dashboard/data.py`\n- `src/jarvis_finance/dashboard/pages/page_13_equity_manage.py`\n- `src/jarvis_finance/market_data/candidates.py`\n- `src/jarvis_finance/storage/migrations.py`\n- `tests/unit/test_schema.py`\n- `tests/unit/test_true_wealth_mapping_candidates_c3.py`\n\nKeine echten Dateien, Exporte, DBs oder Runtime-Daten wurden ins Git aufgenommen.\n\n## 4. Tests ergänzt\n\nAbgedeckt:\n\n- Public Lookup mit Mock Provider erzeugt Kandidaten\n- ISIN-Match erzeugt high-confidence Kandidat\n- mehrere Kandidaten erzeugen `needs_manual_review`\n- kein Kandidat lässt `missing_provider_symbol` aktiv\n- Provider-Lookup-Ausfall crasht nicht\n- Kandidaten werden Runtime-intern gespeichert\n- keine finale automatische Auswahl\n- Mapping Template enthält Kandidatenfelder\n- Dashboard Review UI rendert Kandidaten ohne Live-API\n- Data Quality Center zeigt Kandidaten-/Review-Bedarf\n- `missing_provider_symbol` wird nicht resolved, solange Kandidat nicht bestätigt ist\n- Alert-Dedupe pro Instrument\n- Git-Safety OK\n\n## 5. Produktiver vorsichtiger Runtime-Lauf\n\nAusgeführt gegen Runtime-DB:\n\n- öffentliche Lookup-Kandidaten für die 3 True-Wealth-Instrumente gesucht\n- Kandidaten gespeichert\n- Mapping Review Pack aktualisiert\n- Runtime-only Template aktualisiert\n- Alerts dedupliziert\n- keine finale Auswahl\n- keine Preise\n- keine FX-Werte\n- keine weiteren Imports\n\nAggregierter Stand:\n\n- Instrumente total: `3`\n- Provider-Lookups versucht: `3`\n- Kandidaten gefunden: `57`\n- Confidence high: `36`\n- Confidence medium: `18`\n- Confidence low: `3`\n- Instrumente ohne Kandidat: `0`\n- Instrumente mit mehreren Kandidaten: `3`\n- Review Status: alle `needs_manual_review`\n- Hedge-Status weiterhin unknown: `3`\n- Instrument-Status weiterhin unknown: `3`\n- Provider-Lookup-Unavailable Count: `0`\n\nWichtig: Trotz vieler Kandidaten wurde **nichts final bestätigt**. Alle 3 Instrumente bleiben manuell review-pflichtig.\n\n## 6. Runtime Mapping Template\n\n- Template aktualisiert: ja\n- Anzahl Instrumente: `3`\n- Anzahl Kandidaten: `57`\n- Speicherort: Runtime-Export-Verzeichnis\n- Git-Ablage: nein\n\nEnthaltene neue Felder:\n\n- `candidate_provider`\n- `candidate_provider_symbol`\n- `candidate_exchange`\n- `candidate_currency`\n- `confidence`\n- `hedge_status_candidate`\n- `instrument_status_candidate`\n- `evidence_source`\n- `reviewer_decision`\n- `reviewer_note`\n\n## 7. Data-Quality-Status aggregiert\n\nAktive Alerts nach Bereinigung:\n\n- `ambiguous_provider_mapping`: `3`\n- `cost_basis_uncertain`: `3`\n- `hedge_status_unknown`: `3`\n- `instrument_status_unknown`: `3`\n- `manual_review_needed`: `3`\n- `missing_fx`: `3`\n- `missing_market_price`: `3`\n- `missing_provider_symbol`: `3`\n- `snapshot_only`: `3`\n\nInterpretation:\n\n- Kandidaten sind vorhanden, aber nicht bestätigt.\n- Deshalb bleibt `missing_provider_symbol` korrekt aktiv.\n- Zusätzlich zeigt `ambiguous_provider_mapping`, dass manuelle Auswahl nötig ist.\n- `hedge_status_unknown` und `instrument_status_unknown` bleiben ebenfalls korrekt aktiv.\n- Valuation bleibt nicht ready.\n\n## 8. Abschlussprüfung\n\n- Compile: OK\n- pytest: `205 passed`\n- Git-Safety: `GIT_SAFETY_OK`\n- Git Status: clean\n- Commit: `8e6e8f7`\n- Push: erfolgreich\n\n## Konkrete nächste Empfehlung\n\nAls nächstes im Dashboard:\n\n1. **Equity/ETF Manage → Mapping Candidate Review** öffnen.\n2. Pro True-Wealth-Instrument Kandidatenliste prüfen.\n3. Pro Instrument genau einen Kandidaten manuell bestätigen — nur wenn Exchange, Handelswährung und Provider-Symbol plausibel sind.\n4. Kandidaten mit falscher Börse/Währung ablehnen.\n5. Hedge-Status und Instrument-Status nicht raten; nur bestätigen, wenn Evidence eindeutig ist.\n6. Danach erst:\n - `missing_provider_symbol` auflösen\n - `ambiguous_provider_mapping` auflösen\n - optional Market-Price Dry Run gegen bestätigte Mappings\n\nNoch nicht empfehlenswert:\n\n- Equity/ETF Preisabruf produktiv\n- FX-Setzung\n- Performance-/P&L-Auswertung\n- Rebalancing, Scores, Heatmaps, Monte Carlo oder sonstige Kaffeesatz-Orakel mit UI.",
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"text": "Sir, Phase **C3c — Assisted Public Instrument Lookup & Mapping Candidate Fill** ist abgeschlossen, committed und gepusht.\n\n## Ergebnis\n\n- **Commit:** `8e6e8f7` — `Add assisted public instrument lookup candidates`\n- **Push:** erfolgreich nach `origin/main`\n- **Compile:** OK\n- **Tests:** `205 passed`\n- **Git-Safety:** `GIT_SAFETY_OK`\n- **Git Status:** clean\n- **Runtime-Backup vor produktivem Lauf:** erstellt\n- **Keine Preise abgerufen**\n- **Keine FX-Werte gesetzt**\n- **Keine Portfolio-Imports**\n- **Keine finalen Mappings automatisch bestätigt**\n- **Keine echten Mengen, Werte, Kontostände oder Preise im Chat**\n\n## 1. Vorprüfung `missing_provider_symbol = 6`\n\nErgebnis der Vorprüfung:\n\n- `missing_provider_symbol` aktiv vor Bereinigung: `6`\n- Entity-Type: ausschließlich `instrument`\n- Doppelte Entity-Gruppen: `3`\n\nInterpretation:\n\n- Es waren **keine fachlich unterschiedlichen Entity-Typen**.\n- Es waren **doppelte aktive Alerts pro Instrument**.\n- Ursache: wiederholte Mapping-/Catalog-Läufe mit teils unterschiedlichem Fingerprint-Kontext.\n- Bereinigung wurde implementiert und produktiv ausgeführt.\n\nNach Bereinigung:\n\n- aktive `missing_provider_symbol`: `3`\n- entspricht: ein aktiver Alert pro True-Wealth-Instrument\n- keine Alert-Flut mehr\n\nZusätzlich wurde die Dedupe-Logik auch für mapping-nahe Alerts gehärtet, damit `ambiguous_provider_mapping` und `provider_lookup_unavailable` ebenfalls nicht mehrfach aktiv pro Instrument stehen bleiben. Sehr zivilisiert. Fast untypisch für Data Quality.\n\n## 2. Implementierte Module\n\nNeu/erweitert:\n\n- **Public Lookup Candidate Generator**\n - OpenFIGI ISIN-Mapping Provider\n - Yahoo Search Fallback\n - Composite Provider\n - Provider-Ausfall ohne Crash\n - nur öffentliche Instrumentdaten\n - keine Preise\n - keine FX\n - keine Portfolio-Daten an externe Dienste\n\n- **Candidate Storage erweitert**\n - `candidate_asset_class`\n - `candidate_hedge_status`\n - `candidate_valuation_policy`\n - `candidate_instrument_status`\n - Evidence Source / Note\n - Review Status\n\n- **Mapping Candidate Rules**\n - ISIN-Match stärker als Name/Ticker\n - Name-only bleibt low confidence\n - Ticker ohne Exchange bleibt review-pflichtig\n - mehrere Kandidaten → `needs_manual_review`\n - kein Kandidat → `missing_provider_symbol` bleibt aktiv\n - Kandidaten lösen `missing_provider_symbol` nicht automatisch\n - finale Auswahl bleibt manuell und auditierbar\n\n- **CLI erweitert**\n - `generate-mapping-candidates --public-lookup`\n - `--export-template`\n - `--template-path`\n - `--dedupe-missing-provider-alerts`\n\n- **Runtime-only Mapping Review Template**\n - Export nur unter Runtime-Verzeichnis\n - zusätzliche Kandidatenfelder enthalten\n - keine Git-Ablage\n\n- **Dashboard Review UI erweitert**\n - Kandidatenliste rendert ohne Live-API\n - Provider\n - Provider-Symbol\n - Exchange\n - Handelswährung\n - Hedge-Status\n - Hedged-to Currency\n - Instrument-Status\n - Valuation Policy\n - Evidence Source / Note\n - Confidence\n - Review Status\n - Button: Kandidat bestätigen\n - Button: Kandidat ablehnen\n - manuelle Erfassung bleibt über Instrument Search / Add Position möglich\n - Bestätigung/Ablehnung schreibt Audit-Log\n - keine Portfolio-Transaktion wird durch Review geändert\n\n- **Data Quality Center erweitert**\n - unbestätigte Mapping-Kandidaten\n - Instrumente mit mehreren Mapping-Kandidaten\n - `missing_provider_symbol`\n - `provider_lookup_unavailable`\n - `ambiguous_provider_mapping`\n - `hedge_status_unknown`\n - `instrument_status_unknown`\n - `valuation_not_ready`\n - `manual_review_needed`\n\n## 3. Neue/geänderte Dateien\n\nGeändert:\n\n- `src/jarvis_finance/cli/main.py`\n- `src/jarvis_finance/dashboard/data.py`\n- `src/jarvis_finance/dashboard/pages/page_13_equity_manage.py`\n- `src/jarvis_finance/market_data/candidates.py`\n- `src/jarvis_finance/storage/migrations.py`\n- `tests/unit/test_schema.py`\n- `tests/unit/test_true_wealth_mapping_candidates_c3.py`\n\nKeine echten Dateien, Exporte, DBs oder Runtime-Daten wurden ins Git aufgenommen.\n\n## 4. Tests ergänzt\n\nAbgedeckt:\n\n- Public Lookup mit Mock Provider erzeugt Kandidaten\n- ISIN-Match erzeugt high-confidence Kandidat\n- mehrere Kandidaten erzeugen `needs_manual_review`\n- kein Kandidat lässt `missing_provider_symbol` aktiv\n- Provider-Lookup-Ausfall crasht nicht\n- Kandidaten werden Runtime-intern gespeichert\n- keine finale automatische Auswahl\n- Mapping Template enthält Kandidatenfelder\n- Dashboard Review UI rendert Kandidaten ohne Live-API\n- Data Quality Center zeigt Kandidaten-/Review-Bedarf\n- `missing_provider_symbol` wird nicht resolved, solange Kandidat nicht bestätigt ist\n- Alert-Dedupe pro Instrument\n- Git-Safety OK\n\n## 5. Produktiver vorsichtiger Runtime-Lauf\n\nAusgeführt gegen Runtime-DB:\n\n- öffentliche Lookup-Kandidaten für die 3 True-Wealth-Instrumente gesucht\n- Kandidaten gespeichert\n- Mapping Review Pack aktualisiert\n- Runtime-only Template aktualisiert\n- Alerts dedupliziert\n- keine finale Auswahl\n- keine Preise\n- keine FX-Werte\n- keine weiteren Imports\n\nAggregierter Stand:\n\n- Instrumente total: `3`\n- Provider-Lookups versucht: `3`\n- Kandidaten gefunden: `57`\n- Confidence high: `36`\n- Confidence medium: `18`\n- Confidence low: `3`\n- Instrumente ohne Kandidat: `0`\n- Instrumente mit mehreren Kandidaten: `3`\n- Review Status: alle `needs_manual_review`\n- Hedge-Status weiterhin unknown: `3`\n- Instrument-Status weiterhin unknown: `3`\n- Provider-Lookup-Unavailable Count: `0`\n\nWichtig: Trotz vieler Kandidaten wurde **nichts final bestätigt**. Alle 3 Instrumente bleiben manuell review-pflichtig.\n\n## 6. Runtime Mapping Template\n\n- Template aktualisiert: ja\n- Anzahl Instrumente: `3`\n- Anzahl Kandidaten: `57`\n- Speicherort: Runtime-Export-Verzeichnis\n- Git-Ablage: nein\n\nEnthaltene neue Felder:\n\n- `candidate_provider`\n- `candidate_provider_symbol`\n- `candidate_exchange`\n- `candidate_currency`\n- `confidence`\n- `hedge_status_candidate`\n- `instrument_status_candidate`\n- `evidence_source`\n- `reviewer_decision`\n- `reviewer_note`\n\n## 7. Data-Quality-Status aggregiert\n\nAktive Alerts nach Bereinigung:\n\n- `ambiguous_provider_mapping`: `3`\n- `cost_basis_uncertain`: `3`\n- `hedge_status_unknown`: `3`\n- `instrument_status_unknown`: `3`\n- `manual_review_needed`: `3`\n- `missing_fx`: `3`\n- `missing_market_price`: `3`\n- `missing_provider_symbol`: `3`\n- `snapshot_only`: `3`\n\nInterpretation:\n\n- Kandidaten sind vorhanden, aber nicht bestätigt.\n- Deshalb bleibt `missing_provider_symbol` korrekt aktiv.\n- Zusätzlich zeigt `ambiguous_provider_mapping`, dass manuelle Auswahl nötig ist.\n- `hedge_status_unknown` und `instrument_status_unknown` bleiben ebenfalls korrekt aktiv.\n- Valuation bleibt nicht ready.\n\n## 8. Abschlussprüfung\n\n- Compile: OK\n- pytest: `205 passed`\n- Git-Safety: `GIT_SAFETY_OK`\n- Git Status: clean\n- Commit: `8e6e8f7`\n- Push: erfolgreich\n\n## Konkrete nächste Empfehlung\n\nAls nächstes im Dashboard:\n\n1. **Equity/ETF Manage → Mapping Candidate Review** öffnen.\n2. Pro True-Wealth-Instrument Kandidatenliste prüfen.\n3. Pro Instrument genau einen Kandidaten manuell bestätigen — nur wenn Exchange, Handelswährung und Provider-Symbol plausibel sind.\n4. Kandidaten mit falscher Börse/Währung ablehnen.\n5. Hedge-Status und Instrument-Status nicht raten; nur bestätigen, wenn Evidence eindeutig ist.\n6. Danach erst:\n - `missing_provider_symbol` auflösen\n - `ambiguous_provider_mapping` auflösen\n - optional Market-Price Dry Run gegen bestätigte Mappings\n\nNoch nicht empfehlenswert:\n\n- Equity/ETF Preisabruf produktiv\n- FX-Setzung\n- Performance-/P&L-Auswertung\n- Rebalancing, Scores, Heatmaps, Monte Carlo oder sonstige Kaffeesatz-Orakel mit UI."
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"content": "[M G] Sehr gut. Phase C3c ist akzeptiert.\n\nDer Stand ist sauber:\n\n* Commit 8e6e8f7 gepusht\n* Tests: 205 passed\n* Git-Safety: OK\n* 3 True-Wealth-Instrumente geprüft\n* 57 Mapping-Kandidaten gefunden\n* keine finale Mapping-Auswahl\n* keine Preise abgerufen\n* keine FX-Werte gesetzt\n* keine weiteren Imports\n* keine echten Mengen/Werte/Kontostände im Chat\n\nDas Ergebnis ist korrekt: Kandidaten wurden gefunden, aber nicht automatisch bestätigt.\n\nBitte jetzt noch keine Preise abrufen, keine FX-Werte setzen und keine weiteren Portfolio-Imports durchführen.\n\nDer nächste Schritt ist:\n\n# Phase C3d — Candidate Ranking, Mapping UX und User Decision Pack\n\nZiel:\nDie 57 Mapping-Kandidaten sollen für die 3 True-Wealth-Instrumente so aufbereitet werden, dass ich im Dashboard den richtigen Kandidaten einfach und sicher auswählen kann.\n\nWichtig:\n\n* Keine automatische finale Auswahl.\n* Keine Preise abrufen.\n* Keine FX-Werte setzen.\n* Keine weiteren Imports.\n* Keine echten Mengen/Werte/Kontostände im Chat.\n* Keine echten Dateien ins Git.\n* Dashboard liest nur lokale Runtime-Daten.\n\n## 1. Candidate Ranking verbessern\n\nBitte implementiere ein Scoring für Mapping-Kandidaten.\n\nVorschlag für Ranking-Kriterien:\n\n* exakter ISIN-Match: sehr hoch gewichten\n* Assetklasse passt: ETF vs. Aktie\n* Handelswährung passt zur Quelle\n* Exchange passt oder ist plausibel\n* Provider-Symbol vorhanden\n* Name/Fondsname passt fuzzy, aber Name allein reicht nicht\n* Hedge-Hinweis passt, z.B. CHF hedged / hedged CHF\n* Instrument-Status aktiv\n* Datenquelle vertrauenswürdig\n* Kandidat hat vollständige Felder: Provider, Symbol, Exchange, Währung\n\nNegative Faktoren:\n\n* falsche Währung\n* falsche Assetklasse\n* kein ISIN-Match\n* nur Name-Match\n* Ticker ohne Exchange\n* unklarer Hedge-Status\n* unklarer Instrument-Status\n* mehrere Listings ohne eindeutige Börse/Währung\n\nBitte berechne pro Kandidat:\n\n* ranking_score\n* ranking_reason\n* risk_flags\n* recommended_action:\n\n * select_candidate\n * needs_manual_review\n * reject_candidate\n * insufficient_data\n\nRegel:\nAuch ein Top-Kandidat wird nicht automatisch final bestätigt.\n\n## 2. Spezielles Problem: gleiche ISIN / gleicher Ticker / verschiedene Währungen\n\nBitte explizit berücksichtigen:\n\nEin Instrument kann mit gleicher ISIN und gleichem Symbol mehrere Listings haben, z.B. CHF-Listing und USD-Listing.\n\nDas Dashboard muss daher zeigen:\n\n* Symbol\n* Name\n* ISIN\n* Exchange\n* Handelswährung\n* Provider\n* Provider-Symbol\n* Closing Currency / Price Currency, falls verfügbar\n* Hedge-Status\n* Confidence / Ranking Score\n\nRegel:\nWenn mehrere Listings existieren, darf das System nicht automatisch wählen. Ich muss den richtigen Handelsplatz beziehungsweise die passende Währung bestätigen.\n\n## 3. Candidate Review UI verbessern\n\nBitte erweitere die Mapping Candidate Review UI:\n\nPro Instrument:\n\n* Top-Kandidaten zuerst anzeigen\n* Kandidaten nach Score sortieren\n* Filter:\n\n * Provider\n * Exchange\n * Währung\n * Confidence\n * Hedge-Status\n* Markierung:\n\n * wahrscheinlich passend\n * unsicher\n * wahrscheinlich falsch\n* Begründung anzeigen:\n\n * ISIN passt\n * Währung passt\n * Exchange passt\n * Hedge unklar\n * mehrere Kandidaten vorhanden\n * Ticker ohne Exchange\n* Button:\n\n * Kandidat auswählen\n * Kandidat ablehnen\n * manuell erfassen\n * später prüfen\n\nBestätigung muss Audit-Log schreiben.\n\n## 4. User Decision Pack\n\nBitte erstelle zusätzlich ein Runtime-only Decision Pack für diese 3 Instrumente.\n\nZweck:\nFalls ich das Dashboard nicht sofort öffnen kann, soll es eine sichere Übersicht im Runtime-Export geben, die ich später prüfen kann.\n\nFormat:\n\n* Markdown oder CSV\n* nur Runtime-Export\n* niemals Git\n\nInhalt:\n\n* pro Instrument Anzahl Kandidaten\n* Top 3–5 Kandidaten\n* Provider\n* Provider-Symbol\n* Exchange\n* Währung\n* Hedge-Status\n* Instrument-Status\n* Confidence\n* Ranking Reason\n* Reviewer Decision leer\n* Reviewer Note leer\n\nWichtig:\n\n* keine Mengen\n* keine Depotwerte\n* keine Kaufpreise\n* keine Kontostände\n* keine Portfolioanteile\n\nIm Chat nur aggregiert berichten:\n\n* Decision Pack erzeugt: ja/nein\n* Instrumente: 3\n* Kandidaten total\n*\nTop-Kandid\naten pro Instrument vorhanden: ja/nein\n\n## 5. Data Quality Center erweitern\n\nBitte Data Quality Center ergänzen:\n\n* ambiguous_provider_mapping\n* multiple_listings_same_isin\n* currency_mismatch\n* hedge_status_unknown\n* instrument_status_unknown\n* provider_symbol_missing\n* candidate_review_required\n* valuation_not_ready\n\nWenn Kandidaten vorhanden, aber nicht bestätigt:\n\n* missing_provider_symbol bleibt aktiv\n* candidate_review_required aktiv\n* keine automatische Resolution\n\n## 6. Mapping Confirmation Workflow\n\nBitte sicherstellen:\n\nWenn ich später einen Kandidaten bestätige:\n\n* instrument_price_mappings wird gesetzt\n* instrument_catalog_entry wird aktualisiert\n* provider_symbol wird gesetzt\n* exchange wird gesetzt\n* price_currency wird gesetzt\n* Hedge-Status kann bestätigt werden\n* Instrument-Status kann bestätigt werden\n* Valuation Policy wird gesetzt\n* Audit-Log wird geschrieben\n* missing_provider_symbol wird resolved\n* ambiguous_provider_mapping wird resolved\n* candidate_review_required wird resolved\n* falls Hedge/Status weiterhin unknown bleiben, bleiben entsprechende Warnungen aktiv\n\nKeine Portfolio-Transaktion wird dadurch verändert.\n\n## 7. Personal Finance / Budgeting Backlog vormerken\n\nBitte ergänze das Backlog um einen späteren separaten Modulbereich:\n\n# Personal Finance / Cashflow / Budgeting Module\n\nNoch nicht implementieren, nur sauber vormerken.\n\nZiel:\nSpäter soll das Finance Dashboard nicht nur Anlagen verwalten, sondern auch Einkommen, Ausgaben, Budget, Belege und persönlichen Cashflow.\n\nGeplante Funktionen:\n\n## A. Income / Lohn\n\n* Lohnzahlungen erfassen\n* weitere Einkommen erfassen\n* monatliches Nettoeinkommen\n* wiederkehrende Einnahmen\n* Jahresübersicht\n* Zusammenhang mit Sparrate / Investitionsbetrag\n\n## B. Expense Tracking\n\n* Kreditkarten-CSV-Import\n* Banktransaktions-CSV-Import\n* manuelle Ausgaben\n* Händler/Merchant-Erkennung\n* Kategorie-Erkennung\n* wiederkehrende Ausgaben\n* Abos / Subscriptions\n* Ausgaben nach Monat, Händler, Kategorie\n\n## C. Budgeting\n\n* Monatsbudget\n* Kategorienbudget\n* Fixkosten vs. variable Kosten\n* Food / Grocery Budget\n* Sparziel\n* Budget-Ist-Vergleich\n* Warnungen bei Budgetüberschreitung\n\n## D. Belegimport\n\n* Migros-/Coop-/andere Einkaufsbelege als PDF/CSV\n* spätere OCR/PDF-Extraktion, falls nötig\n* Positionen oder Kategorien aus Belegen\n* Lebensmittelkosten getrennt auswerten\n* Händlernormalisierung\n* keine Belege ins Git\n\n## E. Categorization Engine\n\n* regelbasierte Kategorisierung\n* Merchant Mapping\n* manuelle Review Queue\n* Kategorie-Vorschläge\n* Keine LLM-Pflicht\n* Local LLM später optional für Beleg-/Textklassifikation\n\n## F. Cashflow Dashboard\n\n* Einnahmen\n* Ausgaben\n* Monatsüberschuss\n* Sparrate\n* investierbarer Betrag\n* Liquidität\n* Vergleich Budget vs. Ist\n* Verbindung zum Portfolio:\n\n * Wie viel Cash kann investiert werden?\n * Notgroschen / Health Reserve\n * monatlicher Investment-Plan\n\n## G. Sicherheit\n\n* Zahlungsdaten und Belege sind vertraulich\n* echte CSV/PDF/Belege nur Runtime\n* keine echten Finanzdaten ins Git\n* Import-Dry-Run\n* Audit\n* Data Quality\n* manuelle Bestätigung vor Commit\n\nWichtig:\nDieses Personal-Finance-Modul wird erst später gebaut. Aktuell bleibt der Fokus auf Investment Portfolio MVP.\n\n## 8. Tests\n\nBitte Tests ergänzen für:\n\n* Candidate Ranking nach ISIN/Währung/Exchange\n* gleiche ISIN mit mehreren Listings bleibt review-pflichtig\n* Top-Kandidaten werden sortiert\n* Ranking Reason wird erzeugt\n* Candidate Review UI rendert sortierte Kandidaten ohne Live-API\n* Decision Pack wird nur Runtime erzeugt\n* Decision Pack enthält keine Mengen/Werte\n* Kandidat bestätigen schreibt Audit\n* Bestätigung resolved passende Mapping Alerts\n* Kandidat ablehnen schreibt Audit\n* Missing Provider Symbol bleibt aktiv, solange kein Kandidat bestätigt ist\n* Personal-Finance-Backlog-Dokument existiert, aber keine Implementierung\n* Git-Safety OK\n\n## 9. Produktiver vorsichtiger Runtime-Lauf\n\nBitte gegen Runtime-DB ausführen:\n\n* Ranking für vorhandene 57 Kandidaten berechnen\n* Top-Kandidaten pro Instrument bestimmen\n* Decision Pack Runtime-only erzeugen\n* keine finale Ausw\nahl\n* keine Preise\n* keine FX\n* keine weiteren Imports\n\nBericht nur aggregiert:\n\n* Instrumente total\n* Kandidaten total\n* Top-Kandidaten pro Instrument vorhanden\n* Kandidaten mit high/medium/low Ranking\n* multiple_listings_same_isin Count\n* currency_mismatch Count\n* hedge_status_unknown Count\n* instrument_status_unknown Count\n* Decision Pack erzeugt\n* keine Preise/Werte/Mengen/Kontostände\n\n## 10. Nach Abschluss\n\nBitte ausführen:\n\n* Compile\n* pytest\n* Git-Safety\n* Git Status\n\nWenn Code geändert wurde:\n\n* Commit\n* Push\n\nBitte berichten:\n\n* implementierte Module\n* neue/geänderte Dateien\n* Tests\n* Testergebnis\n* Git-Safety\n* Commit Hash\n* Push Status\n* Candidate Ranking aggregiert\n* Decision Pack Status\n* Data-Quality-Status aggregiert\n* Backlog-Erweiterung Personal Finance vorhanden\n* nächste Empfehlung\n\nKeine echten Mengen, Preise, Werte, Kontostände oder sensitiven Inhalte im Chat."
