\\n@@ -92,7 +118,7 @@\\n \\n \\n \\ndiff --git a/src/jarvis_finance/api/routers/budget.py b/src/jarvis_finance/api/routers/budget.py\\nindex be8c189..67d6d21 100644\\n--- a/src/jarvis_finance/api/routers/budget.py\\n+++ b/src/jarvis_finance/api/routers/budget.py\\n@@ -100,9 +100,13 @@ from jarvis_finance.services.budget_monthly_import import (\\n scan_google_drive_budget_folder,\\n )\\n from jarvis_finance.services.grocery_optimizer import (\\n+ accept_grocery_product_match,\\n add_demo_migros_receipt,\\n+ create_manual_grocery_mapping,\\n generate_grocery_optimization_report,\\n get_grocery_optimizer_dashboard,\\n+ refresh_grocery_mapping_price,\\n+ reject_grocery_product_match,\\n run_grocery_optimization,\\n upsert_product_match,\\n )\\n@@ -164,6 +168,27 @@ def grocery_optimizer_match(payload: dict, conn: Connection = Depends(get_db)):\\n return upsert_product_match(conn, payload[\\\"product_item_id\\\"], retailer=payload[\\\"retailer\\\"], candidate_product_name=payload[\\\"candidate_product_name\\\"], candidate_url=payload.get(\\\"candidate_url\\\") or \\\"https://example.invalid/review\\\", candidate_price_text=payload[\\\"candidate_price_text\\\"], candidate_unit_price_text=payload.get(\\\"candidate_unit_price_text\\\"), quality_flags=payload.get(\\\"quality_flags\\\") or [\\\"needs_review\\\"], match_confidence=payload.get(\\\"match_confidence\\\") or \\\"0.60\\\", status=payload.get(\\\"status\\\") or \\\"suggested\\\", source=payload.get(\\\"source\\\") or \\\"manual\\\")\\n \\n \\n+@router.post(\\\"/grocery-optimizer/matches/{match_id}/accept\\\")\\n+def grocery_optimizer_accept_match(match_id: str, payload: dict | None = None, conn: Connection = Depends(get_db)):\\n+ payload = payload or {}\\n+ return accept_grocery_product_match(conn, match_id, user_note=payload.get(\\\"user_note\\\"), save_as_preferred=bool(payload.get(\\\"save_as_preferred\\\", True)))\\n+\\n+\\n+@router.post(\\\"/grocery-optimizer/matches/{match_id}/reject\\\")\\n+def grocery_optimizer_reject_match(match_id: str, payload: dict | None = None, conn: Connection = Depends(get_db)):\\n+ return reject_grocery_product_match(conn, match_id, user_note=(payload or {}).get(\\\"user_note\\\"))\\n+\\n+\\n+@router.post(\\\"/grocery-optimizer/manual-mapping\\\")\\n+def grocery_optimizer_manual_mapping(payload: dict, conn: Connection = Depends(get_db)):\\n+ return create_manual_grocery_mapping(conn, product_item_id=payload[\\\"product_item_id\\\"], target_retailer=payload[\\\"target_retailer\\\"], target_product_name=payload[\\\"target_product_name\\\"], target_product_url=payload[\\\"target_product_url\\\"], target_brand=payload.get(\\\"target_brand\\\"), target_package_size=payload.get(\\\"target_package_size\\\"), target_unit=payload.get(\\\"target_unit\\\"), match_type=payload.get(\\\"match_type\\\") or \\\"manual_match\\\", candidate_price_text=payload.get(\\\"candidate_price_text\\\"), candidate_unit_price_text=payload.get(\\\"candidate_unit_price_text\\\"), user_note=payload.get(\\\"user_note\\\"))\\n+\\n+\\n+@router.post(\\\"/grocery-optimizer/mappings/{mapping_id}/refresh-price\\\")\\n+def grocery_optimizer_refresh_mapping_price(mapping_id: str, conn: Connection = Depends(get_db)):\\n+ return refresh_grocery_mapping_price(conn, mapping_id)\\n+\\n+\\n @router.post(\\\"/grocery-optimizer/optimize\\\")\\n def grocery_optimizer_run(payload: dict, conn: Connection = Depends(get_db)):\\n return run_grocery_optimization(conn, payload[\\\"receipt_id\\\"], selected_retailers=payload.get(\\\"selected_retailers\\\") or [\\\"Coop\\\", \\\"Aldi Suisse\\\", \\\"Lidl\\\", \\\"Denner\\\", \\\"Otto's\\\"], max_store_count=int(payload.get(\\\"max_store_count\\\") or 3), included_product_item_ids=payload.get(\\\"included_product_item_ids\\\"))\\n@@ -181,6 +206,7 @@ def grocery_optimizer_search_prices(payload: dict, conn: Connection = Depends(ge\\n max_products=int(payload.get(\\\"max_products\\\") or 5),\\n use_cache=bool(payload.get(\\\"use_cache\\\", True)),\\n only_safe_matches=bool(payload.get(\\\"only_safe_matches\\\", True)),\\n+ prefer_known_mappings=bool(payload.get(\\\"prefer_known_mappings\\\", True)),\\n )\\n \\n \\ndiff --git a/src/jarvis_finance/services/grocery_optimizer.py b/src/jarvis_finance/services/grocery_optimizer.py\\nindex 774f5ca..cefed8b 100644\\n--- a/src/jarvis_finance/services/grocery_optimizer.py\\n+++ b/src/jarvis_finance/services/grocery_optimizer.py\\n@@ -14,7 +14,7 @@ from jarvis_finance.config.settings import find_repo_root, load_settings\\n from jarvis_finance.services.budget_common import new_id, row_to_dict\\n \\n SAFE_RETAILERS = {\\\"Coop\\\", \\\"Aldi Suisse\\\", \\\"Lidl\\\", \\\"Denner\\\", \\\"Otto's\\\", \\\"Migros\\\"}\\n-SAFE_FLAGS = {\\\"exact_match\\\", \\\"close_match\\\", \\\"cheaper_private_label\\\"}\\n+SAFE_FLAGS = {\\\"exact_match\\\", \\\"close_match\\\", \\\"cheaper_private_label\\\", \\\"manual_match\\\"}\\n UNCERTAIN_FLAGS = {\\\"different_pack_size\\\", \\\"needs_review\\\", \\\"bio_vs_non_bio\\\", \\\"brand_vs_private_label\\\"}\\n \\n \\n@@ -75,6 +75,8 @@ def get_grocery_optimizer_dashboard(conn: Connection) -> dict[str, Any]:\\n receipts = []\\n for r in rows:\\n items = _items_for_receipt(conn, r[\\\"receipt_id\\\"])\\n+ for item in items:\\n+ item[\\\"known_mappings\\\"] = known_mappings_for_item(conn, item, include_rejected=True)\\n receipts.append({\\\"receipt_id\\\": r[\\\"receipt_id\\\"], \\\"purchase_date\\\": r[\\\"purchase_date\\\"], \\\"store_name\\\": r[\\\"store_name\\\"], \\\"article_count\\\": int(r[\\\"article_count\\\"] or 0), \\\"total_text\\\": _fmt(r[\\\"total_value\\\"]), \\\"items\\\": items})\\n return {\\\"purpose\\\": \\\"migros_product_savings_grocery_optimizer_v1\\\", \\\"receipts\\\": receipts, \\\"supported_retailers\\\": sorted(SAFE_RETAILERS - {\\\"Migros\\\"}), \\\"health_analysis_status\\\": \\\"prepared_not_run\\\", \\\"disclaimer\\\": \\\"Keine medizinische Bewertung; keine automatische Bestellung.\\\"}\\n \\n@@ -105,6 +107,90 @@ def _matches(conn: Connection, product_item_id: str) -> list[dict[str, Any]]:\\n return [row_to_dict(r) for r in conn.execute(\\\"SELECT * FROM grocery_product_matches WHERE product_item_id=? ORDER BY CAST(match_confidence AS REAL) DESC\\\", (product_item_id,)).fetchall()]\\n \\n \\n+def _cache_status_for_url(conn: Connection, retailer: str, url: str) -> dict[str, Any]:\\n+ row = conn.execute(\\\"SELECT * FROM grocery_product_details_cache WHERE retailer=? AND product_url=? ORDER BY fetched_at DESC LIMIT 1\\\", (retailer, url)).fetchone()\\n+ if not row:\\n+ return {\\\"cache_status\\\": \\\"fehlt\\\", \\\"last_price_checked_at\\\": None}\\n+ data = row_to_dict(row)\\n+ try:\\n+ fetched = datetime.fromisoformat(str(data.get(\\\"fetched_at\\\")))\\n+ if fetched.tzinfo is None:\\n+ fetched = fetched.replace(tzinfo=timezone.utc)\\n+ age = (datetime.now(timezone.utc) - fetched).total_seconds()\\n+ status = \\\"frisch\\\" if age <= 86400 else \\\"veraltet\\\"\\n+ except Exception:\\n+ status = \\\"fehler\\\"\\n+ return {\\\"cache_status\\\": status, \\\"last_price_checked_at\\\": data.get(\\\"fetched_at\\\"), \\\"price_text\\\": data.get(\\\"price_text\\\"), \\\"unit_price_text\\\": data.get(\\\"unit_price_text\\\")}\\n+\\n+\\n+def known_mappings_for_item(conn: Connection, item: dict[str, Any], include_rejected: bool = False) -> list[dict[str, Any]]:\\n+ statuses = (\\\"accepted\\\", \\\"needs_review\\\", \\\"rejected\\\") if include_rejected else (\\\"accepted\\\", \\\"needs_review\\\")\\n+ rows = conn.execute(\\n+ f\\\"SELECT * FROM grocery_product_mappings WHERE source_retailer='Migros' AND source_product_normalized_name=? AND status IN ({','.join('?' for _ in statuses)}) ORDER BY status='accepted' DESC, CAST(confidence AS REAL) DESC, updated_at DESC\\\",\\n+ (item.get(\\\"normalized_product_name\\\"), *statuses),\\n+ ).fetchall()\\n+ mappings = []\\n+ for row in rows:\\n+ d = row_to_dict(row)\\n+ d.update(_cache_status_for_url(conn, d[\\\"target_retailer\\\"], d[\\\"target_product_url\\\"]))\\n+ mappings.append(d)\\n+ return mappings\\n+\\n+\\n+def _insert_mapping(conn: Connection, *, item: dict[str, Any], target_retailer: str, target_product_name: str, target_product_url: str, match_type: str, status: str, confidence: str = \\\"0.80\\\", user_note: str | None = None, source_match_id: str | None = None, target_brand: str | None = None, target_package_size: str | None = None, target_unit: str | None = None, target_price_text: str | None = None, target_unit_price_text: str | None = None, quality_flags: list[str] | None = None, last_price_checked_at: str | None = None) -> dict[str, Any]:\\n+ now = _now()\\n+ mapping_id = new_id(\\\"gmap\\\")\\n+ conn.execute(\\n+ \\\"\\\"\\\"INSERT INTO grocery_product_mappings(mapping_id,source_product_normalized_name,source_product_raw_name,source_retailer,target_retailer,target_product_name,target_product_url,target_brand,target_package_size,target_unit,target_price_text,target_unit_price_text,price_currency,match_type,status,confidence,user_note,source_match_id,quality_flags_json,health_analysis_status,health_flags_json,health_notes,created_at,updated_at,last_price_checked_at)\\n+ VALUES (?, ?, ?, 'Migros', ?, ?, ?, ?, ?, ?, ?, ?, 'CHF', ?, ?, ?, ?, ?, ?, 'prepared_not_run', '{}', ?, ?, ?, ?)