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"content": "{\"success\": true, \"name\": \"finance-system-architecture\", \"description\": \"Design/implement the user's JARVIS Finance System: CHF ledger, portfolio accounting, dashboard, imports, reports, secrecy.\", \"tags\": [\"finance\", \"portfolio\", \"accounting\", \"dashboard\", \"csv\", \"fx\", \"tax\", \"privacy\"], \"related_skills\": [], \"content\": \"---\\nname: finance-system-architecture\\ndescription: \\\"Design/implement the user's JARVIS Finance System: CHF ledger, portfolio accounting, dashboard, imports, reports, secrecy.\\\"\\nversion: 1.0.0\\nauthor: Hermes Agent\\nlicense: MIT\\nmetadata:\\n hermes:\\n tags: [finance, portfolio, accounting, dashboard, csv, fx, tax, privacy]\\n---\\n\\n# Finance System Architecture\\n\\n## When to use\\n\\nUse this skill whenever the user asks about the **Finance System – Architektur & Scripts** topic or work involving the user's personal finance-management system: portfolio imports, transaction accounting, Bank/Broker/CSV processing, dashboards, reports, tax/income views, FX logic, market data jobs, alerts, or later implementation.\\n\\nDo **not** use it for pure investment-strategy discussion; those belong in the separate finance strategy topic unless the user explicitly asks for technical implementation.\\n\\n## Core principles\\n\\n1. **No automated trading.** The system may prepare orders and recommendations, but never executes orders or connects to broker trading APIs for execution.\\n2. **Accounting first, opinions later.** MVP must prioritize correct transaction ledger, cash ledger, FX handling, income/tax data, and dashboard before complex scores, news, analyst ratings, or LLM analysis.\\n3. **Rule-based first.** Calculations, scores, alerts, rebalancing and reports must be deterministic and auditable. LLMs may only summarize/explain text or assist extraction with human review.\\n4. **CHF as base currency.** Store every transaction in original currency and CHF using historical FX at transaction/payment date; current valuations use current FX.\\n5. **Financial data secrecy.** Never expose real financial values, portfolio files, raw exports, reports with real numbers, DBs, API keys, or credentials in chat, GitHub, logs, or shared docs unless the user explicitly approves scope.\\n6. **Data ownership.** All data must be exportable: CSV, JSON, Parquet, SQLite/Postgres dump, Markdown/HTML/PDF reports.\\n\\n## Current v0.3 decisions\\n\\nSee `references/spec-v0.2-decisions.md` for the baseline, `references/spec-v0.3-decisions.md` for the priority update, `references/spec-v0.4-implementation-blueprint.md` for the MVP 1 technical implementation blueprint, `references/spec-v0.4.1-corrections.md` for accepted corrections, `references/spec-v0.5-repo-blueprint.md` for the concrete repo/implementation plan, `references/mvp-safety-gate-implementation.md` for the implementation safety-gate sequence and verification commands, `references/mvp-import-pipeline-tasks-9-13.md` for the synthetic CSV import/FX/transaction pipeline pattern, `references/mvp-ledger-cash-wac-positions.md` for cash/WAC/position ledger calculation rules and tests, `references/mvp-crypto-wallet-ledger.md` for crypto wallet/assets/holdings/transfers/buy-sell/fee MVP rules, `references/crypto-xlsx-initial-snapshot-dry-run.md` for the controlled real-file XLSX crypto initial-snapshot dry-run pattern and mapping decisions, `references/crypto-xlsx-initial-snapshot-production-import.md` for productive safe-subset XLSX import operations, compatibility/partial-write recovery, and dashboard correction follow-up, `references/crypto-single-coin-runtime-test.md` for controlled one-coin productive runtime tests and the coin-vs-holding ambiguity guard, `references/multi-wallet-crypto-and-equity-manage-ui.md` for approved multi-wallet single-coin snapshots, SQLite Decimal/TEXT affinity pitfalls, and synthetic-first Equity/ETF Manage UI patterns, `references/crypto-price-refresh-and-idempotent-btc-runtime.md` for robust batch price refresh and re-run-safe BTC/single-coin runtime checks, `references/crypto-runtime-db-consistency-verification.md` for post-import runtime DB consistency checks, exact safe-set verification, dashboard no-live-API testing, and runtime-only report generation, `references/mvp-crypto-manual-management-ui.md` for audited dashboard add/correct/remove crypto holding workflows after an initial snapshot, `references/mvp-market-import-safety-hardening.md` for CoinGecko provider/backoff, CSV importer completion, alert lifecycle, Git-safety and crypto Decimal precision patterns, `references/git-safety-verification-coverage.md` for the verifier-warning workflow and minimum Git-safety test matrix, `references/mvp-streamlit-dashboard.md` for the safe local Streamlit dashboard shell/read-model/testing pattern, `references/mvp-crypto-report-export.md` for local-only crypto report context/export rules, `references/github-token-push-from-drive.md` for the safe Google-Drive-token push workflow when local FinanceManager commits are ahead of GitHub, `references/runtime-backup-and-broker-mapping.md` for runtime DB backup/restore hardening plus PostFinance/True Wealth/Raiffeisen structural mapping/dry-run rules, `references/import-wizard-mapping-layer.md` for the Phase B1 import wizard, instrument/account mapping, review queue, data-quality and read-only safety pattern, `references/broker-parser-dry-run-pipeline.md` for the Phase B2 synthetic broker parser, dry-run, runtime review-item and UI quality-flag pipeline, `references/controlled-real-broker-dry-run.md` for the Phase B3 controlled real-file dry-run pattern with backup, aggregate-only reporting, runtime-only review items, and no productive position writes, and `references/broker-review-queue-hardening.md` for Phase B4 manual review queue filters, auditable mapping actions, import-readiness gating, dry-run session management, and Data Quality Center hardening without productive portfolio writes, and `references/guided-manual-review-pilot.md` for Phase B5 small-scope runtime metadata pilots that move selected review items to `ready_for_import` without productive imports, `references/broker-import-execution-plan-mini-import.md` for Phase B6 final dry-run execution plans plus exactly-one productive broker mini-import, `references/broker-mini-import-regression-and-corrections.md` for post-mini-import regression, void/correction workflows, backup/restore checks, and one-at-a-time follow-up imports, and `references/broker-mini-import-completion-and-dq-consolidation.md` for completing the last ready True-Wealth mini-import plus active-vs-resolved Data Quality alert consolidation, `references/equity-fx-market-data-phase-c.md` for the local FX/market-data foundation after broker mini-imports and before broader Equity/ETF valuation/imports, and `references/true-wealth-valuation-pilot-c2.md` for the True-Wealth valuation pilot safeguards around hedge metadata, provider mappings, historical FX failures, timestamp alignment, corporate-action flags, and aggregate-only runtime reporting, `references/true-wealth-mapping-candidate-review-c3.md` for the controlled mapping-candidate review pattern before any productive Equity/ETF price or FX valuation, `references/instrument-catalog-manual-add-workflow.md` for the general Instrument Catalog + dashboard manual-add workflow that must underpin future Equity/ETF/Crypto adds, and `references/public-instrument-lookup-candidate-generator.md` for runtime-only public metadata lookups, candidate review packs, alert dedupe, and no-auto-selection rules. Key decisions:\\n\\n- Platform/account views: Raiffeisen, PostFinance, True Wealth, Crypto-Coins, plus Gesamtansicht.\\n- Existing Google Drive files under `Finanzen/01 Aktueller Stand Portfolios` are **initial-snapshot reality checks**, not full ledgers.\\n- MVP means the smallest useful first version: correct data foundation, ledger, CHF/FX logic, platform views, crypto inventory, watchlist, reports, workflows and audit log.\\n- Stock/ETF tax documents are downgraded: optional reference/control module and dividend/distribution transparency, not MVP 1 and not a complete tax dossier replacement.\\n- Crypto inventory is promoted to MVP 1: wallet/platform-level holdings, Crypto PDF, CoinGecko valuation, stale-price warnings and manual verification.\\n- Crypto snapshot values are stale; use quantities only and recalculate current values via CoinGecko later.\\n- MVP dashboard recommendation: Streamlit + SQLite + SQLAlchemy/Pandas/Plotly; later migrateable to FastAPI + React/PostgreSQL.\\n- MVP inputs: manual dashboard entry, standard CSV import/export, later broker/bank export import. No direct broker integrations initially.\\n- Telegram crypto buys/sells/transfers should be parsed as pending transactions and only saved after explicit confirmation.\\n- Every portfolio or crypto change must create a History/Audit entry.\\n\\n## Required data model areas\\n\\nAt minimum design for:\\n\\n- `platforms`, `accounts`, `instruments`\\n- `transactions` with original currency and CHF fields\\n- `cash_ledger`\\n- derived `positions_current`\\n- `dividends_distributions`\\n- `market_prices`, `fx_rates`\\n- `watchlist_items`\\n- `alerts`\\n- `decision_journal`\\n- `reports`\\n- `data_quality_issues`\\n\\n## CSV/import rules\\n\\n- For broker/bank imports (PostFinance, True Wealth, Raiffeisen), build the safe review layer before productive imports: Import Wizard, instrument mappings, platform/account mappings, dry-run summaries, Manual Review Queue, Data Quality Center and visible read-only/write-enabled state. Follow `references/import-wizard-mapping-layer.md`. When wiring parser output into the wizard, use the synthetic-first parser/dry-run/review-item pipeline in `references/broker-parser-dry-run-pipeline.md`. After explicit approval for real-file dry-runs, follow `references/controlled-real-broker-dry-run.md`: preflight, verified runtime backup, temp-only file handling, aggregate-only reporting, runtime-only review items, and verification that productive positions/ledger rows stayed unchanged. When the user asks to make real dry-run results manually editable, follow `references/broker-review-queue-hardening.md`: add filters/detail views, auditable review-metadata actions, per-item/session import-readiness status, dry-run session management, and Data Quality Center counts while keeping productive portfolio writes disabled. For a guided manual-review pilot on real runtime items, follow `references/guided-manual-review-pilot.md`: select 1–3 clear ETF/equity items (prefer True Wealth), write only audited review metadata, correct only presence booleans if needed, derive `ready_for_import` via readiness logic, and verify productive tables remain unchanged. Before the first productive broker position import, follow `references/broker-import-execution-plan-mini-import.md`: create runtime-only execution plans from the ready review items, validate exact Decimal-text payloads from the runtime source, preserve missing FX/cost-basis quality flags, then import exactly one ledger `initial_position_snapshot` after a verified backup; do not write `positions_snapshot` as the source of truth. After the first mini-import and before broader imports, follow `references/broker-mini-import-regression-and-corrections.md`: verify import links/audit/Decimal handling/re-import blocking, add or test safe void/correction flows, run backup/restore-to-test-DB regression, and only then optionally import one more ready plan. When the user approves finishing a remaining small set, follow `references/broker-mini-import-completion-and-dq-consolidation.md`: first disambiguate active vs resolved stale crypto alerts with `check-data-quality --scope crypto --resolve-fixed`, then import exactly one remaining ready execution plan after backup/verify, and consolidate Review Queue/Data Quality counts without exposing values.\\n- Do not pivot into later analytics modules while the user has asked for import/mapping hardening. Monte Carlo, backtesting, rebalancing, scores, heatmaps and projections are later phases unless explicitly re-authorized.\\n- Use a canonical CSV format before broker-specific importers.\\n- Imports must be idempotent via external transaction ID or row hash.\\n- Importers must separate dry-run and commit modes, collect validation errors explicitly, and always create an `import_sessions` record even for dry runs or failed imports.\\n- Import results should classify rows as new, existing, duplicate, or failed; do not rely on `INSERT OR IGNORE` as the only duplicate-detection mechanism.\\n- Row hashes must be stable and deterministic: normalize key order, whitespace, and `None` versus empty strings while leaving domain-specific canonicalization to the importer.\\n- If a source file has only current holdings and no full history, import it as `initial_position_snapshot` / `initial_cash_snapshot`, not fake historical buys.\\n- Missing historic FX, fees, taxes, dates, investment case, target weights, or dividend details must be flagged as data-quality gaps.\\n\\n## FX and return rules\\n\\nFor foreign currency assets, always distinguish:\\n\\n- price/security performance in original currency\\n- FX effect to CHF\\n- realized P&L\\n- unrealized P&L\\n- dividends/distributions/income\\n- fees and taxes\\n- Total Return in CHF\\n\\nEvery transaction/income event needs:\\n\\n- original amount and currency\\n- historical FX rate to CHF, or explicit `fx_status=missing` with a critical data-quality alert\\n- FX source and timestamp\\n- CHF equivalent at event date when FX is known\\n\\nManual FX overrides require a non-empty note and an audit-log entry.\\n\\n## Ledger calculation rules\\n\\n- Cash after system start must be calculated from `transactions`; `cash_balances` is only a snapshot/cache/control view.\\n- `initial_cash_snapshot` and `initial_position_snapshot` are explicit starting truths, not fabricated historical trades.\\n- Implement Weighted Average Cost as the MVP internal performance method: buy fees increase cost basis, partial sells remove proportional cost basis, realized P&L is calculated against average cost, full sells zero remaining quantity/cost basis, and dividends do not alter quantity or cost basis.\\n- WAC is not tax-complete; do not add FIFO/LIFO/tax-lot logic in MVP 1, but keep transaction granularity so it can be added later.\\n- Position calculations must keep zero-quantity historical positions visible when sale history exists.\\n- Missing market price or FX must degrade data quality and suppress precise Total Return CHF rather than inventing a value.\\n- Before productive dashboard use, add alert deduplication per rule/entity/date.\\n- Market-FX for non-CHF market prices belongs to the later Market/FX provider block.\\n\\n## Crypto MVP rules\\n\\n- Crypto inventory is MVP-critical but must remain dummy-first until mapper/dry-run layers are ready; do not touch real coin/wallet files during core implementation. After explicit user approval, real files may be read only from temp/runtime for controlled dry runs using `references/crypto-xlsx-initial-snapshot-dry-run.md`; report only aggregate counts/labels and never quantities or values. Productive safe-subset imports require a second explicit approval and must follow `references/crypto-xlsx-initial-snapshot-production-import.md`: external runtime DB only, no real CSV/XLSX/reports/DBs in Git, Git-safety before/after, import-session + audit-log creation, and aggregate-only reporting.\\n- Wallet names must be unique; wallet addresses are optional and must not appear in tests/fixtures.\\n- Validate wallet type against: Hardware Wallet, Software Wallet, Exchange, Bank/Broker, DeFi, Sonstiges.\\n- CoinGecko ID is strongly recommended but not hard-required; missing ID creates a data-quality warning and blocks reliable valuation.\\n- Crypto symbols are not globally unique; symbol conflicts require warning/manual selection, never silent merging.\\n- Initial crypto holdings are confirmed snapshots by wallet+asset. Store legacy values for provenance/control only, never current valuation.\\n- Crypto holdings should be calculated/controlled from initial snapshots plus crypto transactions, not silently overwritten.\\n- Crypto transfers require different source/target wallets, quantity > 0, and same asset; coin fees reduce source-wallet balance.\\n- Negative wallet balances should be blocked in MVP and produce a critical alert unless a future explicit correction workflow is implemented.\\n- Crypto buys/sells with fiat impact must create/reference general ledger transactions via `source_type='crypto'`/`source_id` so cash remains ledger-consistent.\\n- Fiat fees should be ledger fees when unambiguous; avoid double counting when a fee is already embedded in sell net proceeds.\\n- Unknown fee currency creates a data-quality warning instead of invented accounting.\\n- Crypto Cost Basis/WAC is not required for MVP 1; MVP 1 prioritizes crypto holdings, wallet structure, current valuation, reports and audit.\\n- Crypto report context/export must be renderer-neutral and local-only: build from SQLite, aggregate by coin and wallet, use local cached prices only, preserve Decimal/Text values, ignore legacy snapshot values for current valuation, include data-quality warnings, and write generated files only to the external runtime reports directory.\\n- Crypto PDF export should be optional-dependency tolerant: prefer PDF when a renderer is available, otherwise fall back to HTML/Markdown with a clear warning while still recording report metadata and audit.\\n- After productive real-data crypto imports, run the post-import runtime verification in `references/crypto-runtime-db-consistency-verification.md`: exact safe-set membership checks, aggregate-only counts, audit/import-session traceability, dashboard render with no live API, runtime-only report generation, and Git-safety before/after.\\n- Manual dashboard additions/corrections/removals after an initial snapshot must follow `references/mvp-crypto-manual-management-ui.md`: no silent `crypto_holdings` mutation, explicit confirmation, mandatory notes for adjustments/removals, audit-log entries with old/new values, Decimal/TEXT quantity handling, no negative holdings, and no live API lookup during render.\\n- Crypto tax logic, tax lots, FIFO/LIFO and detailed cost basis are later modules.\\n- Keep crypto assets separate from `instruments` for MVP 1, but later evaluate a shared Asset Master if it improves reporting, performance views or watchlists.\\n\\n## Income/tax rules\\n\\nFor dividends and ETF distributions, separately store:\\n\\n- gross dividend/distribution\\n- Swiss withholding tax 35%\\n- foreign withholding tax\\n- other tax/withholding if present\\n- net amount\\n- original currency\\n- historic FX to CHF\\n- gross/net CHF equivalents\\n- platform/account\\n- ISIN/ticker\\n- payment date\\n- ex-dividend date if available\\n\\nPlan later ESTV/ICTax support for Swiss year-end values and tax reports, but label outputs as technical reports, not tax advice.\\n\\n## Market-data rules\\n\\n- Dashboard reads primarily from local DB, not directly from APIs on page load.\\n- For Equity/ETF FX and market-data hardening after broker mini-imports, follow `references/equity-fx-market-data-phase-c.md`: validate active `missing_fx` alerts by original transaction currency first, correct only CHF false positives with audit, keep foreign-currency missing-FX alerts active until local historical rates exist, use ISIN as instrument identity and provider symbols only as market-data mappings, and run market-price providers only from explicit CLI/scheduled jobs.\\n- For the True-Wealth valuation pilot, follow `references/true-wealth-valuation-pilot-c2.md`: do not import more positions, do not guess provider symbols or hedge status, extend instrument metadata for currency hedging/status/valuation policy/corporate-action state, handle historical-FX paywalls as `manual_override_required` without crashing, align price/FX timestamps before claiming valuation precision, and report only aggregate runtime counts.\\n- For True-Wealth mapping-candidate review after the valuation pilot, follow `references/true-wealth-mapping-candidate-review-c3.md`: create runtime-only provider-symbol candidates keyed by ISIN/instrument, keep name-only or ticker-without-exchange candidates review-required, mark multiple candidates `needs_manual_review`, do not auto-select final mappings on ambiguity, keep hedge/instrument status unknown until confirmed, and ensure market-price dry runs call no provider when there are zero confirmed mappings. For public metadata lookup implementation details, provider result caps, OpenFIGI/Yahoo evidence handling, alert dedupe, runtime-only review templates, and UI/test requirements, use `references/public-instrument-lookup-candidate-generator.md`.\\n- For the broader Instrument Catalog + manual-add workflow, follow `references/instrument-catalog-manual-add-workflow.md`: documents/import files are initial-population aids, but the dashboard must allow audited manual add of equities/ETFs and later coins via search, candidate selection, account/wallet selection, Decimal/Text quantity, date, cost-basis/snapshot info and notes. ISIN is primary for equities/ETFs but can have multiple listings; ticker/symbol alone is never unique; provider symbols are market-data mappings only; CoinGecko ID is primary for crypto provider identity. External lookups may use only non-confidential instrument metadata and must never send quantities, balances, account/wallet IDs, cost basis, private notes or source documents.\\n- First Streamlit MVP should be a safe, local, read-first shell over SQLite with explicit synthetic demo DB creation only; page render functions must not call CoinGecko/market APIs, and tests should prove that by monkeypatching provider methods to fail.\\n- Use scheduled jobs to update prices/FX/news.\\n- Store provider, timestamp, quality status and freshness for every price/FX point.\\n- Implement caching, local historical storage, batch requests where possible, provider rate-limit queues, and backoff on HTTP 429.\\n- CoinGecko integrations must be mockable and unit-tested without real API calls; treat HTTP 429 as non-fatal and return a non-fresh data-quality status plus alert after configured retries.\\n- Crypto price refresh belongs in CLI/scheduled-job commands, not dashboard/report rendering. Prefer CoinGecko batch requests over per-coin requests; expose conservative controls (`--sleep-seconds`, `--max-retries`, `--initial-backoff`, `--max-backoff`, `--only-missing`, `--only-stale`, `--only-symbol`, `--limit`, `--dry-run`, `--currency`). Commands should use aggregate-only output (`total_assets/updated/cached/skipped/stale/warnings/errors/assets_still_missing_local_price`), cache by configurable `max_age_seconds`, store exact Decimal prices as TEXT in `crypto_prices`, and verify dashboard/report contexts read local prices with `live_api_calls=False`. For details and tests see `references/crypto-price-refresh-and-idempotent-btc-runtime.md`.\\n- Candidate providers: Finnhub, Financial Modeling Prep, Twelve Data, Stooq, Alpha Vantage selectively, Yahoo Finance fallback only; CoinGecko for crypto; later DefiLlama; ESTV/ICTax for Swiss tax values.\\n\\n## Crypto Decimal precision rules\\n\\nSQLite has no exact native DECIMAL. In the crypto context, store quantities, prices, crypto fees and valuation-relevant amounts as exact Decimal strings (`TEXT`) and compute with Python `Decimal`. Never convert crypto quantity/price/fee/valuation through float/REAL. Format Decimal writes with `format(value, \\\"f\\\")` so small quantities such as `0.00000001` do not become scientific notation. CSV importers must validate Decimal strings, and tests should assert high-precision preservation plus SQLite text storage. For multi-wallet real-data snapshots and Equity/ETF ledger fields, also see `references/multi-wallet-crypto-and-equity-manage-ui.md`; SQLite `NUMERIC` affinity can coerce Decimal-looking text to `real`, so schema/migrations should use `TEXT` for exact quantities, FX rates, original amounts and CHF equivalents where precision matters.\\n\\n## Alert lifecycle rules\\n\\nAlerts must be deduplicated and lifecycle-aware before dashboards run repeated calculations. Use a dedup key from `rule_id`, `entity_type`, `entity_id`, `priority` and an error fingerprint. Alerts should carry `status` (`active`, `resolved`, `muted`), `resolved_at`, optional `muted_until`, `last_seen_at`, `occurrence_count`, `fingerprint` and `dedup_key`. Re-seeing an identical active/resolved/muted alert should update `last_seen_at`/`occurrence_count` rather than create a new active row; changed fingerprints may create a new alert.\\n\\n## Git/GitHub safety\\n\\nCode/scripts/docs may be stored in a private Git repo, but never commit financial data. Use the `github-repo-management` skill and its `references/sensitive-code-backup.md` guidance.\\n\\nMinimum `.gitignore` for finance repos must block `data/`, `reports/`, `exports/`, `backups/`, DB files, spreadsheets, PDFs, DOCX, raw CSV/JSON, `.env`, tokens, credentials and client secrets. Only synthetic examples under `examples/` are acceptable.\\n\\n## MVP implementation safety gate\\n\\nBefore any real broker/bank/portfolio/crypto data is imported, build and verify the safety foundation described in `references/mvp-safety-gate-implementation.md`: repo skeleton, `.gitignore`, `.env.example`, runtime outside repo, settings validation, SQLite schema, synthetic fixtures, audit log, CSV dry-run, duplicate protection, and Git-safety scan. Run the safety scan before staging, committing, or pushing. If GitHub credentials are needed from Drive, use them only in a temporary location and never echo token values.\\n\\nBefore broader productive imports, implement or verify the runtime backup loop in `references/runtime-backup-and-broker-mapping.md`: backup outside Git, SHA256 verification, restore requiring explicit confirmation, tests for backup/restore/checksum, and Git-safety coverage that blocks backup artifacts in the repo. For PostFinance/True Wealth/Raiffeisen, perform structural mapping and dry-runs only until the user approves import; report aggregate counts/field coverage/quality flags only, never real values or raw rows.\\n\\n## Common pitfalls\\n\\n- Starting later analytics (Monte Carlo, backtesting, rebalancing, scoring, heatmaps, projections) while import/mapping/data-quality phases are still being hardened or while the user explicitly asked to postpone them.\\n- Treating a holdings snapshot as a real transaction history.\\n- Mixing price P&L and FX P&L.\\n- Letting dashboard refreshes hammer APIs.\\n- Committing realistic sample data to Git because the repo is private. Private GitHub is not a financial data vault.\\n- Showing real portfolio values back to the user unnecessarily in summaries.\\n- Designing Git-safety scans that block source package names like `src/.../imports` or `src/.../reports`; block top-level runtime/data directories instead.\\n- In broker/bank real-file dry-runs, aggregating Data Quality flags only for `review_status='open'`. Blocked review items are still actionable data-quality issues; include `open` and `blocked` so defensive Raiffeisen aggregate-only rows remain visible.\\n- Letting manual review actions blur into productive import actions. Review-metadata writes (ISIN/ticker/exchange/account/instrument confirmations, ignore/resolve, dry-run archive/current status) may be allowed with audit logs, but they must not write `positions_snapshot`, `transactions`, `cash_balances`, ledger rows, or cash snapshots. Name-only mapping must never become `mapped`/`ready_for_import`; ticker-only without exchange remains review-needed; `aggregate_only` remains blocked for instrument import. In guided pilots, do not force `ready_for_import` by direct status edits; let readiness logic derive it after audited metadata actions, and if parser presence flags were missed, correct only boolean presence metadata with an audit event, never actual quantities/values.\\n- Skipping the execution-plan layer between ready review items and productive broker imports. A final dry-run should materialize runtime-only execution plans with source row hash, target IDs, exact Decimal-text payload summary, quality flags and planned write status. Productive mini-imports should consume exactly one planned ready payload, write exactly one ledger `initial_position_snapshot`, mark that plan/review item imported, leave the other ready plans untouched, and verify zero direct `positions_snapshot`/cash writes. After the first productive mini-import, do not proceed straight to mass import: run regression checks, implement/test void and correction audit paths, verify backup/restore to a separate test DB, and import at most one additional ready plan. When later completing the final ready plan, first resolve Data Quality alert ambiguity by counting only active alerts (`status='active'`) and treating resolved rows as history; then import exactly one plan and consolidate counts. See `references/broker-import-execution-plan-mini-import.md`, `references/broker-mini-import-regression-and-corrections.md`, and `references/broker-mini-import-completion-and-dq-consolidation.md`.\\n- Running compile/tests before Git-safety and forgetting generated `__pycache__`; remove or ignore generated caches before safety scans. `pytest` may recreate `.pytest_cache`, so remove `__pycache__`/`.pytest_cache` again after test execution and before `git-safety-scan`.\\n- Treating every active `missing_fx` alert after a broker mini-import as a bug. First aggregate by original currency: CHF rows may be false positives (`fx=1`, `not_needed`, resolve with audit), but foreign-currency rows without local historical FX should remain active and block precise CHF valuation until rates are populated.\\n- Auto-mapping Equity/ETF market prices by instrument name or ticker alone. ISIN is the instrument identity, but one ISIN can have multiple listings across exchange/currency, so even ISIN matches may need candidate selection. Provider symbols are separate market-data mappings, ticker without exchange is review-needed, and missing provider symbols should create deduplicated Data Quality alerts rather than triggering provider guesses. For mapping-candidate phases, candidate creation is allowed in the runtime DB, but final selection must remain manual/audited unless the user explicitly approves and the match is unambiguous. Public lookup endpoints can return dozens of listings; cap result sets, dedupe active mapping alerts by rule/entity, and do not treat search-fallback results as ISIN-confirmed unless the provider response supplies ISIN evidence.\\n- Designing future portfolio entry as import-file-only. Imports/documents are for initial population and existing holdings; the system must also support dashboard manual add/search workflows with audited ledger writes, explicit candidate selection, Decimal/Text quantities, required notes where history is incomplete, and no silent overwrites. See `references/instrument-catalog-manual-add-workflow.md`.\\n- Letting an Equity/ETF market-price dry run call providers when no confirmed mappings exist. The safe outcome is `total_mappings=0`, no provider calls, and aggregate reporting only.\\n- For valuation pilots on historical broker snapshots, treating a computable current market value as a clean performance result. `snapshot_only`, `cost_basis_uncertain`, missing hedge confirmation, missing historical FX, stale price/FX timestamp alignment, or suspected corporate actions must keep valuation `partially_valuable` or suppress precise Total Return until reviewed.\\n- Inferring CHF-hedged ETF behavior from the name alone. Hedge status is methodology-critical: unknown status should create a warning/review item; confirmed CHF hedging must prevent naive free FX-PnL attribution.\\n- Crashing or blocking on historical-FX provider paywalls. Persist `manual_override_required`, create deduplicated alerts, keep the flow moving, and require a noted audited manual override instead of guessing latest FX.\\n- Productive real-data imports can partially write before surfacing schema/importer compatibility issues. Do not rerun blindly or dump row-level data; inspect aggregate counts and unique identifiers needed for idempotency, patch/complete via missing-only inserts, then verify committed import session, audit log, Git clean and Git-safety OK.\\n- In controlled one-coin runtime tests from a real XLSX, distinguish **one coin/asset** from **one holding/wallet row**. A coin may be split across multiple wallet columns; if the user required an unambiguous target wallet or one holding, stop and ask rather than choosing a wallet silently. If the user explicitly approves multi-wallet import for that coin, import exactly one asset plus one audited holding per non-empty approved wallet cell; verify aggregate counts only. If re-running a BTC/single-coin test finds the exact approved asset and holdings already present, do not import duplicates; perform the aggregate-only idempotency checks and report that asset/holding counts did not increase because duplicate prevention succeeded. See `references/crypto-single-coin-runtime-test.md`, `references/multi-wallet-crypto-and-equity-manage-ui.md`, and `references/crypto-price-refresh-and-idempotent-btc-runtime.md`.\\n- After productive crypto imports, do a separate aggregate-only consistency pass before building new features: DB/runtime outside repo, exact safe-subset membership, no duplicate/negative/orphan holdings, correct snapshot date, null legacy-value fields when ignored, import sessions committed, holding-level audit traces present, dashboard local-read/no-live-API verified, and report generated only under runtime reports.\\n- Letting a dashboard correction UI mutate crypto holdings directly. Add/remove/edit operations must become audited transactions or `manual_adjustment` events with mandatory notes where appropriate; preserve history instead of silently overwriting balances.\\n- Treating verifier/file-mutation warnings as either automatically true or automatically false. 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"content": "{\"content\": \" 1|from __future__ import annotations\\n 2|\\n 3|import csv\\n 4|import json\\n 5|import os\\n 6|import urllib.parse\\n 7|import urllib.request\\n 8|from dataclasses import dataclass, field\\n 9|from pathlib import Path\\n 10|from sqlite3 import Connection\\n 11|from typing import Protocol\\n 12|\\n 13|from jarvis_finance.audit.log import record_audit_event\\n 14|from jarvis_finance.imports.common import stable_id, utc_now\\n 15|from jarvis_finance.market_data.instruments import ensure_instrument_metadata_quality, resolve_instrument_alerts\\n 16|from jarvis_finance.market_data.mappings import confirm_instrument_price_mapping\\n 17|from jarvis_finance.quality.alerts import create_alert\\n 18|\\n 19|HEDGE_MARKERS = (\\\"chf hedged\\\", \\\"hedged chf\\\", \\\"currency hedged\\\", \\\"hedged to chf\\\", \\\"chf-hedged\\\")\\n 20|\\n 21|\\n 22|@dataclass(frozen=True)\\n 23|class ProviderCandidate:\\n 24| provider: str\\n 25| provider_symbol: str\\n 26| exchange: str | None = None\\n 27| currency: str | None = None\\n 28| name: str | None = None\\n 29| isin: str | None = None\\n 30| asset_class: str | None = None\\n 31| is_hedged: bool | None = None\\n 32| hedged_to_currency: str | None = None\\n 33| hedge_status: str = \\\"unknown\\\"\\n 34| instrument_status: str = \\\"unknown\\\"\\n 35| valuation_policy: str = \\\"live_price\\\"\\n 36| evidence_source: str = \\\"provider_lookup\\\"\\n 37| evidence_note: str = \\\"\\\"\\n 38|\\n 39|\\n 40|class InstrumentLookupProvider(Protocol):\\n 41| name: str\\n 42|\\n 43| def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n 44| ...\\n 45|\\n 46|\\n 47|class LookupUnavailable(RuntimeError):\\n 48| pass\\n 49|\\n 50|\\n 51|class EmptyLookupProvider:\\n 52| name = \\\"manual\\\"\\n 53|\\n 54| def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n 55| return []\\n 56|\\n 57|\\n 58|class OpenFIGILookupProvider:\\n 59| \\\"\\\"\\\"Public ISIN-to-instrument metadata lookup via OpenFIGI; no prices or portfolio data.\\\"\\\"\\\"\\n 60|\\n 61| name = \\\"openfigi\\\"\\n 62|\\n 63| def __init__(self, *, timeout_seconds: float = 8.0, max_results: int = 12):\\n 64| self.timeout_seconds = timeout_seconds\\n 65| self.max_results = max_results\\n 66|\\n 67| def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n 68| if not isin:\\n 69| return []\\n 70| token = os.environ.get(\\\"OPENFIGI_API_KEY\\\")\\n 71| headers = {\\\"Content-Type\\\": \\\"application/json\\\", \\\"User-Agent\\\": \\\"JarvisFinance/1.0 public-instrument-lookup\\\"}\\n 72| if token:\\n 73| headers[\\\"X-OPENFIGI-APIKEY\\\"] = token\\n 74| payload = json.dumps([{\\\"idType\\\": \\\"ID_ISIN\\\", \\\"idValue\\\": isin}]).encode(\\\"utf-8\\\")\\n 75| req = urllib.request.Request(\\\"https://api.openfigi.com/v3/mapping\\\", data=payload, headers=headers, method=\\\"POST\\\")\\n 76| try:\\n 77| with urllib.request.urlopen(req, timeout=self.timeout_seconds) as resp:\\n 78| data = json.loads(resp.read().decode(\\\"utf-8\\\"))\\n 79| except Exception as exc: # pragma: no cover - network dependent\\n 80| raise LookupUnavailable(str(exc)) from exc\\n 81| out: list[ProviderCandidate] = []\\n 82| for item in (data[0].get(\\\"data\\\", []) if data else [])[: self.max_results]:\\n 83| symbol = item.get(\\\"ticker\\\") or item.get(\\\"figi\\\")\\n 84| if not symbol:\\n 85| continue\\n 86| sec_type = \\\" \\\".join(str(item.get(k) or \\\"\\\") for k in (\\\"securityType\\\", \\\"securityType2\\\", \\\"marketSector\\\")).lower()\\n 87| asset_class = \\\"etf\\\" if \\\"fund\\\" in sec_type or \\\"etf\\\" in sec_type else \\\"equity\\\" if \\\"equity\\\" in sec_type else None\\n 88| out.append(ProviderCandidate(\\n 89| provider=self.name,\\n 90| provider_symbol=symbol,\\n 91| exchange=item.get(\\\"exchCode\\\") or item.get(\\\"marketSector\\\"),\\n 92| currency=item.get(\\\"currency\\\") or currency,\\n 93| name=item.get(\\\"name\\\"),\\n 94| isin=isin,\\n 95| asset_class=asset_class,\\n 96| hedge_status=\\\"unknown\\\",\\n 97| instrument_status=\\\"unknown\\\",\\n 98| valuation_policy=\\\"live_price\\\",\\n 99| evidence_source=\\\"openfigi_isin_mapping\\\",\\n 100| evidence_note=\\\"Public ISIN mapping metadata only; no prices, holdings, account data, or portfolio quantities sent.\\\",\\n 101| ))\\n 102| return out\\n 103|\\n 104|\\n 105|class YahooSearchLookupProvider:\\n 106| \\\"\\\"\\\"Public metadata lookup via Yahoo Finance search endpoint; no prices or portfolio data.\\\"\\\"\\\"\\n 107|\\n 108| name = \\\"yahoo_fallback\\\"\\n 109|\\n 110| def __init__(self, *, timeout_seconds: float = 8.0, max_results: int = 8):\\n 111| self.timeout_seconds = timeout_seconds\\n 112| self.max_results = max_results\\n 113|\\n 114| def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n 115| queries = [q for q in [isin, ticker, name] if q]\\n 116| if not queries:\\n 117| return []\\n 118| found: dict[tuple[str, str | None], ProviderCandidate] = {}\\n 119| for query in queries[:2]:\\n 120| url = \\\"https://query2.finance.yahoo.com/v1/finance/search?\\\" + urllib.parse.urlencode({\\\"q\\\": query, \\\"quotesCount\\\": self.max_results, \\\"newsCount\\\": 0})\\n 121| try:\\n 122| req = urllib.request.Request(url, headers={\\\"User-Agent\\\": \\\"JarvisFinance/1.0 public-instrument-lookup\\\"})\\n 123| with urllib.request.urlopen(req, timeout=self.timeout_seconds) as resp:\\n 124| payload = json.loads(resp.read().decode(\\\"utf-8\\\"))\\n 125| except Exception as exc: # pragma: no cover - network dependent\\n 126| raise LookupUnavailable(str(exc)) from exc\\n 127| for quote in payload.get(\\\"quotes\\\", [])[: self.max_results]:\\n 128| symbol = quote.get(\\\"symbol\\\")\\n 129| if not symbol:\\n 130| continue\\n 131| qtype = (quote.get(\\\"quoteType\\\") or \\\"\\\").lower()\\n 132| asset_class = \\\"etf\\\" if qtype == \\\"etf\\\" else \\\"equity\\\" if qtype in {\\\"equity\\\", \\\"stock\\\"} else None\\n 133| exch = quote.get(\\\"exchDisp\\\") or quote.get(\\\"exchange\\\")\\n 134| cand = ProviderCandidate(\\n 135| provider=self.name,\\n 136| provider_symbol=symbol,\\n 137| exchange=exch,\\n 138| currency=currency,\\n 139| name=quote.get(\\\"longname\\\") or quote.get(\\\"shortname\\\"),\\n 140| isin=None,\\n 141| asset_class=asset_class,\\n 142| hedge_status=\\\"unknown\\\",\\n 143| instrument_status=\\\"unknown\\\",\\n 144| valuation_policy=\\\"live_price\\\",\\n 145| evidence_source=\\\"yahoo_finance_search\\\",\\n 146| evidence_note=\\\"Public symbol/search metadata only; no prices, holdings, account data, or portfolio quantities sent.\\\",\\n 147| )\\n 148| found[(symbol, exch)] = cand\\n 149| return list(found.values())\\n 150|\\n 151|\\n 152|class CompositePublicLookupProvider:\\n 153| name = \\\"public_composite\\\"\\n 154|\\n 155| def __init__(self, providers: list[InstrumentLookupProvider] | None = None):\\n 156| self.providers = providers or [OpenFIGILookupProvider(), YahooSearchLookupProvider()]\\n 157|\\n 158| def lookup(self, *, isin: str | None, name: str | None, ticker: str | None, exchange: str | None, currency: str | None) -> list[ProviderCandidate]:\\n 159| candidates: list[ProviderCandidate] = []\\n 160| errors = 0\\n 161| for provider in self.providers:\\n 162| try:\\n 163| candidates.extend(provider.lookup(isin=isin, name=name, ticker=ticker, exchange=exchange, currency=currency))\\n 164| except Exception:\\n 165| errors += 1\\n 166| if errors and not candidates:\\n 167| raise LookupUnavailable(\\\"all public lookup providers unavailable\\\")\\n 168| return candidates\\n 169|\\n 170|\\n 171|@dataclass\\n 172|class CandidateGenerationResult:\\n 173| instruments_total: int = 0\\n 174| candidates_found: int = 0\\n 175| high_confidence: int = 0\\n 176| medium_confidence: int = 0\\n 177| low_confidence: int = 0\\n 178| instruments_without_candidate: int = 0\\n 179| instruments_with_hedge_unknown: int = 0\\n 180| instruments_with_status_unknown: int = 0\\n 181| provider_lookup_unavailable: int = 0\\n 182| ambiguous_provider_mapping: int = 0\\n 183| dry_run: bool = False\\n 184| warnings: list[str] = field(default_factory=list)\\n 185|\\n 186|\\n 187|def _instrument_ids_for_true_wealth(conn: Connection, *, limit: int | None = None) -> list[str]:\\n 188| sql = \\\"\\\"\\\"\\n 189| SELECT DISTINCT t.instrument_id\\n 190| FROM transactions t\\n 191| JOIN instruments i ON i.instrument_id=t.instrument_id\\n 192| WHERE t.transaction_type='initial_position_snapshot'\\n 193| AND t.source_type='broker_import_reviewed_snapshot'\\n 194| AND COALESCE(t.is_voided,0)=0\\n 195| AND t.instrument_id IS NOT NULL\\n 196| ORDER BY i.isin, i.name\\n 197| \\\"\\\"\\\"\\n 198| rows = conn.execute(sql).fetchall()\\n 199| ids = [r[\\\"instrument_id\\\"] for r in rows]\\n 200| return ids[:limit] if limit is not None else ids\\n 201|\\n 202|\\n 203|def _infer_hedge(name: str | None, candidate: ProviderCandidate) -> tuple[bool | None, str | None]:\\n 204| if candidate.is_hedged is not None:\\n 205| return candidate.is_hedged, candidate.hedged_to_currency\\n 206| haystack = \\\" \\\".join(x for x in [name, candidate.name, candidate.evidence_note] if x).lower()\\n 207| if any(marker in haystack for marker in HEDGE_MARKERS):\\n 208| return True, \\\"CHF\\\"\\n 209| return None, None\\n 210|\\n 211|\\n 212|def _confidence(inst, cand: ProviderCandidate) -> tuple[str, str]:\\n 213| notes: list[str] = []\\n 214| isin_match = bool(inst[\\\"isin\\\"] and cand.isin and inst[\\\"isin\\\"].upper() == cand.isin.upper())\\n 215| ticker_match = bool(inst[\\\"ticker\\\"] and cand.provider_symbol and inst[\\\"ticker\\\"].upper() in cand.provider_symbol.upper())\\n 216| has_exchange = bool(cand.exchange or inst[\\\"exchange\\\"])\\n 217| currency_match = bool((cand.currency or \\\"\\\").upper() == (inst[\\\"currency\\\"] or \\\"\\\").upper()) if cand.currency and inst[\\\"currency\\\"] else False\\n 218| if isin_match:\\n 219| notes.append(\\\"ISIN match\\\")\\n 220| if cand.provider_symbol and has_exchange:\\n 221| return \\\"high\\\", \\\"; \\\".join(notes + ([\\\"currency match\\\"] if currency_match else []))\\n 222| return \\\"medium\\\", \\\"; \\\".join(notes + [\\\"provider symbol/exchange incomplete\\\"])\\n 223| if ticker_match and has_exchange:\\n 224| return \\\"medium\\\", \\\"ticker+exchange match; requires manual review\\\"\\n 225| if cand.name:\\n 226| return \\\"low\\\", \\\"name-only or weak provider match; manual review required\\\"\\n 227| return \\\"low\\\", \\\"weak candidate; manual review required\\\"\\n 228|\\n 229|\\n 230|def _review_status_for(confidence: str, count: int, inst, cand: ProviderCandidate) -> str:\\n 231| if count > 1:\\n 232| return \\\"needs_manual_review\\\"\\n 233| if confidence == \\\"high\\\":\\n 234| return \\\"proposed\\\"\\n 235| if confidence == \\\"medium\\\":\\n 236| return \\\"needs_manual_review\\\"\\n 237| return \\\"needs_manual_review\\\"\\n 238|\\n 239|\\n 240|def upsert_candidate(conn: Connection, *, instrument_id: str, candidate: ProviderCandidate, confidence: str, review_status: str, evidence_note: str) -> str:\\n 241| inst = conn.execute(\\\"SELECT * FROM instruments WHERE instrument_id=?\\\", (instrument_id,)).fetchone()\\n 242| if inst is None:\\n 243| raise ValueError(f\\\"instrument not found: {instrument_id}\\\")\\n 244| hedged, hedged_to = _infer_hedge(inst[\\\"name\\\"], candidate)\\n 245| hedge_status = candidate.hedge_status if candidate.hedge_status in {\\\"hedged\\\", \\\"unhedged\\\", \\\"unknown\\\"} else \\\"unknown\\\"\\n 246| if hedge_status == \\\"unknown\\\" and hedged is True:\\n 247| hedge_status = \\\"hedged\\\"\\n 248| elif hedge_status == \\\"unknown\\\" and hedged is False:\\n 249| hedge_status = \\\"unhedged\\\"\\n 250| candidate_id = stable_id(\\\"ipmc\\\", instrument_id, candidate.provider, candidate.provider_symbol, candidate.exchange or \\\"\\\", candidate.currency or \\\"\\\")\\n 251| now = utc_now()\\n 252| conn.execute(\\n 253| \\\"\\\"\\\"\\n 254| INSERT INTO instrument_price_mapping_candidates(\\n 255| candidate_id, instrument_id, isin, candidate_provider, candidate_provider_symbol,\\n 256| candidate_exchange, candidate_currency, candidate_name, candidate_asset_class,\\n 257| candidate_is_hedged, candidate_hedged_to_currency, candidate_hedge_status,\\n 258| candidate_instrument_status, candidate_valuation_policy, confidence,\\n 259| evidence_source, evidence_note, review_status, created_at, updated_at\\n 260| ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\\n 261| ON CONFLICT(candidate_id) DO UPDATE SET\\n 262| candidate_exchange=excluded.candidate_exchange,\\n 263| candidate_currency=excluded.candidate_currency,\\n 264| candidate_name=excluded.candidate_name,\\n 265| candidate_asset_class=excluded.candidate_asset_class,\\n 266| candidate_is_hedged=excluded.candidate_is_hedged,\\n 267| candidate_hedged_to_currency=excluded.candidate_hedged_to_currency,\\n 268| candidate_hedge_status=excluded.candidate_hedge_status,\\n 269| candidate_instrument_status=excluded.candidate_instrument_status,\\n 270| candidate_valuation_policy=excluded.candidate_valuation_policy,\\n 271| confidence=excluded.confidence,\\n 272| evidence_source=excluded.evidence_source,\\n 273| evidence_note=excluded.evidence_note,\\n 274| review_status=excluded.review_status,\\n 275| updated_at=excluded.updated_at\\n 276| \\\"\\\"\\\",\\n 277| (\\n 278| candidate_id, instrument_id, inst[\\\"isin\\\"], candidate.provider, candidate.provider_symbol,\\n 279| candidate.exchange, candidate.currency or inst[\\\"currency\\\"], candidate.name, candidate.asset_class or (inst[\\\"asset_class\\\"] or \\\"\\\").lower(),\\n 280| 1 if hedged else 0 if hedged is False else None, hedged_to, hedge_status,\\n 281| candidate.instrument_status or \\\"unknown\\\", candidate.valuation_policy or \\\"live_price\\\", confidence, candidate.evidence_source,\\n 282| evidence_note or candidate.evidence_note, review_status, now, now,\\n 283| ),\\n 284| )\\n 285| return candidate_id\\n 286|\\n 287|\\n 288|def generate_mapping_candidates(\\n 289| conn: Connection,\\n 290| *,\\n 291| provider: InstrumentLookupProvider | None = None,\\n 292| instrument_ids: list[str] | None = None,\\n 293| source: str = \\\"true_wealth\\\",\\n 294| limit: int | None = None,\\n 295| dry_run: bool = False,\\n 296|) -> CandidateGenerationResult:\\n 297| lookup = provider or EmptyLookupProvider()\\n 298| ids = instrument_ids if instrument_ids is not None else _instrument_ids_for_true_wealth(conn, limit=limit)\\n 299| result = CandidateGenerationResult(instruments_total=len(ids), dry_run=dry_run)\\n 300| for instrument_id in ids:\\n 301| inst = conn.execute(\\\"SELECT * FROM instruments WHERE instrument_id=?\\\", (instrument_id,)).fetchone()\\n 302| if inst is None:\\n 303| continue\\n 304| ensure_instrument_metadata_quality(conn, instrument_id=instrument_id)\\n 305| if (inst[\\\"hedge_status\\\"] or \\\"unknown\\\") == \\\"unknown\\\":\\n 306| result.instruments_with_hedge_unknown += 1\\n 307| if (inst[\\\"instrument_status\\\"] or \\\"unknown\\\") == \\\"unknown\\\":\\n 308| result.instruments_with_status_unknown += 1\\n 309| try:\\n 310| candidates = lookup.lookup(isin=inst[\\\"isin\\\"], name=inst[\\\"name\\\"], ticker=inst[\\\"ticker\\\"], exchange=inst[\\\"exchange\\\"], currency=inst[\\\"currency\\\"])\\n 311| except Exception as exc:\\n 312| result.provider_lookup_unavailable += 1\\n 313| result.warnings.append(instrument_id)\\n 314| if not dry_run:\\n 315| create_alert(conn, priority=\\\"warnung\\\", category=\\\"market_data\\\", entity_type=\\\"instrument\\\", entity_id=instrument_id, rule_id=\\\"provider_lookup_unavailable\\\", message=\\\"Provider lookup unavailable for instrument mapping candidates.\\\", evidence={\\\"provider\\\": getattr(lookup, \\\"name\\\", \\\"unknown\\\"), \\\"error_type\\\": type(exc).__name__}, fingerprint=f\\\"provider_lookup_unavailable:{getattr(lookup, 'name', 'unknown')}\\\")\\n 316| continue\\n 317| if not candidates:\\n 318| result.instruments_without_candidate += 1\\n 319| if not dry_run:\\n 320| create_alert(conn, priority=\\\"warnung\\\", category=\\\"market_data\\\", entity_type=\\\"instrument\\\", entity_id=instrument_id, rule_id=\\\"missing_provider_symbol\\\", message=\\\"No provider-symbol candidate found; manual mapping required.\\\", evidence={\\\"source\\\": source, \\\"provider\\\": getattr(lookup, \\\"name\\\", \\\"manual\\\")}, fingerprint=\\\"missing_provider_symbol\\\")\\n 321| continue\\n 322| if len(candidates) > 1:\\n 323| result.ambiguous_provider_mapping += 1\\n 324| if not dry_run:\\n 325| create_alert(conn, priority=\\\"warnung\\\", category=\\\"market_data\\\", entity_type=\\\"instrument\\\", entity_id=instrument_id, rule_id=\\\"ambiguous_provider_mapping\\\", message=\\\"Multiple provider-symbol candidates require manual review.\\\", evidence={\\\"candidate_count\\\": len(candidates), \\\"provider\\\": getattr(lookup, \\\"name\\\", \\\"unknown\\\")}, fingerprint=f\\\"ambiguous_provider_mapping:{getattr(lookup, 'name', 'unknown')}:{len(candidates)}\\\")\\n 326| for cand in candidates:\\n 327| confidence, note = _confidence(inst, cand)\\n 328| if confidence == \\\"high\\\":\\n 329| result.high_confidence += 1\\n 330| elif confidence == \\\"medium\\\":\\n 331| result.medium_confidence += 1\\n 332| else:\\n 333| result.low_confidence += 1\\n 334| status = _review_status_for(confidence, len(candidates), inst, cand)\\n 335| result.candidates_found += 1\\n 336| if not dry_run:\\n 337| upsert_candidate(conn, instrument_id=instrument_id, candidate=cand, confidence=confidence, review_status=status, evidence_note=note)\\n 338| if not dry_run:\\n 339| conn.commit()\\n 340| return result\\n 341|\\n 342|\\n 343|def dedupe_missing_provider_symbol_alerts(conn: Connection) -> int:\\n 344| \\\"\\\"\\\"Keep one active mapping-quality alert per rule/instrument; resolve duplicate active rows.\\\"\\\"\\\"\\n 345| now = utc_now()\\n 346| resolved = 0\\n 347| rows = conn.execute(\\n 348| \\\"\\\"\\\"\\n 349| SELECT rule_id, entity_id, GROUP_CONCAT(alert_id) AS ids, COUNT(*) AS c\\n 350| FROM alerts\\n 351| WHERE status='active'\\n 352| AND rule_id IN ('missing_provider_symbol','ambiguous_provider_mapping','provider_lookup_unavailable')\\n 353| AND entity_type='instrument'\\n 354| GROUP BY rule_id, entity_id\\n 355| HAVING COUNT(*) > 1\\n 356| \\\"\\\"\\\"\\n 357| ).fetchall()\\n 358| for row in rows:\\n 359| ids = [x for x in (row[\\\"ids\\\"] or \\\"\\\").split(\\\",\\\") if x]\\n 360| for alert_id in ids[1:]:\\n 361| conn.execute(\\\"UPDATE alerts SET status='resolved', resolved_at=?, last_seen_at=? WHERE alert_id=?\\\", (now, now, alert_id))\\n 362| resolved += 1\\n 363| conn.commit()\\n 364| return resolved\\n 365|\\n 366|\\n 367|def export_mapping_review_template(conn: Connection, *, output_path: str | Path) -> dict[str, int | str]:\\n 368| path = Path(output_path).expanduser().resolve()\\n 369| path.parent.mkdir(parents=True, exist_ok=True)\\n 370| rows = conn.execute(\\n 371| \\\"\\\"\\\"\\n 372| SELECT i.instrument_id, i.asset_class, i.name, i.isin, i.ticker, i.exchange, i.currency,\\n 373| c.candidate_provider, c.candidate_provider_symbol, c.candidate_exchange,\\n 374| c.candidate_currency, c.confidence, c.candidate_hedge_status,\\n 375| c.candidate_instrument_status, c.evidence_source, c.evidence_note,\\n 376| c.review_status\\n 377| FROM instruments i\\n 378| LEFT JOIN instrument_price_mapping_candidates c ON c.instrument_id=i.instrument_id\\n 379| WHERE i.instrument_id IN (\\n 380| SELECT DISTINCT instrument_id FROM transactions\\n 381| WHERE transaction_type='initial_position_snapshot'\\n 382| AND source_type='broker_import_reviewed_snapshot'\\n 383| AND COALESCE(is_voided,0)=0\\n 384| AND instrument_id IS NOT NULL\\n 385| )\\n 386| ORDER BY i.isin, i.name, c.confidence, c.candidate_provider\\n 387| \\\"\\\"\\\"\\n 388| ).fetchall()\\n 389| fields = [\\n 390| \\\"instrument_id\\\", \\\"asset_class\\\", \\\"name\\\", \\\"isin\\\", \\\"ticker\\\", \\\"exchange\\\", \\\"currency\\\",\\n 391| \\\"candidate_provider\\\", \\\"candidate_provider_symbol\\\", \\\"candidate_exchange\\\", \\\"candidate_currency\\\",\\n 392| \\\"confidence\\\", \\\"hedge_status_candidate\\\", \\\"instrument_status_candidate\\\", \\\"evidence_source\\\",\\n 393| \\\"evidence_note\\\", \\\"review_status\\\", \\\"reviewer_decision\\\", \\\"reviewer_note\\\",\\n 394| ]\\n 395| with path.open(\\\"w\\\", newline=\\\"\\\", encoding=\\\"utf-8\\\") as handle:\\n 396| writer = csv.DictWriter(handle, fieldnames=fields)\\n 397| writer.writeheader()\\n 398| for row in rows:\\n 399| writer.writerow({\\n 400| \\\"instrument_id\\\": row[\\\"instrument_id\\\"], \\\"asset_class\\\": row[\\\"asset_class\\\"], \\\"name\\\": row[\\\"name\\\"],\\n 401| \\\"isin\\\": row[\\\"isin\\\"], \\\"ticker\\\": row[\\\"ticker\\\"], \\\"exchange\\\": row[\\\"exchange\\\"], \\\"currency\\\": row[\\\"currency\\\"],\\n 402| \\\"candidate_provider\\\": row[\\\"candidate_provider\\\"], \\\"candidate_provider_symbol\\\": row[\\\"candidate_provider_symbol\\\"],\\n 403| \\\"candidate_exchange\\\": row[\\\"candidate_exchange\\\"], \\\"candidate_currency\\\": row[\\\"candidate_currency\\\"],\\n 404| \\\"confidence\\\": row[\\\"confidence\\\"], \\\"hedge_status_candidate\\\": row[\\\"candidate_hedge_status\\\"],\\n 405| \\\"instrument_status_candidate\\\": row[\\\"candidate_instrument_status\\\"], \\\"evidence_source\\\": row[\\\"evidence_source\\\"],\\n 406| \\\"evidence_note\\\": row[\\\"evidence_note\\\"], \\\"review_status\\\": row[\\\"review_status\\\"],\\n 407| \\\"reviewer_decision\\\": \\\"\\\", \\\"reviewer_note\\\": \\\"\\\",\\n 408| })\\n 409| return {\\\"output_path\\\": str(path), \\\"rows\\\": len(rows), \\\"candidate_rows\\\": sum(1 for r in rows if r[\\\"candidate_provider_symbol\\\"]), \\\"instrument_count\\\": len({r[\\\"instrument_id\\\"] for r in rows})}\\n 410|\\n 411|\\n 412|def select_mapping_candidate(conn: Connection, *, candidate_id: str, note: str, created_by: str = \\\"system\\\") -> str:\\n 413| if not note.strip():\\n 414| raise ValueError(\\\"candidate selection requires a note\\\")\\n 415| cand = conn.execute(\\\"SELECT * FROM instrument_price_mapping_candidates WHERE candidate_id=?\\\", (candidate_id,)).fetchone()\\n 416| if cand is None:\\n 417| raise ValueError(f\\\"candidate not found: {candidate_id}\\\")\\n 418| mapping_id = confirm_instrument_price_mapping(\\n 419| conn,\\n 420| instrument_id=cand[\\\"instrument_id\\\"],\\n 421| provider=cand[\\\"candidate_provider\\\"],\\n 422| provider_symbol=cand[\\\"candidate_provider_symbol\\\"],\\n 423| provider_market=cand[\\\"candidate_exchange\\\"],\\n 424| confidence=cand[\\\"confidence\\\"],\\n 425| note=note,\\n 426| exchange=cand[\\\"candidate_exchange\\\"],\\n 427| currency=cand[\\\"candidate_currency\\\"],\\n 428| hedge_status=cand[\\\"candidate_hedge_status\\\"] if cand[\\\"candidate_hedge_status\\\"] != \\\"unknown\\\" else None,\\n 429| hedged_to_currency=cand[\\\"candidate_hedged_to_currency\\\"],\\n 430| instrument_status=cand[\\\"candidate_instrument_status\\\"] if cand[\\\"candidate_instrument_status\\\"] != \\\"unknown\\\" else None,\\n 431| valuation_policy=cand[\\\"candidate_valuation_policy\\\"] or (\\\"live_price\\\" if cand[\\\"candidate_instrument_status\\\"] == \\\"active\\\" else None),\\n 432| trading_currency=cand[\\\"candidate_currency\\\"],\\n 433| created_by=created_by,\\n 434| )\\n 435| now = utc_now()\\n 436| conn.execute(\\\"UPDATE instrument_price_mapping_candidates SET review_status='selected', updated_at=? WHERE candidate_id=?\\\", (now, candidate_id))\\n 437| conn.execute(\\\"UPDATE instrument_price_mapping_candidates SET review_status='rejected', updated_at=? WHERE instrument_id=? AND candidate_id<>? AND review_status IN ('proposed','needs_manual_review')\\\", (now, cand[\\\"instrument_id\\\"], candidate_id))\\n 438| record_audit_event(\\n 439| conn,\\n 440| source=\\\"instrument_price_mapping_candidate\\\",\\n 441| action=\\\"select_mapping_candidate\\\",\\n 442| entity_type=\\\"instrument_price_mapping_candidate\\\",\\n 443| entity_id=candidate_id,\\n 444| new_values={\\\"mapping_id\\\": mapping_id, \\\"instrument_id\\\": cand[\\\"instrument_id\\\"], \\\"provider\\\": cand[\\\"candidate_provider\\\"], \\\"provider_symbol\\\": cand[\\\"candidate_provider_symbol\\\"]},\\n 445| user_text_note=note,\\n 446| confirmed=True,\\n 447| created_by=created_by,\\n 448| )\\n 449| resolve_instrument_alerts(conn, instrument_id=cand[\\\"instrument_id\\\"], rule_ids=[\\\"missing_provider_symbol\\\", \\\"ambiguous_provider_mapping\\\"])\\n 450| conn.commit()\\n 451| return mapping_id\\n 452|\\n 453|\\n 454|def reject_mapping_candidate(conn: Connection, *, candidate_id: str, note: str, created_by: str = \\\"system\\\") -> None:\\n 455| if not note.strip():\\n 456| raise ValueError(\\\"candidate rejection requires a note\\\")\\n 457| cand = conn.execute(\\\"SELECT * FROM instrument_price_mapping_candidates WHERE candidate_id=?\\\", (candidate_id,)).fetchone()\\n 458| if cand is None:\\n 459| raise ValueError(f\\\"candidate not found: {candidate_id}\\\")\\n 460| now = utc_now()\\n 461| conn.execute(\\\"UPDATE instrument_price_mapping_candidates SET review_status='rejected', updated_at=? WHERE candidate_id=?\\\", (now, candidate_id))\\n 462| record_audit_event(\\n 463| conn,\\n 464| source=\\\"instrument_price_mapping_candidate\\\",\\n 465| action=\\\"reject_mapping_candidate\\\",\\n 466| entity_type=\\\"instrument_price_mapping_candidate\\\",\\n 467| entity_id=candidate_id,\\n 468| old_values={\\\"review_status\\\": cand[\\\"review_status\\\"]},\\n 469| new_values={\\\"review_status\\\": \\\"rejected\\\"},\\n 470| user_text_note=note,\\n 471| confirmed=True,\\n 472| created_by=created_by,\\n 473| )\\n 474| conn.commit()\\n 475|\\n 476|\\n 477|def get_mapping_candidate_summary(conn: Connection) -> dict[str, int]:\\n 478| rows = conn.execute(\\\"SELECT confidence, COUNT(*) AS c FROM instrument_price_mapping_candidates GROUP BY confidence\\\").fetchall()\\n 479| out = {\\\"total\\\": 0, \\\"high\\\": 0, \\\"medium\\\": 0, \\\"low\\\": 0}\\n 480| for row in rows:\\n 481| key = row[\\\"confidence\\\"] or \\\"low\\\"\\n 482| if key in out:\\n 483| out[key] += int(row[\\\"c\\\"] or 0)\\n 484| out[\\\"total\\\"] += int(row[\\\"c\\\"] or 0)\\n 485| return out\\n 486|\", \"total_lines\": 485, \"file_size\": 24551, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_7uxyImyt8LJaGT52vMjy7u4q"
},
{
"role": "tool",
"name": "read_file",
"content": "{\"content\": \" 1|from __future__ import annotations\\n 2|\\n 3|from decimal import Decimal\\n 4|\\n 5|from jarvis_finance.dashboard import data\\n 6|from jarvis_finance.dashboard.components.tables import show_table\\n 7|from jarvis_finance.equity.manage import add_equity_initial_snapshot, add_equity_transaction, add_manual_position_from_catalog, create_manual_catalog_entry, get_equity_management_options\\n 8|from jarvis_finance.fx.overrides import set_manual_fx_override\\n 9|from jarvis_finance.market_data.candidates import reject_mapping_candidate, select_mapping_candidate\\n 10|\\n 11|PAGE_TITLE = \\\"Equity/ETF Manage\\\"\\n 12|\\n 13|\\n 14|def _account_label(row: dict[str, str]) -> str:\\n 15| return f\\\"{row['platform_name']} / {row['account_name']} [{row['currency']} ]\\\"\\n 16|\\n 17|\\n 18|def _instrument_label(row: dict[str, str]) -> str:\\n 19| suffix = row.get(\\\"isin\\\") or row.get(\\\"ticker\\\") or row[\\\"instrument_id\\\"]\\n 20| return f\\\"{row['name']} ({suffix})\\\"\\n 21|\\n 22|\\n 23|def _selected(rows: list[dict[str, str]], label: str | None, label_fn) -> dict[str, str] | None:\\n 24| if not label:\\n 25| return None\\n 26| for row in rows:\\n 27| if label_fn(row) == label:\\n 28| return row\\n 29| return None\\n 30|\\n 31|\\n 32|def render(st, conn) -> None:\\n 33| st.title(\\\"Equity/ETF Manage\\\")\\n 34| st.caption(\\\"Auditierbare manuelle Aktien-/ETF-Erfassung. Dashboard liest lokal; keine Broker-Dateien oder Live-APIs beim Rendern.\\\")\\n 35| st.warning(\\\"Keine stillen Überschreibungen: Initial Snapshots, Transaktionen und Korrekturen werden als bestätigte Ledger-Ereignisse mit Audit-Log gespeichert.\\\")\\n 36|\\n 37| options = get_equity_management_options(conn)\\n 38| account_labels = [_account_label(row) for row in options[\\\"accounts\\\"]]\\n 39| instrument_labels = [_instrument_label(row) for row in options[\\\"instruments\\\"]]\\n 40| tabs = st.tabs([\\\"Instrument Search / Add Position\\\", \\\"Hinzufügen\\\", \\\"Kaufen\\\", \\\"Partial Sell\\\", \\\"Full Sell\\\", \\\"Dividende\\\", \\\"ETF-Ausschüttung\\\", \\\"Fee\\\", \\\"Korrigieren\\\", \\\"Review\\\"])\\n 41|\\n 42| with tabs[0]:\\n 43| st.subheader(\\\"Instrument Search / Add Position\\\")\\n 44| st.caption(\\\"Lokaler Katalog zuerst; externe Lookups nur über freigegebene Provider. Mehrere Listings bleiben Auswahlpflicht.\\\")\\n 45| summary = data.get_instrument_catalog_summary(conn)\\n 46| st.write(summary)\\n 47| query = st.text_input(\\\"Suche nach ISIN, Symbol, Name, Provider-Symbol, Exchange oder Currency\\\", key=\\\"catalog_search_query\\\")\\n 48| class_filter = st.selectbox(\\\"Filter\\\", [\\\"\\\", \\\"equity\\\", \\\"etf\\\", \\\"crypto\\\", \\\"cash\\\"], key=\\\"catalog_search_class\\\")\\n 49| catalog_rows = data.get_instrument_catalog_entries(conn, query=query or None, asset_class=class_filter or None)\\n 50| show_table(st, catalog_rows)\\n 51| st.divider()\\n 52| st.subheader(\\\"Katalogeintrag manuell anlegen\\\")\\n 53| c_asset = st.selectbox(\\\"Assetklasse\\\", [\\\"equity\\\", \\\"etf\\\"], key=\\\"catalog_new_asset\\\")\\n 54| c_name = st.text_input(\\\"Name\\\", key=\\\"catalog_new_name\\\")\\n 55| c_isin = st.text_input(\\\"ISIN\\\", key=\\\"catalog_new_isin\\\")\\n 56| c_ticker = st.text_input(\\\"Ticker/Symbol\\\", key=\\\"catalog_new_ticker\\\")\\n 57| c_exchange = st.text_input(\\\"Exchange\\\", key=\\\"catalog_new_exchange\\\")\\n 58| c_currency = st.selectbox(\\\"Trading/Instrument Currency\\\", [\\\"CHF\\\", \\\"EUR\\\", \\\"USD\\\"], key=\\\"catalog_new_currency\\\")\\n 59| c_provider = st.text_input(\\\"Provider\\\", value=\\\"manual\\\", key=\\\"catalog_new_provider\\\")\\n 60| c_provider_symbol = st.text_input(\\\"Provider-Symbol\\\", key=\\\"catalog_new_provider_symbol\\\")\\n 61| c_hedge = st.selectbox(\\\"Hedge Status\\\", [\\\"unknown\\\", \\\"hedged\\\", \\\"unhedged\\\"], key=\\\"catalog_new_hedge\\\")\\n 62| c_status = st.selectbox(\\\"Instrument Status\\\", [\\\"unknown\\\", \\\"active\\\", \\\"suspended\\\", \\\"delisted\\\", \\\"merged\\\", \\\"inactive\\\"], key=\\\"catalog_new_status\\\")\\n 63| c_policy = st.selectbox(\\\"Valuation Policy\\\", [\\\"live_price\\\", \\\"last_known_price\\\", \\\"manual_value\\\", \\\"exclude_from_auto_price_update\\\"], key=\\\"catalog_new_policy\\\")\\n 64| c_note = st.text_area(\\\"Katalog-Notiz (Pflicht)\\\", key=\\\"catalog_new_note\\\")\\n 65| if st.button(\\\"Katalogeintrag speichern\\\", key=\\\"catalog_new_save\\\"):\\n 66| try:\\n 67| cid = create_manual_catalog_entry(conn, asset_class=c_asset, name=c_name, isin=c_isin, ticker=c_ticker, exchange=c_exchange, currency=c_currency, provider=c_provider, provider_symbol=c_provider_symbol, hedge_status=c_hedge, instrument_status=c_status, valuation_policy=c_policy, note=c_note)\\n 68| st.success(\\\"Katalogeintrag gespeichert; Audit-Log geschrieben.\\\")\\n 69| st.write({\\\"catalog_entry_id\\\": cid})\\n 70| except Exception as exc:\\n 71| st.error(f\\\"Katalogspeicherung abgelehnt: {exc}\\\")\\n 72| st.divider()\\n 73| st.subheader(\\\"Position aus Katalog hinzufügen\\\")\\n 74| entry_labels = [f\\\"{r.get('catalog_entry_id')} | {r.get('ticker') or ''} | {r.get('name')} | {r.get('isin') or ''} | {r.get('exchange') or ''} | {r.get('trading_currency') or ''}\\\" for r in catalog_rows]\\n 75| entry_label = st.selectbox(\\\"Katalog-Kandidat auswählen\\\", entry_labels, key=\\\"catalog_position_entry\\\") if entry_labels else None\\n 76| pos_account_label = st.selectbox(\\\"Depot/Konto\\\", account_labels, key=\\\"catalog_position_account\\\") if account_labels else None\\n 77| pos_type = st.selectbox(\\\"Positionstyp\\\", [\\\"initial_snapshot\\\", \\\"buy\\\", \\\"manual_adjustment\\\"], key=\\\"catalog_position_type\\\")\\n 78| pos_qty = st.text_input(\\\"Menge als Decimal-Text\\\", key=\\\"catalog_position_qty\\\")\\n 79| pos_date = st.date_input(\\\"Datum\\\", key=\\\"catalog_position_date\\\")\\n 80| pos_currency = st.selectbox(\\\"Währung\\\", [\\\"CHF\\\", \\\"EUR\\\", \\\"USD\\\"], key=\\\"catalog_position_currency\\\")\\n 81| pos_cost = st.text_input(\\\"Einstandspreis / Cost Basis optional\\\", key=\\\"catalog_position_cost\\\")\\n 82| pos_fx_status = st.selectbox(\\\"FX-Status\\\", [\\\"not_needed\\\", \\\"missing\\\", \\\"manual_override\\\", \\\"manual_override_required\\\"], key=\\\"catalog_position_fx_status\\\")\\n 83| pos_fx_rate = st.text_input(\\\"FX-Rate optional\\\", key=\\\"catalog_position_fx_rate\\\")\\n 84| pos_fx_source = st.text_input(\\\"FX-Quelle optional\\\", key=\\\"catalog_position_fx_source\\\")\\n 85| pos_note = st.text_area(\\\"Review-/Bestätigungsnotiz\\\", key=\\\"catalog_position_note\\\")\\n 86| pos_confirm = st.checkbox(\\\"Ich bestätige diese einzelne Katalog-Position\\\", key=\\\"catalog_position_confirm\\\")\\n 87| selected_pos_account = _selected(options[\\\"accounts\\\"], pos_account_label, _account_label)\\n 88| if st.button(\\\"Position aus Katalog speichern\\\", key=\\\"catalog_position_save\\\", type=\\\"primary\\\"):\\n 89| try:\\n 90| if not entry_label or not selected_pos_account:\\n 91| raise ValueError(\\\"catalog entry and account are required\\\")\\n 92| result = add_manual_position_from_catalog(conn, catalog_entry_id=entry_label.split(\\\" | \\\", 1)[0], account_id=selected_pos_account[\\\"account_id\\\"], position_type=pos_type, quantity_text=pos_qty, trade_date=str(pos_date), currency=pos_currency, cost_basis_original_text=pos_cost or None, fx_status=pos_fx_status, fx_rate_to_chf_text=pos_fx_rate or None, fx_source=pos_fx_source or None, note=pos_note, confirm=bool(pos_confirm))\\n 93| st.success(\\\"Position gespeichert und auditierbar erfasst.\\\")\\n 94| st.write({\\\"instrument_id\\\": result.instrument_id, \\\"transaction_id\\\": result.transaction_id, \\\"warnings\\\": result.warnings})\\n 95| except Exception as exc:\\n 96| st.error(f\\\"Positionsspeicherung abgelehnt: {exc}\\\")\\n 97|\\n 98| with tabs[1]:\\n 99| st.subheader(\\\"Aktie/ETF als Initial Snapshot hinzufügen\\\")\\n 100| account_label = st.selectbox(\\\"Depot/Konto\\\", account_labels, key=\\\"equity_add_account\\\") if account_labels else None\\n 101| asset_class = st.selectbox(\\\"Assetklasse\\\", [\\\"stock\\\", \\\"ETF\\\"], key=\\\"equity_add_class\\\")\\n 102| name = st.text_input(\\\"Name\\\", key=\\\"equity_add_name\\\")\\n 103| isin = st.text_input(\\\"ISIN (primäre Identifikation)\\\", key=\\\"equity_add_isin\\\")\\n 104| ticker = st.text_input(\\\"Ticker optional\\\", key=\\\"equity_add_ticker\\\")\\n 105| exchange = st.text_input(\\\"Exchange optional\\\", key=\\\"equity_add_exchange\\\")\\n 106| currency = st.selectbox(\\\"Währung\\\", [\\\"CHF\\\", \\\"EUR\\\", \\\"USD\\\"], key=\\\"equity_add_currency\\\")\\n 107| quantity = st.text_input(\\\"Menge als Decimal-Text\\\", key=\\\"equity_add_qty\\\")\\n 108| cost_basis = st.text_input(\\\"Einstandspreis / Cost Basis Originalwährung\\\", key=\\\"equity_add_cost\\\")\\n 109| fx_rate = st.text_input(\\\"FX-Kurs zu CHF (bei EUR/USD)\\\", key=\\\"equity_add_fx\\\")\\n 110| fx_source = st.text_input(\\\"FX-Quelle\\\", key=\\\"equity_add_fx_source\\\")\\n 111| fx_status = st.selectbox(\\\"FX-Status\\\", [\\\"ok\\\", \\\"missing\\\"], key=\\\"equity_add_fx_status\\\")\\n 112| snapshot_date = st.date_input(\\\"Snapshot-Datum\\\", key=\\\"equity_add_date\\\")\\n 113| category = st.selectbox(\\\"Kategorie\\\", [\\\"Core\\\", \\\"Opportunity\\\", \\\"Unknown\\\"], key=\\\"equity_add_category\\\")\\n 114| note = st.text_area(\\\"Notiz (Pflicht bei unvollständiger Historie)\\\", key=\\\"equity_add_note\\\")\\n 115| with st.expander(\\\"ETF-spezifische Felder\\\"):\\n 116| ter = st.text_input(\\\"TER optional\\\", key=\\\"equity_add_ter\\\")\\n 117| distribution_policy = st.text_input(\\\"ausschüttend/thesaurierend optional\\\", key=\\\"equity_add_distribution\\\")\\n 118| index_name = st.text_input(\\\"Index optional\\\", key=\\\"equity_add_index\\\")\\n 119| fund_domicile = st.text_input(\\\"Fondsdomizil optional\\\", key=\\\"equity_add_domicile\\\")\\n 120| benchmark = st.text_input(\\\"Benchmark optional\\\", key=\\\"equity_add_benchmark\\\")\\n 121| confirm = st.checkbox(\\\"Ich bestätige diese einzelne Änderung\\\", key=\\\"equity_add_confirm\\\")\\n 122| selected_account = _selected(options[\\\"accounts\\\"], account_label, _account_label)\\n 123| st.write({\\\"Aktion\\\": \\\"initial_position_snapshot\\\", \\\"Name\\\": name, \\\"ISIN\\\": isin or \\\"\\\", \\\"Ticker\\\": ticker or \\\"\\\", \\\"Währung\\\": currency, \\\"Datum\\\": str(snapshot_date), \\\"Hinweis\\\": \\\"Keine Massenänderung; Speicherung erst nach Bestätigung.\\\"})\\n 124| if st.button(\\\"Bestätigt speichern\\\", key=\\\"equity_add_save\\\", type=\\\"primary\\\"):\\n 125| try:\\n 126| if not selected_account:\\n 127| raise ValueError(\\\"account is required\\\")\\n 128| result = add_equity_initial_snapshot(\\n 129| conn,\\n 130| account_id=selected_account[\\\"account_id\\\"],\\n 131| asset_class=asset_class,\\n 132| name=name,\\n 133| isin=isin,\\n 134| ticker=ticker,\\n 135| exchange=exchange,\\n 136| currency=currency,\\n 137| quantity_text=quantity,\\n 138| cost_basis_original_text=cost_basis,\\n 139| snapshot_date=str(snapshot_date),\\n 140| category=category,\\n 141| note=note,\\n 142| fx_rate_to_chf_text=fx_rate or None,\\n 143| fx_source=fx_source or None,\\n 144| fx_status=fx_status,\\n 145| ter_text=ter or None,\\n 146| distribution_policy=distribution_policy or None,\\n 147| index_name=index_name or None,\\n 148| fund_domicile=fund_domicile or None,\\n 149| benchmark=benchmark or None,\\n 150| confirm=bool(confirm),\\n 151| )\\n 152| st.success(\\\"Initial Snapshot gespeichert und auditierbar erfasst.\\\")\\n 153| st.write({\\\"instrument_id\\\": result.instrument_id, \\\"transaction_id\\\": result.transaction_id, \\\"warnings\\\": result.warnings})\\n 154| except Exception as exc:\\n 155| st.error(f\\\"Speichern abgelehnt: {exc}\\\")\\n 156|\\n 157| def transaction_form(tab, title: str, tx_type: str) -> None:\\n 158| with tab:\\n 159| st.subheader(title)\\n 160| account_label = st.selectbox(\\\"Depot/Konto\\\", account_labels, key=f\\\"equity_{tx_type}_account\\\") if account_labels else None\\n 161| instrument_label = st.selectbox(\\\"Instrument\\\", instrument_labels, key=f\\\"equity_{tx_type}_instrument\\\") if instrument_labels else None\\n 162| date_value = st.date_input(\\\"Datum\\\", key=f\\\"equity_{tx_type}_date\\\")\\n 163| qty_default = \\\"0\\\" if tx_type in {\\\"dividend\\\", \\\"etf_distribution\\\", \\\"fee\\\"} else \\\"\\\"\\n 164| quantity = st.text_input(\\\"Menge als Decimal-Text\\\", value=qty_default, key=f\\\"equity_{tx_type}_qty\\\")\\n 165| gross = st.text_input(\\\"Brutto/Cost/Proceeds Originalwährung\\\", key=f\\\"equity_{tx_type}_gross\\\")\\n 166| currency = st.selectbox(\\\"Währung\\\", [\\\"CHF\\\", \\\"EUR\\\", \\\"USD\\\"], key=f\\\"equity_{tx_type}_currency\\\")\\n 167| fx_rate = st.text_input(\\\"FX-Kurs zu CHF (bei EUR/USD)\\\", key=f\\\"equity_{tx_type}_fx\\\")\\n 168| fx_source = st.text_input(\\\"FX-Quelle\\\", key=f\\\"equity_{tx_type}_fx_source\\\")\\n 169| fx_status = st.selectbox(\\\"FX-Status\\\", [\\\"ok\\\", \\\"missing\\\"], key=f\\\"equity_{tx_type}_fx_status\\\")\\n 170| note = st.text_area(\\\"Notiz / Grund\\\", key=f\\\"equity_{tx_type}_note\\\")\\n 171| confirm = st.checkbox(\\\"Ich bestätige diese Änderung\\\", key=f\\\"equity_{tx_type}_confirm\\\")\\n 172| selected_account = _selected(options[\\\"accounts\\\"], account_label, _account_label)\\n 173| selected_instrument = _selected(options[\\\"instruments\\\"], instrument_label, _instrument_label)\\n 174| st.write({\\\"Aktion\\\": tx_type, \\\"Instrument\\\": instrument_label, \\\"Datum\\\": str(date_value), \\\"FX-Status\\\": fx_status})\\n 175| if st.button(\\\"Bestätigt speichern\\\", key=f\\\"equity_{tx_type}_save\\\"):\\n 176| try:\\n 177| if not selected_account or not selected_instrument:\\n 178| raise ValueError(\\\"account and instrument are required\\\")\\n 179| result = add_equity_transaction(\\n 180| conn,\\n 181| account_id=selected_account[\\\"account_id\\\"],\\n 182| instrument_id=selected_instrument[\\\"instrument_id\\\"],\\n 183| transaction_type=tx_type,\\n 184| trade_date=str(date_value),\\n 185| quantity_text=quantity,\\n 186| gross_amount_original_text=gross,\\n 187| currency=currency,\\n 188| fx_rate_to_chf_text=fx_rate or None,\\n 189| fx_source=fx_source or None,\\n 190| fx_status=fx_status,\\n 191| note=note,\\n 192| confirm=bool(confirm),\\n 193| )\\n 194| st.success(\\\"Transaktion gespeichert und auditierbar erfasst.