\\\"\\\"\\\",\\n+ (mapping_id, item.get(\\\"normalized_product_name\\\"), item.get(\\\"raw_product_name\\\"), target_retailer, target_product_name, target_product_url, target_brand, target_package_size, target_unit, _fmt(target_price_text) if target_price_text else None, target_unit_price_text, match_type, status, confidence, user_note, source_match_id, json.dumps(quality_flags or [match_type]), \\\"Gesundheitsanalyse später\\\", now, now, last_price_checked_at),\\n+ )\\n+ conn.commit()\\n+ return row_to_dict(conn.execute(\\\"SELECT * FROM grocery_product_mappings WHERE mapping_id=?\\\", (mapping_id,)).fetchone())\\n+\\n+\\n+def accept_grocery_product_match(conn: Connection, match_id: str, *, user_note: str | None = None, save_as_preferred: bool = True) -> dict[str, Any]:\\n+ row = conn.execute(\\\"SELECT * FROM grocery_product_matches WHERE match_id=?\\\", (match_id,)).fetchone()\\n+ if not row:\\n+ raise ValueError(\\\"match_not_found\\\")\\n+ match = row_to_dict(row)\\n+ item = row_to_dict(conn.execute(\\\"SELECT * FROM grocery_product_items WHERE product_item_id=?\\\", (match[\\\"product_item_id\\\"],)).fetchone())\\n+ conn.execute(\\\"UPDATE grocery_product_matches SET status='accepted' WHERE match_id=?\\\", (match_id,))\\n+ mapping = _insert_mapping(conn, item=item, target_retailer=match[\\\"retailer\\\"], target_product_name=match[\\\"candidate_product_name\\\"], target_product_url=match[\\\"candidate_url\\\"], target_brand=match.get(\\\"candidate_brand\\\"), target_package_size=match.get(\\\"candidate_package_size\\\"), target_unit=match.get(\\\"candidate_unit\\\"), target_price_text=match.get(\\\"candidate_price_text\\\"), target_unit_price_text=match.get(\\\"candidate_unit_price_text\\\"), match_type=(json.loads(match.get(\\\"quality_flags_json\\\") or \\\"[]\\\") or [\\\"manual_match\\\"])[0], status=\\\"accepted\\\" if save_as_preferred else \\\"needs_review\\\", confidence=match.get(\\\"match_confidence\\\") or \\\"0.80\\\", user_note=user_note, source_match_id=match_id, quality_flags=json.loads(match.get(\\\"quality_flags_json\\\") or \\\"[]\\\"), last_price_checked_at=match.get(\\\"fetched_at\\\"))\\n+ return mapping\\n+\\n+\\n+def reject_grocery_product_match(conn: Connection, match_id: str, *, user_note: str | None = None) -> dict[str, Any]:\\n+ row = conn.execute(\\\"SELECT * FROM grocery_product_matches WHERE match_id=?\\\", (match_id,)).fetchone()\\n+ if not row:\\n+ raise ValueError(\\\"match_not_found\\\")\\n+ match = row_to_dict(row)\\n+ item = row_to_dict(conn.execute(\\\"SELECT * FROM grocery_product_items WHERE product_item_id=?\\\", (match[\\\"product_item_id\\\"],)).fetchone())\\n+ conn.execute(\\\"UPDATE grocery_product_matches SET status='rejected' WHERE match_id=?\\\", (match_id,))\\n+ mapping = _insert_mapping(conn, item=item, target_retailer=match[\\\"retailer\\\"], target_product_name=match[\\\"candidate_product_name\\\"], target_product_url=match[\\\"candidate_url\\\"], target_brand=match.get(\\\"candidate_brand\\\"), target_package_size=match.get(\\\"candidate_package_size\\\"), target_unit=match.get(\\\"candidate_unit\\\"), target_price_text=match.get(\\\"candidate_price_text\\\"), target_unit_price_text=match.get(\\\"candidate_unit_price_text\\\"), match_type=\\\"close_match\\\", status=\\\"rejected\\\", confidence=match.get(\\\"match_confidence\\\") or \\\"0.50\\\", user_note=user_note, source_match_id=match_id, quality_flags=json.loads(match.get(\\\"quality_flags_json\\\") or \\\"[]\\\"), last_price_checked_at=match.get(\\\"fetched_at\\\"))\\n+ return mapping\\n+\\n+\\n+def create_manual_grocery_mapping(conn: Connection, *, product_item_id: str, target_retailer: str, target_product_name: str, target_product_url: str, match_type: str = \\\"manual_match\\\", candidate_price_text: str | None = None, candidate_unit_price_text: str | None = None, target_brand: str | None = None, target_package_size: str | None = None, target_unit: str | None = None, user_note: str | None = None, confidence: str = \\\"0.95\\\") -> dict[str, Any]:\\n+ item = row_to_dict(conn.execute(\\\"SELECT * FROM grocery_product_items WHERE product_item_id=?\\\", (product_item_id,)).fetchone())\\n+ mapping = _insert_mapping(conn, item=item, target_retailer=target_retailer, target_product_name=target_product_name, target_product_url=target_product_url, target_brand=target_brand, target_package_size=target_package_size, target_unit=target_unit, target_price_text=candidate_price_text, target_unit_price_text=candidate_unit_price_text, match_type=match_type, status=\\\"accepted\\\", confidence=confidence, user_note=user_note, quality_flags=[match_type], last_price_checked_at=_now() if candidate_price_text else None)\\n+ if candidate_price_text:\\n+ upsert_product_match(conn, product_item_id, retailer=target_retailer, candidate_product_name=target_product_name, candidate_url=target_product_url, candidate_price_text=candidate_price_text, candidate_unit_price_text=candidate_unit_price_text, quality_flags=[match_type], match_confidence=confidence, status=\\\"accepted\\\", source=\\\"manual_mapping\\\", candidate_brand=target_brand, candidate_package_size=target_package_size, candidate_unit=target_unit)\\n+ return mapping\\n+\\n+\\n+def refresh_grocery_mapping_price(conn: Connection, mapping_id: str) -> dict[str, Any]:\\n+ row = conn.execute(\\\"SELECT * FROM grocery_product_mappings WHERE mapping_id=?\\\", (mapping_id,)).fetchone()\\n+ if not row:\\n+ raise ValueError(\\\"mapping_not_found\\\")\\n+ mapping = row_to_dict(row)\\n+ now = _now()\\n+ conn.execute(\\\"UPDATE grocery_product_mappings SET last_price_checked_at=?, updated_at=? WHERE mapping_id=?\\\", (now, now, mapping_id))\\n+ conn.commit()\\n+ mapping.update({\\\"last_price_checked_at\\\": now, \\\"cache_status\\\": _cache_status_for_url(conn, mapping[\\\"target_retailer\\\"], mapping[\\\"target_product_url\\\"])[\\\"cache_status\\\"]})\\n+ return mapping\\n+\\n+\\n def _safe_match(match: dict[str, Any]) -> bool:\\n flags = set(json.loads(match.get(\\\"quality_flags_json\\\") or \\\"[]\\\"))\\n return match.get(\\\"status\\\") in {\\\"suggested\\\", \\\"accepted\\\"} and flags <= SAFE_FLAGS and bool(flags & SAFE_FLAGS)\\n@@ -128,13 +214,17 @@ def run_grocery_optimization(conn: Connection, receipt_id: str, *, selected_reta\\n for item in items:\\n item_price = _money(item[\\\"total_price_text\\\"])\\n candidates = [m for m in _matches(conn, item[\\\"product_item_id\\\"]) if m[\\\"retailer\\\"] in selected]\\n+ for mapping in known_mappings_for_item(conn, item, include_rejected=False):\\n+ if mapping[\\\"status\\\"] == \\\"accepted\\\" and mapping[\\\"target_retailer\\\"] in selected and mapping.get(\\\"target_price_text\\\"):\\n+ candidates.append({\\\"match_id\\\": mapping[\\\"mapping_id\\\"], \\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": mapping[\\\"target_retailer\\\"], \\\"candidate_product_name\\\": mapping[\\\"target_product_name\\\"], \\\"candidate_url\\\": mapping[\\\"target_product_url\\\"], \\\"candidate_brand\\\": mapping.get(\\\"target_brand\\\"), \\\"candidate_package_size\\\": mapping.get(\\\"target_package_size\\\"), \\\"candidate_unit\\\": mapping.get(\\\"target_unit\\\"), \\\"candidate_price_text\\\": mapping.get(\\\"target_price_text\\\"), \\\"candidate_unit_price_text\\\": mapping.get(\\\"target_unit_price_text\\\"), \\\"match_confidence\\\": mapping.get(\\\"confidence\\\") or \\\"0.95\\\", \\\"quality_flags_json\\\": mapping.get(\\\"quality_flags_json\\\") or json.dumps([mapping.get(\\\"match_type\\\") or \\\"manual_match\\\"]), \\\"status\\\": \\\"accepted\\\", \\\"source\\\": \\\"known_mapping\\\"})\\n+ rejected_mappings = [m for m in conn.execute(\\\"SELECT * FROM grocery_product_mappings WHERE source_product_normalized_name=? AND status='rejected'\\\", (item.get(\\\"normalized_product_name\\\"),)).fetchall()]\\n safe = [m for m in candidates if _safe_match(m)]\\n best = min(safe, key=lambda m: _money(m[\\\"candidate_price_text\\\"]), default=None)\\n if best:\\n retailer_savings[best[\\\"retailer\\\"]] += max(Decimal(\\\"0.00\\\"), item_price - _money(best[\\\"candidate_price_text\\\"]))\\n elif candidates:\\n uncertain += 1\\n- item_options.append({\\\"item\\\": item, \\\"item_price\\\": item_price, \\\"candidates\\\": candidates, \\\"safe\\\": safe, \\\"best\\\": best})\\n+ item_options.append({\\\"item\\\": item, \\\"item_price\\\": item_price, \\\"candidates\\\": candidates, \\\"safe\\\": safe, \\\"best\\\": best, \\\"has_rejected\\\": bool(rejected_mappings)})\\n \\n allowed_retailers = set(r for r, _saving in sorted(retailer_savings.items(), key=lambda kv: kv[1], reverse=True)[:max_store_count])\\n comparisons = []\\n@@ -162,12 +252,14 @@ def run_grocery_optimization(conn: Connection, receipt_id: str, *, selected_reta\\n if original_best and original_best.get(\\\"retailer\\\") not in allowed_retailers:\\n status = \\\"not_selected_due_to_store_limit\\\"\\n flags = json.loads(original_best.get(\\\"quality_flags_json\\\") or \\\"[]\\\")\\n+ elif option.get(\\\"has_rejected\\\"):\\n+ status = \\\"rejected\\\"\\n elif option[\\\"candidates\\\"]:\\n status = \\\"needs_review\\\"\\n flags = json.loads(option[\\\"candidates\\\"][0].get(\\\"quality_flags_json\\\") or \\\"[]\\\")\\n comparisons.append({\\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"migros_product\\\": item[\\\"raw_product_name\\\"], \\\"migros_price_text\\\": _fmt(item_price), \\\"best_alternative\\\": best[\\\"candidate_product_name\\\"] if best else None, \\\"retailer\\\": best[\\\"retailer\\\"] if best else None, \\\"alternative_price_text\\\": _fmt(best[\\\"candidate_price_text\\\"]) if best else None, \\\"unit_price_text\\\": best.get(\\\"candidate_unit_price_text\\\") if best else None, \\\"savings_text\\\": _fmt(savings), \\\"confidence\\\": best.get(\\\"match_confidence\\\") if best else \\\"0\\\", \\\"status\\\": status, \\\"quality_flags\\\": flags, \\\"source_url\\\": best.get(\\\"candidate_url\\\") if best else None})\\n stores = sorted(by_store.items(), key=lambda kv: len(kv[1]), reverse=True)\\n- optimized_lists = [{\\\"variant\\\": \\\"max_3_stores\\\", \\\"store_count\\\": len(stores), \\\"stores\\\": [{\\\"retailer\\\": retailer, \\\"items\\\": rows} for retailer, rows in stores], \\\"not_found_products\\\": [c[\\\"migros_product\\\"] for c in comparisons if c[\\\"status\\\"] == \\\"not_found\\\"], \\\"needs_review_products\\\": [c[\\\"migros_product\\\"] for c in comparisons if c[\\\"status\\\"] == \\\"needs_review\\\"], \\\"store_limit_omitted_products\\\": [c[\\\"migros_product\\\"] for c in comparisons if c[\\\"status\\\"] == \\\"not_selected_due_to_store_limit\\\"]}]\\n+ optimized_lists = [{\\\"variant\\\": \\\"max_3_stores\\\", \\\"store_count\\\": len(stores), \\\"stores\\\": [{\\\"retailer\\\": retailer, \\\"items\\\": rows} for retailer, rows in stores], \\\"not_found_products\\\": [c[\\\"migros_product\\\"] for c in comparisons if c[\\\"status\\\"] == \\\"not_found\\\"], \\\"needs_review_products\\\": [c[\\\"migros_product\\\"] for c in comparisons if c[\\\"status\\\"] == \\\"needs_review\\\"], \\\"rejected_products\\\": [c[\\\"migros_product\\\"] for c in comparisons if c[\\\"status\\\"] == \\\"rejected\\\"], \\\"store_limit_omitted_products\\\": [c[\\\"migros_product\\\"] for c in comparisons if c[\\\"status\\\"] == \\\"not_selected_due_to_store_limit\\\"]}]\\n savings_total = max(Decimal(\\\"0.00\\\"), original - optimized)\\n quality = \\\"review_required\\\" if uncertain or any(c[\\\"status\\\"] != \\\"suggested\\\" for c in comparisons) else \\\"ok\\\"\\n run_id = new_id(\\\"grun\\\")\\n@@ -204,6 +296,9 @@ def generate_grocery_optimization_report(conn: Connection, run_id: str, *, repor\\n lines = [f\\\"# Migros Einkaufsoptimierung – {date}\\\", \\\"\\\", \\\"## Originalwarenkorb\\\", f\\\"- Artikel: {len(items)}\\\", f\\\"- Originaltotal: CHF {run['original_total_text']}\\\", \\\"\\\", \\\"## Optimierung\\\", f\\\"- Optimiertes Total: CHF {run['optimized_total_text']}\\\", f\\\"- Geschätzte Ersparnis: CHF {run['estimated_savings_text']}\\\", f\\\"- Qualität: {run['quality_status']}\\\", \\\"\\\", \\\"## Produkte ohne sichere Alternative\\\"]\\n lines += [f\\\"- {p}\\\" for p in summary.get(\\\"optimized_lists\\\", [{}])[0].get(\\\"not_found_products\\\", [])] or [\\\"- keine\\\"]\\n lines += [\\\"\\\", \\\"## Unsichere Matches\\\"] + ([f\\\"- {p}\\\" for p in summary.get(\\\"optimized_lists\\\", [{}])[0].get(\\\"needs_review_products\\\", [])] or [\\\"- keine\\\"])\\n+ lines += [\\\"\\\", \\\"## Bekannte Mappings\\\"]\\n+ mappings = conn.execute(\\\"SELECT * FROM grocery_product_mappings WHERE source_product_normalized_name IN (SELECT normalized_product_name FROM grocery_product_items WHERE receipt_id=?) ORDER BY status, target_retailer\\\", (run[\\\"receipt_id\\\"],)).fetchall()\\n+ lines += [f\\\"- {m['source_product_raw_name'] or m['source_product_normalized_name']} → {m['target_retailer']} · {m['target_product_name']} · {m['target_product_url']} · Status {m['status']} · Preiszeitpunkt {m['last_price_checked_at'] or 'fehlt'}\\\" for m in mappings] or [\\\"- keine\\\"]\\n lines += [\\\"\\\", \\\"## Quellen\\\", \\\"Alle Alternativen enthalten Quellen-URLs und Zeitstempel im lokalen Cache.\\\", \\\"\\\", \\\"## Disclaimer\\\", \\\"Preise können sich ändern. Produktgleichheit nicht garantiert. Verfügbarkeit nicht garantiert. Dies ist keine medizinische Empfehlung. Keine automatische Bestellung.\\\"]\\n path.write_text(\\\"\\\\n\\\".join(lines), encoding=\\\"utf-8\\\")\\n conn.execute(\\\"UPDATE grocery_optimization_runs SET report_path=? WHERE run_id=?\\\", (str(path), run_id)); conn.commit()\\ndiff --git a/src/jarvis_finance/services/grocery_price_providers.py b/src/jarvis_finance/services/grocery_price_providers.py\\nindex 31f6efa..739137b 100644\\n--- a/src/jarvis_finance/services/grocery_price_providers.py\\n+++ b/src/jarvis_finance/services/grocery_price_providers.py\\n@@ -13,7 +13,7 @@ from urllib.parse import quote_plus, urljoin\\n from urllib.request import Request, urlopen\\n \\n from jarvis_finance.services.budget_common import new_id, row_to_dict\\n-from jarvis_finance.services.grocery_optimizer import _items_for_receipt, upsert_product_match\\n+from jarvis_finance.services.grocery_optimizer import _items_for_receipt, upsert_product_match, known_mappings_for_item\\n \\n SAFE_MATCH_FLAGS = {\\\"exact_match\\\", \\\"close_match\\\", \\\"cheaper_private_label\\\"}\\n UNSAFE_FLAGS = {\\\"needs_review\\\", \\\"no_price\\\", \\\"no_unit_price\\\", \\\"different_pack_size\\\", \\\"different_quality\\\", \\\"organic_mismatch\\\"}\\n@@ -296,7 +296,7 @@ def compare_product_prices(*, original_price_text: str, candidate_price_text: st\\n return {\\\"can_calculate_savings\\\": False, \\\"savings_text\\\": \\\"0.00\\\", \\\"basis\\\": \\\"none\\\", \\\"quality_flags\\\": flags}\\n \\n \\n-def search_and_store_product_matches(conn: Connection, receipt_id: str, *, providers: list[GroceryProductProvider], included_product_item_ids: list[str] | None = None, max_products: int = 5, use_cache: bool = True, only_safe_matches: bool = True) -> dict[str, Any]:\\n+def search_and_store_product_matches(conn: Connection, receipt_id: str, *, providers: list[GroceryProductProvider], included_product_item_ids: list[str] | None = None, max_products: int = 5, use_cache: bool = True, only_safe_matches: bool = True, prefer_known_mappings: bool = True) -> dict[str, Any]:\\n items = _items_for_receipt(conn, receipt_id)\\n if included_product_item_ids is not None:\\n allowed = set(included_product_item_ids)\\n@@ -305,8 +305,21 @@ def search_and_store_product_matches(conn: Connection, receipt_id: str, *, provi\\n matches: list[dict[str, Any]] = []\\n provider_calls = 0\\n cache_hits = 0\\n+ known_mapping_hits = 0\\n for item in items:\\n query = item.get(\\\"normalized_product_name\\\") or item.get(\\\"raw_product_name\\\")\\n+ if prefer_known_mappings:\\n+ accepted = [m for m in known_mappings_for_item(conn, item, include_rejected=False) if m.get(\\\"status\\\") == \\\"accepted\\\"]\\n+ if accepted:\\n+ for m in accepted:\\n+ matches.append({\\\"mapping_id\\\": m[\\\"mapping_id\\\"], \\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": m[\\\"target_retailer\\\"], \\\"product_name\\\": m[\\\"target_product_name\\\"], \\\"product_url\\\": m[\\\"target_product_url\\\"], \\\"price_text\\\": m.get(\\\"target_price_text\\\"), \\\"unit_price_text\\\": m.get(\\\"target_unit_price_text\\\"), \\\"source_fetched_at\\\": m.get(\\\"last_price_checked_at\\\"), \\\"fetched_at\\\": m.get(\\\"updated_at\\\"), \\\"quality_flags\\\": json.loads(m.get(\\\"quality_flags_json\\\") or \\\"[]\\\"), \\\"confidence\\\": m.get(\\\"confidence\\\"), \\\"status\\\": \\\"suggested\\\" if m.get(\\\"target_price_text\\\") else \\\"needs_review\\\", \\\"source\\\": \\\"known_mapping\\\", \\\"cache_status\\\": m.get(\\\"cache_status\\\")})\\n+ known_mapping_hits += 1\\n+ continue\\n+ rejected = conn.execute(\\\"SELECT 1 FROM grocery_product_mappings WHERE source_product_normalized_name=? AND status='rejected' LIMIT 1\\\", (item.get(\\\"normalized_product_name\\\"),)).fetchone()\\n+ if rejected:\\n+ matches.append({\\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": None, \\\"product_name\\\": item.get(\\\"raw_product_name\\\"), \\\"status\\\": \\\"rejected\\\", \\\"quality_flags\\\": [\\\"rejected\\\"], \\\"source\\\": \\\"known_mapping\\\"})\\n+ known_mapping_hits += 1\\n+ continue\\n for provider in providers:\\n before = provider.request_count\\n results = provider.search_products(conn, query, use_cache=use_cache, max_results=3)\\n@@ -324,5 +337,5 @@ def search_and_store_product_matches(conn: Connection, receipt_id: str, *, provi\\n matches.append({\\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": result.get(\\\"retailer\\\"), \\\"product_name\\\": result.get(\\\"product_name\\\"), \\\"product_url\\\": result.get(\\\"product_url\\\"), \\\"price_text\\\": result.get(\\\"price_decimal_text\\\") or result.get(\\\"price_text\\\"), \\\"unit_price_text\\\": result.get(\\\"unit_price_text\\\"), \\\"source_fetched_at\\\": result.get(\\\"fetched_at\\\"), \\\"fetched_at\\\": result.get(\\\"fetched_at\\\"), \\\"quality_flags\\\": comparison[\\\"quality_flags\\\"], \\\"confidence\\\": result.get(\\\"confidence\\\"), \\\"status\\\": status, \\\"source\\\": result.get(\\\"source\\\")})\\n continue\\n stored = upsert_product_match(conn, item[\\\"product_item_id\\\"], retailer=result[\\\"retailer\\\"], candidate_product_name=result[\\\"product_name\\\"], candidate_url=result[\\\"product_url\\\"], candidate_price_text=result.get(\\\"price_decimal_text\\\") or result.get(\\\"price_text\\\") or \\\"0\\\", candidate_unit_price_text=result.get(\\\"unit_price_text\\\"), quality_flags=comparison[\\\"quality_flags\\\"], match_confidence=result.get(\\\"confidence\\\") or \\\"0.60\\\", status=status, source=result.get(\\\"source\\\") or \\\"web_fetch\\\", candidate_brand=result.get(\\\"brand\\\"), candidate_package_size=result.get(\\\"package_size\\\"), candidate_unit=result.get(\\\"unit\\\"))\\n- matches.append({\\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": result[\\\"retailer\\\"], \\\"product_name\\\": result[\\\"product_name\\\"], \\\"product_url\\\": result[\\\"product_url\\\"], \\\"price_text\\\": result.get(\\\"price_decimal_text\\\") or result.get(\\\"price_text\\\"), \\\"unit_price_text\\\": result.get(\\\"unit_price_text\\\"), \\\"source_fetched_at\\\": result.get(\\\"fetched_at\\\"), \\\"fetched_at\\\": stored.get(\\\"fetched_at\\\"), \\\"quality_flags\\\": comparison[\\\"quality_flags\\\"], \\\"confidence\\\": result.get(\\\"confidence\\\"), \\\"status\\\": status, \\\"source\\\": result.get(\\\"source\\\")})\\n- return {\\\"receipt_id\\\": receipt_id, \\\"provider_calls\\\": provider_calls, \\\"cache_hits\\\": cache_hits, \\\"matches\\\": matches}\\n+ matches.append({\\\"match_id\\\": stored.get(\\\"match_id\\\"), \\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": result[\\\"retailer\\\"], \\\"product_name\\\": result[\\\"product_name\\\"], \\\"product_url\\\": result[\\\"product_url\\\"], \\\"price_text\\\": result.get(\\\"price_decimal_text\\\") or result.get(\\\"price_text\\\"), \\\"unit_price_text\\\": result.get(\\\"unit_price_text\\\"), \\\"source_fetched_at\\\": result.get(\\\"fetched_at\\\"), \\\"fetched_at\\\": stored.get(\\\"fetched_at\\\"), \\\"quality_flags\\\": comparison[\\\"quality_flags\\\"], \\\"confidence\\\": result.get(\\\"confidence\\\"), \\\"status\\\": status, \\\"source\\\": result.get(\\\"source\\\")})\\n+ return {\\\"receipt_id\\\": receipt_id, \\\"provider_calls\\\": provider_calls, \\\"cache_hits\\\": cache_hits, \\\"known_mapping_hits\\\": known_mapping_hits, \\\"matches\\\": matches}\\ndiff --git a/src/jarvis_finance/storage/migrations.py b/src/jarvis_finance/storage/migrations.py\\nindex 9f985eb..3ffac3e 100644\\n--- a/src/jarvis_finance/storage/migrations.py\\n+++ b/src/jarvis_finance/storage/migrations.py\\n@@ -6,8 +6,8 @@ from sqlite3 import Connection\\n \\n from .schema import INITIAL_SCHEMA_SQL\\n \\n-MIGRATION_VERSION = 33\\n-MIGRATION_NAME = \\\"033_grocery_product_price_providers_v1\\\"\\n+MIGRATION_VERSION = 34\\n+MIGRATION_NAME = \\\"034_grocery_matching_review_learning_v2\\\"\\n \\n INSTRUMENT_OPTIONAL_COLUMNS = {\\n \\\"position_category\\\": \\\"TEXT\\\",\\n@@ -1337,6 +1337,42 @@ def _add_grocery_price_provider_v1_columns(conn: Connection) -> None:\\n conn.execute(f\\\"ALTER TABLE grocery_product_details_cache ADD COLUMN {name} {col_type}\\\")\\n \\n \\n+def _create_grocery_matching_learning_v2_tables(conn: Connection) -> None:\\n+ conn.executescript(\\n+ \\\"\\\"\\\"\\n+ CREATE TABLE IF NOT EXISTS grocery_product_mappings (\\n+ mapping_id TEXT PRIMARY KEY,\\n+ source_product_normalized_name TEXT NOT NULL,\\n+ source_product_raw_name TEXT,\\n+ source_retailer TEXT NOT NULL DEFAULT 'Migros',\\n+ target_retailer TEXT NOT NULL,\\n+ target_product_name TEXT NOT NULL,\\n+ target_product_url TEXT NOT NULL,\\n+ target_brand TEXT,\\n+ target_package_size TEXT,\\n+ target_unit TEXT,\\n+ target_price_text TEXT,\\n+ target_unit_price_text TEXT,\\n+ price_currency TEXT NOT NULL DEFAULT 'CHF',\\n+ match_type TEXT NOT NULL,\\n+ status TEXT NOT NULL DEFAULT 'needs_review',\\n+ confidence TEXT NOT NULL DEFAULT '0',\\n+ user_note TEXT,\\n+ source_match_id TEXT,\\n+ quality_flags_json TEXT NOT NULL DEFAULT '[]',\\n+ health_analysis_status TEXT NOT NULL DEFAULT 'prepared_not_run',\\n+ health_flags_json TEXT NOT NULL DEFAULT '{}',\\n+ health_notes TEXT,\\n+ created_at TEXT NOT NULL,\\n+ updated_at TEXT NOT NULL,\\n+ last_price_checked_at TEXT\\n+ );\\n+ CREATE INDEX IF NOT EXISTS idx_grocery_mappings_source ON grocery_product_mappings(source_product_normalized_name, source_retailer, status);\\n+ CREATE INDEX IF NOT EXISTS idx_grocery_mappings_target ON grocery_product_mappings(target_retailer, target_product_url, status);\\n+ \\\"\\\"\\\"\\n+ )\\n+\\n+\\n def _apply_compat_migrations(conn: Connection) -> None:\\n _add_missing_instrument_columns(conn)\\n for table, text_columns in TEXT_AFFINITY_COLUMNS.items():\\n@@ -1360,6 +1396,7 @@ def _apply_compat_migrations(conn: Connection) -> None:\\n _create_budget_monthly_import_rule_learning_v1_tables(conn)\\n _create_grocery_optimizer_v1_tables(conn)\\n _add_grocery_price_provider_v1_columns(conn)\\n+ _create_grocery_matching_learning_v2_tables(conn)\\n \\n \\n def apply_migrations(conn: Connection) -> None:\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_3jFBy3ulE842zGuMywQhpb79"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Investigating context and functions**\n\nI think I need more context on the full functions and perhaps a report on the schema. There might also be untracked tests documented that require inspection. I should check for any secrets or artifacts too. It would be helpful to use git status to see the names and maybe create some search patterns to examine everything thoroughly. I’m curious about what I might uncover!",
"finish_reason": "tool_calls",
"reasoning_content": "**Investigating context and functions**\n\nI think I need more context on the full functions and perhaps a report on the schema. There might also be untracked tests documented that require inspection. I should check for any secrets or artifacts too. It would be helpful to use git status to see the names and maybe create some search patterns to examine everything thoroughly. I’m curious about what I might uncover!",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABqDGF62jcIno2G2XNBLeoX1HLi2uRq2F4jc9cGtpJv1KcFarHHrH5m0Frn1HRauzyTPY7UWsX8ZHFoz873mu227ybNf4o1bwz5YWPnf3PD0Nldab4wo3VyhM7W6GFoy8iKI3qQefcbQO_wf1FPMTOIQRvmW4Mw-66PdVGef_yy8Ggr0RtFu4ReBkONdJxOTAu1Ee2oRnpQtfWiPEPZTo8UoyrnzKtQUPf3d4lnx5RginObcOhh7tBgB1Wp1f2HMjLMAhVYKCty7hnmLc39ShCInYw47kIyAvmUIacJKfoDrcviKzXJBY3chYkqkFo40jCy1HpHFWvHGl9eSsVxf8sZiUUAz_pZoEt6tPpwt08G1pzX79o4gnGlSjyERXzN9FPBVm1vaiZV6Hg1lk52WIiYbN0TgrXwdq1jOlwZHHrxjllgdiJCLJxEtchhOG4RGcBaVDQ6TBk22YMXQJ--swuYnmRESMU289bTGXQgvcsIv4_WfBvVD_VZpG7A-_lUANK7FVVx543BTGRfPmngaU4FHYqeiAJLyRrcCfr_LqnkI58kammFCnl85NWvJqZtNM8GlB5tTLCpYCACPtgADIaOssbDz9unIrg1ZDemvDCMmV2nIE1BuIkS5dDh_YdqoKm2C158DWzkd8HlXrD2rgTdjrKC2w3ZY-d1uFvqsF85V9KfV2AALvWDYH-UCd4ihuEp8pdtiw2vFP3HEcnegc10Tq0Cy9h4o7iz4kUoKp9Tv8d2kJ5q4x3Y-iXZEi6KRKiP0w2n7ao1b4SWKLP5an2O4h3en3Mi_0lBt_5L6UDLhlrpD2zkZVkww8wUZtTQHkC_Tw5wH3I_WLELsQDH-qCBQwB1R5kQwuYE1nYzQfA0DEjn1YRTLMYppBtYG5ZDU7k8oPIeHbr4-cyvYlWMoLjdQCO-AAP6HUM_RB9Bwb1jaUQJptXBdjJjKjfKu5OTjexpPVOu1intoRW3FVPuE8JQaH6EC3hSb9uKphi-tF3N71B3BOHBDuu5Z_fn7gz9lEFySBCqT82CXmT7H_niLh7DrSQAuRM8Gd_FWDbSzfoFrrPBp5U-riBSG8wngqPzj_8U_-x-4NlMIi0QFVnw5w0hfBxst6YjmFBEKp_BtyTWELAKsVXV0dSoNtmoGZ6cMgW5CvN0",
"id": "rs_036558bf15c99fac016a0c6178872481919969ba2c43e55df8",
"summary": [
{
"type": "summary_text",
"text": "**Investigating context and functions**\n\nI think I need more context on the full functions and perhaps a report on the schema. There might also be untracked tests documented that require inspection. I should check for any secrets or artifacts too. It would be helpful to use git status to see the names and maybe create some search patterns to examine everything thoroughly. I’m curious about what I might uncover!"
}
]
}
],
"tool_calls": [
{
"id": "call_BidZIXCGeAb4j9ENnJmJ9PvS",
"call_id": "call_BidZIXCGeAb4j9ENnJmJ9PvS",
"response_item_id": "fc_036558bf15c99fac016a0c617ac5cc81918ceed9ccb8091781",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"python3 - <<'PY'\\nfrom pathlib import Path\\nfiles=[\\n'src/jarvis_finance/services/grocery_optimizer.py',\\n'src/jarvis_finance/services/grocery_price_providers.py',\\n'src/jarvis_finance/api/routers/budget.py',\\n'frontend/src/pages/BudgetGroceryOptimizerPage.vue',\\n'docs/grocery/product-matching-learning-v2.md',\\n'tests/unit/test_grocery_matching_learning_v2.py',\\n'frontend/src/pages/GroceryMatchingLearningV2.test.ts',\\n]\\nfor f in files:\\n print('\\\\n---',f,'---')\\n p=Path(f)\\n if p.exists():\\n text=p.read_text(errors='replace')\\n for i,line in enumerate(text.splitlines(),1):\\n if any(s in line.lower() for s in ['grocery_product_mappings','known_mappings','search_and_store_product_matches','accept_grocery','reject_grocery','manual','refresh_grocery','report','provider','medical','health','histamine','behcet','secret','api_key','password','token']):\\n print(f'{i}: {line[:240]}')\\n else: print('missing')\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"--- src/jarvis_finance/services/grocery_optimizer.py ---\\n17: SAFE_FLAGS = {\\\"exact_match\\\", \\\"close_match\\\", \\\"cheaper_private_label\\\", \\\"manual_match\\\"}\\n58: \\\"\\\"\\\"INSERT INTO grocery_product_items(product_item_id,source_type,receipt_id,receipt_key,source_line_id,purchase_date,store_name,raw_product_name,normalized_product_name,normalization_confidence,brand_hint,quantity_hint,quantity_\\n79: item[\\\"known_mappings\\\"] = known_mappings_for_item(conn, item, include_rejected=True)\\n81: return {\\\"purpose\\\": \\\"migros_product_savings_grocery_optimizer_v1\\\", \\\"receipts\\\": receipts, \\\"supported_retailers\\\": sorted(SAFE_RETAILERS - {\\\"Migros\\\"}), \\\"health_analysis_status\\\": \\\"prepared_not_run\\\", \\\"disclaimer\\\": \\\"Keine medizinische Bewertun\\n84: def upsert_product_match(conn: Connection, product_item_id: str, *, retailer: str, candidate_product_name: str, candidate_url: str, candidate_price_text: str, candidate_unit_price_text: str | None = None, quality_flags: list[str] | None = N\\n126: def known_mappings_for_item(conn: Connection, item: dict[str, Any], include_rejected: bool = False) -> list[dict[str, Any]]:\\n129: f\\\"SELECT * FROM grocery_product_mappings WHERE source_retailer='Migros' AND source_product_normalized_name=? AND status IN ({','.join('?' for _ in statuses)}) ORDER BY status='accepted' DESC, CAST(confidence AS REAL) DESC, updated_a\\n144: \\\"\\\"\\\"INSERT INTO grocery_product_mappings(mapping_id,source_product_normalized_name,source_product_raw_name,source_retailer,target_retailer,target_product_name,target_product_url,target_brand,target_package_size,target_unit,target_pri\\n149: return row_to_dict(conn.execute(\\\"SELECT * FROM grocery_product_mappings WHERE mapping_id=?\\\", (mapping_id,)).fetchone())\\n152: def accept_grocery_product_match(conn: Connection, match_id: str, *, user_note: str | None = None, save_as_preferred: bool = True) -> dict[str, Any]:\\n159: mapping = _insert_mapping(conn, item=item, target_retailer=match[\\\"retailer\\\"], target_product_name=match[\\\"candidate_product_name\\\"], target_product_url=match[\\\"candidate_url\\\"], target_brand=match.get(\\\"candidate_brand\\\"), target_package_size\\n163: def reject_grocery_product_match(conn: Connection, match_id: str, *, user_note: str | None = None) -> dict[str, Any]:\\n174: def create_manual_grocery_mapping(conn: Connection, *, product_item_id: str, target_retailer: str, target_product_name: str, target_product_url: str, match_type: str = \\\"manual_match\\\", candidate_price_text: str | None = None, candidate_unit_\\n178: upsert_product_match(conn, product_item_id, retailer=target_retailer, candidate_product_name=target_product_name, candidate_url=target_product_url, candidate_price_text=candidate_price_text, candidate_unit_price_text=candidate_unit_\\n182: def refresh_grocery_mapping_price(conn: Connection, mapping_id: str) -> dict[str, Any]:\\n183: row = conn.execute(\\\"SELECT * FROM grocery_product_mappings WHERE mapping_id=?\\\", (mapping_id,)).fetchone()\\n188: conn.execute(\\\"UPDATE grocery_product_mappings SET last_price_checked_at=?, updated_at=? WHERE mapping_id=?\\\", (now, now, mapping_id))\\n217: for mapping in known_mappings_for_item(conn, item, include_rejected=False):\\n219: candidates.append({\\\"match_id\\\": mapping[\\\"mapping_id\\\"], \\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": mapping[\\\"target_retailer\\\"], \\\"candidate_product_name\\\": mapping[\\\"target_product_name\\\"], \\\"candidate_url\\\": mapping[\\\"ta\\n220: rejected_mappings = [m for m in conn.execute(\\\"SELECT * FROM grocery_product_mappings WHERE source_product_normalized_name=? AND status='rejected'\\\", (item.get(\\\"normalized_product_name\\\"),)).fetchall()]\\n269: return {\\\"run_id\\\": run_id, \\\"receipt_id\\\": receipt_id, \\\"max_store_count\\\": max_store_count, \\\"original_total_text\\\": _fmt(original), \\\"optimized_total_text\\\": _fmt(optimized), \\\"quality_status\\\": quality, \\\"summary\\\": summary, \\\"optimized_lists\\\": op\\n279: def generate_grocery_optimization_report(conn: Connection, run_id: str, *, reports_dir: Path | None = None, repo_root: Path | None = None) -> dict[str, Any]:\\n281: if reports_dir is None:\\n282: reports_dir = load_settings(repo_root=repo).runtime_paths.reports_dir / \\\"grocery_optimizer\\\"\\n283: reports_dir = reports_dir.resolve()\\n284: if not _outside_repo(reports_dir, repo):\\n285: raise ValueError(\\\"reports_dir_must_be_outside_repo\\\")\\n292: reports_dir.mkdir(parents=True, exist_ok=True)\\n293: path = (reports_dir / f\\\"migros_einkaufsoptimierung_{date}_{run_id}.md\\\").resolve()\\n294: if reports_dir not in path.parents:\\n295: raise ValueError(\\\"report_path_must_stay_under_runtime_reports_dir\\\")\\n300: mappings = conn.execute(\\\"SELECT * FROM grocery_product_mappings WHERE source_product_normalized_name IN (SELECT normalized_product_name FROM grocery_product_items WHERE receipt_id=?) ORDER BY status, target_retailer\\\", (run[\\\"receipt_id\\\"]\\n304: conn.execute(\\\"UPDATE grocery_optimization_runs SET report_path=? WHERE run_id=?\\\", (str(path), run_id)); conn.commit()\\n305: return {\\\"run_id\\\": run_id, \\\"format\\\": \\\"markdown\\\", \\\"report_path\\\": str(path), \\\"runtime_only\\\": True}\\n\\n--- src/jarvis_finance/services/grocery_price_providers.py ---\\n16: from jarvis_finance.services.grocery_optimizer import _items_for_receipt, upsert_product_match, known_mappings_for_item\\n48: class GroceryProviderRateLimitError(RuntimeError):\\n53: class GroceryProviderResult:\\n107: class GroceryProductProvider:\\n126: raise GroceryProviderRateLimitError(\\\"rate_limited\\\")\\n132: raise GroceryProviderRateLimitError(\\\"rate_limited\\\")\\n135: def normalize_result(self, raw_result: dict[str, Any]) -> GroceryProviderResult:\\n136: return GroceryProviderResult(retailer=self.retailer, **raw_result)\\n160: return f\\\"provider-search://{self.retailer}/{quote_plus(query.lower().strip())}\\\"\\n200: except GroceryProviderRateLimitError:\\n203: return [{\\\"retailer\\\": self.retailer, \\\"query\\\": query, \\\"status\\\": \\\"needs_review\\\", \\\"quality_flags\\\": [\\\"provider_error\\\", \\\"needs_review\\\"], \\\"error\\\": type(exc).