\\\")\\n 195| st.write({\\\"transaction_id\\\": result.transaction_id, \\\"warnings\\\": result.warnings})\\n 196| except Exception as exc:\\n 197| st.error(f\\\"Speichern abgelehnt: {exc}\\\")\\n 198|\\n 199| transaction_form(tabs[2], \\\"Kauf erfassen\\\", \\\"buy\\\")\\n 200| transaction_form(tabs[3], \\\"Teilverkauf erfassen\\\", \\\"partial_sell\\\")\\n 201| transaction_form(tabs[4], \\\"Vollverkauf erfassen\\\", \\\"full_sell\\\")\\n 202| transaction_form(tabs[5], \\\"Dividende erfassen\\\", \\\"dividend\\\")\\n 203| transaction_form(tabs[6], \\\"ETF-Ausschüttung erfassen\\\", \\\"etf_distribution\\\")\\n 204| transaction_form(tabs[7], \\\"Fee erfassen\\\", \\\"fee\\\")\\n 205| transaction_form(tabs[8], \\\"Korrektur als manual_adjustment\\\", \\\"manual_adjustment\\\")\\n 206|\\n 207| with tabs[9]:\\n 208| st.subheader(\\\"Aktuelle Equity/ETF Übersicht\\\")\\n 209| show_table(st, data.get_positions(conn))\\n 210| st.divider()\\n 211| st.subheader(\\\"Instrument Price Mapping Review\\\")\\n 212| st.caption(\\\"Runtime-Review: Kandidaten ansehen und manuell bestätigen. Keine Live-API und keine Positionsänderung beim Rendern.\\\")\\n 213| review_rows = data.get_instrument_mapping_review(conn)\\n 214| show_table(st, review_rows)\\n 215| candidates = data.get_instrument_mapping_candidates(conn)\\n 216| show_table(st, candidates)\\n 217| candidate_labels = [f\\\"{c['candidate_id']} | {c['candidate_provider']} | {c['candidate_provider_symbol']} | {c['candidate_exchange']} | {c['candidate_currency']} | {c['confidence']} | {c['review_status']}\\\" for c in candidates]\\n 218| selected_candidate_label = st.selectbox(\\\"Mapping-Kandidat auswählen\\\", candidate_labels, key=\\\"mapping_candidate_select\\\") if candidate_labels else None\\n 219| mapping_note = st.text_area(\\\"Bestätigungsnotiz für Mapping-Auswahl\\\", key=\\\"mapping_candidate_note\\\")\\n 220| if st.button(\\\"Ausgewählten Mapping-Kandidaten bestätigen\\\", key=\\\"mapping_candidate_confirm\\\"):\\n 221| try:\\n 222| if not selected_candidate_label:\\n 223| raise ValueError(\\\"candidate is required\\\")\\n 224| candidate_id = selected_candidate_label.split(\\\" | \\\", 1)[0]\\n 225| mapping_id = select_mapping_candidate(conn, candidate_id=candidate_id, note=mapping_note, created_by=\\\"dashboard\\\")\\n 226| st.success(\\\"Mapping-Kandidat bestätigt; Audit-Log geschrieben.\\\")\\n 227| st.write({\\\"mapping_id\\\": mapping_id})\\n 228| except Exception as exc:\\n 229| st.error(f\\\"Mapping-Auswahl abgelehnt: {exc}\\\")\\n 230| if st.button(\\\"Ausgewählten Mapping-Kandidaten ablehnen\\\", key=\\\"mapping_candidate_reject\\\"):\\n 231| try:\\n 232| if not selected_candidate_label:\\n 233| raise ValueError(\\\"candidate is required\\\")\\n 234| candidate_id = selected_candidate_label.split(\\\" | \\\", 1)[0]\\n 235| reject_mapping_candidate(conn, candidate_id=candidate_id, note=mapping_note, created_by=\\\"dashboard\\\")\\n 236| st.success(\\\"Mapping-Kandidat abgelehnt; Audit-Log geschrieben.\\\")\\n 237| except Exception as exc:\\n 238| st.error(f\\\"Mapping-Ablehnung abgelehnt: {exc}\\\")\\n 239| st.caption(\\\"Manuell erfassen: neuen Katalogeintrag im Tab 'Instrument Search / Add Position' speichern. Keine Portfolio-Transaktion wird durch Mapping Review geändert.\\\")\\n 240| st.divider()\\n 241| st.subheader(\\\"FX Override Review\\\")\\n 242| st.caption(\\\"Historische FX-Rates nur manuell mit Quelle/Notiz erfassen. Keine Rates ohne bewusste Speicherung.\\\")\\n 243| fx_rows = data.get_fx_override_requirements(conn)\\n 244| show_table(st, fx_rows)\\n 245| fx_labels = [f\\\"{r['base_currency']}/{r['quote_currency']} {r['rate_date']} ({r['fx_status']})\\\" for r in fx_rows]\\n 246| fx_label = st.selectbox(\\\"FX-Paar/Datum\\\", fx_labels, key=\\\"fx_override_select\\\") if fx_labels else None\\n 247| fx_rate = st.text_input(\\\"FX-Rate zu CHF\\\", key=\\\"fx_override_rate\\\")\\n 248| fx_note = st.text_area(\\\"FX-Quelle/Notiz (Pflicht)\\\", key=\\\"fx_override_note\\\")\\n 249| if st.button(\\\"Manual FX Override speichern\\\", key=\\\"fx_override_save\\\"):\\n 250| try:\\n 251| if not fx_label:\\n 252| raise ValueError(\\\"fx pair/date is required\\\")\\n 253| pair, date_part = fx_label.split(\\\" \\\", 1)\\n 254| base, quote = pair.split(\\\"/\\\", 1)\\n 255| rate_date = date_part.split(\\\" \\\", 1)[0]\\n 256| set_manual_fx_override(conn, base_currency=base, quote_currency=quote, rate_date=rate_date, rate=Decimal(fx_rate), note=fx_note, created_by=\\\"dashboard\\\")\\n 257| st.success(\\\"Manual FX Override gespeichert und auditierbar erfasst.\\\")\\n 258| except Exception as exc:\\n 259| st.error(f\\\"FX Override abgelehnt: {exc}\\\")\\n 260|\", \"total_lines\": 259, \"file_size\": 18367, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_4J7jK8wim6iwQJohvyQ8HRIX"
},
{
"role": "tool",
"name": "read_file",
"content": "{\"content\": \" 250| FROM alerts\\n 251| ORDER BY CASE priority WHEN 'kritisch' THEN 0 WHEN 'warnung' THEN 1 ELSE 2 END, status, created_at DESC\\n 252| \\\"\\\"\\\"\\n 253| ).fetchall())\\n 254|\\n 255|\\n 256|def get_audit_events(conn: Connection, limit: int = 200) -> list[dict[str, str]]:\\n 257| rows = conn.execute(\\n 258| \\\"\\\"\\\"\\n 259| SELECT timestamp, source, action, entity_type, entity_id, old_values_json, new_values_json,\\n 260| confirmed, created_by, quality_status\\n 261| FROM audit_log ORDER BY timestamp DESC LIMIT ?\\n 262| \\\"\\\"\\\", (limit,)\\n 263| ).fetchall()\\n 264| out: list[dict[str, str]] = []\\n 265| for row in rows:\\n 266| item = {k: (\\\"\\\" if row[k] is None else str(row[k])) for k in row.keys()}\\n 267| for key in (\\\"old_values_json\\\", \\\"new_values_json\\\"):\\n 268| if item[key]:\\n 269| try:\\n 270| item[key] = json.dumps(json.loads(item[key]), ensure_ascii=False, indent=2, sort_keys=True)\\n 271| except json.JSONDecodeError:\\n 272| pass\\n 273| out.append(item)\\n 274| return out\\n 275|\\n 276|\\n 277|def get_data_quality(conn: Connection) -> list[dict[str, str]]:\\n 278| items: list[dict[str, str]] = []\\n 279| checks = [\\n 280| (\\\"fehlende FX\\\", \\\"SELECT COUNT(*) AS c FROM transactions WHERE fx_status='missing'\\\", \\\"kritisch\\\"),\\n 281| (\\\"fehlende/stale FX Alerts\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id IN ('missing_fx','stale_fx','historical_fx_unavailable','manual_override_required')\\\", \\\"kritisch\\\"),\\n 282| (\\\"historical FX unavailable\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='historical_fx_unavailable'\\\", \\\"kritisch\\\"),\\n 283| (\\\"manual override required\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='manual_override_required'\\\", \\\"kritisch\\\"),\\n 284| (\\\"fehlende Provider-Symbole\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='missing_provider_symbol'\\\", \\\"warnung\\\"),\\n 285| (\\\"provider lookup unavailable\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='provider_lookup_unavailable'\\\", \\\"warnung\\\"),\\n 286| (\\\"ambiguous provider mapping\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='ambiguous_provider_mapping'\\\", \\\"warnung\\\"),\\n 287| (\\\"instrument status unknown\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='instrument_status_unknown'\\\", \\\"warnung\\\"),\\n 288| (\\\"manual FX override required\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id IN ('manual_override_required','manual_fx_override_required')\\\", \\\"kritisch\\\"),\\n 289| (\\\"fehlende Market Prices\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='missing_market_price'\\\", \\\"warnung\\\"),\\n 290| (\\\"stale Market Prices\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='stale_market_price'\\\", \\\"warnung\\\"),\\n 291| (\\\"ambiguous Instrument Mapping\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='ambiguous_instrument_mapping'\\\", \\\"warnung\\\"),\\n 292| (\\\"price currency mismatch\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='price_currency_mismatch'\\\", \\\"warnung\\\"),\\n 293| (\\\"hedge status unknown\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='hedge_status_unknown'\\\", \\\"warnung\\\"),\\n 294| (\\\"stale valuation\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='stale_valuation'\\\", \\\"warnung\\\"),\\n 295| (\\\"corporate action suspected\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='corporate_action_suspected'\\\", \\\"warnung\\\"),\\n 296| (\\\"split/corporate action review\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='split_or_corporate_action_review_required'\\\", \\\"warnung\\\"),\\n 297| (\\\"delisted/suspended\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='delisted_or_suspended'\\\", \\\"warnung\\\"),\\n 298| (\\\"snapshot_only Alerts\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='snapshot_only'\\\", \\\"info\\\"),\\n 299| (\\\"cost_basis_uncertain Alerts\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='cost_basis_uncertain'\\\", \\\"warnung\\\"),\\n 300| (\\\"fehlende CoinGecko-ID\\\", \\\"SELECT COUNT(*) AS c FROM crypto_assets WHERE coingecko_id IS NULL OR coingecko_id='' \\\", \\\"warnung\\\"),\\n 301| (\\\"fehlende Crypto-Preise\\\", \\\"SELECT COUNT(*) AS c FROM crypto_assets ca LEFT JOIN crypto_prices cp ON cp.asset_id=ca.asset_id WHERE cp.crypto_price_id IS NULL\\\", \\\"warnung\\\"),\\n 302| (\\\"fehlende ISIN\\\", \\\"SELECT COUNT(*) AS c FROM instrument_mappings WHERE asset_class IN ('equity','etf') AND (isin IS NULL OR isin='') AND mapping_status!='ignored'\\\", \\\"warnung\\\"),\\n 303| (\\\"Catalog Instrumente ohne ISIN\\\", \\\"SELECT COUNT(*) AS c FROM instrument_catalog_entries WHERE asset_class IN ('equity','stock','etf') AND (isin IS NULL OR isin='')\\\", \\\"warnung\\\"),\\n 304| (\\\"Catalog Ticker ohne Exchange\\\", \\\"SELECT COUNT(*) AS c FROM instrument_catalog_entries WHERE COALESCE(ticker,'')<>'' AND COALESCE(exchange,'')=''\\\", \\\"warnung\\\"),\\n 305| (\\\"Catalog mehrere Listings gleicher ISIN\\\", \\\"SELECT COUNT(*) AS c FROM (SELECT isin FROM instrument_catalog_entries WHERE COALESCE(isin,'')<>'' GROUP BY isin HAVING COUNT(DISTINCT COALESCE(exchange,'') || ':' || COALESCE(trading_currency,''))>1)\\\", \\\"info\\\"),\\n 306| (\\\"Manual Review needed\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id='manual_review_needed'\\\", \\\"warnung\\\"),\\n 307| (\\\"Mapping-Kandidaten unbestätigt\\\", \\\"SELECT COUNT(*) AS c FROM instrument_price_mapping_candidates WHERE review_status IN ('proposed','needs_manual_review')\\\", \\\"warnung\\\"),\\n 308| (\\\"Instrumente mit mehreren Mapping-Kandidaten\\\", \\\"SELECT COUNT(*) AS c FROM (SELECT instrument_id FROM instrument_price_mapping_candidates WHERE review_status IN ('proposed','needs_manual_review') GROUP BY instrument_id HAVING COUNT(*) > 1)\\\", \\\"warnung\\\"),\\n 309| (\\\"Valuation not ready\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id IN ('missing_provider_symbol','missing_market_price','missing_fx','hedge_status_unknown','instrument_status_unknown')\\\", \\\"warnung\\\"),\\n 310| (\\\"fehlende FX in Import-Reviews\\\", \\\"SELECT COUNT(*) AS c FROM instrument_mappings WHERE quality_flags_json LIKE '%missing_fx%' AND mapping_status!='ignored'\\\", \\\"warnung\\\"),\\n 311| (\\\"snapshot_only Positionen\\\", \\\"SELECT COUNT(*) AS c FROM instrument_mappings WHERE quality_flags_json LIKE '%snapshot_only%' AND mapping_status!='ignored'\\\", \\\"info\\\"),\\n 312| (\\\"cost_basis_uncertain\\\", \\\"SELECT COUNT(*) AS c FROM instrument_mappings WHERE quality_flags_json LIKE '%cost_basis_uncertain%' AND mapping_status!='ignored'\\\", \\\"warnung\\\"),\\n 313| (\\\"aktive Alerts\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active'\\\", \\\"warnung\\\"),\\n 314| (\\\"resolved Alerts\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='resolved'\\\", \\\"ok\\\"),\\n 315| (\\\"alte aktive Alerts\\\", \\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND last_seen_at < datetime('now', '-7 days')\\\", \\\"info\\\"),\\n 316| ]\\n 317| for label, sql, severity in checks:\\n 318| row = conn.execute(sql).fetchone()\\n 319| count = int(row[\\\"c\\\"] or 0) if row else 0\\n 320| sev = severity if count else \\\"ok\\\"\\n 321| items.append({\\\"check\\\": label, \\\"count\\\": str(count), \\\"severity\\\": sev})\\n 322| for flag_row in get_review_quality_flag_counts(conn):\\n 323| count = int(flag_row[\\\"open_items\\\"] or 0)\\n 324| items.append({\\\"check\\\": f\\\"Review Flag: {flag_row['quality_flag']}\\\", \\\"count\\\": str(count), \\\"severity\\\": \\\"warnung\\\" if count else \\\"ok\\\"})\\n 325| for ready in get_review_readiness_counts(conn):\\n 326| count = int(ready[\\\"count\\\"] or 0)\\n 327| sev = \\\"ok\\\" if ready[\\\"readiness_status\\\"] in {\\\"ready_for_import\\\", \\\"ignored\\\"} else (\\\"warnung\\\" if count else \\\"ok\\\")\\n 328| items.append({\\\"check\\\": f\\\"Review Readiness: {ready['readiness_status']}\\\", \\\"count\\\": str(count), \\\"severity\\\": sev})\\n 329| for source in get_ready_for_import_by_source(conn):\\n 330| if int(source[\\\"total\\\"] or 0) and int(source[\\\"ready_for_import\\\"] or 0) == 0:\\n 331| items.append({\\\"check\\\": f\\\"Quelle ohne ready_for_import: {source['source_platform']}\\\", \\\"count\\\": source[\\\"total\\\"], \\\"severity\\\": \\\"warnung\\\"})\\n 332| missing_snapshot = conn.execute(\\\"SELECT COUNT(*) AS c FROM broker_import_dry_runs WHERE snapshot_date_status='missing'\\\").fetchone()\\n 333| count = int(missing_snapshot[\\\"c\\\"] or 0) if missing_snapshot else 0\\n 334| items.append({\\\"check\\\": \\\"Dry Runs ohne Snapshot Date\\\", \\\"count\\\": str(count), \\\"severity\\\": \\\"warnung\\\" if count else \\\"ok\\\"})\\n 335| return items\\n 336|\\n 337|\\n 338|def get_instrument_catalog_entries(conn: Connection, query: str | None = None, asset_class: str | None = None) -> list[dict[str, str]]:\\n 339| if query:\\n 340| from jarvis_finance.market_data.catalog import search_local_catalog\\n 341| return [r.__dict__ for r in search_local_catalog(conn, query, asset_class)]\\n 342| sql = \\\"\\\"\\\"\\n 343| SELECT catalog_entry_id, asset_class, name, isin, ticker, exchange, trading_currency,\\n 344| instrument_currency, provider, provider_symbol, provider_market, hedge_status,\\n 345| instrument_status, valuation_policy, source, source_confidence, last_verified_at\\n 346| FROM instrument_catalog_entries\\n 347| \\\"\\\"\\\"\\n 348| params: list[object] = []\\n 349| if asset_class:\\n 350| sql += \\\" WHERE asset_class=?\\\"\\n 351| params.append(asset_class.lower())\\n 352| sql += \\\" ORDER BY name, exchange, trading_currency LIMIT 100\\\"\\n 353| return rowdicts(conn.execute(sql, tuple(params)).fetchall())\\n 354|\\n 355|\\n 356|def get_instrument_catalog_summary(conn: Connection) -> dict[str, str]:\\n 357| total = conn.execute(\\\"SELECT COUNT(*) AS c FROM instrument_catalog_entries\\\").fetchone()[\\\"c\\\"]\\n 358| multi = conn.execute(\\\"SELECT COUNT(*) AS c FROM (SELECT isin FROM instrument_catalog_entries WHERE COALESCE(isin,'')<>'' GROUP BY isin HAVING COUNT(DISTINCT COALESCE(exchange,'') || ':' || COALESCE(trading_currency,''))>1)\\\").fetchone()[\\\"c\\\"]\\n 359| no_provider = conn.execute(\\\"SELECT COUNT(*) AS c FROM instrument_catalog_entries WHERE COALESCE(provider_symbol,'')='' \\\").fetchone()[\\\"c\\\"]\\n 360| manual = conn.execute(\\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id IN ('manual_review_needed','missing_provider_symbol','ambiguous_provider_mapping')\\\").fetchone()[\\\"c\\\"]\\n 361| return {\\\"catalog_entries\\\": str(total or 0), \\\"multiple_listings\\\": str(multi or 0), \\\"without_provider_symbol\\\": str(no_provider or 0), \\\"manual_review_required\\\": str(manual or 0)}\\n 362|\\n 363|\\n 364|def get_instrument_mapping_review(conn: Connection) -> list[dict[str, str]]:\\n 365| rows = conn.execute(\\n 366| \\\"\\\"\\\"\\n 367| SELECT i.instrument_id, i.isin, i.name, i.ticker, i.exchange, i.currency,\\n 368| i.hedge_status, i.instrument_status, i.valuation_policy,\\n 369| COALESCE(m.mapping_status, 'missing_provider_symbol') AS mapping_status,\\n 370| COALESCE(m.provider, '') AS provider,\\n 371| COALESCE(m.provider_symbol, '') AS provider_symbol,\\n 372| COUNT(c.candidate_id) AS candidate_count\\n 373| FROM instruments i\\n 374| JOIN transactions t ON t.instrument_id=i.instrument_id\\n 375| LEFT JOIN instrument_price_mappings m ON m.instrument_id=i.instrument_id AND m.mapping_status='mapped'\\n 376| LEFT JOIN instrument_price_mapping_candidates c ON c.instrument_id=i.instrument_id AND c.review_status IN ('proposed','needs_manual_review')\\n 377| WHERE t.transaction_type='initial_position_snapshot'\\n 378| AND t.source_type='broker_import_reviewed_snapshot'\\n 379| AND COALESCE(t.is_voided,0)=0\\n 380| GROUP BY i.instrument_id\\n 381| ORDER BY i.isin, i.name\\n 382| \\\"\\\"\\\"\\n 383| ).fetchall()\\n 384| return rowdicts(rows)\\n 385|\\n 386|\\n 387|def get_instrument_mapping_candidates(conn: Connection, instrument_id: str | None = None) -> list[dict[str, str]]:\\n 388| if instrument_id:\\n 389| rows = conn.execute(\\n 390| \\\"\\\"\\\"\\n 391| SELECT candidate_id, instrument_id, isin, candidate_provider, candidate_provider_symbol,\\n 392| candidate_exchange, candidate_currency, candidate_name, candidate_asset_class,\\n 393| candidate_is_hedged, candidate_hedged_to_currency, candidate_hedge_status,\\n 394| candidate_instrument_status, candidate_valuation_policy, confidence,\\n 395| evidence_source, evidence_note, review_status, created_at\\n 396| FROM instrument_price_mapping_candidates WHERE instrument_id=?\\n 397| ORDER BY CASE confidence WHEN 'high' THEN 0 WHEN 'medium' THEN 1 ELSE 2 END, candidate_provider\\n 398| \\\"\\\"\\\",\\n 399| (instrument_id,),\\n 400| ).fetchall()\\n 401| else:\\n 402| rows = conn.execute(\\n 403| \\\"\\\"\\\"\\n 404| SELECT candidate_id, instrument_id, isin, candidate_provider, candidate_provider_symbol,\\n 405| candidate_exchange, candidate_currency, candidate_name, candidate_asset_class,\\n 406| candidate_is_hedged, candidate_hedged_to_currency, candidate_hedge_status,\\n 407| candidate_instrument_status, candidate_valuation_policy, confidence,\\n 408| evidence_source, evidence_note, review_status, created_at\\n 409| FROM instrument_price_mapping_candidates\\n 410| ORDER BY instrument_id, CASE confidence WHEN 'high' THEN 0 WHEN 'medium' THEN 1 ELSE 2 END, candidate_provider\\n 411| \\\"\\\"\\\"\\n 412| ).fetchall()\\n 413| return rowdicts(rows)\\n 414|\\n 415|\\n 416|def get_fx_override_requirements(conn: Connection) -> list[dict[str, str]]:\\n 417| rows = conn.execute(\\n 418| \\\"\\\"\\\"\\n 419| SELECT t.currency_original AS base_currency, 'CHF' AS quote_currency, t.trade_date AS rate_date,\\n 420| COUNT(DISTINCT t.instrument_id) AS instrument_count,\\n 421| CASE WHEN fr.fx_rate_id IS NULL THEN 'missing_fx' ELSE fr.quality_status END AS fx_status\\n 422| FROM transactions t\\n 423| LEFT JOIN fx_rates fr ON fr.base_currency=t.currency_original AND fr.quote_currency='CHF' AND fr.rate_date=t.trade_date\\n 424| WHERE t.transaction_type='initial_position_snapshot'\\n 425| AND t.source_type='broker_import_reviewed_snapshot'\\n 426| AND COALESCE(t.is_voided,0)=0\\n 427| AND t.currency_original IS NOT NULL\\n 428| AND t.currency_original <> 'CHF'\\n 429| GROUP BY t.currency_original, t.trade_date, fx_status\\n 430| ORDER BY t.currency_original, t.trade_date\\n 431| \\\"\\\"\\\"\\n 432| ).fetchall()\\n 433| return rowdicts(rows)\\n 434|\\n 435|\\n 436|def get_import_wizard_summary(conn: Connection) -> dict[str, str]:\\n 437| from jarvis_finance.imports.broker_mapping import build_import_wizard_summary\\n 438|\\n 439| return build_import_wizard_summary(conn)\\n 440|\\n 441|\\n 442|def get_manual_review_items(conn: Connection) -> list[dict[str, str]]:\\n 443| from jarvis_finance.imports.broker_mapping import get_manual_review_queue\\n 444|\\n 445| return get_manual_review_queue(conn)\\n 446|\\n 447|\\n 448|def get_broker_dry_runs(conn: Connection, limit: int = 20) -> list[dict[str, str]]:\\n 449| from jarvis_finance.imports.broker_mapping import get_dry_run_sessions\\n 450|\\n 451| return get_dry_run_sessions(conn, limit=limit)\\n 452|\\n 453|\\n 454|def get_safe_mode_status(conn: Connection) -> dict[str, str]:\\n 455| backup = conn.execute(\\\"SELECT created_at FROM audit_log WHERE action LIKE '%backup%' ORDER BY created_at DESC LIMIT 1\\\").fetchone()\\n 456| return {\\n 457| \\\"db_mode\\\": \\\"Runtime\\\",\\n 458| \\\"write_mode\\\": \\\"Read-only\\\",\\n 459| \\\"last_backup_at\\\": backup[\\\"created_at\\\"] if backup else \\\"nicht verfügbar\\\",\\n 460| \\\"git_safety_status\\\": \\\"zuletzt OK / CLI prüfen\\\",\\n 461| \\\"data_location\\\": \\\"Echte Daten liegen außerhalb Git\\\",\\n 462| }\\n 463|\\n 464|\\n 465|def get_broker_review_items(conn: Connection, limit: int = 100, **filters) -> list[dict[str, str]]:\\n 466| from jarvis_finance.imports.broker_mapping import get_broker_review_items as _items\\n 467|\\n 468| return _items(conn, limit=limit, **filters)\\n 469|\\n 470|\\n 471|def get_review_readiness_counts(conn: Connection) -> list[dict[str, str]]:\\n 472| from jarvis_finance.imports.broker_mapping import get_review_readiness_counts as _counts\\n 473|\\n 474| return _counts(conn)\\n 475|\\n 476|\\n 477|def get_ready_for_import_by_source(conn: Connection) -> list[dict[str, str]]:\\n 478| from jarvis_finance.imports.broker_mapping import get_ready_for_import_by_source as _counts\\n 479|\\n 480| return _counts(conn)\\n 481|\\n 482|\\n 483|def get_review_quality_flag_counts(conn: Connection) -> list[dict[str, str]]:\\n 484| from jarvis_finance.imports.broker_mapping import aggregate_review_quality_flags\\n 485|\\n 486| return [{\\\"quality_flag\\\": k, \\\"open_items\\\": str(v)} for k, v in sorted(aggregate_review_quality_flags(conn).items())]\\n 487|\\n 488|\\n 489|def get_command_center_summary(conn: Connection) -> dict[str, str]:\\n 490| cash_rows = get_cash_overview(conn)\\n 491| crypto_rows = get_crypto_overview(conn)\\n 492| cash_total = sum(d(r[\\\"amount_chf\\\"]) for r in cash_rows if r[\\\"amount_chf\\\"])\\n 493| crypto_total = sum(d(r[\\\"market_value_chf\\\"]) for r in crypto_rows if r[\\\"market_value_chf\\\"])\\n 494| alert_counts = conn.execute(\\\"SELECT priority, COUNT(*) AS c FROM alerts WHERE status='active' GROUP BY priority\\\").fetchall()\\n 495| quality = get_data_quality(conn)\\n 496| return {\\n 497| \\\"base_currency\\\": \\\"CHF\\\",\\n 498| \\\"cash_total_chf\\\": dec_text(cash_total, \\\"0.01\\\"),\\n 499| \\\"crypto_total_chf\\\": dec_text(crypto_total, \\\"0.01\\\"),\\n 500| \\\"total_value_chf\\\": dec_text(cash_total + crypto_total, \\\"0.01\\\"),\\n 501| \\\"active_alerts\\\": \\\", \\\".join(f\\\"{r['priority']}: {r['c']}\\\" for r in alert_counts) or \\\"0\\\",\\n 502| \\\"data_quality_status\\\": \\\"kritisch\\\" if any(i[\\\"severity\\\"] == \\\"kritisch\\\" and i[\\\"count\\\"] != \\\"0\\\" for i in quality) else (\\\"warnung\\\" if any(i[\\\"severity\\\"] == \\\"warnung\\\" and i[\\\"count\\\"] != \\\"0\\\" for i in quality) else \\\"ok\\\"),\\n 503| \\\"crypto_price_data_as_of\\\": max((r[\\\"fetched_at\\\"] for r in crypto_rows if r.get(\\\"fetched_at\\\")), default=\\\"\\\"),\\n 504| }\\n 505|\", \"total_lines\": 504, \"file_size\": 29037, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
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"content": "{\"content\": \" 1|from __future__ import annotations\\n 2|\\n 3|import hashlib\\n 4|from datetime import datetime, timezone\\n 5|from sqlite3 import Connection\\n 6|\\n 7|from .schema import INITIAL_SCHEMA_SQL\\n 8|\\n 9|MIGRATION_VERSION = 13\\n 10|MIGRATION_NAME = \\\"013_public_instrument_lookup_candidates\\\"\\n 11|\\n 12|INSTRUMENT_OPTIONAL_COLUMNS = {\\n 13| \\\"position_category\\\": \\\"TEXT\\\",\\n 14| \\\"ter\\\": \\\"TEXT\\\",\\n 15| \\\"distribution_policy\\\": \\\"TEXT\\\",\\n 16| \\\"index_name\\\": \\\"TEXT\\\",\\n 17| \\\"fund_domicile\\\": \\\"TEXT\\\",\\n 18| \\\"benchmark\\\": \\\"TEXT\\\",\\n 19| \\\"is_currency_hedged\\\": \\\"INTEGER NOT NULL DEFAULT 0\\\",\\n 20| \\\"hedged_to_currency\\\": \\\"TEXT\\\",\\n 21| \\\"hedge_status\\\": \\\"TEXT NOT NULL DEFAULT 'unknown'\\\",\\n 22| \\\"base_exposure_currency\\\": \\\"TEXT\\\",\\n 23| \\\"trading_currency\\\": \\\"TEXT\\\",\\n 24| \\\"instrument_status\\\": \\\"TEXT NOT NULL DEFAULT 'unknown'\\\",\\n 25| \\\"valuation_policy\\\": \\\"TEXT NOT NULL DEFAULT 'live_price'\\\",\\n 26| \\\"corporate_action_status\\\": \\\"TEXT NOT NULL DEFAULT 'not_checked'\\\",\\n 27| \\\"split_or_corporate_action_review_required\\\": \\\"INTEGER NOT NULL DEFAULT 0\\\",\\n 28|}\\n 29|\\n 30|TEXT_AFFINITY_COLUMNS = {\\n 31| \\\"transactions\\\": {\\\"quantity\\\", \\\"price_original\\\", \\\"gross_amount_original\\\", \\\"fee_original\\\", \\\"tax_original\\\", \\\"net_amount_original\\\", \\\"fx_rate_to_chf\\\", \\\"gross_amount_chf\\\", \\\"fee_chf\\\", \\\"tax_chf\\\", \\\"net_amount_chf\\\"},\\n 32| \\\"crypto_holdings\\\": {\\\"quantity\\\", \\\"legacy_snapshot_value_original\\\", \\\"legacy_snapshot_value_chf\\\"},\\n 33| \\\"crypto_transactions\\\": {\\\"quantity\\\", \\\"price_original\\\", \\\"gross_amount_original\\\", \\\"fee_quantity\\\", \\\"fee_original\\\", \\\"fx_rate_to_chf\\\", \\\"amount_chf\\\"},\\n 34| \\\"crypto_prices\\\": {\\\"price\\\", \\\"market_cap\\\", \\\"volume_24h\\\", \\\"change_24h_pct\\\"},\\n 35| \\\"fx_rates\\\": {\\\"rate\\\"},\\n 36| \\\"market_prices\\\": {\\\"open\\\", \\\"high\\\", \\\"low\\\", \\\"close\\\", \\\"adjusted_close\\\"},\\n 37|}\\n 38|\\n 39|\\n 40|def utc_now() -> str:\\n 41| return datetime.now(timezone.utc).isoformat()\\n 42|\\n 43|\\n 44|def checksum_sql(sql: str) -> str:\\n 45| return hashlib.sha256(sql.encode(\\\"utf-8\\\")).hexdigest()\\n 46|\\n 47|\\n 48|def get_schema_version(conn: Connection) -> int:\\n 49| row = conn.execute(\\\"SELECT MAX(version) AS version FROM schema_migrations\\\").fetchone()\\n 50| return int(row[\\\"version\\\"] or 0) if row else 0\\n 51|\\n 52|\\n 53|def _table_columns(conn: Connection, table: str) -> dict[str, str]:\\n 54| return {row[\\\"name\\\"]: (row[\\\"type\\\"] or \\\"\\\") for row in conn.execute(f\\\"PRAGMA table_info({table})\\\").fetchall()}\\n 55|\\n 56|\\n 57|def _add_missing_instrument_columns(conn: Connection) -> None:\\n 58| existing = _table_columns(conn, \\\"instruments\\\")\\n 59| for name, col_type in INSTRUMENT_OPTIONAL_COLUMNS.items():\\n 60| if name not in existing:\\n 61| conn.execute(f\\\"ALTER TABLE instruments ADD COLUMN {name} {col_type}\\\")\\n 62|\\n 63|\\n 64|def _rebuild_table_with_text_columns(conn: Connection, table: str, text_columns: set[str]) -> None:\\n 65| cols = conn.execute(f\\\"PRAGMA table_info({table})\\\").fetchall()\\n 66| if not cols:\\n 67| return\\n 68| needs_rebuild = any(row[\\\"name\\\"] in text_columns and (row[\\\"type\\\"] or \\\"\\\").upper() != \\\"TEXT\\\" for row in cols)\\n 69| if not needs_rebuild:\\n 70| return\\n 71| tmp = f\\\"{table}__text_migration\\\"\\n 72| col_defs: list[str] = []\\n 73| pk_cols = [row[\\\"name\\\"] for row in cols if row[\\\"pk\\\"]]\\n 74| for row in cols:\\n 75| name = row[\\\"name\\\"]\\n 76| col_type = \\\"TEXT\\\" if name in text_columns else (row[\\\"type\\\"] or \\\"TEXT\\\")\\n 77| parts = [name, col_type]\\n 78| if row[\\\"pk\\\"] and len(pk_cols) == 1:\\n 79| parts.append(\\\"PRIMARY KEY\\\")\\n 80| if row[\\\"notnull\\\"]:\\n 81| parts.append(\\\"NOT NULL\\\")\\n 82| if row[\\\"dflt_value\\\"] is not None:\\n 83| parts.append(f\\\"DEFAULT {row['dflt_value']}\\\")\\n 84| col_defs.append(\\\" \\\".join(parts))\\n 85| if len(pk_cols) > 1:\\n 86| col_defs.append(\\\"PRIMARY KEY (\\\" + \\\", \\\".join(pk_cols) + \\\")\\\")\\n 87| conn.execute(f\\\"DROP TABLE IF EXISTS {tmp}\\\")\\n 88| conn.execute(f\\\"CREATE TABLE {tmp} (\\\" + \\\", \\\".join(col_defs) + \\\")\\\")\\n 89| names = [row[\\\"name\\\"] for row in cols]\\n 90| select_exprs = [f\\\"CAST({name} AS TEXT)\\\" if name in text_columns else name for name in names]\\n 91| conn.execute(f\\\"INSERT INTO {tmp} ({', '.join(names)}) SELECT {', '.join(select_exprs)} FROM {table}\\\")\\n 92| conn.execute(f\\\"DROP TABLE {table}\\\")\\n 93| conn.execute(f\\\"ALTER TABLE {tmp} RENAME TO {table}\\\")\\n 94| if table == \\\"crypto_holdings\\\":\\n 95| conn.execute(\\\"CREATE UNIQUE INDEX IF NOT EXISTS idx_crypto_holdings_asset_wallet ON crypto_holdings(asset_id, wallet_id)\\\")\\n 96|\\n 97|\\n 98|def _add_missing_columns(conn: Connection, table: str, columns: dict[str, str]) -> None:\\n 99| existing = _table_columns(conn, table)\\n 100| for name, col_type in columns.items():\\n 101| if name not in existing:\\n 102| conn.execute(f\\\"ALTER TABLE {table} ADD COLUMN {name} {col_type}\\\")\\n 103|\\n 104|\\n 105|def _create_broker_bank_mapping_tables(conn: Connection) -> None:\\n 106| conn.executescript(\\n 107| \\\"\\\"\\\"\\n 108| CREATE TABLE IF NOT EXISTS instrument_mappings (\\n 109| mapping_id TEXT PRIMARY KEY,\\n 110| source_name TEXT,\\n 111| source_platform TEXT NOT NULL,\\n 112| source_account TEXT,\\n 113| source_label TEXT NOT NULL,\\n 114| normalized_name TEXT NOT NULL,\\n 115| isin TEXT,\\n 116| ticker TEXT,\\n 117| exchange TEXT,\\n 118| currency TEXT,\\n 119| asset_class TEXT NOT NULL DEFAULT 'other',\\n 120| source_instrument_name TEXT,\\n 121| source_isin TEXT,\\n 122| source_ticker TEXT,\\n 123| source_exchange TEXT,\\n 124| source_currency TEXT,\\n 125| instrument_id TEXT REFERENCES instruments(instrument_id),\\n 126| mapping_status TEXT NOT NULL DEFAULT 'needs_manual_review',\\n 127| confidence TEXT NOT NULL DEFAULT '0',\\n 128| quality_flags_json TEXT,\\n 129| notes TEXT,\\n 130| created_at TEXT NOT NULL,\\n 131| updated_at TEXT\\n 132| );\\n 133|\\n 134| CREATE TABLE IF NOT EXISTS platform_account_mappings (\\n 135| mapping_id TEXT PRIMARY KEY,\\n 136| source_name TEXT,\\n 137| source_platform TEXT NOT NULL,\\n 138| source_platform_label TEXT,\\n 139| source_account_label TEXT NOT NULL,\\n 140| normalized_platform TEXT NOT NULL,\\n 141| normalized_account_name TEXT NOT NULL,\\n 142| source_account_type TEXT,\\n 143| account_type TEXT NOT NULL DEFAULT 'other',\\n 144| source_currency TEXT,\\n 145| currency TEXT,\\n 146| platform_id TEXT REFERENCES platforms(platform_id),\\n 147| account_id TEXT REFERENCES accounts(account_id),\\n 148| internal_platform_id TEXT REFERENCES platforms(platform_id),\\n 149| internal_account_id TEXT REFERENCES accounts(account_id),\\n 150| mapping_status TEXT NOT NULL DEFAULT 'needs_manual_review',\\n 151| quality_flags_json TEXT,\\n 152| notes TEXT,\\n 153| created_at TEXT NOT NULL,\\n 154| updated_at TEXT\\n 155| );\\n 156|\\n 157| CREATE TABLE IF NOT EXISTS broker_import_dry_runs (\\n 158| dry_run_id TEXT PRIMARY KEY,\\n 159| source_name TEXT,\\n 160| source_platform TEXT NOT NULL,\\n 161| source_file_label TEXT,\\n 162| source_file_type TEXT NOT NULL,\\n 163| source_hash TEXT,\\n 164| source_filename_hash TEXT,\\n 165| detected_snapshot_date TEXT,\\n 166| snapshot_date_status TEXT NOT NULL DEFAULT 'missing',\\n 167| detected_sections_json TEXT NOT NULL,\\n 168| field_coverage_json TEXT,\\n 169| rows_total INTEGER NOT NULL DEFAULT 0,\\n 170| rows_position_candidates INTEGER NOT NULL DEFAULT 0,\\n 171| rows_cash_candidates INTEGER NOT NULL DEFAULT 0,\\n 172| candidate_positions INTEGER NOT NULL DEFAULT 0,\\n 173| candidate_cash_rows INTEGER NOT NULL DEFAULT 0,\\n 174| mapped_positions INTEGER NOT NULL DEFAULT 0,\\n 175| blocked_positions INTEGER NOT NULL DEFAULT 0,\\n 176| warnings_count INTEGER NOT NULL DEFAULT 0,\\n 177| errors_count INTEGER NOT NULL DEFAULT 0,\\n 178| quality_flags_json TEXT NOT NULL,\\n 179| summary_json TEXT NOT NULL DEFAULT '{}',\\n 180| created_at TEXT NOT NULL,\\n 181| notes TEXT\\n 182| );\\n 183| \\\"\\\"\\\"\\n 184| )\\n 185| _add_missing_columns(conn, \\\"instrument_mappings\\\", {\\n 186| \\\"source_name\\\": \\\"TEXT\\\",\\n 187| \\\"source_platform\\\": \\\"TEXT\\\",\\n 188| \\\"source_account\\\": \\\"TEXT\\\",\\n 189| \\\"source_label\\\": \\\"TEXT\\\",\\n 190| \\\"normalized_name\\\": \\\"TEXT\\\",\\n 191| \\\"isin\\\": \\\"TEXT\\\",\\n 192| \\\"ticker\\\": \\\"TEXT\\\",\\n 193| \\\"exchange\\\": \\\"TEXT\\\",\\n 194| \\\"currency\\\": \\\"TEXT\\\",\\n 195| \\\"asset_class\\\": \\\"TEXT DEFAULT 'other'\\\",\\n 196| \\\"confidence\\\": \\\"TEXT DEFAULT '0'\\\",\\n 197| })\\n 198| _add_missing_columns(conn, \\\"platform_account_mappings\\\", {\\n 199| \\\"source_platform\\\": \\\"TEXT\\\",\\n 200| \\\"normalized_platform\\\": \\\"TEXT\\\",\\n 201| \\\"normalized_account_name\\\": \\\"TEXT\\\",\\n 202| \\\"account_type\\\": \\\"TEXT DEFAULT 'other'\\\",\\n 203| \\\"currency\\\": \\\"TEXT\\\",\\n 204| \\\"internal_platform_id\\\": \\\"TEXT\\\",\\n 205| \\\"internal_account_id\\\": \\\"TEXT\\\",\\n 206| })\\n 207| _add_missing_columns(conn, \\\"broker_import_dry_runs\\\", {\\n 208| \\\"source_platform\\\": \\\"TEXT\\\",\\n 209| \\\"source_filename_hash\\\": \\\"TEXT\\\",\\n 210| \\\"detected_snapshot_date\\\": \\\"TEXT\\\",\\n 211| \\\"snapshot_date_status\\\": \\\"TEXT DEFAULT 'missing'\\\",\\n 212| \\\"candidate_positions\\\": \\\"INTEGER DEFAULT 0\\\",\\n 213| \\\"candidate_cash_rows\\\": \\\"INTEGER DEFAULT 0\\\",\\n 214| \\\"mapped_positions\\\": \\\"INTEGER DEFAULT 0\\\",\\n 215| \\\"blocked_positions\\\": \\\"INTEGER DEFAULT 0\\\",\\n 216| \\\"warnings_count\\\": \\\"INTEGER DEFAULT 0\\\",\\n 217| \\\"errors_count\\\": \\\"INTEGER DEFAULT 0\\\",\\n 218| \\\"summary_json\\\": \\\"TEXT DEFAULT '{}'\\\",\\n 219| \\\"session_status\\\": \\\"TEXT DEFAULT 'active'\\\",\\n 220| \\\"is_current\\\": \\\"INTEGER DEFAULT 0\\\",\\n 221| \\\"archived_at\\\": \\\"TEXT\\\",\\n 222| \\\"discarded_at\\\": \\\"TEXT\\\",\\n 223| })\\n 224|\\n 225|\\n 226|def _create_broker_import_review_items(conn: Connection) -> None:\\n 227| conn.executescript(\\n 228| \\\"\\\"\\\"\\n 229| CREATE TABLE IF NOT EXISTS broker_import_review_items (\\n 230| review_item_id TEXT PRIMARY KEY,\\n 231| dry_run_id TEXT NOT NULL REFERENCES broker_import_dry_runs(dry_run_id),\\n 232| source_platform TEXT NOT NULL,\\n 233| source_file_type TEXT NOT NULL,\\n 234| source_row_ref TEXT NOT NULL,\\n 235| row_hash TEXT NOT NULL,\\n 236| source_label TEXT,\\n 237| normalized_name TEXT,\\n 238| detected_asset_class TEXT,\\n 239| detected_currency TEXT,\\n 240| detected_quantity_present INTEGER NOT NULL DEFAULT 0,\\n 241| detected_market_value_present INTEGER NOT NULL DEFAULT 0,\\n 242| isin TEXT,\\n 243| ticker TEXT,\\n 244| exchange TEXT,\\n 245| mapped_instrument_id TEXT REFERENCES instruments(instrument_id),\\n 246| mapped_account_id TEXT REFERENCES accounts(account_id),\\n 247| quality_flags_json TEXT NOT NULL,\\n 248| review_status TEXT NOT NULL DEFAULT 'open',\\n 249| reviewer_note TEXT,\\n 250| created_at TEXT NOT NULL,\\n 251| updated_at TEXT\\n 252| );\\n 253| CREATE INDEX IF NOT EXISTS idx_broker_review_items_dry_run ON broker_import_review_items(dry_run_id);\\n 254| CREATE INDEX IF NOT EXISTS idx_broker_review_items_status ON broker_import_review_items(review_status);\\n 255| \\\"\\\"\\\"\\n 256| )\\n 257| _add_missing_columns(conn, \\\"broker_import_review_items\\\", {\\n 258| \\\"import_readiness_status\\\": \\\"TEXT DEFAULT 'not_ready'\\\",\\n 259| \\\"reviewer_confirmed\\\": \\\"INTEGER DEFAULT 0\\\",\\n 260| \\\"snapshot_date_confirmed\\\": \\\"INTEGER DEFAULT 0\\\",\\n 261|\", \"total_lines\": 451, \"file_size\": 19933, \"truncated\": true, \"hint\": \"Use offset=261 to continue reading (showing 1-260 of 451 lines)\", \"is_binary\": false, \"is_image\": false}",
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"content": "{\"content\": \" 300| \\\"correction_reason\\\": \\\"TEXT\\\",\\n 301| })\\n 302| conn.execute(\\\"CREATE INDEX IF NOT EXISTS idx_transactions_voided ON transactions(is_voided)\\\")\\n 303| conn.execute(\\\"CREATE INDEX IF NOT EXISTS idx_transactions_correction_of ON transactions(correction_of_transaction_id)\\\")\\n 304|\\n 305|\\n 306|def _create_fx_market_data_tables(conn: Connection) -> None:\\n 307| conn.executescript(\\n 308| \\\"\\\"\\\"\\n 309| CREATE TABLE IF NOT EXISTS instrument_price_mappings (\\n 310| mapping_id TEXT PRIMARY KEY,\\n 311| instrument_id TEXT NOT NULL REFERENCES instruments(instrument_id),\\n 312| isin TEXT,\\n 313| ticker TEXT,\\n 314| exchange TEXT,\\n 315| currency TEXT,\\n 316| provider TEXT NOT NULL,\\n 317| provider_symbol TEXT,\\n 318| provider_market TEXT,\\n 319| mapping_status TEXT NOT NULL DEFAULT 'needs_manual_review',\\n 320| confidence TEXT,\\n 321| notes TEXT,\\n 322| created_at TEXT NOT NULL,\\n 323| updated_at TEXT,\\n 324| UNIQUE(instrument_id, provider)\\n 325| );\\n 326| CREATE INDEX IF NOT EXISTS idx_instrument_price_mappings_status ON instrument_price_mappings(mapping_status);\\n 327| CREATE INDEX IF NOT EXISTS idx_instrument_price_mappings_provider_symbol ON instrument_price_mappings(provider, provider_symbol);\\n 328| \\\"\\\"\\\"\\n 329| )\\n 330| _add_missing_columns(conn, \\\"market_prices\\\", {\\n 331| \\\"provider_market\\\": \\\"TEXT\\\",\\n 332| \\\"error_message\\\": \\\"TEXT\\\",\\n 333| \\\"corporate_action_status\\\": \\\"TEXT NOT NULL DEFAULT 'not_checked'\\\",\\n 334| })\\n 335| _add_missing_columns(conn, \\\"fx_rates\\\", {\\n 336| \\\"error_status\\\": \\\"TEXT\\\",\\n 337| \\\"error_message\\\": \\\"TEXT\\\",\\n 338| })\\n 339| _add_missing_columns(conn, \\\"instrument_price_mappings\\\", {\\n 340| \\\"hedge_status\\\": \\\"TEXT NOT NULL DEFAULT 'unknown'\\\",\\n 341| \\\"is_currency_hedged\\\": \\\"INTEGER NOT NULL DEFAULT 0\\\",\\n 342| \\\"hedged_to_currency\\\": \\\"TEXT\\\",\\n 343| \\\"instrument_status\\\": \\\"TEXT NOT NULL DEFAULT 'unknown'\\\",\\n 344| \\\"valuation_policy\\\": \\\"TEXT NOT NULL DEFAULT 'live_price'\\\",\\n 345| \\\"trading_currency\\\": \\\"TEXT\\\",\\n 346| \\\"base_exposure_currency\\\": \\\"TEXT\\\",\\n 347| })\\n 348| conn.executescript(\\n 349| \\\"\\\"\\\"\\n 350| CREATE TABLE IF NOT EXISTS instrument_catalog_entries (\\n 351| catalog_entry_id TEXT PRIMARY KEY,\\n 352| asset_class TEXT NOT NULL,\\n 353| name TEXT NOT NULL,\\n 354| normalized_name TEXT NOT NULL,\\n 355| isin TEXT,\\n 356| ticker TEXT,\\n 357| exchange TEXT,\\n 358| trading_currency TEXT,\\n 359| instrument_currency TEXT,\\n 360| provider TEXT,\\n 361| provider_symbol TEXT,\\n 362| provider_market TEXT,\\n 363| country TEXT,\\n 364| sector TEXT,\\n 365| issuer TEXT,\\n 366| fund_type TEXT,\\n 367| is_currency_hedged INTEGER,\\n 368| hedged_to_currency TEXT,\\n 369| hedge_status TEXT NOT NULL DEFAULT 'unknown',\\n 370| instrument_status TEXT NOT NULL DEFAULT 'unknown',\\n 371| valuation_policy TEXT NOT NULL DEFAULT 'live_price',\\n 372| source TEXT NOT NULL DEFAULT 'manual',\\n 373| source_confidence TEXT NOT NULL DEFAULT 'low',\\n 374| last_verified_at TEXT,\\n 375| notes TEXT,\\n 376| created_at TEXT NOT NULL,\\n 377| updated_at TEXT\\n 378| );\\n 379| CREATE INDEX IF NOT EXISTS idx_catalog_isin ON instrument_catalog_entries(isin);\\n 380| CREATE INDEX IF NOT EXISTS idx_catalog_ticker_exchange ON instrument_catalog_entries(ticker, exchange, trading_currency);\\n 381| CREATE INDEX IF NOT EXISTS idx_catalog_provider_symbol ON instrument_catalog_entries(provider, provider_symbol);\\n 382| CREATE INDEX IF NOT EXISTS idx_catalog_normalized_name ON instrument_catalog_entries(normalized_name);\\n 383| \\\"\\\"\\\"\\n 384| )\\n 385| conn.executescript(\\n 386| \\\"\\\"\\\"\\n 387| CREATE TABLE IF NOT EXISTS instrument_price_mapping_candidates (\\n 388| candidate_id TEXT PRIMARY KEY,\\n 389| instrument_id TEXT NOT NULL REFERENCES instruments(instrument_id),\\n 390| isin TEXT,\\n 391| candidate_provider TEXT NOT NULL,\\n 392| candidate_provider_symbol TEXT NOT NULL,\\n 393| candidate_exchange TEXT,\\n 394| candidate_currency TEXT,\\n 395| candidate_name TEXT,\\n 396| candidate_asset_class TEXT,\\n 397| candidate_is_hedged INTEGER,\\n 398| candidate_hedged_to_currency TEXT,\\n 399| candidate_hedge_status TEXT NOT NULL DEFAULT 'unknown',\\n 400| candidate_instrument_status TEXT NOT NULL DEFAULT 'unknown',\\n 401| candidate_valuation_policy TEXT NOT NULL DEFAULT 'live_price',\\n 402| confidence TEXT NOT NULL DEFAULT 'low',\\n 403| evidence_source TEXT,\\n 404| evidence_note TEXT,\\n 405| review_status TEXT NOT NULL DEFAULT 'proposed',\\n 406| created_at TEXT NOT NULL,\\n 407| updated_at TEXT\\n 408| );\\n 409| CREATE INDEX IF NOT EXISTS idx_ipmc_instrument ON instrument_price_mapping_candidates(instrument_id);\\n 410| CREATE INDEX IF NOT EXISTS idx_ipmc_review_status ON instrument_price_mapping_candidates(review_status);\\n 411| CREATE INDEX IF NOT EXISTS idx_ipmc_confidence ON instrument_price_mapping_candidates(confidence);\\n 412| \\\"\\\"\\\"\\n 413| )\\n 414| _add_missing_columns(conn, \\\"instrument_price_mapping_candidates\\\", {\\n 415| \\\"candidate_asset_class\\\": \\\"TEXT\\\",\\n 416| \\\"candidate_hedge_status\\\": \\\"TEXT NOT NULL DEFAULT 'unknown'\\\",\\n 417| \\\"candidate_valuation_policy\\\": \\\"TEXT NOT NULL DEFAULT 'live_price'\\\",\\n 418| })\\n 419| conn.execute(\\\"CREATE UNIQUE INDEX IF NOT EXISTS idx_market_prices_unique_provider_date ON market_prices(instrument_id, price_date, provider)\\\")\\n 420| conn.execute(\\\"CREATE INDEX IF NOT EXISTS idx_market_prices_instrument_date ON market_prices(instrument_id, price_date)\\\")\\n 421| conn.execute(\\\"CREATE UNIQUE INDEX IF NOT EXISTS idx_fx_rates_unique_provider_date ON fx_rates(base_currency, quote_currency, rate_date, provider, rate_type)\\\")\\n 422| conn.execute(\\\"CREATE INDEX IF NOT EXISTS idx_fx_rates_pair_date ON fx_rates(base_currency, quote_currency, rate_date)\\\")\\n 423|\\n 424|\\n 425|def _apply_compat_migrations(conn: Connection) -> None:\\n 426| _add_missing_instrument_columns(conn)\\n 427| for table, text_columns in TEXT_AFFINITY_COLUMNS.items():\\n 428| _rebuild_table_with_text_columns(conn, table, text_columns)\\n 429| _create_broker_bank_mapping_tables(conn)\\n 430| _create_broker_import_review_items(conn)\\n 431| _create_broker_import_execution_plans(conn)\\n 432| _add_transaction_void_columns(conn)\\n 433| _create_fx_market_data_tables(conn)\\n 434|\\n 435|\\n 436|def apply_migrations(conn: Connection) -> None:\\n 437| conn.executescript(INITIAL_SCHEMA_SQL)\\n 438| existing_initial = conn.execute(\\\"SELECT 1 FROM schema_migrations WHERE version = 1\\\").fetchone()\\n 439| if not existing_initial:\\n 440| conn.execute(\\n 441| \\\"INSERT INTO schema_migrations(version, name, applied_at, checksum) VALUES (?, ?, ?, ?)\\\",\\n 442| (1, \\\"001_initial_schema\\\", utc_now(), checksum_sql(INITIAL_SCHEMA_SQL)),\\n 443| )\\n 444| _apply_compat_migrations(conn)\\n 445| existing = conn.execute(\\\"SELECT 1 FROM schema_migrations WHERE version = ?\\\", (MIGRATION_VERSION,)).fetchone()\\n 446| if not existing:\\n 447| conn.execute(\\n 448| \\\"INSERT INTO schema_migrations(version, name, applied_at, checksum) VALUES (?, ?, ?, ?)\\\",\\n 449| (MIGRATION_VERSION, MIGRATION_NAME, utc_now(), checksum_sql(MIGRATION_NAME)),\\n 450| )\\n 451| conn.commit()\\n 452|\", \"total_lines\": 451, \"file_size\": 19933, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_ad6WlIK7Vr9D9hBgIJ16B7RG"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Considering edits and mapping**\n\nI need to make substantial edits, and I'm thinking a Python script could help with that. It seems essential to confirm that the mapping resolves correctly. I’m curious about how best to approach this task and how the script will improve the editing process. Breaking it down into manageable steps might make it easier to tackle. It's like piecing together a puzzle! Let's see how to get this right.",
"finish_reason": "tool_calls",
"reasoning_content": "**Considering edits and mapping**\n\nI need to make substantial edits, and I'm thinking a Python script could help with that. It seems essential to confirm that the mapping resolves correctly. I’m curious about how best to approach this task and how the script will improve the editing process. Breaking it down into manageable steps might make it easier to tackle. It's like piecing together a puzzle! Let's see how to get this right.",
"codex_reasoning_items": [
{
"type": "reasoning",
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"id": "rs_0134d7700e125cf0016a07237bae008191bb7eb9fef53257bc",
"summary": [
{
"type": "summary_text",
"text": "**Considering edits and mapping**\n\nI need to make substantial edits, and I'm thinking a Python script could help with that. It seems essential to confirm that the mapping resolves correctly. I’m curious about how best to approach this task and how the script will improve the editing process. Breaking it down into manageable steps might make it easier to tackle. It's like piecing together a puzzle! Let's see how to get this right."
}
]
}
],
"tool_calls": [
{
"id": "call_Yv52EfyNEbHfzZQSwtpvgYOK",
"call_id": "call_Yv52EfyNEbHfzZQSwtpvgYOK",
"response_item_id": "fc_0134d7700e125cf0016a07237f937c8191bb3f7ec7e4e5135c",
"type": "function",
"function": {
"name": "read_file",
"arguments": "{\"limit\":240,\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/mappings.py\"}"
}
}
]
},
{
"role": "tool",
"name": "read_file",
"content": "{\"content\": \" 1|from __future__ import annotations\\n 2|\\n 3|from dataclasses import dataclass, field\\n 4|from sqlite3 import Connection\\n 5|\\n 6|from jarvis_finance.audit.log import record_audit_event\\n 7|from jarvis_finance.imports.common import stable_id, utc_now\\n 8|from jarvis_finance.market_data.instruments import ensure_instrument_metadata_quality, resolve_instrument_alerts, update_instrument_metadata\\n 9|from jarvis_finance.quality.alerts import create_alert\\n 10|\\n 11|\\n 12|@dataclass\\n 13|class MappingQualityResult:\\n 14| instrument_id: str\\n 15| mapping_status: str\\n 16| quality_flags: list[str] = field(default_factory=list)\\n 17|\\n 18|\\n 19|def _instrument(conn: Connection, instrument_id: str):\\n 20| row = conn.execute(\\\"SELECT * FROM instruments WHERE instrument_id=?\\\", (instrument_id,)).fetchone()\\n 21| if row is None:\\n 22| raise ValueError(f\\\"instrument not found: {instrument_id}\\\")\\n 23| return row\\n 24|\\n 25|\\n 26|def confirm_instrument_price_mapping(\\n 27| conn: Connection,\\n 28| *,\\n 29| instrument_id: str,\\n 30| provider: str,\\n 31| provider_symbol: str,\\n 32| provider_market: str | None,\\n 33| confidence: str,\\n 34| note: str,\\n 35| exchange: str | None = None,\\n 36| currency: str | None = None,\\n 37| hedge_status: str | None = None,\\n 38| hedged_to_currency: str | None = None,\\n 39| instrument_status: str | None = None,\\n 40| valuation_policy: str | None = None,\\n 41| base_exposure_currency: str | None = None,\\n 42| trading_currency: str | None = None,\\n 43| created_by: str = \\\"system\\\",\\n 44|) -> str:\\n 45| if not note.strip():\\n 46| raise ValueError(\\\"instrument price mapping confirmation requires a note\\\")\\n 47| if not provider_symbol.strip():\\n 48| raise ValueError(\\\"provider_symbol is required\\\")\\n 49| inst = _instrument(conn, instrument_id)\\n 50| now = utc_now()\\n 51| final_exchange = exchange if exchange is not None else inst[\\\"exchange\\\"]\\n 52| final_currency = (currency if currency is not None else inst[\\\"currency\\\"]) or inst[\\\"trading_currency\\\"]\\n 53| if any(v is not None for v in [hedge_status, hedged_to_currency, instrument_status, valuation_policy, base_exposure_currency, trading_currency, currency, exchange]):\\n 54| update_instrument_metadata(\\n 55| conn,\\n 56| instrument_id=instrument_id,\\n 57| hedge_status=hedge_status,\\n 58| hedged_to_currency=hedged_to_currency,\\n 59| instrument_status=instrument_status,\\n 60| valuation_policy=valuation_policy,\\n 61| base_exposure_currency=base_exposure_currency,\\n 62| trading_currency=trading_currency or final_currency,\\n 63| note=note,\\n 64| created_by=created_by,\\n 65| )\\n 66| inst = _instrument(conn, instrument_id)\\n 67| mapping_id = stable_id(\\\"ipm\\\", instrument_id, provider)\\n 68| conn.execute(\\n 69| \\\"\\\"\\\"\\n 70| INSERT INTO instrument_price_mappings(\\n 71| mapping_id, instrument_id, isin, ticker, exchange, currency, provider, provider_symbol,\\n 72| provider_market, mapping_status, confidence, notes, created_at, updated_at,\\n 73| hedge_status, is_currency_hedged, hedged_to_currency, instrument_status, valuation_policy,\\n 74| trading_currency, base_exposure_currency\\n 75| ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, 'mapped', ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\\n 76| ON CONFLICT(instrument_id, provider) DO UPDATE SET\\n 77| isin=excluded.isin, ticker=excluded.ticker, exchange=excluded.exchange, currency=excluded.currency,\\n 78| provider_symbol=excluded.provider_symbol, provider_market=excluded.provider_market,\\n 79| mapping_status='mapped', confidence=excluded.confidence, notes=excluded.notes, updated_at=excluded.updated_at,\\n 80| hedge_status=excluded.hedge_status, is_currency_hedged=excluded.is_currency_hedged,\\n 81| hedged_to_currency=excluded.hedged_to_currency, instrument_status=excluded.instrument_status,\\n 82| valuation_policy=excluded.valuation_policy, trading_currency=excluded.trading_currency,\\n 83| base_exposure_currency=excluded.base_exposure_currency\\n 84| \\\"\\\"\\\",\\n 85| (\\n 86| mapping_id, instrument_id, inst[\\\"isin\\\"], inst[\\\"ticker\\\"], final_exchange, final_currency,\\n 87| provider, provider_symbol, provider_market, confidence, note, now, now,\\n 88| inst[\\\"hedge_status\\\"], inst[\\\"is_currency_hedged\\\"], inst[\\\"hedged_to_currency\\\"],\\n 89| inst[\\\"instrument_status\\\"], inst[\\\"valuation_policy\\\"], inst[\\\"trading_currency\\\"] or final_currency,\\n 90| inst[\\\"base_exposure_currency\\\"],\\n 91| ),\\n 92| )\\n 93| record_audit_event(\\n 94| conn,\\n 95| source=\\\"instrument_price_mapping\\\",\\n 96| action=\\\"confirm_instrument_price_mapping\\\",\\n 97| entity_type=\\\"instrument_price_mapping\\\",\\n 98| entity_id=mapping_id,\\n 99| new_values={\\\"instrument_id\\\": instrument_id, \\\"provider\\\": provider, \\\"provider_symbol\\\": provider_symbol, \\\"provider_market\\\": provider_market, \\\"hedge_status\\\": inst[\\\"hedge_status\\\"], \\\"instrument_status\\\": inst[\\\"instrument_status\\\"], \\\"valuation_policy\\\": inst[\\\"valuation_policy\\\"]},\\n 100| user_text_note=note,\\n 101| confirmed=True,\\n 102| created_by=created_by,\\n 103| )\\n 104| resolve_instrument_alerts(conn, instrument_id=instrument_id, rule_ids=[\\\"missing_provider_symbol\\\", \\\"ambiguous_instrument_mapping\\\"])\\n 105| ensure_instrument_metadata_quality(conn, instrument_id=instrument_id)\\n 106| conn.commit()\\n 107| return mapping_id\\n 108|\\n 109|\\n 110|def ensure_instrument_price_mapping_quality(conn: Connection, *, instrument_id: str, provider: str = \\\"mock\\\") -> MappingQualityResult:\\n 111| inst = _instrument(conn, instrument_id)\\n 112| ensure_instrument_metadata_quality(conn, instrument_id=instrument_id)\\n 113| existing = conn.execute(\\\"SELECT * FROM instrument_price_mappings WHERE instrument_id=? AND provider=?\\\", (instrument_id, provider)).fetchone()\\n 114| flags: list[str] = []\\n 115| status = existing[\\\"mapping_status\\\"] if existing else \\\"needs_manual_review\\\"\\n 116| if existing and existing[\\\"provider_symbol\\\"] and existing[\\\"mapping_status\\\"] == \\\"mapped\\\":\\n 117| return MappingQualityResult(instrument_id=instrument_id, mapping_status=\\\"mapped\\\", quality_flags=[])\\n 118| if not inst[\\\"provider_symbol\\\"]:\\n 119| status = \\\"missing_provider_symbol\\\"\\n 120| flags.append(\\\"missing_provider_symbol\\\")\\n 121| create_alert(conn, priority=\\\"warnung\\\", category=\\\"market_data\\\", entity_type=\\\"instrument\\\", entity_id=instrument_id, rule_id=\\\"missing_provider_symbol\\\", message=\\\"Instrument has no provider symbol for local market-price updates.\\\", evidence={\\\"isin\\\": inst[\\\"isin\\\"], \\\"ticker\\\": inst[\\\"ticker\\\"], \\\"provider\\\": provider}, fingerprint=\\\"missing_provider_symbol\\\")\\n 122| if inst[\\\"ticker\\\"] and not inst[\\\"exchange\\\"]:\\n 123| flags.append(\\\"ticker_without_exchange\\\")\\n 124| create_alert(conn, priority=\\\"warnung\\\", category=\\\"market_data\\\", entity_type=\\\"instrument\\\", entity_id=instrument_id, rule_id=\\\"ambiguous_instrument_mapping\\\", message=\\\"Instrument ticker has no exchange; market-data mapping needs manual review.\\\", evidence={\\\"isin\\\": inst[\\\"isin\\\"], \\\"ticker\\\": inst[\\\"ticker\\\"], \\\"provider\\\": provider}, fingerprint=f\\\"ambiguous_instrument_mapping:{provider}\\\")\\n 125| if status == \\\"needs_manual_review\\\":\\n 126| status = \\\"ambiguous\\\"\\n 127| now = utc_now()\\n 128| mapping_id = stable_id(\\\"ipm\\\", instrument_id, provider)\\n 129| conn.execute(\\n 130| \\\"\\\"\\\"\\n 131| INSERT INTO instrument_price_mappings(\\n 132| mapping_id, instrument_id, isin, ticker, exchange, currency, provider, provider_symbol,\\n 133| provider_market, mapping_status, confidence, notes, created_at, updated_at,\\n 134| hedge_status, is_currency_hedged, hedged_to_currency, instrument_status, valuation_policy,\\n 135| trading_currency, base_exposure_currency\\n 136| ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, '0', ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\\n 137| ON CONFLICT(instrument_id, provider) DO UPDATE SET\\n 138| mapping_status=excluded.mapping_status, updated_at=excluded.updated_at,\\n 139| hedge_status=excluded.hedge_status, is_currency_hedged=excluded.is_currency_hedged,\\n 140| hedged_to_currency=excluded.hedged_to_currency, instrument_status=excluded.instrument_status,\\n 141| valuation_policy=excluded.valuation_policy, trading_currency=excluded.trading_currency,\\n 142| base_exposure_currency=excluded.base_exposure_currency\\n 143| \\\"\\\"\\\",\\n 144| (mapping_id, instrument_id, inst[\\\"isin\\\"], inst[\\\"ticker\\\"], inst[\\\"exchange\\\"], inst[\\\"currency\\\"], provider, inst[\\\"provider_symbol\\\"], inst[\\\"exchange\\\"], status, \\\",\\\".join(flags), now, now, inst[\\\"hedge_status\\\"], inst[\\\"is_currency_hedged\\\"], inst[\\\"hedged_to_currency\\\"], inst[\\\"instrument_status\\\"], inst[\\\"valuation_policy\\\"], inst[\\\"trading_currency\\\"], inst[\\\"base_exposure_currency\\\"]),\\n 145| )\\n 146| conn.commit()\\n 147| return MappingQualityResult(instrument_id=instrument_id, mapping_status=status, quality_flags=flags)\\n 148|\", \"total_lines\": 147, \"file_size\": 8518, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_Yv52EfyNEbHfzZQSwtpvgYOK"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Resolving candidate review**\n\nI need to resolve the candidate review requirement and then add this to the selection process. The user asked for an update on the instrument catalog entry. I might need to confirm any updates instead of updating the catalog itself. However, the current candidate selection could be sufficient. I’ll implement an \"upsert\" for the catalog entry based on the candidate, and I plan to inspect the catalog function as well.",
"finish_reason": "tool_calls",
"reasoning_content": "**Resolving candidate review**\n\nI need to resolve the candidate review requirement and then add this to the selection process. The user asked for an update on the instrument catalog entry. I might need to confirm any updates instead of updating the catalog itself. However, the current candidate selection could be sufficient. I’ll implement an \"upsert\" for the catalog entry based on the candidate, and I plan to inspect the catalog function as well.",
"codex_reasoning_items": [
{
"type": "reasoning",
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"id": "rs_0134d7700e125cf0016a07238461e08191ab60731d0adc4c11",
"summary": [
{
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"text": "**Resolving candidate review**\n\nI need to resolve the candidate review requirement and then add this to the selection process. The user asked for an update on the instrument catalog entry. I might need to confirm any updates instead of updating the catalog itself. However, the current candidate selection could be sufficient. I’ll implement an \"upsert\" for the catalog entry based on the candidate, and I plan to inspect the catalog function as well."
}
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}
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"arguments": "{\"limit\":260,\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/catalog.py\"}"
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"content": "{\"content\": \" 1|from __future__ import annotations\\n 2|\\n 3|import re\\n 4|from dataclasses import dataclass, field\\n 5|from sqlite3 import Connection\\n 6|from typing import Protocol\\n 7|\\n 8|from jarvis_finance.audit.log import record_audit_event\\n 9|from jarvis_finance.imports.common import stable_id, utc_now\\n 10|from jarvis_finance.market_data.candidates import ProviderCandidate, LookupUnavailable\\n 11|from jarvis_finance.market_data.instruments import ensure_instrument_metadata_quality\\n 12|from jarvis_finance.quality.alerts import create_alert\\n 13|\\n 14|ASSET_CLASSES = {\\\"equity\\\", \\\"stock\\\", \\\"etf\\\", \\\"crypto\\\", \\\"cash\\\", \\\"other\\\"}\\n 15|CONFIDENCES = {\\\"high\\\", \\\"medium\\\", \\\"low\\\"}\\n 16|HEDGE_STATUSES = {\\\"hedged\\\", \\\"unhedged\\\", \\\"unknown\\\"}\\n 17|INSTRUMENT_STATUSES = {\\\"active\\\", \\\"suspended\\\", \\\"delisted\\\", \\\"merged\\\", \\\"inactive\\\", \\\"unknown\\\", \\\"suspected_inactive\\\"}\\n 18|VALUATION_POLICIES = {\\\"live_price\\\", \\\"last_known_price\\\", \\\"manual_value\\\", \\\"exclude_from_auto_price_update\\\"}\\n 19|\\n 20|\\n 21|def normalize_name(value: str | None) -> str:\\n 22| text = (value or \\\"\\\").strip().lower()\\n 23| return re.sub(r\\\"\\\\s+\\\", \\\" \\\", re.sub(r\\\"[^a-z0-9]+\\\", \\\" \\\", text)).strip()\\n 24|\\n 25|\\n 26|@dataclass(frozen=True)\\n 27|class CatalogEntryInput:\\n 28| asset_class: str\\n 29| name: str\\n 30| isin: str | None = None\\n 31| ticker: str | None = None\\n 32| exchange: str | None = None\\n 33| trading_currency: str | None = None\\n 34| instrument_currency: str | None = None\\n 35| provider: str | None = None\\n 36| provider_symbol: str | None = None\\n 37| provider_market: str | None = None\\n 38| country: str | None = None\\n 39| sector: str | None = None\\n 40| issuer: str | None = None\\n 41| fund_type: str | None = None\\n 42| is_currency_hedged: bool | None = None\\n 43| hedged_to_currency: str | None = None\\n 44| hedge_status: str = \\\"unknown\\\"\\n 45| instrument_status: str = \\\"unknown\\\"\\n 46| valuation_policy: str = \\\"live_price\\\"\\n 47| source: str = \\\"manual\\\"\\n 48| source_confidence: str = \\\"low\\\"\\n 49| notes: str | None = None\\n 50|\\n 51|\\n 52|@dataclass\\n 53|class CatalogSearchResult:\\n 54| catalog_entry_id: str | None\\n 55| asset_class: str\\n 56| name: str\\n 57| isin: str | None = None\\n 58| ticker: str | None = None\\n 59| exchange: str | None = None\\n 60| trading_currency: str | None = None\\n 61| instrument_currency: str | None = None\\n 62| provider: str | None = None\\n 63| provider_symbol: str | None = None\\n 64| provider_market: str | None = None\\n 65| hedge_status: str = \\\"unknown\\\"\\n 66| instrument_status: str = \\\"unknown\\\"\\n 67| confidence: str = \\\"low\\\"\\n 68| source: str = \\\"local_catalog\\\"\\n 69| evidence_note: str = \\\"\\\"\\n 70|\\n 71|\\n 72|class CatalogLookupProvider(Protocol):\\n 73| name: str\\n 74|\\n 75| def search(self, *, query: str, asset_class: str | None = None) -> list[CatalogSearchResult]:\\n 76| ...\\n 77|\\n 78|\\n 79|class UnavailableCatalogLookupProvider:\\n 80| name = \\\"unavailable\\\"\\n 81|\\n 82| def search(self, *, query: str, asset_class: str | None = None) -> list[CatalogSearchResult]:\\n 83| raise LookupUnavailable(\\\"external instrument lookup is not configured\\\")\\n 84|\\n 85|\\n 86|def _validate_entry(entry: CatalogEntryInput) -> None:\\n 87| if entry.asset_class.lower() not in ASSET_CLASSES:\\n 88| raise ValueError(\\\"invalid asset_class\\\")\\n 89| if not entry.name.strip():\\n 90| raise ValueError(\\\"name is required\\\")\\n 91| if entry.source_confidence not in CONFIDENCES:\\n 92| raise ValueError(\\\"invalid source_confidence\\\")\\n 93| if entry.hedge_status not in HEDGE_STATUSES:\\n 94| raise ValueError(\\\"invalid hedge_status\\\")\\n 95| if entry.instrument_status not in INSTRUMENT_STATUSES:\\n 96| raise ValueError(\\\"invalid instrument_status\\\")\\n 97| if entry.valuation_policy not in VALUATION_POLICIES:\\n 98| raise ValueError(\\\"invalid valuation_policy\\\")\\n 99|\\n 100|\\n 101|def upsert_catalog_entry(conn: Connection, entry: CatalogEntryInput, *, note: str, created_by: str = \\\"system\\\") -> str:\\n 102| if not note.strip():\\n 103| raise ValueError(\\\"catalog entry upsert requires a note\\\")\\n 104| _validate_entry(entry)\\n 105| isin = (entry.isin or \\\"\\\").strip().upper() or None\\n 106| ticker = (entry.ticker or \\\"\\\").strip().upper() or None\\n 107| exchange = (entry.exchange or \\\"\\\").strip().upper() or None\\n 108| trading_currency = (entry.trading_currency or \\\"\\\").strip().upper() or None\\n 109| instrument_currency = (entry.instrument_currency or trading_currency or \\\"\\\").strip().upper() or None\\n 110| provider = (entry.provider or \\\"manual\\\").strip().lower()\\n 111| provider_symbol = (entry.provider_symbol or \\\"\\\").strip() or None\\n 112| provider_market = (entry.provider_market or exchange or \\\"\\\").strip().upper() or None\\n 113| catalog_entry_id = stable_id(\\\"catalog\\\", entry.asset_class.lower(), isin or \\\"\\\", ticker or \\\"\\\", exchange or \\\"\\\", trading_currency or \\\"\\\", provider, provider_symbol or \\\"\\\", entry.name)\\n 114| now = utc_now()\\n 115| old = conn.execute(\\\"SELECT * FROM instrument_catalog_entries WHERE catalog_entry_id=?\\\", (catalog_entry_id,)).fetchone()\\n 116| conn.execute(\\n 117| \\\"\\\"\\\"\\n 118| INSERT INTO instrument_catalog_entries(\\n 119| catalog_entry_id, asset_class, name, normalized_name, isin, ticker, exchange,\\n 120| trading_currency, instrument_currency, provider, provider_symbol, provider_market,\\n 121| country, sector, issuer, fund_type, is_currency_hedged, hedged_to_currency,\\n 122| hedge_status, instrument_status, valuation_policy, source, source_confidence,\\n 123| last_verified_at, notes, created_at, updated_at\\n 124| ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\\n 125| ON CONFLICT(catalog_entry_id) DO UPDATE SET\\n 126| name=excluded.name,\\n 127| normalized_name=excluded.normalized_name,\\n 128| provider_symbol=excluded.provider_symbol,\\n 129| provider_market=excluded.provider_market,\\n 130| country=excluded.country,\\n 131| sector=excluded.sector,\\n 132| issuer=excluded.issuer,\\n 133| fund_type=excluded.fund_type,\\n 134| is_currency_hedged=excluded.is_currency_hedged,\\n 135| hedged_to_currency=excluded.hedged_to_currency,\\n 136| hedge_status=excluded.hedge_status,\\n 137| instrument_status=excluded.instrument_status,\\n 138| valuation_policy=excluded.valuation_policy,\\n 139| source=excluded.source,\\n 140| source_confidence=excluded.source_confidence,\\n 141| last_verified_at=excluded.last_verified_at,\\n 142| notes=excluded.notes,\\n 143| updated_at=excluded.updated_at\\n 144| \\\"\\\"\\\",\\n 145| (\\n 146| catalog_entry_id, entry.asset_class.lower(), entry.name.strip(), normalize_name(entry.name), isin, ticker, exchange,\\n 147| trading_currency, instrument_currency, provider, provider_symbol, provider_market,\\n 148| entry.country, entry.sector, entry.issuer, entry.fund_type, 1 if entry.is_currency_hedged else 0 if entry.is_currency_hedged is False else None,\\n 149| (entry.hedged_to_currency or \\\"\\\").strip().upper() or None, entry.hedge_status, entry.instrument_status,\\n 150| entry.valuation_policy, entry.source, entry.source_confidence, now, entry.notes, now, now,\\n 151| ),\\n 152| )\\n 153| record_audit_event(\\n 154| conn,\\n 155| source=\\\"instrument_catalog\\\",\\n 156| action=\\\"upsert_catalog_entry\\\",\\n 157| entity_type=\\\"instrument_catalog_entry\\\",\\n 158| entity_id=catalog_entry_id,\\n 159| old_values=dict(old) if old else None,\\n 160| new_values={\\\"asset_class\\\": entry.asset_class.lower(), \\\"isin\\\": isin, \\\"ticker\\\": ticker, \\\"exchange\\\": exchange, \\\"provider\\\": provider, \\\"provider_symbol\\\": provider_symbol},\\n 161| user_text_note=note,\\n 162| confirmed=True,\\n 163| created_by=created_by,\\n 164| )\\n 165| conn.commit()\\n 166| return catalog_entry_id\\n 167|\\n 168|\\n 169|def search_local_catalog(conn: Connection, query: str, asset_class: str | None = None) -> list[CatalogSearchResult]:\\n 170| q = (query or \\\"\\\").strip()\\n 171| if not q:\\n 172| return []\\n 173| clauses = [\\\"(upper(COALESCE(isin,''))=upper(?) OR upper(COALESCE(ticker,''))=upper(?) OR upper(COALESCE(provider_symbol,''))=upper(?) OR normalized_name LIKE ? OR upper(COALESCE(exchange,''))=upper(?) OR upper(COALESCE(trading_currency,''))=upper(?))\\\"]\\n 174| params: list[object] = [q, q, q, f\\\"%{normalize_name(q)}%\\\", q, q]\\n 175| if asset_class:\\n 176| ac = asset_class.lower()\\n 177| if ac == \\\"equity\\\":\\n 178| clauses.append(\\\"asset_class IN ('equity','stock')\\\")\\n 179| else:\\n 180| clauses.append(\\\"asset_class=?\\\")\\n 181| params.append(ac)\\n 182| rows = conn.execute(\\n 183| \\\"SELECT * FROM instrument_catalog_entries WHERE \\\" + \\\" AND \\\".join(clauses) + \\\" ORDER BY source_confidence, name, exchange, trading_currency LIMIT 50\\\",\\n 184| tuple(params),\\n 185| ).fetchall()\\n 186| return [\\n 187| CatalogSearchResult(\\n 188| catalog_entry_id=row[\\\"catalog_entry_id\\\"], asset_class=row[\\\"asset_class\\\"], name=row[\\\"name\\\"], isin=row[\\\"isin\\\"], ticker=row[\\\"ticker\\\"], exchange=row[\\\"exchange\\\"],\\n 189| trading_currency=row[\\\"trading_currency\\\"], instrument_currency=row[\\\"instrument_currency\\\"], provider=row[\\\"provider\\\"], provider_symbol=row[\\\"provider_symbol\\\"],\\n 190| provider_market=row[\\\"provider_market\\\"], hedge_status=row[\\\"hedge_status\\\"] or \\\"unknown\\\", instrument_status=row[\\\"instrument_status\\\"] or \\\"unknown\\\",\\n 191| confidence=row[\\\"source_confidence\\\"] or \\\"low\\\", source=\\\"local_catalog\\\", evidence_note=\\\"local catalog match\\\",\\n 192| )\\n 193| for row in rows\\n 194| ]\\n 195|\\n 196|\\n 197|def search_instruments(conn: Connection, query: str, asset_class: str | None = None, *, providers: list[CatalogLookupProvider] | None = None) -> tuple[list[CatalogSearchResult], list[str]]:\\n 198| results = search_local_catalog(conn, query, asset_class)\\n 199| warnings: list[str] = []\\n 200| for provider in providers or []:\\n 201| try:\\n 202| external = provider.search(query=query, asset_class=asset_class)\\n 203| except Exception:\\n 204| warnings.append(\\\"provider_lookup_unavailable\\\")\\n 205| create_alert(conn, priority=\\\"warnung\\\", category=\\\"market_data\\\", entity_type=\\\"instrument_catalog\\\", entity_id=\\\"external_lookup\\\", rule_id=\\\"provider_lookup_unavailable\\\", message=\\\"External instrument catalog provider unavailable.\\\", evidence={\\\"provider\\\": getattr(provider, \\\"name\\\", \\\"unknown\\\")}, fingerprint=f\\\"catalog_provider_lookup_unavailable:{getattr(provider, 'name', 'unknown')}\\\")\\n 206| continue\\n 207| results.extend(external)\\n 208| conn.commit()\\n 209| return results, warnings\\n 210|\\n 211|\\n 212|def prepare_catalog_from_instruments(conn: Connection, *, instrument_ids: list[str], source: str = \\\"true_wealth\\\", note: str = \\\"prepare catalog from existing instruments\\\") -> dict[str, int]:\\n 213| summary = {\\\"instruments_total\\\": 0, \\\"catalog_entries_created\\\": 0, \\\"multiple_listings\\\": 0, \\\"manual_review_required\\\": 0, \\\"hedge_unknown\\\": 0, \\\"instrument_status_unknown\\\": 0, \\\"valuation_ready\\\": 0}\\n 214| seen_isin: dict[str, set[tuple[str | None, str | None]]] = {}\\n 215| for instrument_id in instrument_ids:\\n 216| row = conn.execute(\\\"SELECT * FROM instruments WHERE instrument_id=?\\\", (instrument_id,)).fetchone()\\n 217| if row is None:\\n 218| continue\\n 219| summary[\\\"instruments_total\\\"] += 1\\n 220| ensure_instrument_metadata_quality(conn, instrument_id=instrument_id)\\n 221| entry = CatalogEntryInput(\\n 222| asset_class=\\\"etf\\\" if (row[\\\"asset_class\\\"] or \\\"\\\").lower() == \\\"etf\\\" else \\\"equity\\\",\\n 223| name=row[\\\"name\\\"], isin=row[\\\"isin\\\"], ticker=row[\\\"ticker\\\"], exchange=row[\\\"exchange\\\"], trading_currency=row[\\\"trading_currency\\\"] or row[\\\"currency\\\"], instrument_currency=row[\\\"currency\\\"],\\n 224| provider=\\\"manual\\\", provider_symbol=None, provider_market=row[\\\"exchange\\\"], is_currency_hedged=bool(row[\\\"is_currency_hedged\\\"]) if row[\\\"is_currency_hedged\\\"] is not None else None,\\n 225| hedged_to_currency=row[\\\"hedged_to_currency\\\"], hedge_status=row[\\\"hedge_status\\\"] or \\\"unknown\\\", instrument_status=row[\\\"instrument_status\\\"] or \\\"unknown\\\",\\n 226| valuation_policy=row[\\\"valuation_policy\\\"] or \\\"live_price\\\", source=source, source_confidence=\\\"medium\\\" if row[\\\"isin\\\"] else \\\"low\\\", notes=\\\"Prepared from existing runtime instrument metadata; no portfolio amounts included.\\\",\\n 227| )\\n 228| before = conn.execute(\\\"SELECT COUNT(*) AS c FROM instrument_catalog_entries\\\").fetchone()[\\\"c\\\"]\\n 229| upsert_catalog_entry(conn, entry, note=note)\\n 230| after = conn.execute(\\\"SELECT COUNT(*) AS c FROM instrument_catalog_entries\\\").fetchone()[\\\"c\\\"]\\n 231| if after > before:\\n 232| summary[\\\"catalog_entries_created\\\"] += 1\\n 233| if row[\\\"isin\\\"]:\\n 234| seen_isin.setdefault(row[\\\"isin\\\"], set()).add((row[\\\"exchange\\\"], row[\\\"currency\\\"]))\\n 235| if (row[\\\"hedge_status\\\"] or \\\"unknown\\\") == \\\"unknown\\\":\\n 236| summary[\\\"hedge_unknown\\\"] += 1\\n 237| if (row[\\\"instrument_status\\\"] or \\\"unknown\\\") == \\\"unknown\\\":\\n 238| summary[\\\"instrument_status_unknown\\\"] += 1\\n 239| if row[\\\"provider_symbol\\\"] and row[\\\"instrument_status\\\"] == \\\"active\\\" and row[\\\"hedge_status\\\"] != \\\"unknown\\\":\\n 240| summary[\\\"valuation_ready\\\"] += 1\\n 241| else:\\n 242| summary[\\\"manual_review_required\\\"] += 1\\n 243| create_alert(conn, priority=\\\"warnung\\\", category=\\\"market_data\\\", entity_type=\\\"instrument\\\", entity_id=instrument_id, rule_id=\\\"manual_review_needed\\\", message=\\\"Instrument requires manual catalog/mapping review before valuation readiness.\\\", evidence={\\\"source\\\": source}, fingerprint=\\\"manual_review_needed\\\")\\n 244| summary[\\\"multiple_listings\\\"] = sum(1 for listings in seen_isin.values() if len(listings) > 1)\\n 245| conn.commit()\\n 246| return summary\\n 247|\\n 248|\\n 249|def catalog_entry_to_provider_candidate(conn: Connection, catalog_entry_id: str) -> ProviderCandidate:\\n 250| row = conn.execute(\\\"SELECT * FROM instrument_catalog_entries WHERE catalog_entry_id=?\\\", (catalog_entry_id,)).fetchone()\\n 251| if row is None:\\n 252| raise ValueError(\\\"catalog entry not found\\\")\\n 253| return ProviderCandidate(\\n 254| provider=row[\\\"provider\\\"] or \\\"manual\\\",\\n 255| provider_symbol=row[\\\"provider_symbol\\\"] or row[\\\"ticker\\\"] or \\\"\\\",\\n 256| exchange=row[\\\"exchange\\\"], currency=row[\\\"trading_currency\\\"], name=row[\\\"name\\\"], isin=row[\\\"isin\\\"],\\n 257| is_hedged=True if row[\\\"hedge_status\\\"] == \\\"hedged\\\" else False if row[\\\"hedge_status\\\"] == \\\"unhedged\\\" else None,\\n 258| hedged_to_currency=row[\\\"hedged_to_currency\\\"], instrument_status=row[\\\"instrument_status\\\"] or \\\"unknown\\\", evidence_source=\\\"instrument_catalog\\\", evidence_note=\\\"manual catalog selection\\\",\\n 259| )\\n 260|\", \"total_lines\": 259, \"file_size\": 13814, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
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"reasoning": "**Implementing code updates**\n\nI'm thinking about how to implement this code script. I need to rewrite `candidates.py` by adding helpers using a patch. I also want to create alerts and define the necessary table columns. My plan is to use Python to insert new functions after `_confidence`, while also modifying the upsert SQL, and handling export and select processes. There's definitely a lot to keep track of, but I'm sure I can manage it!",
"finish_reason": "tool_calls",
"reasoning_content": "**Implementing code updates**\n\nI'm thinking about how to implement this code script. I need to rewrite `candidates.py` by adding helpers using a patch. I also want to create alerts and define the necessary table columns. My plan is to use Python to insert new functions after `_confidence`, while also modifying the upsert SQL, and handling export and select processes. There's definitely a lot to keep track of, but I'm sure I can manage it!",
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"text": "**Implementing code updates**\n\nI'm thinking about how to implement this code script. I need to rewrite `candidates.py` by adding helpers using a patch. I also want to create alerts and define the necessary table columns. My plan is to use Python to insert new functions after `_confidence`, while also modifying the upsert SQL, and handling export and select processes. There's definitely a lot to keep track of, but I'm sure I can manage it!"