__name__, \\\"source\\\": \\\"web_fetch\\\", \\\"fetched_at\\\": _now()}]\\n211: class MigrosProvider(GroceryProductProvider):\\n219: class CoopProvider(GroceryProductProvider):\\n227: class AldiSuisseProvider(GroceryProductProvider):\\n229: future_status = \\\"skeleton_provider_not_live\\\"\\n232: class LidlSchweizProvider(GroceryProductProvider):\\n234: future_status = \\\"skeleton_provider_not_live\\\"\\n237: class DennerProvider(GroceryProductProvider):\\n239: future_status = \\\"skeleton_provider_not_live\\\"\\n242: class OttosProvider(GroceryProductProvider):\\n244: future_status = \\\"skeleton_provider_not_live\\\"\\n247: def provider_for_retailer(retailer: str) -> GroceryProductProvider:\\n248: mapping: dict[str, type[GroceryProductProvider]] = {\\\"Migros\\\": MigrosProvider, \\\"Coop\\\": CoopProvider, \\\"Aldi Suisse\\\": AldiSuisseProvider, \\\"Lidl\\\": LidlSchweizProvider, \\\"Denner\\\": DennerProvider, \\\"Otto's\\\": OttosProvider}\\n249: return mapping.get(retailer, GroceryProductProvider)()\\n262: elif any(token in candidate for token in original.split()[:2]):\\n299: def search_and_store_product_matches(conn: Connection, receipt_id: str, *, providers: list[GroceryProductProvider], included_product_item_ids: list[str] | None = None, max_products: int = 5, use_cache: bool = True, only_safe_matches: bool =\\n306: provider_calls = 0\\n311: if prefer_known_mappings:\\n312: accepted = [m for m in known_mappings_for_item(conn, item, include_rejected=False) if m.get(\\\"status\\\") == \\\"accepted\\\"]\\n318: rejected = conn.execute(\\\"SELECT 1 FROM grocery_product_mappings WHERE source_product_normalized_name=? AND status='rejected' LIMIT 1\\\", (item.get(\\\"normalized_product_name\\\"),)).fetchone()\\n323: for provider in providers:\\n324: before = provider.request_count\\n325: results = provider.search_products(conn, query, use_cache=use_cache, max_results=3)\\n326: provider_calls += max(0, provider.request_count - before)\\n341: return {\\\"receipt_id\\\": receipt_id, \\\"provider_calls\\\": provider_calls, \\\"cache_hits\\\": cache_hits, \\\"known_mapping_hits\\\": known_mapping_hits, \\\"matches\\\": matches}\\n\\n--- src/jarvis_finance/api/routers/budget.py ---\\n84: confirm_manual_recurring_payment,\\n88: preview_manual_recurring_payment,\\n103: accept_grocery_product_match,\\n105: create_manual_grocery_mapping,\\n106: generate_grocery_optimization_report,\\n108: refresh_grocery_mapping_price,\\n109: reject_grocery_product_match,\\n113: from jarvis_finance.services.grocery_price_providers import provider_for_retailer, search_and_store_product_matches\\n168: return upsert_product_match(conn, payload[\\\"product_item_id\\\"], retailer=payload[\\\"retailer\\\"], candidate_product_name=payload[\\\"candidate_product_name\\\"], candidate_url=payload.get(\\\"candidate_url\\\") or \\\"https://example.invalid/review\\\", candid\\n174: return accept_grocery_product_match(conn, match_id, user_note=payload.get(\\\"user_note\\\"), save_as_preferred=bool(payload.get(\\\"save_as_preferred\\\", True)))\\n179: return reject_grocery_product_match(conn, match_id, user_note=(payload or {}).get(\\\"user_note\\\"))\\n182: @router.post(\\\"/grocery-optimizer/manual-mapping\\\")\\n183: def grocery_optimizer_manual_mapping(payload: dict, conn: Connection = Depends(get_db)):\\n184: return create_manual_grocery_mapping(conn, product_item_id=payload[\\\"product_item_id\\\"], target_retailer=payload[\\\"target_retailer\\\"], target_product_name=payload[\\\"target_product_name\\\"], target_product_url=payload[\\\"target_product_url\\\"], tar\\n189: return refresh_grocery_mapping_price(conn, mapping_id)\\n200: providers = [provider_for_retailer(retailer) for retailer in retailers]\\n201: return search_and_store_product_matches(\\n204: providers=providers,\\n209: prefer_known_mappings=bool(payload.get(\\\"prefer_known_mappings\\\", True)),\\n213: @router.post(\\\"/grocery-optimizer/report\\\")\\n214: def grocery_optimizer_report(payload: dict, conn: Connection = Depends(get_db)):\\n215: return generate_grocery_optimization_report(conn, payload[\\\"run_id\\\"])\\n304: @router.post(\\\"/recurring/manual/preview\\\")\\n305: def recurring_manual_preview(payload: dict, conn: Connection = Depends(get_db)):\\n306: return preview_manual_recurring_payment(conn, payload)\\n309: @router.post(\\\"/recurring/manual/confirm\\\")\\n310: def recurring_manual_confirm(payload: dict, conn: Connection = Depends(get_db)):\\n311: return confirm_manual_recurring_payment(conn, payload)\\n\\n--- frontend/src/pages/BudgetGroceryOptimizerPage.vue ---\\n12:
Report erzeugen \\n14:
Gesundheitsanalyse später: health_analysis_status ist vorbereitet, aber Histamin/Behçet/Trigger werden in v1 nicht bewertet.
\\n38:
\\n40:
\\n62:
Provider werden nur nach Klick auf „Preise online suchen“ aufgerufen. Keine Provider-Calls beim Seiten-Rendern.
\\n84:
Coop Denner Aldi Suisse Lidl Otto's \\n86: manual_match exact_match close_match cheaper_private_label Als bevorzugte Alternative speichern \\n115: {{ reportMessage }}
\\n121: import { acceptGroceryProductMatch, addGroceryProductMatch, createGroceryDemoReceipt, generateGroceryOptimizationReport, getGroceryOptimizerDashboard, refreshGroceryMappingPrice, rejectGroceryProductMatch, runGroceryOptimization, saveManual\\n130: const manualRetailer = ref('Coop')\\n131: const manualName = ref('')\\n132: const manualUrl = ref('')\\n133: const manualPrice = ref('')\\n134: const manualUnitPrice = ref('')\\n135: const manualMatchType = ref('manual_match')\\n136: const reportMessage = ref('')\\n142: reportMessage.value = ''\\n152: const result = await searchGroceryOnlinePrices({ receipt_id: selectedReceipt.value.receipt_id, retailers: selectedRetailers.value, included_product_item_ids, use_cache: useCache.value, max_products: 5, max_retailers: Math.min(3, selectedR\\n158: if (item.normalized_product_name === 'milch' && includedItems.value[item.product_item_id]) await addGroceryProductMatch({ product_item_id: item.product_item_id, retailer: 'Coop', candidate_product_name: 'Prix Garantie Milch 1L', candida\\n163: async function acceptMatch(match: GroceryOnlinePriceMatch) { if (!match.match_id) return; await acceptGroceryProductMatch({ match_id: match.match_id, save_as_preferred: true }); reportMessage.value = 'Mapping akzeptiert und gespeichert'; aw\\n164: async function rejectMatch(match: GroceryOnlinePriceMatch) { if (!match.match_id) return; await rejectGroceryProductMatch({ match_id: match.match_id }); onlineMatches.value = onlineMatches.value.filter((m) => m.match_id !== match.match_id);\\n165: async function refreshMapping(mapping_id: string) { await refreshGroceryMappingPrice({ mapping_id }); reportMessage.value = 'Preisaktualisierung angefragt'; await load() }\\n166: async function saveManualMapping() {\\n170: await saveManualGroceryMapping({ product_item_id: firstIncluded.product_item_id, target_retailer: manualRetailer.value, target_product_name: manualName.value, target_product_url: manualUrl.value, candidate_price_text: manualPrice.value ||\\n171: reportMessage.value = 'Manuelles Mapping gespeichert'\\n174: async function createReport() { if (!run.value) return; const result = await generateGroceryOptimizationReport({ run_id: run.value.run_id }); reportMessage.value = `Runtime-only Report erstellt: ${(result as any).format || 'markdown'}` }\\n176: defineExpose({ dashboard, selectedReceipt, includedItems, selectedRetailers, useCache, onlySafeMatches, onlineMatches, run, load, selectReceipt, seedDemo, searchOnlinePrices, startAnalysis, acceptMatch, rejectMatch, refreshMapping, saveManu\\n\\n--- docs/grocery/product-matching-learning-v2.md ---\\n1: # Grocery Optimizer Provider & Matching Learning v2 Notes\\n7: ## Provider-Status v2\\n9: - Coop: v1 Provider bleibt kontrolliert und explizit ausgelöst; Parser/Cache sind testbar. Für produktive breite Nutzung weiterhin nur Low-volume und cache-first.\\n10: - Migros: v1 Provider bleibt kontrolliert und explizit ausgelöst. Der Migros-Bon ist Quelle für Originalprodukte; Live-Migros-Produktseiten sind nicht zwingend für Savings-Mapping.\\n18: Akzeptierte Matches werden in `grocery_product_mappings` gespeichert und beim nächsten Bon bevorzugt. Abgelehnte Matches werden ebenfalls dauerhaft gespeichert und blockieren erneute Vorschläge, außer ein späterer Reset-/Archiv-Flow wird ex\\n\\n--- tests/unit/test_grocery_matching_learning_v2.py ---\\n11: accept_grocery_product_match,\\n12: reject_grocery_product_match,\\n13: create_manual_grocery_mapping,\\n16: generate_grocery_optimization_report,\\n18: from jarvis_finance.services.grocery_price_providers import search_and_store_product_matches, CoopProvider\\n33: def test_accept_match_creates_preferred_mapping_and_next_receipt_reuses_without_provider_call() -> None:\\n36: provider = CoopProvider(fetcher=lambda _url: 'Prix Garantie Milch 1L CHF 1.20 1.20/l Coop Milch 1L CHF 1.20 1.20/l ]*data-product[^>]*>(.*?)\\\", html_text, flags=re.I | re.S) or [html_text]\\n140: results: list[dict[str, Any]] = []\\n141: for chunk in chunks[:5]:\\n142: link = re.search(r\\\"]+href=[\\\\\\\"']([^\\\\\\\"']+)[\\\\\\\"'][^>]*>(.*?)\\\", chunk, flags=re.I | re.S)\\n143: price = re.search(r\\\"class=[\\\\\\\"'][^\\\\\\\"']*price[^\\\\\\\"']*[\\\\\\\"'][^>]*>(.*?)]*>(.*?)]*>(.*?)]+>\\\", \\\"\\\", link.group(2)).strip()\\n149: results.append({\\n150: \\\"product_name\\\": html.unescape(name),\\n151: \\\"product_url\\\": _abs_url(self.base_url, link.group(1)),\\n152: \\\"price_text\\\": re.sub(r\\\"<[^>]+>\\\", \\\"\\\", price.group(1)).strip() if price else None,\\n153: \\\"unit_price_text\\\": re.sub(r\\\"<[^>]+>\\\", \\\"\\\", unit_price.group(1)).strip() if unit_price else None,\\n154: \\\"brand\\\": re.sub(r\\\"<[^>]+>\\\", \\\"\\\", brand.group(1)).strip() if brand else None,\\n155: \\\"raw_result\\\": {\\\"source\\\": \\\"html_article\\\"},\\n156: })\\n157: return results\\n158: \\n159: def _cache_key(self, query: str) -> str:\\n160: return f\\\"provider-search://{self.retailer}/{quote_plus(query.lower().strip())}\\\"\\n161: \\n162: def get_cached_result(self, conn: Connection, query: str, max_results: int = 5, max_age_seconds: int = 86400) -> list[dict[str, Any]]:\\n163: rows = conn.execute(\\\"SELECT * FROM grocery_product_details_cache WHERE retailer=? AND source_hash=? AND cache_status='cached' ORDER BY fetched_at DESC LIMIT ?