}
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}
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"arguments": "{\"mode\":\"replace\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\",\"old_string\":\"MIGRATION_VERSION = 13\\nMIGRATION_NAME = \\\"013_public_instrument_lookup_candidates\\\"\",\"new_string\":\"MIGRATION_VERSION = 14\\nMIGRATION_NAME = \\\"014_candidate_ranking_decision_pack\\\"\"}"
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"arguments": "{\"mode\":\"replace\",\"old_string\":\"def _review_status_for(confidence: str, count: int, inst, cand: ProviderCandidate) -> str:\\n if count > 1:\\n return \\\"needs_manual_review\\\"\\n if confidence == \\\"high\\\":\\n return \\\"proposed\\\"\\n if confidence == \\\"medium\\\":\\n return \\\"needs_manual_review\\\"\\n return \\\"needs_manual_review\\\"\\n\",\"new_string\":\"def _norm(value: str | None) -> str:\\n return re.sub(r\\\"[^a-z0-9]+\\\", \\\" \\\", (value or \\\"\\\").lower()).strip()\\n\\n\\ndef _name_similarity(a: str | None, b: str | None) -> float:\\n na, nb = _norm(a), _norm(b)\\n if not na or not nb:\\n return 0.0\\n return SequenceMatcher(None, na, nb).ratio()\\n\\n\\ndef rank_candidate(inst, cand: ProviderCandidate, *, candidate_count: int = 1) -> CandidateRanking:\\n score = 0\\n reasons: list[str] = []\\n risks: list[str] = []\\n inst_isin = (inst[\\\"isin\\\"] or \\\"\\\").upper()\\n cand_isin = (cand.isin or \\\"\\\").upper()\\n inst_currency = (inst[\\\"currency\\\"] or inst[\\\"trading_currency\\\"] or \\\"\\\").upper()\\n cand_currency = (cand.currency or \\\"\\\").upper()\\n inst_asset_class = (inst[\\\"asset_class\\\"] or \\\"\\\").lower()\\n cand_asset_class = (cand.asset_class or \\\"\\\").lower()\\n if inst_isin and cand_isin and inst_isin == cand_isin:\\n score += 45\\n reasons.append(\\\"ISIN passt exakt\\\")\\n elif inst_isin:\\n score -= 25\\n risks.append(\\\"kein ISIN-Match\\\")\\n if cand.provider_symbol:\\n score += 10\\n reasons.append(\\\"Provider-Symbol vorhanden\\\")\\n else:\\n score -= 30\\n risks.append(\\\"provider_symbol_missing\\\")\\n if cand.exchange:\\n score += 8\\n reasons.append(\\\"Exchange vorhanden\\\")\\n if inst[\\\"exchange\\\"] and cand.exchange.upper() == inst[\\\"exchange\\\"].upper():\\n score += 12\\n reasons.append(\\\"Exchange passt\\\")\\n else:\\n score -= 18\\n risks.append(\\\"Ticker ohne Exchange\\\")\\n if inst_currency and cand_currency and inst_currency == cand_currency:\\n score += 18\\n reasons.append(\\\"Währung passt\\\")\\n elif inst_currency and cand_currency and inst_currency != cand_currency:\\n score -= 35\\n risks.append(\\\"currency_mismatch\\\")\\n elif not cand_currency:\\n score -= 12\\n risks.append(\\\"Währung fehlt\\\")\\n if inst_asset_class and cand_asset_class and (inst_asset_class == cand_asset_class or {inst_asset_class, cand_asset_class} <= {\\\"equity\\\", \\\"stock\\\"}):\\n score += 12\\n reasons.append(\\\"Assetklasse passt\\\")\\n elif inst_asset_class and cand_asset_class and inst_asset_class != cand_asset_class:\\n score -= 25\\n risks.append(\\\"Assetklasse abweichend\\\")\\n sim = _name_similarity(inst[\\\"name\\\"], cand.name)\\n if sim >= 0.82:\\n score += 12\\n reasons.append(\\\"Name passt fuzzy\\\")\\n elif sim >= 0.55:\\n score += 5\\n reasons.append(\\\"Name teilweise ähnlich\\\")\\n elif cand.name:\\n risks.append(\\\"Name unsicher\\\")\\n hay = \\\" \\\".join(x for x in [inst[\\\"name\\\"], cand.name, cand.evidence_note] if x).lower()\\n hedge_hint = any(marker in hay for marker in HEDGE_MARKERS)\\n if (cand.hedge_status or \\\"unknown\\\") != \\\"unknown\\\":\\n score += 8\\n reasons.append(\\\"Hedge-Status vorhanden\\\")\\n elif hedge_hint:\\n score += 3\\n reasons.append(\\\"Hedge-Hinweis gefunden\\\")\\n else:\\n risks.append(\\\"Hedge unklar\\\")\\n if (cand.instrument_status or \\\"unknown\\\") == \\\"active\\\":\\n score += 10\\n reasons.append(\\\"Instrument-Status aktiv\\\")\\n elif (cand.instrument_status or \\\"unknown\\\") == \\\"unknown\\\":\\n risks.append(\\\"Instrument-Status unklar\\\")\\n else:\\n score -= 25\\n risks.append(\\\"Instrument-Status nicht aktiv\\\")\\n if cand.evidence_source == \\\"openfigi_isin_mapping\\\":\\n score += 10\\n reasons.append(\\\"OpenFIGI ISIN-Datenquelle\\\")\\n elif cand.evidence_source == \\\"yahoo_finance_search\\\":\\n score -= 5\\n reasons.append(\\\"Yahoo Search Fallback\\\")\\n if not cand_isin:\\n risks.append(\\\"Search-Fallback ohne ISIN-Evidence\\\")\\n completeness = sum(bool(x) for x in [cand.provider, cand.provider_symbol, cand.exchange, cand.currency])\\n score += completeness * 3\\n if completeness < 4:\\n risks.append(\\\"Kandidatenfelder unvollständig\\\")\\n if candidate_count > 1:\\n risks.append(\\\"mehrere Listings/Kandidaten vorhanden\\\")\\n if cand.provider_symbol and not cand.exchange:\\n risks.append(\\\"Ticker ohne eindeutige Börse\\\")\\n action = \\\"needs_manual_review\\\"\\n if score >= 80 and not any(flag in risks for flag in [\\\"currency_mismatch\\\", \\\"Assetklasse abweichend\\\", \\\"kein ISIN-Match\\\"]) and candidate_count == 1:\\n action = \\\"select_candidate\\\"\\n elif score < 25 or \\\"currency_mismatch\\\" in risks or \\\"Assetklasse abweichend\\\" in risks:\\n action = \\\"reject_candidate\\\"\\n elif not cand.provider_symbol or not cand.exchange or not cand.currency:\\n action = \\\"insufficient_data\\\"\\n return CandidateRanking(max(0, min(100, score)), \\\"; \\\".join(reasons) or \\\"Keine starken positiven Signale\\\", \\\",\\\".join(dict.fromkeys(risks)), action)\\n\\n\\ndef _review_status_for(confidence: str, count: int, inst, cand: ProviderCandidate) -> str:\\n # Even strong candidates remain review-required when multiple listings/currencies exist.\\n if count > 1:\\n return \\\"needs_manual_review\\\"\\n ranking = rank_candidate(inst, cand, candidate_count=count)\\n if ranking.recommended_action == \\\"select_candidate\\\" and confidence == \\\"high\\\":\\n return \\\"proposed\\\"\\n return \\\"needs_manual_review\\\"\\n\"}"
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"arguments": "{\"mode\":\"replace\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\",\"old_string\":\"def _review_status_for(confidence: str, count: int, inst, cand: ProviderCandidate) -> str:\\n if count > 1:\\n return \\\"needs_manual_review\\\"\\n if confidence == \\\"high\\\":\\n return \\\"proposed\\\"\\n if confidence == \\\"medium\\\":\\n return \\\"needs_manual_review\\\"\\n return \\\"needs_manual_review\\\"\\n\",\"new_string\":\"def _norm(value: str | None) -> str:\\n return re.sub(r\\\"[^a-z0-9]+\\\", \\\" \\\", (value or \\\"\\\").lower()).strip()\\n\\n\\ndef _name_similarity(a: str | None, b: str | None) -> float:\\n na, nb = _norm(a), _norm(b)\\n if not na or not nb:\\n return 0.0\\n return SequenceMatcher(None, na, nb).ratio()\\n\\n\\ndef rank_candidate(inst, cand: ProviderCandidate, *, candidate_count: int = 1) -> CandidateRanking:\\n score = 0\\n reasons: list[str] = []\\n risks: list[str] = []\\n inst_isin = (inst[\\\"isin\\\"] or \\\"\\\").upper()\\n cand_isin = (cand.isin or \\\"\\\").upper()\\n inst_currency = (inst[\\\"currency\\\"] or inst[\\\"trading_currency\\\"] or \\\"\\\").upper()\\n cand_currency = (cand.currency or \\\"\\\").upper()\\n inst_asset_class = (inst[\\\"asset_class\\\"] or \\\"\\\").lower()\\n cand_asset_class = (cand.asset_class or \\\"\\\").lower()\\n if inst_isin and cand_isin and inst_isin == cand_isin:\\n score += 45\\n reasons.append(\\\"ISIN passt exakt\\\")\\n elif inst_isin:\\n score -= 25\\n risks.append(\\\"kein ISIN-Match\\\")\\n if cand.provider_symbol:\\n score += 10\\n reasons.append(\\\"Provider-Symbol vorhanden\\\")\\n else:\\n score -= 30\\n risks.append(\\\"provider_symbol_missing\\\")\\n if cand.exchange:\\n score += 8\\n reasons.append(\\\"Exchange vorhanden\\\")\\n if inst[\\\"exchange\\\"] and cand.exchange.upper() == inst[\\\"exchange\\\"].upper():\\n score += 12\\n reasons.append(\\\"Exchange passt\\\")\\n else:\\n score -= 18\\n risks.append(\\\"Ticker ohne Exchange\\\")\\n if inst_currency and cand_currency and inst_currency == cand_currency:\\n score += 18\\n reasons.append(\\\"Währung passt\\\")\\n elif inst_currency and cand_currency and inst_currency != cand_currency:\\n score -= 35\\n risks.append(\\\"currency_mismatch\\\")\\n elif not cand_currency:\\n score -= 12\\n risks.append(\\\"Währung fehlt\\\")\\n if inst_asset_class and cand_asset_class and (inst_asset_class == cand_asset_class or {inst_asset_class, cand_asset_class} <= {\\\"equity\\\", \\\"stock\\\"}):\\n score += 12\\n reasons.append(\\\"Assetklasse passt\\\")\\n elif inst_asset_class and cand_asset_class and inst_asset_class != cand_asset_class:\\n score -= 25\\n risks.append(\\\"Assetklasse abweichend\\\")\\n sim = _name_similarity(inst[\\\"name\\\"], cand.name)\\n if sim >= 0.82:\\n score += 12\\n reasons.append(\\\"Name passt fuzzy\\\")\\n elif sim >= 0.55:\\n score += 5\\n reasons.append(\\\"Name teilweise ähnlich\\\")\\n elif cand.name:\\n risks.append(\\\"Name unsicher\\\")\\n hay = \\\" \\\".join(x for x in [inst[\\\"name\\\"], cand.name, cand.evidence_note] if x).lower()\\n hedge_hint = any(marker in hay for marker in HEDGE_MARKERS)\\n if (cand.hedge_status or \\\"unknown\\\") != \\\"unknown\\\":\\n score += 8\\n reasons.append(\\\"Hedge-Status vorhanden\\\")\\n elif hedge_hint:\\n score += 3\\n reasons.append(\\\"Hedge-Hinweis gefunden\\\")\\n else:\\n risks.append(\\\"Hedge unklar\\\")\\n if (cand.instrument_status or \\\"unknown\\\") == \\\"active\\\":\\n score += 10\\n reasons.append(\\\"Instrument-Status aktiv\\\")\\n elif (cand.instrument_status or \\\"unknown\\\") == \\\"unknown\\\":\\n risks.append(\\\"Instrument-Status unklar\\\")\\n else:\\n score -= 25\\n risks.append(\\\"Instrument-Status nicht aktiv\\\")\\n if cand.evidence_source == \\\"openfigi_isin_mapping\\\":\\n score += 10\\n reasons.append(\\\"OpenFIGI ISIN-Datenquelle\\\")\\n elif cand.evidence_source == \\\"yahoo_finance_search\\\":\\n score -= 5\\n reasons.append(\\\"Yahoo Search Fallback\\\")\\n if not cand_isin:\\n risks.append(\\\"Search-Fallback ohne ISIN-Evidence\\\")\\n completeness = sum(bool(x) for x in [cand.provider, cand.provider_symbol, cand.exchange, cand.currency])\\n score += completeness * 3\\n if completeness < 4:\\n risks.append(\\\"Kandidatenfelder unvollständig\\\")\\n if candidate_count > 1:\\n risks.append(\\\"mehrere Listings/Kandidaten vorhanden\\\")\\n if cand.provider_symbol and not cand.exchange:\\n risks.append(\\\"Ticker ohne eindeutige Börse\\\")\\n action = \\\"needs_manual_review\\\"\\n if score >= 80 and not any(flag in risks for flag in [\\\"currency_mismatch\\\", \\\"Assetklasse abweichend\\\", \\\"kein ISIN-Match\\\"]) and candidate_count == 1:\\n action = \\\"select_candidate\\\"\\n elif score < 25 or \\\"currency_mismatch\\\" in risks or \\\"Assetklasse abweichend\\\" in risks:\\n action = \\\"reject_candidate\\\"\\n elif not cand.provider_symbol or not cand.exchange or not cand.currency:\\n action = \\\"insufficient_data\\\"\\n return CandidateRanking(max(0, min(100, score)), \\\"; \\\".join(reasons) or \\\"Keine starken positiven Signale\\\", \\\",\\\".join(dict.fromkeys(risks)), action)\\n\\n\\ndef _review_status_for(confidence: str, count: int, inst, cand: ProviderCandidate) -> str:\\n # Even strong candidates remain review-required when multiple listings/currencies exist.\\n if count > 1:\\n return \\\"needs_manual_review\\\"\\n ranking = rank_candidate(inst, cand, candidate_count=count)\\n if ranking.recommended_action == \\\"select_candidate\\\" and confidence == \\\"high\\\":\\n return \\\"proposed\\\"\\n return \\\"needs_manual_review\\\"\\n\"}"
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"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -237,13 +237,123 @@\\n return \\\"low\\\", \\\"weak candidate; manual review required\\\"\\n \\n \\n+def _norm(value: str | None) -> str:\\n+ return re.sub(r\\\"[^a-z0-9]+\\\", \\\" \\\", (value or \\\"\\\").lower()).strip()\\n+\\n+\\n+def _name_similarity(a: str | None, b: str | None) -> float:\\n+ na, nb = _norm(a), _norm(b)\\n+ if not na or not nb:\\n+ return 0.0\\n+ return SequenceMatcher(None, na, nb).ratio()\\n+\\n+\\n+def rank_candidate(inst, cand: ProviderCandidate, *, candidate_count: int = 1) -> CandidateRanking:\\n+ score = 0\\n+ reasons: list[str] = []\\n+ risks: list[str] = []\\n+ inst_isin = (inst[\\\"isin\\\"] or \\\"\\\").upper()\\n+ cand_isin = (cand.isin or \\\"\\\").upper()\\n+ inst_currency = (inst[\\\"currency\\\"] or inst[\\\"trading_currency\\\"] or \\\"\\\").upper()\\n+ cand_currency = (cand.currency or \\\"\\\").upper()\\n+ inst_asset_class = (inst[\\\"asset_class\\\"] or \\\"\\\").lower()\\n+ cand_asset_class = (cand.asset_class or \\\"\\\").lower()\\n+ if inst_isin and cand_isin and inst_isin == cand_isin:\\n+ score += 45\\n+ reasons.append(\\\"ISIN passt exakt\\\")\\n+ elif inst_isin:\\n+ score -= 25\\n+ risks.append(\\\"kein ISIN-Match\\\")\\n+ if cand.provider_symbol:\\n+ score += 10\\n+ reasons.append(\\\"Provider-Symbol vorhanden\\\")\\n+ else:\\n+ score -= 30\\n+ risks.append(\\\"provider_symbol_missing\\\")\\n+ if cand.exchange:\\n+ score += 8\\n+ reasons.append(\\\"Exchange vorhanden\\\")\\n+ if inst[\\\"exchange\\\"] and cand.exchange.upper() == inst[\\\"exchange\\\"].upper():\\n+ score += 12\\n+ reasons.append(\\\"Exchange passt\\\")\\n+ else:\\n+ score -= 18\\n+ risks.append(\\\"Ticker ohne Exchange\\\")\\n+ if inst_currency and cand_currency and inst_currency == cand_currency:\\n+ score += 18\\n+ reasons.append(\\\"Währung passt\\\")\\n+ elif inst_currency and cand_currency and inst_currency != cand_currency:\\n+ score -= 35\\n+ risks.append(\\\"currency_mismatch\\\")\\n+ elif not cand_currency:\\n+ score -= 12\\n+ risks.append(\\\"Währung fehlt\\\")\\n+ if inst_asset_class and cand_asset_class and (inst_asset_class == cand_asset_class or {inst_asset_class, cand_asset_class} <= {\\\"equity\\\", \\\"stock\\\"}):\\n+ score += 12\\n+ reasons.append(\\\"Assetklasse passt\\\")\\n+ elif inst_asset_class and cand_asset_class and inst_asset_class != cand_asset_class:\\n+ score -= 25\\n+ risks.append(\\\"Assetklasse abweichend\\\")\\n+ sim = _name_similarity(inst[\\\"name\\\"], cand.name)\\n+ if sim >= 0.82:\\n+ score += 12\\n+ reasons.append(\\\"Name passt fuzzy\\\")\\n+ elif sim >= 0.55:\\n+ score += 5\\n+ reasons.append(\\\"Name teilweise ähnlich\\\")\\n+ elif cand.name:\\n+ risks.append(\\\"Name unsicher\\\")\\n+ hay = \\\" \\\".join(x for x in [inst[\\\"name\\\"], cand.name, cand.evidence_note] if x).lower()\\n+ hedge_hint = any(marker in hay for marker in HEDGE_MARKERS)\\n+ if (cand.hedge_status or \\\"unknown\\\") != \\\"unknown\\\":\\n+ score += 8\\n+ reasons.append(\\\"Hedge-Status vorhanden\\\")\\n+ elif hedge_hint:\\n+ score += 3\\n+ reasons.append(\\\"Hedge-Hinweis gefunden\\\")\\n+ else:\\n+ risks.append(\\\"Hedge unklar\\\")\\n+ if (cand.instrument_status or \\\"unknown\\\") == \\\"active\\\":\\n+ score += 10\\n+ reasons.append(\\\"Instrument-Status aktiv\\\")\\n+ elif (cand.instrument_status or \\\"unknown\\\") == \\\"unknown\\\":\\n+ risks.append(\\\"Instrument-Status unklar\\\")\\n+ else:\\n+ score -= 25\\n+ risks.append(\\\"Instrument-Status nicht aktiv\\\")\\n+ if cand.evidence_source == \\\"openfigi_isin_mapping\\\":\\n+ score += 10\\n+ reasons.append(\\\"OpenFIGI ISIN-Datenquelle\\\")\\n+ elif cand.evidence_source == \\\"yahoo_finance_search\\\":\\n+ score -= 5\\n+ reasons.append(\\\"Yahoo Search Fallback\\\")\\n+ if not cand_isin:\\n+ risks.append(\\\"Search-Fallback ohne ISIN-Evidence\\\")\\n+ completeness = sum(bool(x) for x in [cand.provider, cand.provider_symbol, cand.exchange, cand.currency])\\n+ score += completeness * 3\\n+ if completeness < 4:\\n+ risks.append(\\\"Kandidatenfelder unvollständig\\\")\\n+ if candidate_count > 1:\\n+ risks.append(\\\"mehrere Listings/Kandidaten vorhanden\\\")\\n+ if cand.provider_symbol and not cand.exchange:\\n+ risks.append(\\\"Ticker ohne eindeutige Börse\\\")\\n+ action = \\\"needs_manual_review\\\"\\n+ if score >= 80 and not any(flag in risks for flag in [\\\"currency_mismatch\\\", \\\"Assetklasse abweichend\\\", \\\"kein ISIN-Match\\\"]) and candidate_count == 1:\\n+ action = \\\"select_candidate\\\"\\n+ elif score < 25 or \\\"currency_mismatch\\\" in risks or \\\"Assetklasse abweichend\\\" in risks:\\n+ action = \\\"reject_candidate\\\"\\n+ elif not cand.provider_symbol or not cand.exchange or not cand.currency:\\n+ action = \\\"insufficient_data\\\"\\n+ return CandidateRanking(max(0, min(100, score)), \\\"; \\\".join(reasons) or \\\"Keine starken positiven Signale\\\", \\\",\\\".join(dict.fromkeys(risks)), action)\\n+\\n+\\n def _review_status_for(confidence: str, count: int, inst, cand: ProviderCandidate) -> str:\\n+ # Even strong candidates remain review-required when multiple listings/currencies exist.\\n if count > 1:\\n return \\\"needs_manual_review\\\"\\n- if confidence == \\\"high\\\":\\n+ ranking = rank_candidate(inst, cand, candidate_count=count)\\n+ if ranking.recommended_action == \\\"select_candidate\\\" and confidence == \\\"high\\\":\\n return \\\"proposed\\\"\\n- if confidence == \\\"medium\\\":\\n- return \\\"needs_manual_review\\\"\\n return \\\"needs_manual_review\\\"\\n \\n \\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"arguments": "{\"mode\":\"replace\",\"new_string\":\" candidate_id = stable_id(\\\"ipmc\\\", instrument_id, candidate.provider, candidate.provider_symbol, candidate.exchange or \\\"\\\", candidate.currency or \\\"\\\")\\n ranking = rank_candidate(inst, candidate, candidate_count=1)\\n now = utc_now()\",\"old_string\":\" candidate_id = stable_id(\\\"ipmc\\\", instrument_id, candidate.provider, candidate.provider_symbol, candidate.exchange or \\\"\\\", candidate.currency or \\\"\\\")\\n now = utc_now()\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
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"reasoning": "**Considering function adjustments**\n\nI realize I need to include candidate_count in the upsert function. So, I’ll change the signature accordingly to accommodate this new parameter. It’s important to make sure that all necessary details are incorporated to avoid any issues later on. Let’s clarify what information to pass, double-check everything, and ensure smooth functionality moving forward. This will help prevent any errors during execution and keep things running efficiently.",
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"reasoning_content": "**Considering function adjustments**\n\nI realize I need to include candidate_count in the upsert function. So, I’ll change the signature accordingly to accommodate this new parameter. It’s important to make sure that all necessary details are incorporated to avoid any issues later on. Let’s clarify what information to pass, double-check everything, and ensure smooth functionality moving forward. This will help prevent any errors during execution and keep things running efficiently.",
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"encrypted_content": "gAAAAABqByQFVk5v4VvUH2_jKWHrvjHyt2ItumXVQEnPKJWyks-qRdKeYC82qlyifMxpXBlo3U2fRIuBOYsQrnLwuJeWIayhk1K-4nqiAanf478jpNI_YyTh9LqnBoLBQtRHmUq8QlhrQI2K3jcwnP8kMqKpULmDhmUirOFNAVgEnycx756SiVSRM0LFnIQdrbg1Nt-jckL-oQ-MZX4sr_O7qHFWzGpY64wLqLs-u_pGG48EifcbwjrR-1sodL2srGCdi18R0ehqk7I9ZbIOmJ_v0n1AiLnod2NpdSDonzIAspEOZbqfkTHXqR8HhJ0BKl0PtivewWaWeTtkmbUe4WyTR24bJBaTpdKPCfiAU5LfxK0g-aA1TayJT4hU_O0T8vrDXt5TUXhcvEx-jNjpYgRj4gs3ugT3ICnUoS-7wzmBfpw1x8QtGc7q5aTpAHw2N7cS8Kya9jdwyXTX8P1-KmOvLZ1RXBA2J0jCLjOMqb-kqbuFcKDfpsedlepsLvur9d4wFNf3_5EpGYQvAxvogBGlBhbkLwiWB-0JijLtqt2frtS3R_34nirLTWDDx5w3XslegP5V9_7v_XsxdLxZYzG4ASuXWiFlWZGdEMzj4dNWmr7H5l7ABU-QaShhUHC3BJsUoWlmReP2PMWt0TdRK5uj85SsOmp69KiO6PeR4WXo8Llf97JK2W0y8VJBNgNdAambRkS6uN1JWzXrrO3-jxxUewR2Ye5pLHIo0jIqiUgtDBHXEgHOBfcBefB3sMDpCtU0lh4RHDLJFMhlPnBPPuYOH6MZ-mcpMeXkHb_NACTOpRz0EnHxF7rpom70LzdoFeXszsmHUvZgajtn-FVBEmgGE6dr2q4LS1m0rDkVi3NUg1sxVbbYzDFtVjjXtKRTrelhyr7MVGhixgDN84k16qACywx9oO_JRbfa7rY4di_D-QkEPOzOPW_QjNgnE95WZrIBWczvqZiUmkrHDkG-RxFf9tcgvejZ7W-3wYeU3zaOS4r8_VfL8QQ=",
"id": "rs_0134d7700e125cf0016a0724043f9c81918daf60a445e93b88",
"summary": [
{
"type": "summary_text",
"text": "**Considering function adjustments**\n\nI realize I need to include candidate_count in the upsert function. So, I’ll change the signature accordingly to accommodate this new parameter. It’s important to make sure that all necessary details are incorporated to avoid any issues later on. Let’s clarify what information to pass, double-check everything, and ensure smooth functionality moving forward. This will help prevent any errors during execution and keep things running efficiently."
}
]
}
],
"tool_calls": [
{
"id": "call_ECDZlcRpC4wA6v9vptpRUYls",
"call_id": "call_ECDZlcRpC4wA6v9vptpRUYls",
"response_item_id": "fc_0134d7700e125cf0016a072405e1e48191a474fd50a76a0349",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\"def upsert_candidate(conn: Connection, *, instrument_id: str, candidate: ProviderCandidate, confidence: str, review_status: str, evidence_note: str, candidate_count: int = 1) -> str:\",\"old_string\":\"def upsert_candidate(conn: Connection, *, instrument_id: str, candidate: ProviderCandidate, confidence: str, review_status: str, evidence_note: str) -> str:\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
}
]
},
{
"role": "tool",
"name": "patch",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -357,7 +357,7 @@\\n return \\\"needs_manual_review\\\"\\n \\n \\n-def upsert_candidate(conn: Connection, *, instrument_id: str, candidate: ProviderCandidate, confidence: str, review_status: str, evidence_note: str) -> str:\\n+def upsert_candidate(conn: Connection, *, instrument_id: str, candidate: ProviderCandidate, confidence: str, review_status: str, evidence_note: str, candidate_count: int = 1) -> str:\\n inst = conn.execute(\\\"SELECT * FROM instruments WHERE instrument_id=?\\\", (instrument_id,)).fetchone()\\n if inst is None:\\n raise ValueError(f\\\"instrument not found: {instrument_id}\\\")\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_ECDZlcRpC4wA6v9vptpRUYls"
},
{
"role": "assistant",
"content": "",
"reasoning": null,
"finish_reason": "tool_calls",
"tool_calls": [
{
"id": "call_3dWlximt3dtNPiamUr3zKEZT",
"call_id": "call_3dWlximt3dtNPiamUr3zKEZT",
"response_item_id": "fc_0134d7700e125cf0016a07240b90188191ae5031d34f47d66e",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\" ranking = rank_candidate(inst, candidate, candidate_count=candidate_count)\",\"old_string\":\" ranking = rank_candidate(inst, candidate, candidate_count=1)\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
}
]
},
{
"role": "tool",
"name": "patch",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -368,7 +368,7 @@\\n elif hedge_status == \\\"unknown\\\" and hedged is False:\\n hedge_status = \\\"unhedged\\\"\\n candidate_id = stable_id(\\\"ipmc\\\", instrument_id, candidate.provider, candidate.provider_symbol, candidate.exchange or \\\"\\\", candidate.currency or \\\"\\\")\\n- ranking = rank_candidate(inst, candidate, candidate_count=1)\\n+ ranking = rank_candidate(inst, candidate, candidate_count=candidate_count)\\n now = utc_now()\\n conn.execute(\\n \\\"\\\"\\\"\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_3dWlximt3dtNPiamUr3zKEZT"
},
{
"role": "assistant",
"content": "",
"reasoning": null,
"finish_reason": "tool_calls",
"tool_calls": [
{
"id": "call_kAIlPi5wfD4dcAikpev5ah4d",
"call_id": "call_kAIlPi5wfD4dcAikpev5ah4d",
"response_item_id": "fc_0134d7700e125cf0016a072410f3f08191ae64291d385d37fa",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\" candidate_instrument_status, candidate_valuation_policy, ranking_score,\\n ranking_reason, risk_flags, recommended_action, confidence,\",\"old_string\":\" candidate_instrument_status, candidate_valuation_policy, confidence,\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
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]
},
{
"role": "tool",
"name": "patch",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -376,7 +376,8 @@\\n candidate_id, instrument_id, isin, candidate_provider, candidate_provider_symbol,\\n candidate_exchange, candidate_currency, candidate_name, candidate_asset_class,\\n candidate_is_hedged, candidate_hedged_to_currency, candidate_hedge_status,\\n- candidate_instrument_status, candidate_valuation_policy, confidence,\\n+ candidate_instrument_status, candidate_valuation_policy, ranking_score,\\n+ ranking_reason, risk_flags, recommended_action, confidence,\\n evidence_source, evidence_note, review_status, created_at, updated_at\\n ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\\n ON CONFLICT(candidate_id) DO UPDATE SET\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_kAIlPi5wfD4dcAikpev5ah4d"
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{
"role": "assistant",
"content": "",
"reasoning": null,
"finish_reason": "tool_calls",
"tool_calls": [
{
"id": "call_Bti5t02lS9CXPk2hpxTYYlX4",
"call_id": "call_Bti5t02lS9CXPk2hpxTYYlX4",
"response_item_id": "fc_0134d7700e125cf0016a072416ba4881918c21a61359488648",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\" ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\",\"old_string\":\" ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
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]
},
{
"role": "tool",
"name": "patch",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -379,7 +379,7 @@\\n candidate_instrument_status, candidate_valuation_policy, ranking_score,\\n ranking_reason, risk_flags, recommended_action, confidence,\\n evidence_source, evidence_note, review_status, created_at, updated_at\\n- ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\\n+ ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\\n ON CONFLICT(candidate_id) DO UPDATE SET\\n candidate_exchange=excluded.candidate_exchange,\\n candidate_currency=excluded.candidate_currency,\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_Bti5t02lS9CXPk2hpxTYYlX4"
},
{
"role": "assistant",
"content": "",
"reasoning": null,
"finish_reason": "tool_calls",
"tool_calls": [
{
"id": "call_T4zkdM2XzuUSdZIOCfRwfwyX",
"call_id": "call_T4zkdM2XzuUSdZIOCfRwfwyX",
"response_item_id": "fc_0134d7700e125cf0016a07241ca5e88191b03a0a5113470ff6",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\" candidate_instrument_status=excluded.candidate_instrument_status,\\n candidate_valuation_policy=excluded.candidate_valuation_policy,\\n ranking_score=excluded.ranking_score,\\n ranking_reason=excluded.ranking_reason,\\n risk_flags=excluded.risk_flags,\\n recommended_action=excluded.recommended_action,\\n confidence=excluded.confidence,\",\"old_string\":\" candidate_instrument_status=excluded.candidate_instrument_status,\\n candidate_valuation_policy=excluded.candidate_valuation_policy,\\n confidence=excluded.confidence,\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
}
]
},
{
"role": "tool",
"name": "patch",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -390,6 +390,10 @@\\n candidate_hedge_status=excluded.candidate_hedge_status,\\n candidate_instrument_status=excluded.candidate_instrument_status,\\n candidate_valuation_policy=excluded.candidate_valuation_policy,\\n+ ranking_score=excluded.ranking_score,\\n+ ranking_reason=excluded.ranking_reason,\\n+ risk_flags=excluded.risk_flags,\\n+ recommended_action=excluded.recommended_action,\\n confidence=excluded.confidence,\\n evidence_source=excluded.evidence_source,\\n evidence_note=excluded.evidence_note,\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_T4zkdM2XzuUSdZIOCfRwfwyX"
},
{
"role": "assistant",
"content": "",
"reasoning": null,
"finish_reason": "tool_calls",
"tool_calls": [
{
"id": "call_09HFuLFvVxivNkHxjCtSLoAx",
"call_id": "call_09HFuLFvVxivNkHxjCtSLoAx",
"response_item_id": "fc_0134d7700e125cf0016a07242324a481919b3aa37a3fc55764",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\" candidate.instrument_status or \\\"unknown\\\", candidate.valuation_policy or \\\"live_price\\\",\\n ranking.ranking_score, ranking.ranking_reason, ranking.risk_flags, ranking.recommended_action,\\n confidence, candidate.evidence_source,\",\"old_string\":\" candidate.instrument_status or \\\"unknown\\\", candidate.valuation_policy or \\\"live_price\\\", confidence, candidate.evidence_source,\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
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},
{
"role": "tool",
"name": "patch",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -404,7 +404,9 @@\\n candidate_id, instrument_id, inst[\\\"isin\\\"], candidate.provider, candidate.provider_symbol,\\n candidate.exchange, candidate.currency or inst[\\\"currency\\\"], candidate.name, candidate.asset_class or (inst[\\\"asset_class\\\"] or \\\"\\\").lower(),\\n 1 if hedged else 0 if hedged is False else None, hedged_to, hedge_status,\\n- candidate.instrument_status or \\\"unknown\\\", candidate.valuation_policy or \\\"live_price\\\", confidence, candidate.evidence_source,\\n+ candidate.instrument_status or \\\"unknown\\\", candidate.valuation_policy or \\\"live_price\\\",\\n+ ranking.ranking_score, ranking.ranking_reason, ranking.risk_flags, ranking.recommended_action,\\n+ confidence, candidate.evidence_source,\\n evidence_note or candidate.evidence_note, review_status, now, now,\\n ),\\n )\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_09HFuLFvVxivNkHxjCtSLoAx"
},
{
"role": "assistant",
"content": "",
"reasoning": null,
"finish_reason": "tool_calls",
"tool_calls": [
{
"id": "call_HjtFiPPIG9JhoxMXNJnd7nKA",
"call_id": "call_HjtFiPPIG9JhoxMXNJnd7nKA",
"response_item_id": "fc_0134d7700e125cf0016a072429166c8191844b96674e7d7b63",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\" upsert_candidate(conn, instrument_id=instrument_id, candidate=cand, confidence=confidence, review_status=status, evidence_note=note, candidate_count=len(candidates))\",\"old_string\":\" upsert_candidate(conn, instrument_id=instrument_id, candidate=cand, confidence=confidence, review_status=status, evidence_note=note)\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
}
]
},
{
"role": "tool",
"name": "patch",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -462,7 +462,7 @@\\n status = _review_status_for(confidence, len(candidates), inst, cand)\\n result.candidates_found += 1\\n if not dry_run:\\n- upsert_candidate(conn, instrument_id=instrument_id, candidate=cand, confidence=confidence, review_status=status, evidence_note=note)\\n+ upsert_candidate(conn, instrument_id=instrument_id, candidate=cand, confidence=confidence, review_status=status, evidence_note=note, candidate_count=len(candidates))\\n if not dry_run:\\n conn.commit()\\n return result\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"reasoning": "**Recalculating function for rows**\n\nI need to recalibrate the function for the existing rows, specifically to utilize the ProviderCandidate. This means I should also add a helper function to support this process. It’s important to ensure everything is set up correctly so that the system can work efficiently. Let’s clarify that, and then I’ll proceed to implement these updates without any hiccups! Keeping everything organized will help in the long run.",
"finish_reason": "tool_calls",
"reasoning_content": "**Recalculating function for rows**\n\nI need to recalibrate the function for the existing rows, specifically to utilize the ProviderCandidate. This means I should also add a helper function to support this process. It’s important to ensure everything is set up correctly so that the system can work efficiently. Let’s clarify that, and then I’ll proceed to implement these updates without any hiccups! Keeping everything organized will help in the long run.",
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"id": "rs_0134d7700e125cf0016a07242ecf3c8191bafb1b1f16f797ef",
"summary": [
{
"type": "summary_text",
"text": "**Recalculating function for rows**\n\nI need to recalibrate the function for the existing rows, specifically to utilize the ProviderCandidate. This means I should also add a helper function to support this process. It’s important to ensure everything is set up correctly so that the system can work efficiently. Let’s clarify that, and then I’ll proceed to implement these updates without any hiccups! Keeping everything organized will help in the long run."
}
]
}
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"id": "call_0tatbBLKjvaQN4sr4jpw0Z9K",
"call_id": "call_0tatbBLKjvaQN4sr4jpw0Z9K",
"response_item_id": "fc_0134d7700e125cf0016a07243156b88191ae8b1ecc3416e6ff",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\"def _candidate_from_row(row) -> ProviderCandidate:\\n return ProviderCandidate(\\n provider=row[\\\"candidate_provider\\\"],\\n provider_symbol=row[\\\"candidate_provider_symbol\\\"],\\n exchange=row[\\\"candidate_exchange\\\"],\\n currency=row[\\\"candidate_currency\\\"],\\n name=row[\\\"candidate_name\\\"],\\n isin=row[\\\"isin\\\"],\\n asset_class=row[\\\"candidate_asset_class\\\"],\\n is_hedged=True if row[\\\"candidate_is_hedged\\\"] == 1 else False if row[\\\"candidate_is_hedged\\\"] == 0 else None,\\n hedged_to_currency=row[\\\"candidate_hedged_to_currency\\\"],\\n hedge_status=row[\\\"candidate_hedge_status\\\"] or \\\"unknown\\\",\\n instrument_status=row[\\\"candidate_instrument_status\\\"] or \\\"unknown\\\",\\n valuation_policy=row[\\\"candidate_valuation_policy\\\"] or \\\"live_price\\\",\\n evidence_source=row[\\\"evidence_source\\\"] or \\\"provider_lookup\\\",\\n evidence_note=row[\\\"evidence_note\\\"] or \\\"\\\",\\n )\\n\\n\\ndef recalculate_candidate_rankings(conn: Connection, *, instrument_ids: list[str] | None = None) -> dict[str, int]:\\n clauses = []\\n params: list[object] = []\\n if instrument_ids:\\n clauses.append(\\\"c.instrument_id IN (\\\" + \\\",\\\".join(\\\"?\\\" for _ in instrument_ids) + \\\")\\\")\\n params.extend(instrument_ids)\\n where = \\\" WHERE \\\" + \\\" AND \\\".join(clauses) if clauses else \\\"\\\"\\n rows = conn.execute(\\n \\\"\\\"\\\"\\n SELECT c.*, i.asset_class AS instrument_asset_class, i.name AS instrument_name,\\n i.ticker AS instrument_ticker, i.exchange AS instrument_exchange,\\n i.currency AS instrument_currency, i.trading_currency AS instrument_trading_currency,\\n i.hedge_status AS instrument_hedge_status, i.instrument_status AS source_instrument_status\\n FROM instrument_price_mapping_candidates c\\n JOIN instruments i ON i.instrument_id=c.instrument_id\\n \\\"\\\"\\\" + where,\\n tuple(params),\\n ).fetchall()\\n counts: dict[str, int] = {}\\n for row in rows:\\n counts[row[\\\"instrument_id\\\"]] = counts.get(row[\\\"instrument_id\\\"], 0) + 1\\n summary = {\\\"candidates_total\\\": len(rows), \\\"rank_high\\\": 0, \\\"rank_medium\\\": 0, \\\"rank_low\\\": 0, \\\"multiple_listings_same_isin\\\": 0, \\\"currency_mismatch\\\": 0, \\\"hedge_status_unknown\\\": 0, \\\"instrument_status_unknown\\\": 0, \\\"candidate_review_required\\\": 0}\\n by_isin: dict[str, set[tuple[str, str]]] = {}\\n for row in rows:\\n inst = {\\n \\\"isin\\\": row[\\\"isin\\\"],\\n \\\"asset_class\\\": row[\\\"instrument_asset_class\\\"],\\n \\\"name\\\": row[\\\"instrument_name\\\"],\\n \\\"ticker\\\": row[\\\"instrument_ticker\\\"],\\n \\\"exchange\\\": row[\\\"instrument_exchange\\\"],\\n \\\"currency\\\": row[\\\"instrument_currency\\\"],\\n \\\"trading_currency\\\": row[\\\"instrument_trading_currency\\\"],\\n }\\n cand = _candidate_from_row(row)\\n ranking = rank_candidate(inst, cand, candidate_count=counts[row[\\\"instrument_id\\\"]])\\n if ranking.ranking_score >= 75:\\n summary[\\\"rank_high\\\"] += 1\\n elif ranking.ranking_score >= 50:\\n summary[\\\"rank_medium\\\"] += 1\\n else:\\n summary[\\\"rank_low\\\"] += 1\\n risk_flags = set(filter(None, ranking.risk_flags.split(\\\",\\\")))\\n if \\\"currency_mismatch\\\" in risk_flags:\\n summary[\\\"currency_mismatch\\\"] += 1\\n if (row[\\\"candidate_hedge_status\\\"] or \\\"unknown\\\") == \\\"unknown\\\":\\n summary[\\\"hedge_status_unknown\\\"] += 1\\n if (row[\\\"candidate_instrument_status\\\"] or \\\"unknown\\\") == \\\"unknown\\\":\\n summary[\\\"instrument_status_unknown\\\"] += 1\\n if row[\\\"review_status\\\"] in {\\\"proposed\\\", \\\"needs_manual_review\\\"}:\\n summary[\\\"candidate_review_required\\\"] += 1\\n if row[\\\"isin\\\"]:\\n by_isin.setdefault(row[\\\"isin\\\"], set()).add((row[\\\"candidate_exchange\\\"] or \\\"\\\", row[\\\"candidate_currency\\\"] or \\\"\\\"))\\n conn.execute(\\n \\\"\\\"\\\"\\n UPDATE instrument_price_mapping_candidates\\n SET ranking_score=?, ranking_reason=?, risk_flags=?, recommended_action=?, updated_at=?\\n WHERE candidate_id=?\\n \\\"\\\"\\\",\\n (ranking.ranking_score, ranking.ranking_reason, ranking.risk_flags, ranking.recommended_action, utc_now(), row[\\\"candidate_id\\\"]),\\n )\\n summary[\\\"multiple_listings_same_isin\\\"] = sum(1 for listings in by_isin.values() if len(listings) > 1)\\n for instrument_id, count in counts.items():\\n if count:\\n create_alert(conn, priority=\\\"warnung\\\", category=\\\"market_data\\\", entity_type=\\\"instrument\\\", entity_id=instrument_id, rule_id=\\\"candidate_review_required\\\", message=\\\"Provider-symbol candidates exist but require manual selection before valuation.\\\", evidence={\\\"candidate_count\\\": count}, fingerprint=\\\"candidate_review_required\\\")\\n conn.commit()\\n return summary\\n\\n\\ndef dedupe_missing_provider_symbol_alerts(conn: Connection) -> int:\",\"old_string\":\"def dedupe_missing_provider_symbol_alerts(conn: Connection) -> int:\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
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"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -468,6 +468,93 @@\\n return result\\n \\n \\n+def _candidate_from_row(row) -> ProviderCandidate:\\n+ return ProviderCandidate(\\n+ provider=row[\\\"candidate_provider\\\"],\\n+ provider_symbol=row[\\\"candidate_provider_symbol\\\"],\\n+ exchange=row[\\\"candidate_exchange\\\"],\\n+ currency=row[\\\"candidate_currency\\\"],\\n+ name=row[\\\"candidate_name\\\"],\\n+ isin=row[\\\"isin\\\"],\\n+ asset_class=row[\\\"candidate_asset_class\\\"],\\n+ is_hedged=True if row[\\\"candidate_is_hedged\\\"] == 1 else False if row[\\\"candidate_is_hedged\\\"] == 0 else None,\\n+ hedged_to_currency=row[\\\"candidate_hedged_to_currency\\\"],\\n+ hedge_status=row[\\\"candidate_hedge_status\\\"] or \\\"unknown\\\",\\n+ instrument_status=row[\\\"candidate_instrument_status\\\"] or \\\"unknown\\\",\\n+ valuation_policy=row[\\\"candidate_valuation_policy\\\"] or \\\"live_price\\\",\\n+ evidence_source=row[\\\"evidence_source\\\"] or \\\"provider_lookup\\\",\\n+ evidence_note=row[\\\"evidence_note\\\"] or \\\"\\\",\\n+ )\\n+\\n+\\n+def recalculate_candidate_rankings(conn: Connection, *, instrument_ids: list[str] | None = None) -> dict[str, int]:\\n+ clauses = []\\n+ params: list[object] = []\\n+ if instrument_ids:\\n+ clauses.append(\\\"c.instrument_id IN (\\\" + \\\",\\\".join(\\\"?\\\" for _ in instrument_ids) + \\\")\\\")\\n+ params.extend(instrument_ids)\\n+ where = \\\" WHERE \\\" + \\\" AND \\\".join(clauses) if clauses else \\\"\\\"\\n+ rows = conn.execute(\\n+ \\\"\\\"\\\"\\n+ SELECT c.*, i.asset_class AS instrument_asset_class, i.name AS instrument_name,\\n+ i.ticker AS instrument_ticker, i.exchange AS instrument_exchange,\\n+ i.currency AS instrument_currency, i.trading_currency AS instrument_trading_currency,\\n+ i.hedge_status AS instrument_hedge_status, i.instrument_status AS source_instrument_status\\n+ FROM instrument_price_mapping_candidates c\\n+ JOIN instruments i ON i.instrument_id=c.instrument_id\\n+ \\\"\\\"\\\" + where,\\n+ tuple(params),\\n+ ).fetchall()\\n+ counts: dict[str, int] = {}\\n+ for row in rows:\\n+ counts[row[\\\"instrument_id\\\"]] = counts.get(row[\\\"instrument_id\\\"], 0) + 1\\n+ summary = {\\\"candidates_total\\\": len(rows), \\\"rank_high\\\": 0, \\\"rank_medium\\\": 0, \\\"rank_low\\\": 0, \\\"multiple_listings_same_isin\\\": 0, \\\"currency_mismatch\\\": 0, \\\"hedge_status_unknown\\\": 0, \\\"instrument_status_unknown\\\": 0, \\\"candidate_review_required\\\": 0}\\n+ by_isin: dict[str, set[tuple[str, str]]] = {}\\n+ for row in rows:\\n+ inst = {\\n+ \\\"isin\\\": row[\\\"isin\\\"],\\n+ \\\"asset_class\\\": row[\\\"instrument_asset_class\\\"],\\n+ \\\"name\\\": row[\\\"instrument_name\\\"],\\n+ \\\"ticker\\\": row[\\\"instrument_ticker\\\"],\\n+ \\\"exchange\\\": row[\\\"instrument_exchange\\\"],\\n+ \\\"currency\\\": row[\\\"instrument_currency\\\"],\\n+ \\\"trading_currency\\\": row[\\\"instrument_trading_currency\\\"],\\n+ }\\n+ cand = _candidate_from_row(row)\\n+ ranking = rank_candidate(inst, cand, candidate_count=counts[row[\\\"instrument_id\\\"]])\\n+ if ranking.ranking_score >= 75:\\n+ summary[\\\"rank_high\\\"] += 1\\n+ elif ranking.ranking_score >= 50:\\n+ summary[\\\"rank_medium\\\"] += 1\\n+ else:\\n+ summary[\\\"rank_low\\\"] += 1\\n+ risk_flags = set(filter(None, ranking.risk_flags.split(\\\",\\\")))\\n+ if \\\"currency_mismatch\\\" in risk_flags:\\n+ summary[\\\"currency_mismatch\\\"] += 1\\n+ if (row[\\\"candidate_hedge_status\\\"] or \\\"unknown\\\") == \\\"unknown\\\":\\n+ summary[\\\"hedge_status_unknown\\\"] += 1\\n+ if (row[\\\"candidate_instrument_status\\\"] or \\\"unknown\\\") == \\\"unknown\\\":\\n+ summary[\\\"instrument_status_unknown\\\"] += 1\\n+ if row[\\\"review_status\\\"] in {\\\"proposed\\\", \\\"needs_manual_review\\\"}:\\n+ summary[\\\"candidate_review_required\\\"] += 1\\n+ if row[\\\"isin\\\"]:\\n+ by_isin.setdefault(row[\\\"isin\\\"], set()).add((row[\\\"candidate_exchange\\\"] or \\\"\\\", row[\\\"candidate_currency\\\"] or \\\"\\\"))\\n+ conn.execute(\\n+ \\\"\\\"\\\"\\n+ UPDATE instrument_price_mapping_candidates\\n+ SET ranking_score=?, ranking_reason=?, risk_flags=?, recommended_action=?, updated_at=?\\n+ WHERE candidate_id=?\\n+ \\\"\\\"\\\",\\n+ (ranking.ranking_score, ranking.ranking_reason, ranking.risk_flags, ranking.recommended_action, utc_now(), row[\\\"candidate_id\\\"]),\\n+ )\\n+ summary[\\\"multiple_listings_same_isin\\\"] = sum(1 for listings in by_isin.values() if len(listings) > 1)\\n+ for instrument_id, count in counts.items():\\n+ if count:\\n+ create_alert(conn, priority=\\\"warnung\\\", category=\\\"market_data\\\", entity_type=\\\"instrument\\\", entity_id=instrument_id, rule_id=\\\"candidate_review_required\\\", message=\\\"Provider-symbol candidates exist but require manual selection before valuation.\\\", evidence={\\\"candidate_count\\\": count}, fingerprint=\\\"candidate_review_required\\\")\\n+ conn.commit()\\n+ return summary\\n+\\n+\\n def dedupe_missing_provider_symbol_alerts(conn: Connection) -> int:\\n \\\"\\\"\\\"Keep one active mapping-quality alert per rule/instrument; resolve duplicate active rows.\\\"\\\"\\\"\\n now = utc_now()\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"text": "**Organizing candidate data**\n\nI need to current candidates and realize there are no columns until the migrations are complete. This is a bit tricky, but I’ll be fine. I’ll have to export the data and then add some ranking fields for clarity. Sorting it out will help in understanding how these candidates stack up, but I want to ensure I'm doing it correctly while keeping everything organized. Let's get this right!"
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"arguments": "{\"mode\":\"replace\",\"new_string\":\" c.candidate_currency, c.confidence, c.ranking_score, c.ranking_reason,\\n c.risk_flags, c.recommended_action, c.candidate_hedge_status,\",\"old_string\":\" c.candidate_currency, c.confidence, c.candidate_hedge_status,\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
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"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -586,7 +586,8 @@\\n \\\"\\\"\\\"\\n SELECT i.instrument_id, i.asset_class, i.name, i.isin, i.ticker, i.exchange, i.currency,\\n c.candidate_provider, c.candidate_provider_symbol, c.candidate_exchange,\\n- c.candidate_currency, c.confidence, c.candidate_hedge_status,\\n+ c.candidate_currency, c.confidence, c.ranking_score, c.ranking_reason,\\n+ c.risk_flags, c.recommended_action, c.candidate_hedge_status,\\n c.candidate_instrument_status, c.evidence_source, c.evidence_note,\\n c.review_status\\n FROM instruments i\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"arguments": "{\"mode\":\"replace\",\"new_string\":\" ORDER BY i.isin, i.name, c.ranking_score DESC, c.confidence, c.candidate_provider\",\"old_string\":\" ORDER BY i.isin, i.name, c.confidence, c.candidate_provider\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
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"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -599,7 +599,7 @@\\n AND COALESCE(is_voided,0)=0\\n AND instrument_id IS NOT NULL\\n )\\n- ORDER BY i.isin, i.name, c.confidence, c.candidate_provider\\n+ ORDER BY i.isin, i.name, c.ranking_score DESC, c.confidence, c.candidate_provider\\n \\\"\\\"\\\"\\n ).fetchall()\\n fields = [\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"arguments": "{\"mode\":\"replace\",\"new_string\":\" \\\"candidate_provider\\\", \\\"candidate_provider_symbol\\\", \\\"candidate_exchange\\\", \\\"candidate_currency\\\",\\n \\\"confidence\\\", \\\"ranking_score\\\", \\\"ranking_reason\\\", \\\"risk_flags\\\", \\\"recommended_action\\\", \\\"hedge_status_candidate\\\", \\\"instrument_status_candidate\\\", \\\"evidence_source\\\",\",\"old_string\":\" \\\"candidate_provider\\\", \\\"candidate_provider_symbol\\\", \\\"candidate_exchange\\\", \\\"candidate_currency\\\",\\n \\\"confidence\\\", \\\"hedge_status_candidate\\\", \\\"instrument_status_candidate\\\", \\\"evidence_source\\\",\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
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"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -605,7 +605,7 @@\\n fields = [\\n \\\"instrument_id\\\", \\\"asset_class\\\", \\\"name\\\", \\\"isin\\\", \\\"ticker\\\", \\\"exchange\\\", \\\"currency\\\",\\n \\\"candidate_provider\\\", \\\"candidate_provider_symbol\\\", \\\"candidate_exchange\\\", \\\"candidate_currency\\\",\\n- \\\"confidence\\\", \\\"hedge_status_candidate\\\", \\\"instrument_status_candidate\\\", \\\"evidence_source\\\",\\n+ \\\"confidence\\\", \\\"ranking_score\\\", \\\"ranking_reason\\\", \\\"risk_flags\\\", \\\"recommended_action\\\", \\\"hedge_status_candidate\\\", \\\"instrument_status_candidate\\\", \\\"evidence_source\\\",\\n \\\"evidence_note\\\", \\\"review_status\\\", \\\"reviewer_decision\\\", \\\"reviewer_note\\\",\\n ]\\n with path.open(\\\"w\\\", newline=\\\"\\\", encoding=\\\"utf-8\\\") as handle:\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"arguments": "{\"mode\":\"replace\",\"new_string\":\" \\\"confidence\\\": row[\\\"confidence\\\"], \\\"ranking_score\\\": row[\\\"ranking_score\\\"] or 0,\\n \\\"ranking_reason\\\": row[\\\"ranking_reason\\\"] or \\\"\\\", \\\"risk_flags\\\": row[\\\"risk_flags\\\"] or \\\"\\\",\\n \\\"recommended_action\\\": row[\\\"recommended_action\\\"] or \\\"needs_manual_review\\\", \\\"hedge_status_candidate\\\": row[\\\"candidate_hedge_status\\\"],\",\"old_string\":\" \\\"confidence\\\": row[\\\"confidence\\\"], \\\"hedge_status_candidate\\\": row[\\\"candidate_hedge_status\\\"],\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
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"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -617,7 +617,9 @@\\n \\\"isin\\\": row[\\\"isin\\\"], \\\"ticker\\\": row[\\\"ticker\\\"], \\\"exchange\\\": row[\\\"exchange\\\"], \\\"currency\\\": row[\\\"currency\\\"],\\n \\\"candidate_provider\\\": row[\\\"candidate_provider\\\"], \\\"candidate_provider_symbol\\\": row[\\\"candidate_provider_symbol\\\"],\\n \\\"candidate_exchange\\\": row[\\\"candidate_exchange\\\"], \\\"candidate_currency\\\": row[\\\"candidate_currency\\\"],\\n- \\\"confidence\\\": row[\\\"confidence\\\"], \\\"hedge_status_candidate\\\": row[\\\"candidate_hedge_status\\\"],\\n+ \\\"confidence\\\": row[\\\"confidence\\\"], \\\"ranking_score\\\": row[\\\"ranking_score\\\"] or 0,\\n+ \\\"ranking_reason\\\": row[\\\"ranking_reason\\\"] or \\\"\\\", \\\"risk_flags\\\": row[\\\"risk_flags\\\"] or \\\"\\\",\\n+ \\\"recommended_action\\\": row[\\\"recommended_action\\\"] or \\\"needs_manual_review\\\", \\\"hedge_status_candidate\\\": row[\\\"candidate_hedge_status\\\"],\\n \\\"instrument_status_candidate\\\": row[\\\"candidate_instrument_status\\\"], \\\"evidence_source\\\": row[\\\"evidence_source\\\"],\\n \\\"evidence_note\\\": row[\\\"evidence_note\\\"], \\\"review_status\\\": row[\\\"review_status\\\"],\\n \\\"reviewer_decision\\\": \\\"\\\", \\\"reviewer_note\\\": \\\"\\\",\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"encrypted_content": "gAAAAABqByRs9aIKAl5Y1pQXDyL22NPUHFUndJnCgm-sdxuSknIaH5XB0cMnTu82mmIa6PHjACSH3sWvYISl7M9gH2W_ZpaqR078NG6rzxHf0JUyyiRfTC8EGGQuEYZvlP4wkpri2W6Q27HUnVdpVSfBvKV2x_nXCkUdoyaGwle7QxVXdFORRil2xPx8yC1zKOH5Qldp9VU1DjPukH3fvb1HDywSbfk1z8V3dtViCBl_7Uk7SyRGUG6BJW_j6_MNDkjZYq0jASES6gV_pxBD8nWzENjJAsMrynOxuxghQAXDOvmj_1eT8wuALE6JR2lKBnCbmIvRBIZDUPTXXqNYh2ptZMGTXSRhL-ir3A6Cood7vPg1zbybjrI5cqsSd32jJN1ELZErUZitrrKsMXItVw4OeXlLYbRpm9yRwlyukhUYuk-cRLgIrLVTnqIH8bSb4dp6cMWDBdOmKZ3elKlclALT9lR6UDvZf_Dbk8k0U5jMDUK4wa9pAGdTPFTMgtW2_HyI0xbxXO5-0tnynw9G-CQFSsKU-gapcVZoKrl9kPu7N_vryMDS7NCcc6EW8pbg63fCnncTfwamPHK5joz8sBupZv5Jgfh3qi3Clfgil6yLh8xbYbM86TVfbqKT_ZwojQ8FNzpqEFN-RT33emWTkqnEuvB1PpzLAPv7kwn7sYNuI-fZA02361UoOj_pEhFgtsdBfAySeKK678mTX04C8L8s9mqKLwjU9FnKWtH9dIhuwH3KOtf2ZhXAwnYibiNFDyhg6e0FWX9CL-YeykDH2jfgqYrG5NMvzmTnPkUirQafo8tOqpbz0g7GOEsPJti_8MvAIpEJnrtsQwal5jwjzMTrOpXNOqlsYjZSzJ-IdhjDG0rmkgGxBKDC8b_WtlMRM1E_ywOKceB6Pe8Qk9EdtppbCw8c9ca9fDjlQc4HqZDr5jL4dAZLIraudjYllTxFYsLn9OyHsH3i4PnKUOfbzc6rlDpnfO0-1Q==",
"id": "rs_0134d7700e125cf0016a07246c2878819189119e8db1148e0b",
"summary": []
}
],
"tool_calls": [
{
"id": "call_itgt4QaQYdbmdnkwA7lbNh1I",
"call_id": "call_itgt4QaQYdbmdnkwA7lbNh1I",
"response_item_id": "fc_0134d7700e125cf0016a07246cbf508191be4d1cb82ae6f9dc",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\"def export_mapping_decision_pack(conn: Connection, *, output_path: str | Path, top_n: int = 5) -> dict[str, int | str | bool]:\\n path = Path(output_path).expanduser().resolve()\\n path.parent.mkdir(parents=True, exist_ok=True)\\n instruments = conn.execute(\\n \\\"\\\"\\\"\\n SELECT DISTINCT i.instrument_id, i.name, i.isin, i.ticker, i.exchange, i.currency\\n FROM instruments i\\n JOIN transactions t ON t.instrument_id=i.instrument_id\\n WHERE t.transaction_type='initial_position_snapshot'\\n AND t.source_type='broker_import_reviewed_snapshot'\\n AND COALESCE(t.is_voided,0)=0\\n ORDER BY i.isin, i.name\\n \\\"\\\"\\\"\\n ).fetchall()\\n lines = [\\\"# Mapping Candidate Decision Pack\\\", \\\"\\\", \\\"Runtime-only review aid. Contains no quantities, values, prices, account balances or portfolio weights.\\\", \\\"\\\"]\\n total_candidates = 0\\n instruments_with_top = 0\\n for inst in instruments:\\n candidates = conn.execute(\\n \\\"\\\"\\\"\\n SELECT candidate_provider, candidate_provider_symbol, candidate_exchange, candidate_currency,\\n candidate_name, isin, candidate_hedge_status, candidate_instrument_status,\\n confidence, ranking_score, ranking_reason, risk_flags, recommended_action\\n FROM instrument_price_mapping_candidates\\n WHERE instrument_id=? AND review_status IN ('proposed','needs_manual_review')\\n ORDER BY ranking_score DESC, CASE confidence WHEN 'high' THEN 0 WHEN 'medium' THEN 1 ELSE 2 END, candidate_provider\\n \\\"\\\"\\\",\\n (inst[\\\"instrument_id\\\"],),\\n ).fetchall()\\n total_candidates += len(candidates)\\n if candidates:\\n instruments_with_top += 1\\n lines.extend([f\\\"## Instrument {inst['instrument_id']}\\\", \\\"\\\", f\\\"- Name: {inst['name'] or ''}\\\", f\\\"- ISIN: {inst['isin'] or ''}\\\", f\\\"- Source ticker: {inst['ticker'] or ''}\\\", f\\\"- Source exchange: {inst['exchange'] or ''}\\\", f\\\"- Source currency: {inst['currency'] or ''}\\\", f\\\"- Candidate count: {len(candidates)}\\\", \\\"\\\", \\\"### Top Candidates\\\", \\\"\\\"])\\n for idx, row in enumerate(candidates[:top_n], start=1):\\n lines.extend([\\n f\\\"#### Candidate {idx}\\\",\\n f\\\"- Provider: {row['candidate_provider'] or ''}\\\",\\n f\\\"- Provider-Symbol: {row['candidate_provider_symbol'] or ''}\\\",\\n f\\\"- Name: {row['candidate_name'] or ''}\\\",\\n f\\\"- ISIN: {row['isin'] or ''}\\\",\\n f\\\"- Exchange: {row['candidate_exchange'] or ''}\\\",\\n f\\\"- Währung: {row['candidate_currency'] or ''}\\\",\\n f\\\"- Closing/Price Currency: {row['candidate_currency'] or ''}\\\",\\n f\\\"- Hedge-Status: {row['candidate_hedge_status'] or 'unknown'}\\\",\\n f\\\"- Instrument-Status: {row['candidate_instrument_status'] or 'unknown'}\\\",\\n f\\\"- Confidence: {row['confidence'] or ''}\\\",\\n f\\\"- Ranking Score: {row['ranking_score'] or 0}\\\",\\n f\\\"- Recommended Action: {row['recommended_action'] or 'needs_manual_review'}\\\",\\n f\\\"- Ranking Reason: {row['ranking_reason'] or ''}\\\",\\n f\\\"- Risk Flags: {row['risk_flags'] or ''}\\\",\\n \\\"- Reviewer Decision: \\\",\\n \\\"- Reviewer Note: \\\",\\n \\\"\\\",\\n ])\\n path.write_text(\\\"\\\\n\\\".join(lines), encoding=\\\"utf-8\\\")\\n return {\\\"output_path\\\": str(path), \\\"instrument_count\\\": len(instruments), \\\"candidate_rows\\\": total_candidates, \\\"instruments_with_top_candidates\\\": instruments_with_top, \\\"top_candidates_present\\\": instruments_with_top == len(instruments) if instruments else False}\\n\\n\\ndef select_mapping_candidate(conn: Connection, *, candidate_id: str, note: str, created_by: str = \\\"system\\\") -> str:\",\"old_string\":\"def select_mapping_candidate(conn: Connection, *, candidate_id: str, note: str, created_by: str = \\\"system\\\") -> str:\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
}
]
},
{
"role": "tool",
"name": "patch",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -627,6 +627,64 @@\\n return {\\\"output_path\\\": str(path), \\\"rows\\\": len(rows), \\\"candidate_rows\\\": sum(1 for r in rows if r[\\\"candidate_provider_symbol\\\"]), \\\"instrument_count\\\": len({r[\\\"instrument_id\\\"] for r in rows})}\\n \\n \\n+def export_mapping_decision_pack(conn: Connection, *, output_path: str | Path, top_n: int = 5) -> dict[str, int | str | bool]:\\n+ path = Path(output_path).expanduser().resolve()\\n+ path.parent.mkdir(parents=True, exist_ok=True)\\n+ instruments = conn.execute(\\n+ \\\"\\\"\\\"\\n+ SELECT DISTINCT i.instrument_id, i.name, i.isin, i.ticker, i.exchange, i.currency\\n+ FROM instruments i\\n+ JOIN transactions t ON t.instrument_id=i.instrument_id\\n+ WHERE t.transaction_type='initial_position_snapshot'\\n+ AND t.source_type='broker_import_reviewed_snapshot'\\n+ AND COALESCE(t.is_voided,0)=0\\n+ ORDER BY i.isin, i.name\\n+ \\\"\\\"\\\"\\n+ ).fetchall()\\n+ lines = [\\\"# Mapping Candidate Decision Pack\\\", \\\"\\\", \\\"Runtime-only review aid. Contains no quantities, values, prices, account balances or portfolio weights.\\\", \\\"\\\"]\\n+ total_candidates = 0\\n+ instruments_with_top = 0\\n+ for inst in instruments:\\n+ candidates = conn.execute(\\n+ \\\"\\\"\\\"\\n+ SELECT candidate_provider, candidate_provider_symbol, candidate_exchange, candidate_currency,\\n+ candidate_name, isin, candidate_hedge_status, candidate_instrument_status,\\n+ confidence, ranking_score, ranking_reason, risk_flags, recommended_action\\n+ FROM instrument_price_mapping_candidates\\n+ WHERE instrument_id=? AND review_status IN ('proposed','needs_manual_review')\\n+ ORDER BY ranking_score DESC, CASE confidence WHEN 'high' THEN 0 WHEN 'medium' THEN 1 ELSE 2 END, candidate_provider\\n+ \\\"\\\"\\\",\\n+ (inst[\\\"instrument_id\\\"],),\\n+ ).fetchall()\\n+ total_candidates += len(candidates)\\n+ if candidates:\\n+ instruments_with_top += 1\\n+ lines.extend([f\\\"## Instrument {inst['instrument_id']}\\\", \\\"\\\", f\\\"- Name: {inst['name'] or ''}\\\", f\\\"- ISIN: {inst['isin'] or ''}\\\", f\\\"- Source ticker: {inst['ticker'] or ''}\\\", f\\\"- Source exchange: {inst['exchange'] or ''}\\\", f\\\"- Source currency: {inst['currency'] or ''}\\\", f\\\"- Candidate count: {len(candidates)}\\\", \\\"\\\", \\\"### Top Candidates\\\", \\\"\\\"])\\n+ for idx, row in enumerate(candidates[:top_n], start=1):\\n+ lines.extend([\\n+ f\\\"#### Candidate {idx}\\\",\\n+ f\\\"- Provider: {row['candidate_provider'] or ''}\\\",\\n+ f\\\"- Provider-Symbol: {row['candidate_provider_symbol'] or ''}\\\",\\n+ f\\\"- Name: {row['candidate_name'] or ''}\\\",\\n+ f\\\"- ISIN: {row['isin'] or ''}\\\",\\n+ f\\\"- Exchange: {row['candidate_exchange'] or ''}\\\",\\n+ f\\\"- Währung: {row['candidate_currency'] or ''}\\\",\\n+ f\\\"- Closing/Price Currency: {row['candidate_currency'] or ''}\\\",\\n+ f\\\"- Hedge-Status: {row['candidate_hedge_status'] or 'unknown'}\\\",\\n+ f\\\"- Instrument-Status: {row['candidate_instrument_status'] or 'unknown'}\\\",\\n+ f\\\"- Confidence: {row['confidence'] or ''}\\\",\\n+ f\\\"- Ranking Score: {row['ranking_score'] or 0}\\\",\\n+ f\\\"- Recommended Action: {row['recommended_action'] or 'needs_manual_review'}\\\",\\n+ f\\\"- Ranking Reason: {row['ranking_reason'] or ''}\\\",\\n+ f\\\"- Risk Flags: {row['risk_flags'] or ''}\\\",\\n+ \\\"- Reviewer Decision: \\\",\\n+ \\\"- Reviewer Note: \\\",\\n+ \\\"\\\",\\n+ ])\\n+ path.write_text(\\\"\\\\n\\\".join(lines), encoding=\\\"utf-8\\\")\\n+ return {\\\"output_path\\\": str(path), \\\"instrument_count\\\": len(instruments), \\\"candidate_rows\\\": total_candidates, \\\"instruments_with_top_candidates\\\": instruments_with_top, \\\"top_candidates_present\\\": instruments_with_top == len(instruments) if instruments else False}\\n+\\n+\\n def select_mapping_candidate(conn: Connection, *, candidate_id: str, note: str, created_by: str = \\\"system\\\") -> str:\\n if not note.strip():\\n raise ValueError(\\\"candidate selection requires a note\\\")\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_itgt4QaQYdbmdnkwA7lbNh1I"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Resolving catalog issues**\n\nI need to select an update for the catalog and handle the candidate review requirement. I'm considering importing the catalog within the function to prevent circular imports since candidates would circularly import the catalog. I think it makes sense to do a local import inside the select function. I might add this after mapping the data. Overall, I just know I need those catalog updates handled properly!",
"finish_reason": "tool_calls",
"reasoning_content": "**Resolving catalog issues**\n\nI need to select an update for the catalog and handle the candidate review requirement. I'm considering importing the catalog within the function to prevent circular imports since candidates would circularly import the catalog. I think it makes sense to do a local import inside the select function. I might add this after mapping the data. Overall, I just know I need those catalog updates handled properly!",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABqBySFHkWT0eLV42fK1RDIXw3gGOgrQMN_pLgiaeuGtvs8PfWIsjjEtJgYArhABb2TItBG-6upQu0802OKI9cxEDy7GtnF6gzwQGZCPu5Y0iLFrE-WBYPLiRUYhWKajTuf2y8IZey6BwDCMwR-M0mTYi-LfYY2PGY7ssIZLOkOTMgEQyTE83fYB-lbPJgjsJ3RZA-tGzObxaerJtmDigv60697zf76333bOlmGtmgOUIqnfF4MwpDMgvViIwR2KEekcbPW44m8qzHg8u_99MDH6vFBhzr22rwgUWCa-KABBL-_d07Hmp3rGsg4JReh6d_EH-Gr1l4BzITDD6R_olZHx9AUy_3Ai9dPcj9MMJHbLMgX34yHHswL0VEIT5-F851n68lRjKD88RwCx6VGNYYC9y3FeeZZMVWA-B7Q9olf3xAll_HjRn8r8yeXF4aLhGIRvDDxUn6b5TdX6iKCWqCMjjwXbl1f5VLqi5VzWMf3k-sDmpbWqM5CeKHioLtoIvfRMv_M0FqNZJBQqCzZHIypy9TsfjqJX974o-Ke3cvQDGDa3LuIllg8A7nCUepwRgbnBz3rr4EEMo5lnUrSr-5gYX6T_md1RSmGMLrjDy0ArU6rySsyaTqaxU0Hp9FHyiH8ramIUIIupZePN7AISQUi2MlZyxj-YbQyxE_vgrX3h2eV5v2lcOnpMwo_nq9lNWN5yCAX2UMpvnn7zEehjY1DOohiCLjVEQazQ-0MZRWKSiG7_VuaK8wQq7Eqm5SPw7bMP7gcw_8k7LFHx4jIRzpK8rA3KYnW2vIZX4wDF3T7k18djx2mObpc3pF04NzSKwa03VZFtstlP-F1S0P4PVFnjU9R1sPlb99z7ju8BWgOTMMVpnIQLQBUEkWgRPb9nK-xArEU_VU63GvLbzy1vvv4CGQzCSXKqZ4zmwQimv5OtkqCwoCJGlVfISeYKEPmypCTMsHE4hMTPd3r7mA-x9bTmHPd6sVWwaqHACSSztl0y2flAUeo8_nR_S948OzoEI5T-K0PBkwTrgNA_p_g9U8pvS1l48K1Xckp54h5Eqj04bQ4QeaTQOJtl9zNFyYG2f8FSGEjbvzwHkj4M43svzKW-RnV-e9OFMy-Lyh2iTYO23jO4XZm_KoqFcgR5BedCfO0QZBqMwJcUN_XoxEWXnmB5KaOLYu3ZfnOZlm9VOp2WCmIDEwgElJQ9ulfzOps55n8JXGD2xa-46fbsePSE0K5J2uOyuVuITglawCfNtLCSxzgTKJzFvjK-qWPk1iMGbgEPLW-",
"id": "rs_0134d7700e125cf0016a07248375748191aacc14313bc67d2a",
"summary": [
{
"type": "summary_text",
"text": "**Resolving catalog issues**\n\nI need to select an update for the catalog and handle the candidate review requirement. I'm considering importing the catalog within the function to prevent circular imports since candidates would circularly import the catalog. I think it makes sense to do a local import inside the select function. I might add this after mapping the data. Overall, I just know I need those catalog updates handled properly!"
}
]
}
],
"tool_calls": [
{
"id": "call_9ZUQeHhoNcxjrEAKdzjIp1sH",
"call_id": "call_9ZUQeHhoNcxjrEAKdzjIp1sH",
"response_item_id": "fc_0134d7700e125cf0016a072485b9e081919d1ce8e9b2f14021",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"new_string\":\" now = utc_now()\\n try:\\n from jarvis_finance.market_data.catalog import CatalogEntryInput, upsert_catalog_entry\\n inst = conn.execute(\\\"SELECT * FROM instruments WHERE instrument_id=?\\\", (cand[\\\"instrument_id\\\"],)).fetchone()\\n upsert_catalog_entry(\\n conn,\\n CatalogEntryInput(\\n asset_class=(cand[\\\"candidate_asset_class\\\"] or inst[\\\"asset_class\\\"] or \\\"equity\\\"),\\n name=cand[\\\"candidate_name\\\"] or inst[\\\"name\\\"],\\n isin=cand[\\\"isin\\\"] or inst[\\\"isin\\\"],\\n ticker=inst[\\\"ticker\\\"],\\n exchange=cand[\\\"candidate_exchange\\\"],\\n trading_currency=cand[\\\"candidate_currency\\\"],\\n instrument_currency=cand[\\\"candidate_currency\\\"] or inst[\\\"currency\\\"],\\n provider=cand[\\\"candidate_provider\\\"],\\n provider_symbol=cand[\\\"candidate_provider_symbol\\\"],\\n provider_market=cand[\\\"candidate_exchange\\\"],\\n is_currency_hedged=True if cand[\\\"candidate_hedge_status\\\"] == \\\"hedged\\\" else False if cand[\\\"candidate_hedge_status\\\"] == \\\"unhedged\\\" else None,\\n hedged_to_currency=cand[\\\"candidate_hedged_to_currency\\\"],\\n hedge_status=cand[\\\"candidate_hedge_status\\\"] or \\\"unknown\\\",\\n instrument_status=cand[\\\"candidate_instrument_status\\\"] or \\\"unknown\\\",\\n valuation_policy=cand[\\\"candidate_valuation_policy\\\"] or \\\"live_price\\\",\\n source=\\\"mapping_candidate_review\\\",\\n source_confidence=cand[\\\"confidence\\\"] or \\\"low\\\",\\n notes=\\\"Created/updated from confirmed mapping candidate; no portfolio amounts included.\\\",\\n ),\\n note=note,\\n created_by=created_by,\\n )\\n except Exception:\\n # Mapping confirmation already wrote the authoritative mapping; catalog update is best-effort and audited by upsert when it succeeds.\\n pass\\n conn.execute(\\\"UPDATE instrument_price_mapping_candidates SET review_status='selected', updated_at=? WHERE candidate_id=?\\\", (now, candidate_id))\",\"old_string\":\" now = utc_now()\\n conn.execute(\\\"UPDATE instrument_price_mapping_candidates SET review_status='selected', updated_at=? WHERE candidate_id=?\\\", (now, candidate_id))\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
}
]
},
{
"role": "tool",
"name": "patch",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -709,6 +709,37 @@\\n created_by=created_by,\\n )\\n now = utc_now()\\n+ try:\\n+ from jarvis_finance.market_data.catalog import CatalogEntryInput, upsert_catalog_entry\\n+ inst = conn.execute(\\\"SELECT * FROM instruments WHERE instrument_id=?\\\", (cand[\\\"instrument_id\\\"],)).fetchone()\\n+ upsert_catalog_entry(\\n+ conn,\\n+ CatalogEntryInput(\\n+ asset_class=(cand[\\\"candidate_asset_class\\\"] or inst[\\\"asset_class\\\"] or \\\"equity\\\"),\\n+ name=cand[\\\"candidate_name\\\"] or inst[\\\"name\\\"],\\n+ isin=cand[\\\"isin\\\"] or inst[\\\"isin\\\"],\\n+ ticker=inst[\\\"ticker\\\"],\\n+ exchange=cand[\\\"candidate_exchange\\\"],\\n+ trading_currency=cand[\\\"candidate_currency\\\"],\\n+ instrument_currency=cand[\\\"candidate_currency\\\"] or inst[\\\"currency\\\"],\\n+ provider=cand[\\\"candidate_provider\\\"],\\n+ provider_symbol=cand[\\\"candidate_provider_symbol\\\"],\\n+ provider_market=cand[\\\"candidate_exchange\\\"],\\n+ is_currency_hedged=True if cand[\\\"candidate_hedge_status\\\"] == \\\"hedged\\\" else False if cand[\\\"candidate_hedge_status\\\"] == \\\"unhedged\\\" else None,\\n+ hedged_to_currency=cand[\\\"candidate_hedged_to_currency\\\"],\\n+ hedge_status=cand[\\\"candidate_hedge_status\\\"] or \\\"unknown\\\",\\n+ instrument_status=cand[\\\"candidate_instrument_status\\\"] or \\\"unknown\\\",\\n+ valuation_policy=cand[\\\"candidate_valuation_policy\\\"] or \\\"live_price\\\",\\n+ source=\\\"mapping_candidate_review\\\",\\n+ source_confidence=cand[\\\"confidence\\\"] or \\\"low\\\",\\n+ notes=\\\"Created/updated from confirmed mapping candidate; no portfolio amounts included.\\\",\\n+ ),\\n+ note=note,\\n+ created_by=created_by,\\n+ )\\n+ except Exception:\\n+ # Mapping confirmation already wrote the authoritative mapping; catalog update is best-effort and audited by upsert when it succeeds.\\n+ pass\\n conn.execute(\\\"UPDATE instrument_price_mapping_candidates SET review_status='selected', updated_at=? WHERE candidate_id=?\\\", (now, candidate_id))\\n conn.execute(\\\"UPDATE instrument_price_mapping_candidates SET review_status='rejected', updated_at=? WHERE instrument_id=? AND candidate_id<>? AND review_status IN ('proposed','needs_manual_review')\\\", (now, cand[\\\"instrument_id\\\"], candidate_id))\\n record_audit_event(\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
"tool_call_id": "call_9ZUQeHhoNcxjrEAKdzjIp1sH"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Evaluating function commits**\n\nI’m thinking about potential upsert commits in mid function, which sounds like it could be important. I need to figure out how to resolve the add candidate review required aspect, which might involve checking details to ensure everything aligns correctly. It feels like there’s a bit to untangle here, but I'll focus on getting it right so I can move forward confidently with this function. Let me just take a closer look at the specifics!",
"finish_reason": "tool_calls",
"reasoning_content": "**Evaluating function commits**\n\nI’m thinking about potential upsert commits in mid function, which sounds like it could be important. I need to figure out how to resolve the add candidate review required aspect, which might involve checking details to ensure everything aligns correctly. It feels like there’s a bit to untangle here, but I'll focus on getting it right so I can move forward confidently with this function. Let me just take a closer look at the specifics!",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABqBySW72K_O1arTkNfmErETL_Q77OU2zUNWGnS-aksHDGrVs5MHm13CWoU98b4sEBt_OZLOOtRhjnJRGIoYF_-q1L6GeVAI5m10hJhxAVEJ1IpkPwQmf79kVXFqykc7WxqIuxXtLtKTRjf-NSVubanFYvphVJDRquU9_20UDDFEXWmiligxGjYzOiQcVPz3iVMI6ZlSKRjkdgRmXtIG_yp8JKAeAIeUP8clzF0dR9HlYVsIPvN-QR-p8WudJfDnPa8h0mc1UR2kvuPWH-_8uT6xjP5gJnAPmgnP-bZC9g3g1ez5OzWiCbUBavVST1iVf2ZepvZgZzmce7B3wmNTJJ9PGvJDONHoBvCBXKmktgpPPOk5EKWV6ZPd5DeNMcdDGd9-leTB17iIe1f2QBph4RXW081BXOPLxdh-0ob7wD5Ow6MZE2AwrWD3p_kjlUIOV5PwOXArJrKfmw0JTrP0ppOftZccjCnpEqXNOtCSxQJI4uoDPiCejYUkenlU1-7XTGsMFqJfSZ1UDCKxF1JbBucZAEhb8kPYQZKQllDjjJmQDfoOUsLSALlfKlIubbkEMMPAD8dqd21-fdAun2lbmovEZk-Tg4ddVKyfgLizG9loK8Xl3xh3kuhg1EqfkV4kJ1STQERWZz_BSJJOjaGKuj_3dF6KGDoM3dbNwDHwEUNDHjPBXm1lgxiQmzHbmb4K2uB4xZi8epi6ZhR8e6KwV9Sb2lfSxFIuj49AZ717FapNMXLFhPetEzqsYuxw8PQj_9U4m4l9yjKkihA5aXIYQXza6PoAA0v3TGphzzBy0dJZlbh9CxWZHI3dJVjue1mAmmgolVJIvAJONKEOroI2vgRnoZp4FgTmaXK9cF06OLoUv4UN1aNyexU9S5w2Mu6tSfXypk9RAlpOsbnBONYfqv-YWHe2iCUSU3e0t-em5I_HtCWvDM3R26bON3QW0qTzSyORi9zJEEVMlFZG2Xa1nc46kUPE8_ZKis4rijaMHYhM0xSaYnO8f2lWW7kUbukYBOMd5xe",
"id": "rs_0134d7700e125cf0016a072493d75c8191bd6e4994429078a0",
"summary": [
{
"type": "summary_text",
"text": "**Evaluating function commits**\n\nI’m thinking about potential upsert commits in mid function, which sounds like it could be important. I need to figure out how to resolve the add candidate review required aspect, which might involve checking details to ensure everything aligns correctly. It feels like there’s a bit to untangle here, but I'll focus on getting it right so I can move forward confidently with this function. Let me just take a closer look at the specifics!"
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"arguments": "{\"mode\":\"replace\",\"new_string\":\" resolve_instrument_alerts(conn, instrument_id=cand[\\\"instrument_id\\\"], rule_ids=[\\\"missing_provider_symbol\\\", \\\"ambiguous_provider_mapping\\\", \\\"candidate_review_required\\\"])\",\"old_string\":\" resolve_instrument_alerts(conn, instrument_id=cand[\\\"instrument_id\\\"], rule_ids=[\\\"missing_provider_symbol\\\", \\\"ambiguous_provider_mapping\\\"])\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"}"
}
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},
{
"role": "tool",
"name": "patch",
"content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\\n@@ -753,7 +753,7 @@\\n confirmed=True,\\n created_by=created_by,\\n )\\n- resolve_instrument_alerts(conn, instrument_id=cand[\\\"instrument_id\\\"], rule_ids=[\\\"missing_provider_symbol\\\", \\\"ambiguous_provider_mapping\\\"])\\n+ resolve_instrument_alerts(conn, instrument_id=cand[\\\"instrument_id\\\"], rule_ids=[\\\"missing_provider_symbol\\\", \\\"ambiguous_provider_mapping\\\", \\\"candidate_review_required\\\"])\\n conn.commit()\\n return mapping_id\\n \\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/market_data/candidates.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"content": "{\"content\": \" 1|from __future__ import annotations\\n 2|\\n 3|import argparse\\n 4|from decimal import Decimal\\n 5|from pathlib import Path\\n 6|\\n 7|from jarvis_finance.config.settings import ensure_runtime_dirs, load_settings\\n 8|from jarvis_finance.fx.providers import MockFxProvider\\n 9|from jarvis_finance.fx.rates import recheck_transaction_fx_status, update_fx_rates\\n 10|from jarvis_finance.market.providers import CoinGeckoClient, refresh_crypto_prices\\n 11|from jarvis_finance.market_data.candidates import CompositePublicLookupProvider, EmptyLookupProvider, dedupe_missing_provider_symbol_alerts, export_mapping_review_template, generate_mapping_candidates\\n 12|from jarvis_finance.market_data.catalog import prepare_catalog_from_instruments\\n 13|from jarvis_finance.market_data.prices import MockEquityPriceProvider, refresh_market_prices\\n 14|from jarvis_finance.quality.data_quality import check_crypto_data_quality\\n 15|from jarvis_finance.quality.git_safety import assert_safe, scan_path\\n 16|from jarvis_finance.runtime.backup import backup_runtime_db, restore_runtime_db, verify_backup\\n 17|from jarvis_finance.storage.database import connect\\n 18|from jarvis_finance.storage.migrations import apply_migrations, get_schema_version\\n 19|\\n 20|\\n 21|def main(argv: list[str] | None = None) -> int:\\n 22| parser = argparse.ArgumentParser(prog=\\\"finance\\\")\\n 23| sub = parser.add_subparsers(dest=\\\"command\\\", required=True)\\n 24| sub.add_parser(\\\"init-db\\\")\\n 25| sub.add_parser(\\\"migrate\\\")\\n 26| scan = sub.add_parser(\\\"git-safety-scan\\\")\\n 27| scan.add_argument(\\\"path\\\", nargs=\\\"?\\\", default=\\\".\\\")\\n 28| prices = sub.add_parser(\\\"update-crypto-prices\\\")\\n 29| prices.add_argument(\\\"--currency\\\", default=\\\"CHF\\\")\\n 30| prices.add_argument(\\\"--max-age-seconds\\\", type=int, default=3600)\\n 31| prices.add_argument(\\\"--sleep-seconds\\\", type=float, default=0.0)\\n 32| prices.add_argument(\\\"--max-retries\\\", type=int, default=2)\\n 33| prices.add_argument(\\\"--initial-backoff\\\", type=float, default=1.0)\\n 34| prices.add_argument(\\\"--max-backoff\\\", type=float, default=8.0)\\n 35| prices.add_argument(\\\"--only-missing\\\", action=\\\"store_true\\\")\\n 36| prices.add_argument(\\\"--only-stale\\\", action=\\\"store_true\\\")\\n 37| prices.add_argument(\\\"--only-symbol\\\")\\n 38| prices.add_argument(\\\"--limit\\\", type=int)\\n 39| prices.add_argument(\\\"--dry-run\\\", action=\\\"store_true\\\")\\n 40| dq = sub.add_parser(\\\"check-data-quality\\\")\\n 41| dq.add_argument(\\\"--scope\\\", choices=[\\\"crypto\\\"], default=\\\"crypto\\\")\\n 42| dq.add_argument(\\\"--resolve-fixed\\\", action=\\\"store_true\\\")\\n 43| dq.add_argument(\\\"--dry-run\\\", action=\\\"store_true\\\")\\n 44| dq.add_argument(\\\"--currency\\\", default=\\\"CHF\\\")\\n 45| dq.add_argument(\\\"--max-age-seconds\\\", type=int, default=86_400)\\n 46| fx = sub.add_parser(\\\"update-fx-rates\\\")\\n 47| fx.add_argument(\\\"--date\\\", dest=\\\"rate_date\\\")\\n 48| fx.add_argument(\\\"--latest\\\", action=\\\"store_true\\\")\\n 49| fx.add_argument(\\\"--missing-only\\\", action=\\\"store_true\\\")\\n 50| fx.add_argument(\\\"--dry-run\\\", action=\\\"store_true\\\")\\n 51| fx.add_argument(\\\"--currency\\\", action=\\\"append\\\", dest=\\\"currencies\\\")\\n 52| fx.add_argument(\\\"--mock-rate\\\", action=\\\"append\\\", default=[], help=\\\"Test-only BASE=RATE, e.g. USD=0.9\\\")\\n 53| fx.add_argument(\\\"--recheck-transactions\\\", action=\\\"store_true\\\")\\n 54| fx.add_argument(\\\"--source-type\\\")\\n 55| market_prices = sub.add_parser(\\\"update-market-prices\\\")\\n 56| market_prices.add_argument(\\\"--asset-class\\\", choices=[\\\"etf\\\", \\\"equity\\\"], required=True)\\n 57| market_prices.add_argument(\\\"--only-missing\\\", action=\\\"store_true\\\")\\n 58| market_prices.add_argument(\\\"--only-stale\\\", action=\\\"store_true\\\")\\n 59| market_prices.add_argument(\\\"--only-isin\\\")\\n 60| market_prices.add_argument(\\\"--limit\\\", type=int)\\n 61| market_prices.add_argument(\\\"--dry-run\\\", action=\\\"store_true\\\")\\n 62| market_prices.add_argument(\\\"--date\\\", dest=\\\"price_date\\\")\\n 63| market_prices.add_argument(\\\"--mock-price\\\", action=\\\"append\\\", default=[], help=\\\"Test-only SYMBOL=PRICE\\\")\\n 64| catalog = sub.add_parser(\\\"prepare-instrument-catalog\\\")\\n 65| catalog.add_argument(\\\"--source\\\", default=\\\"true_wealth\\\")\\n 66| catalog.add_argument(\\\"--limit\\\", type=int)\\n 67| candidates = sub.add_parser(\\\"generate-mapping-candidates\\\")\\n 68| candidates.add_argument(\\\"--source\\\", default=\\\"true_wealth\\\")\\n 69| candidates.add_argument(\\\"--limit\\\", type=int)\\n 70| candidates.add_argument(\\\"--dry-run\\\", action=\\\"store_true\\\")\\n 71| candidates.add_argument(\\\"--public-lookup\\\", action=\\\"store_true\\\")\\n 72| candidates.add_argument(\\\"--export-template\\\", action=\\\"store_true\\\")\\n 73| candidates.add_argument(\\\"--template-path\\\")\\n 74| candidates.add_argument(\\\"--dedupe-missing-provider-alerts\\\", action=\\\"store_true\\\")\\n 75| sub.add_parser(\\\"backup-runtime-db\\\")\\n 76| restore = sub.add_parser(\\\"restore-runtime-db\\\")\\n 77| restore.add_argument(\\\"--from\\\", dest=\\\"backup_file\\\", required=True)\\n 78| restore.add_argument(\\\"--yes\\\", action=\\\"store_true\\\")\\n 79| verify = sub.add_parser(\\\"verify-backup\\\")\\n 80| verify.add_argument(\\\"--file\\\", required=True)\\n 81| args = parser.parse_args(argv)\\n 82|\\n 83| if args.command in {\\\"init-db\\\", \\\"migrate\\\"}:\\n 84| settings = load_settings()\\n 85| ensure_runtime_dirs(settings)\\n 86| conn = connect(settings.db_path)\\n 87| apply_migrations(conn)\\n 88| print(f\\\"SCHEMA_VERSION={get_schema_version(conn)}\\\")\\n 89| return 0\\n 90| if args.command == \\\"git-safety-scan\\\":\\n 91| findings = scan_path(Path(args.path))\\n 92| if findings:\\n 93| for finding in findings:\\n 94| print(f\\\"{finding.path}: {finding.reason}\\\")\\n 95| return 1\\n 96| assert_safe(Path(args.path))\\n 97| print(\\\"GIT_SAFETY_OK\\\")\\n 98| return 0\\n 99| if args.command == \\\"update-crypto-prices\\\":\\n 100| settings = load_settings()\\n 101| ensure_runtime_dirs(settings)\\n 102| conn = connect(settings.db_path)\\n 103| try:\\n 104| apply_migrations(conn)\\n 105| result = refresh_crypto_prices(\\n 106| conn,\\n 107| provider=CoinGeckoClient(\\n 108| max_retries=args.max_retries,\\n 109| initial_backoff_seconds=args.initial_backoff,\\n 110| max_backoff_seconds=args.max_backoff,\\n 111| ),\\n 112| currency=args.currency,\\n 113| max_age_seconds=args.max_age_seconds,\\n 114| only_missing=args.only_missing,\\n 115| only_stale=args.only_stale,\\n 116| only_symbol=args.only_symbol,\\n 117| limit=args.limit,\\n 118| dry_run=args.dry_run,\\n 119| sleep_seconds=args.sleep_seconds,\\n 120| )\\n 121| print(\\n 122| \\\"CRYPTO_PRICE_UPDATE \\\"\\n 123| f\\\"currency={result.currency} total_assets={result.total_assets} \\\"\\n 124| f\\\"updated={result.updated_count} cached={result.cached_count} \\\"\\n 125| f\\\"skipped={result.skipped_count} stale={result.stale_count} \\\"\\n 126| f\\\"warnings={result.warning_count} errors={result.error_count} \\\"\\n 127| f\\\"assets_still_missing_local_price={result.missing_local_price_count} \\\"\\n 128| f\\\"dry_run={str(result.dry_run).lower()}\\\"\\n 129| )\\n 130| return 1 if result.error_count else 0\\n 131| finally:\\n 132| conn.close()\\n 133| if args.command == \\\"update-fx-rates\\\":\\n 134| settings = load_settings()\\n 135| ensure_runtime_dirs(settings)\\n 136| conn = connect(settings.db_path)\\n 137| try:\\n 138| apply_migrations(conn)\\n 139| if args.recheck_transactions:\\n 140| result = recheck_transaction_fx_status(conn, source_type=args.source_type, dry_run=args.dry_run)\\n 141| print(\\n 142| \\\"FX_RECHECK \\\"\\n 143| f\\\"transactions={result.transaction_count} chf_positions={result.chf_positions} \\\"\\n 144| f\\\"foreign_currency_positions={result.foreign_currency_positions} \\\"\\n 145| f\\\"justified_missing_fx_alerts={result.justified_missing_fx_alerts} \\\"\\n 146| f\\\"false_positive_missing_fx_alerts={result.false_positive_missing_fx_alerts} \\\"\\n 147| f\\\"corrected_transactions={result.corrected_transactions} resolved_alerts={result.resolved_alerts} \\\"\\n 148| f\\\"audit_events={result.audit_events} dry_run={str(result.dry_run).lower()}\\\"\\n 149| )\\n 150| return 0\\n 151| if not args.rate_date and not args.latest:\\n 152| parser.error(\\\"update-fx-rates requires --date or --latest unless --recheck-transactions is used\\\")\\n 153| mock_rates: dict[tuple[str, str, str], Decimal | None] = {}\\n 154| for item in args.mock_rate:\\n 155| base, rate = item.split(\\\"=\\\", 1)\\n 156| mock_rates[(base.upper(), \\\"CHF\\\", args.rate_date or \\\"latest\\\")] = Decimal(rate)\\n 157| currencies = args.currencies or sorted({r[\\\"currency_original\\\"] for r in conn.execute(\\\"SELECT DISTINCT currency_original FROM transactions WHERE currency_original IS NOT NULL\\\").fetchall()})\\n 158| provider = MockFxProvider(mock_rates)\\n 159| result = update_fx_rates(conn, provider=provider, currencies=currencies, rate_date=args.rate_date or \\\"latest\\\", latest=args.latest, missing_only=args.missing_only, dry_run=args.dry_run)\\n 160| print(\\n 161| \\\"FX_RATE_UPDATE \\\"\\n 162| f\\\"updated={result.updated_count} cached={result.cached_count} skipped={result.skipped_count} \\\"\\n 163| f\\\"warnings={result.warning_count} errors={result.error_count} resolved_alerts={result.resolved_alerts} \\\"\\n 164| f\\\"dry_run={str(result.dry_run).lower()}\\\"\\n 165| )\\n 166| return 1 if result.error_count else 0\\n 167| finally:\\n 168| conn.close()\\n 169| if args.command == \\\"update-market-prices\\\":\\n 170| settings = load_settings()\\n 171| ensure_runtime_dirs(settings)\\n 172| conn = connect(settings.db_path)\\n 173| try:\\n 174| apply_migrations(conn)\\n 175| prices = {}\\n 176| for item in args.mock_price:\\n 177| symbol, price = item.split(\\\"=\\\", 1)\\n 178| prices[symbol] = Decimal(price)\\n 179| result = refresh_market_prices(\\n 180| conn,\\n 181| provider=MockEquityPriceProvider(prices),\\n 182| asset_class=args.asset_class,\\n 183| price_date=args.price_date,\\n 184| only_missing=args.only_missing,\\n 185| only_stale=args.only_stale,\\n 186| only_isin=args.only_isin,\\n 187| limit=args.limit,\\n 188| dry_run=args.dry_run,\\n 189| )\\n 190| print(\\n 191| \\\"MARKET_PRICE_UPDATE \\\"\\n 192| f\\\"asset_class={result.asset_class} total_mappings={result.total_mappings} updated={result.updated_count} \\\"\\n 193| f\\\"cached={result.cached_count} skipped={result.skipped_count} stale={result.stale_count} \\\"\\n 194| f\\\"warnings={result.warning_count} errors={result.error_count} dry_run={str(result.dry_run).lower()}\\\"\\n 195| )\\n 196| return 1 if result.error_count else 0\\n 197| finally:\\n 198| conn.close()\\n 199| if args.command == \\\"prepare-instrument-catalog\\\":\\n 200| settings = load_settings()\\n 201| ensure_runtime_dirs(settings)\\n 202| conn = connect(settings.db_path)\\n 203| try:\\n 204| apply_migrations(conn)\\n 205| rows = conn.execute(\\n 206| \\\"\\\"\\\"\\n 207| SELECT DISTINCT t.instrument_id\\n 208| FROM transactions t JOIN instruments i ON i.instrument_id=t.instrument_id\\n 209| WHERE t.transaction_type='initial_position_snapshot'\\n 210| AND t.source_type='broker_import_reviewed_snapshot'\\n 211| AND COALESCE(t.is_voided,0)=0\\n 212| AND t.instrument_id IS NOT NULL\\n 213| ORDER BY i.isin, i.name\\n 214| \\\"\\\"\\\"\\n 215| ).fetchall()\\n 216| ids = [r[\\\"instrument_id\\\"] for r in rows]\\n 217| if args.limit is not None:\\n 218| ids = ids[:args.limit]\\n 219| summary = prepare_catalog_from_instruments(conn, instrument_ids=ids, source=args.source)\\n 220| print(\\n 221| \\\"INSTRUMENT_CATALOG_PREP \\\"\\n 222| f\\\"instruments_total={summary['instruments_total']} catalog_entries_created={summary['catalog_entries_created']} \\\"\\n 223| f\\\"multiple_listings={summary['multiple_listings']} manual_review_required={summary['manual_review_required']} \\\"\\n 224| f\\\"hedge_unknown={summary['hedge_unknown']} instrument_status_unknown={summary['instrument_status_unknown']} \\\"\\n 225| f\\\"valuation_ready={summary['valuation_ready']}\\\"\\n 226| )\\n 227| return 0\\n 228| finally:\\n 229| conn.close()\\n 230| if args.command == \\\"generate-mapping-candidates\\\":\\n 231| settings = load_settings()\\n 232| ensure_runtime_dirs(settings)\\n 233| conn = connect(settings.db_path)\\n 234| try:\\n 235| apply_migrations(conn)\\n 236| if args.dedupe_missing_provider_alerts:\\n 237| resolved = dedupe_missing_provider_symbol_alerts(conn)\\n 238| else:\\n 239| resolved = 0\\n 240| provider = CompositePublicLookupProvider() if args.public_lookup else EmptyLookupProvider()\\n 241| result = generate_mapping_candidates(conn, provider=provider, source=args.source, limit=args.limit, dry_run=args.dry_run)\\n 242| template = None\\n 243| if args.export_template:\\n 244| template_path = args.template_path or str(settings.runtime_paths.exports_dir / \\\"true_wealth_mapping_review_template.csv\\\")\\n 245| template = export_mapping_review_template(conn, output_path=template_path)\\n 246| print(\\n 247| \\\"MAPPING_CANDIDATES \\\"\\n 248| f\\\"instruments_total={result.instruments_total} candidates_found={result.candidates_found} \\\"\\n 249| f\\\"high={result.high_confidence} medium={result.medium_confidence} low={result.low_confidence} \\\"\\n 250| f\\\"instruments_without_candidate={result.instruments_without_candidate} \\\"\\n 251| f\\\"hedge_unknown={result.instruments_with_hedge_unknown} instrument_status_unknown={result.instruments_with_status_unknown} \\\"\\n 252| f\\\"provider_lookup_unavailable={result.provider_lookup_unavailable} ambiguous={result.ambiguous_provider_mapping} \\\"\\n 253| f\\\"deduped_missing_provider_alerts={resolved} \\\"\\n 254| f\\\"template_updated={str(bool(template)).lower()} template_instruments={template['instrument_count'] if template else 0} template_candidates={template['candidate_rows'] if template else 0} \\\"\\n 255| f\\\"dry_run={str(result.dry_run).lower()}\\\"\\n 256| )\\n 257| return 0\\n 258| finally:\\n 259| conn.close()\\n 260| if args.command == \\\"check-data-quality\\\":\\n 261| settings = load_settings()\\n 262| ensure_runtime_dirs(settings)\\n 263| conn = connect(settings.db_path)\\n 264| try:\\n 265| apply_migrations(conn)\\n 266| result = check_crypto_data_quality(\\n 267| conn,\\n 268| currency=args.currency,\\n 269| max_age_seconds=args.max_age_seconds,\\n 270| resolve_fixed=args.resolve_fixed,\\n 271| dry_run=args.dry_run,\\n 272| )\\n 273| print(\\n 274| \\\"DATA_QUALITY_CHECK \\\"\\n 275| f\\\"scope={result.scope} active_crypto_assets={result.active_crypto_assets} \\\"\\n 276| f\\\"fresh_price_assets={result.fresh_price_assets} \\\"\\n 277| f\\\"active_stale_price_alerts_before={result.active_stale_price_alerts_before} \\\"\\n 278| f\\\"active_stale_price_alerts_after={result.active_stale_price_alerts_after} \\\"\\n 279| f\\\"resolved_alerts={result.resolved_alerts} \\\"\\n 280| f\\\"warnings={result.warnings} errors={result.errors} \\\"\\n 281|\", \"total_lines\": 328, \"file_size\": 16731, \"truncated\": true, \"hint\": \"Use offset=281 to continue reading (showing 1-280 of 328 lines)\", \"is_binary\": false, \"is_image\": false}",
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