\\\", (self.retailer, self._cache_key(query), max_results)).fetchall()\\n164: output = []\\n165: cutoff = datetime.now(timezone.utc) - timedelta(seconds=max_age_seconds)\\n166: for row in rows:\\n167: d = row_to_dict(row)\\n168: try:\\n169: fetched_dt = datetime.fromisoformat(str(d.get(\\\"fetched_at\\\")))\\n170: if fetched_dt.tzinfo is None:\\n171: fetched_dt = fetched_dt.replace(tzinfo=timezone.utc)\\n172: if fetched_dt < cutoff:\\n173: continue\\n174: except Exception:\\n175: continue\\n176: output.append({\\\"retailer\\\": d[\\\"retailer\\\"], \\\"product_name\\\": d.get(\\\"product_name\\\"), \\\"brand\\\": d.get(\\\"brand\\\"), \\\"product_url\\\": d.get(\\\"product_url\\\"), \\\"image_url\\\": d.get(\\\"image_url\\\"), \\\"price_text\\\": d.get(\\\"price_text\\\"), \\\"price_decimal_text\\\": d.get(\\\"price_decimal_text\\\"), \\\"currency\\\": d.get(\\\"currency\\\") or \\\"CHF\\\", \\\"package_size\\\": d.get(\\\"package_size\\\"), \\\"unit\\\": d.get(\\\"unit\\\"), \\\"unit_price_text\\\": d.get(\\\"unit_price_text\\\"), \\\"unit_price_decimal_text\\\": d.get(\\\"unit_price_decimal_text\\\"), \\\"availability_status\\\": d.get(\\\"availability_status\\\"), \\\"promotion_text\\\": d.get(\\\"promotion_text\\\"), \\\"fetched_at\\\": d.get(\\\"fetched_at\\\"), \\\"source\\\": \\\"cache\\\", \\\"confidence\\\": d.get(\\\"confidence\\\") or \\\"0\\\", \\\"quality_flags\\\": json.loads(d.get(\\\"quality_flags_json\\\") or \\\"[]\\\"), \\\"status\\\": \\\"suggested\\\"})\\n177: return output\\n178: \\n179: def store_cache(self, conn: Connection, query: str, result: dict[str, Any]) -> None:\\n180: detail_id = new_id(\\\"gdetail\\\")\\n181: conn.execute(\\\"\\\"\\\"INSERT OR REPLACE INTO grocery_product_details_cache(detail_id,retailer,product_url,product_name,price_text,unit_price_text,package_size,ingredients_text,nutrition_json,fetched_at,cache_status,source_hash,brand,image_url,price_decimal_text,currency,unit,unit_price_decimal_text,availability_status,promotion_text,source,confidence,quality_flags_json,raw_result_json)\\n182: VALUES (COALESCE((SELECT detail_id FROM grocery_product_details_cache WHERE retailer=? AND product_url=?), ?), ?, ?, ?, ?, ?, ?, NULL, '{}', ?, 'cached', ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\\\"\\\"\\\",\\n183: (self.retailer, result[\\\"product_url\\\"], detail_id, self.retailer, result[\\\"product_url\\\"], result.get(\\\"product_name\\\"), result.get(\\\"price_text\\\"), result.get(\\\"unit_price_text\\\"), result.get(\\\"package_size\\\"), result.get(\\\"fetched_at\\\") or _now(), self._cache_key(query), result.get(\\\"brand\\\"), result.get(\\\"image_url\\\"), result.get(\\\"price_decimal_text\\\"), result.get(\\\"currency\\\") or \\\"CHF\\\", result.get(\\\"unit\\\"), result.get(\\\"unit_price_decimal_text\\\"), result.get(\\\"availability_status\\\"), result.get(\\\"promotion_text\\\"), result.get(\\\"source\\\"), result.get(\\\"confidence\\\"), json.dumps(result.get(\\\"quality_flags\\\") or []), json.dumps(result.get(\\\"raw_result\\\") or {})))\\n184: conn.commit()\\n185: \\n186: def search_products(self, conn: Connection, query: str, retailer: str | None = None, locale: str = \\\"de-CH\\\", use_cache: bool = True, max_results: int = 5, max_age_seconds: int = 86400) -> list[dict[str, Any]]:\\n187: if self.future_status:\\n188: return [{\\\"retailer\\\": self.retailer, \\\"query\\\": query, \\\"status\\\": \\\"needs_review\\\", \\\"future_status\\\": self.future_status, \\\"quality_flags\\\": [\\\"needs_review\\\"], \\\"source\\\": \\\"skeleton\\\"}]\\n189: if use_cache:\\n190: cached = self.get_cached_result(conn, query, max_results=max_results, max_age_seconds=max_age_seconds)\\n191: if cached:\\n192: return cached\\n193: try:\\n194: html_text = self._fetch(self.search_url(query, locale=locale))\\n195: raw_rows = self.parse_search_results(html_text)[:max_results]\\n196: results = [self.normalize_result(raw).as_dict() for raw in raw_rows]\\n197: for result in results:\\n198: self.store_cache(conn, query, result)\\n199: return results\\n200: except GroceryProviderRateLimitError:\\n201: return [{\\\"retailer\\\": self.retailer, \\\"query\\\": query, \\\"status\\\": \\\"needs_review\\\", \\\"quality_flags\\\": [\\\"rate_limited\\\", \\\"needs_review\\\"], \\\"source\\\": \\\"web_fetch\\\", \\\"fetched_at\\\": _now()}]\\n202: except Exception as exc:\\n203: return [{\\\"retailer\\\": self.retailer, \\\"query\\\": query, \\\"status\\\": \\\"needs_review\\\", \\\"quality_flags\\\": [\\\"provider_error\\\", \\\"needs_review\\\"], \\\"error\\\": type(exc).__name__, \\\"source\\\": \\\"web_fetch\\\", \\\"fetched_at\\\": _now()}]\\n204: \\n205: def fetch_product_detail(self, url: str) -> dict[str, Any]:\\n206: html_text = self._fetch(url)\\n207: parsed = self.parse_search_results(html_text)\\n208: return parsed[0] if parsed else {\\\"product_url\\\": url, \\\"status\\\": \\\"needs_review\\\"}\\n209: \\n210: \\n211: class MigrosProvider(GroceryProductProvider):\\n212: retailer = \\\"Migros\\\"\\n213: base_url = \\\"https://www.migros.ch/de/search?query=\\\"\\n214: \\n215: def search_url(self, query: str, locale: str = \\\"de-CH\\\") -> str:\\n216: return self.base_url + quote_plus(query)\\n217: \\n218: \\n219: class CoopProvider(GroceryProductProvider):\\n220: retailer = \\\"Coop\\\"\\n221: base_url = \\\"https://www.coop.ch/de/search/?text=\\\"\\n222: \\n223: def search_url(self, query: str, locale: str = \\\"de-CH\\\") -> str:\\n224: return self.base_url + quote_plus(query)\\n225: \\n226: \\n227: class AldiSuisseProvider(GroceryProductProvider):\\n228: retailer = \\\"Aldi Suisse\\\"\\n229: future_status = \\\"skeleton_provider_not_live\\\"\\n230: \\n231: \\n232: class LidlSchweizProvider(GroceryProductProvider):\\n233: retailer = \\\"Lidl\\\"\\n234: future_status = \\\"skeleton_provider_not_live\\\"\\n235: \\n236: \\n237: class DennerProvider(GroceryProductProvider):\\n238: retailer = \\\"Denner\\\"\\n239: future_status = \\\"skeleton_provider_not_live\\\"\\n240: \\n241: \\n242: class OttosProvider(GroceryProductProvider):\\n243: retailer = \\\"Otto's\\\"\\n244: future_status = \\\"skeleton_provider_not_live\\\"\\n245: \\n246: \\n247: def provider_for_retailer(retailer: str) -> GroceryProductProvider:\\n248: mapping: dict[str, type[GroceryProductProvider]] = {\\\"Migros\\\": MigrosProvider, \\\"Coop\\\": CoopProvider, \\\"Aldi Suisse\\\": AldiSuisseProvider, \\\"Lidl\\\": LidlSchweizProvider, \\\"Denner\\\": DennerProvider, \\\"Otto's\\\": OttosProvider}\\n249: return mapping.get(retailer, GroceryProductProvider)()\\n250: \\n251: \\n252: def quality_flags_for_match(original_name: str, result: dict[str, Any]) -> list[str]:\\n253: original = original_name.lower()\\n254: candidate = str(result.get(\\\"product_name\\\") or \\\"\\\").lower()\\n255: flags: list[str] = []\\n256: if not result.get(\\\"price_decimal_text\\\"):\\n257: flags.append(\\\"no_price\\\")\\n258: if not result.get(\\\"unit_price_decimal_text\\\"):\\n259: flags.append(\\\"no_unit_price\\\")\\n260: if original and original == candidate:\\n261: flags.append(\\\"exact_match\\\")\\n262: elif any(token in candidate for token in original.split()[:2]):\\n263: flags.append(\\\"close_match\\\")\\n264: else:\\n265: flags.append(\\\"needs_review\\\")\\n266: if (\\\"bio\\\" in original) != (\\\"bio\\\" in candidate):\\n267: flags.append(\\\"organic_mismatch\\\")\\n268: if result.get(\\\"brand\\\") and str(result.get(\\\"brand\\\")).lower() in {\\\"prix garantie\\\", \\\"m-budget\\\", \\\"aldi\\\", \\\"lidl\\\"}:\\n269: flags.append(\\\"cheaper_private_label\\\")\\n270: if \\\"no_price\\\" in flags or \\\"needs_review\\\" in flags:\\n271: if \\\"needs_review\\\" not in flags:\\n272: flags.append(\\\"needs_review\\\")\\n273: return flags\\n274: \\n275: \\n276: def compare_product_prices(*, original_price_text: str, candidate_price_text: str | None, original_unit_price_text: str | None = None, candidate_unit_price_text: str | None = None, currency: str = \\\"CHF\\\", quality_flags: list[str] | None = None) -> dict[str, Any]:\\n277: flags = list(quality_flags or [])\\n278: if currency != \\\"CHF\\\" or not candidate_price_text or \\\"needs_review\\\" in flags or \\\"no_price\\\" in flags:\\n279: return {\\\"can_calculate_savings\\\": False, \\\"savings_text\\\": \\\"0.00\\\", \\\"basis\\\": \\\"none\\\", \\\"quality_flags\\\": flags}\\n280: if original_unit_price_text and candidate_unit_price_text and _decimal_text(original_unit_price_text) and _decimal_text(candidate_unit_price_text):\\n281: raw_savings = _money(original_unit_price_text) - _money(candidate_unit_price_text)\\n282: if raw_savings <= Decimal(\\\"0.00\\\"):\\n283: if \\\"not_cheaper\\\" not in flags:\\n284: flags.append(\\\"not_cheaper\\\")\\n285: return {\\\"can_calculate_savings\\\": False, \\\"savings_text\\\": \\\"0.00\\\", \\\"basis\\\": \\\"unit_price\\\", \\\"quality_flags\\\": flags}\\n286: return {\\\"can_calculate_savings\\\": True, \\\"savings_text\\\": f\\\"{raw_savings:.2f}\\\", \\\"basis\\\": \\\"unit_price\\\", \\\"quality_flags\\\": flags}\\n287: if not any(f in flags for f in [\\\"different_pack_size\\\", \\\"different_quality\\\", \\\"organic_mismatch\\\"]):\\n288: raw_savings = _money(original_price_text) - _money(candidate_price_text)\\n289: if raw_savings <= Decimal(\\\"0.00\\\"):\\n290: if \\\"not_cheaper\\\" not in flags:\\n291: flags.append(\\\"not_cheaper\\\")\\n292: return {\\\"can_calculate_savings\\\": False, \\\"savings_text\\\": \\\"0.00\\\", \\\"basis\\\": \\\"package_price\\\", \\\"quality_flags\\\": flags}\\n293: if \\\"package_price_fallback\\\" not in flags:\\n294: flags.append(\\\"package_price_fallback\\\")\\n295: return {\\\"can_calculate_savings\\\": True, \\\"savings_text\\\": f\\\"{raw_savings:.2f}\\\", \\\"basis\\\": \\\"package_price\\\", \\\"quality_flags\\\": flags}\\n296: return {\\\"can_calculate_savings\\\": False, \\\"savings_text\\\": \\\"0.00\\\", \\\"basis\\\": \\\"none\\\", \\\"quality_flags\\\": flags}\\n297: \\n298: \\n299: def search_and_store_product_matches(conn: Connection, receipt_id: str, *, providers: list[GroceryProductProvider], included_product_item_ids: list[str] | None = None, max_products: int = 5, use_cache: bool = True, only_safe_matches: bool = True, prefer_known_mappings: bool = True) -> dict[str, Any]:\\n300: items = _items_for_receipt(conn, receipt_id)\\n301: if included_product_item_ids is not None:\\n302: allowed = set(included_product_item_ids)\\n303: items = [item for item in items if item[\\\"product_item_id\\\"] in allowed]\\n304: items = items[:max_products]\\n305: matches: list[dict[str, Any]] = []\\n306: provider_calls = 0\\n307: cache_hits = 0\\n308: known_mapping_hits = 0\\n309: for item in items:\\n310: query = item.get(\\\"normalized_product_name\\\") or item.get(\\\"raw_product_name\\\")\\n311: if prefer_known_mappings:\\n312: accepted = [m for m in known_mappings_for_item(conn, item, include_rejected=False) if m.get(\\\"status\\\") == \\\"accepted\\\"]\\n313: if accepted:\\n314: for m in accepted:\\n315: matches.append({\\\"mapping_id\\\": m[\\\"mapping_id\\\"], \\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": m[\\\"target_retailer\\\"], \\\"product_name\\\": m[\\\"target_product_name\\\"], \\\"product_url\\\": m[\\\"target_product_url\\\"], \\\"price_text\\\": m.get(\\\"target_price_text\\\"), \\\"unit_price_text\\\": m.get(\\\"target_unit_price_text\\\"), \\\"source_fetched_at\\\": m.get(\\\"last_price_checked_at\\\"), \\\"fetched_at\\\": m.get(\\\"updated_at\\\"), \\\"quality_flags\\\": json.loads(m.get(\\\"quality_flags_json\\\") or \\\"[]\\\"), \\\"confidence\\\": m.get(\\\"confidence\\\"), \\\"status\\\": \\\"suggested\\\" if m.get(\\\"target_price_text\\\") else \\\"needs_review\\\", \\\"source\\\": \\\"known_mapping\\\", \\\"cache_status\\\": m.get(\\\"cache_status\\\")})\\n316: known_mapping_hits += 1\\n317: continue\\n318: rejected = conn.execute(\\\"SELECT 1 FROM grocery_product_mappings WHERE source_product_normalized_name=? AND status='rejected' LIMIT 1\\\", (item.get(\\\"normalized_product_name\\\"),)).fetchone()\\n319: if rejected:\\n320: matches.append({\\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": None, \\\"product_name\\\": item.get(\\\"raw_product_name\\\"), \\\"status\\\": \\\"rejected\\\", \\\"quality_flags\\\": [\\\"rejected\\\"], \\\"source\\\": \\\"known_mapping\\\"})\\n321: known_mapping_hits += 1\\n322: continue\\n323: for provider in providers:\\n324: before = provider.request_count\\n325: results = provider.search_products(conn, query, use_cache=use_cache, max_results=3)\\n326: provider_calls += max(0, provider.request_count - before)\\n327: for result in results:\\n328: if result.get(\\\"source\\\") == \\\"cache\\\":\\n329: cache_hits += 1\\n330: if not result.get(\\\"product_url\\\") or not result.get(\\\"product_name\\\"):\\n331: matches.append({\\\"product_item_id\\\": item[\\\"product_item_id\\\"], **result})\\n332: continue\\n333: flags = quality_flags_for_match(item.get(\\\"normalized_product_name\\\") or item.get(\\\"raw_product_name\\\"), result)\\n334: comparison = compare_product_prices(original_price_text=str(item.get(\\\"total_price_text\\\") or \\\"0\\\"), original_unit_price_text=item.get(\\\"unit_price_text\\\"), candidate_price_text=result.get(\\\"price_decimal_text\\\") or result.get(\\\"price_text\\\"), candidate_unit_price_text=result.get(\\\"unit_price_decimal_text\\\") or result.get(\\\"unit_price_text\\\"), currency=result.get(\\\"currency\\\") or \\\"CHF\\\", quality_flags=flags)\\n335: status = \\\"suggested\\\" if comparison[\\\"can_calculate_savings\\\"] and (not only_safe_matches or not (set(flags) & UNSAFE_FLAGS)) else \\\"needs_review\\\"\\n336: if not comparison[\\\"can_calculate_savings\\\"] or not result.get(\\\"price_decimal_text\\\"):\\n337: matches.append({\\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": result.get(\\\"retailer\\\"), \\\"product_name\\\": result.get(\\\"product_name\\\"), \\\"product_url\\\": result.get(\\\"product_url\\\"), \\\"price_text\\\": result.get(\\\"price_decimal_text\\\") or result.get(\\\"price_text\\\"), \\\"unit_price_text\\\": result.get(\\\"unit_price_text\\\"), \\\"source_fetched_at\\\": result.get(\\\"fetched_at\\\"), \\\"fetched_at\\\": result.get(\\\"fetched_at\\\"), \\\"quality_flags\\\": comparison[\\\"quality_flags\\\"], \\\"confidence\\\": result.get(\\\"confidence\\\"), \\\"status\\\": status, \\\"source\\\": result.get(\\\"source\\\")})\\n338: continue\\n339: stored = upsert_product_match(conn, item[\\\"product_item_id\\\"], retailer=result[\\\"retailer\\\"], candidate_product_name=result[\\\"product_name\\\"], candidate_url=result[\\\"product_url\\\"], candidate_price_text=result.get(\\\"price_decimal_text\\\") or result.get(\\\"price_text\\\") or \\\"0\\\", candidate_unit_price_text=result.get(\\\"unit_price_text\\\"), quality_flags=comparison[\\\"quality_flags\\\"], match_confidence=result.get(\\\"confidence\\\") or \\\"0.60\\\", status=status, source=result.get(\\\"source\\\") or \\\"web_fetch\\\", candidate_brand=result.get(\\\"brand\\\"), candidate_package_size=result.get(\\\"package_size\\\"), candidate_unit=result.get(\\\"unit\\\"))\\n340: matches.append({\\\"match_id\\\": stored.get(\\\"match_id\\\"), \\\"product_item_id\\\": item[\\\"product_item_id\\\"], \\\"retailer\\\": result[\\\"retailer\\\"], \\\"product_name\\\": result[\\\"product_name\\\"], \\\"product_url\\\": result[\\\"product_url\\\"], \\\"price_text\\\": result.get(\\\"price_decimal_text\\\") or result.get(\\\"price_text\\\"), \\\"unit_price_text\\\": result.get(\\\"unit_price_text\\\"), \\\"source_fetched_at\\\": result.get(\\\"fetched_at\\\"), \\\"fetched_at\\\": stored.get(\\\"fetched_at\\\"), \\\"quality_flags\\\": comparison[\\\"quality_flags\\\"], \\\"confidence\\\": result.get(\\\"confidence\\\"), \\\"status\\\": status, \\\"source\\\": result.get(\\\"source\\\")})\\n341: return {\\\"receipt_id\\\": receipt_id, \\\"provider_calls\\\": provider_calls, \\\"cache_hits\\\": cache_hits, \\\"known_mapping_hits\\\": known_mapping_hits, \\\"matches\\\": matches}\\n\\n--- src/jarvis_finance/api/routers/budget.py 150 220 ---\\n150: update_budget_transaction,\\n151: )\\n152: \\n153: router = APIRouter(prefix=\\\"/budget\\\", tags=[\\\"budget\\\"])\\n154: \\n155: \\n156: @router.get(\\\"/grocery-optimizer/dashboard\\\")\\n157: def grocery_optimizer_dashboard(conn: Connection = Depends(get_db)):\\n158: return get_grocery_optimizer_dashboard(conn)\\n159: \\n160: \\n161: @router.post(\\\"/grocery-optimizer/demo-receipt\\\")\\n162: def grocery_optimizer_demo_receipt(payload: dict, conn: Connection = Depends(get_db)):\\n163: return add_demo_migros_receipt(conn, purchase_date=payload.get(\\\"purchase_date\\\") or \\\"2026-05-19\\\", store_name=payload.get(\\\"store_name\\\") or \\\"Migros\\\", items=payload.get(\\\"items\\\") or [])\\n164: \\n165: \\n166: @router.post(\\\"/grocery-optimizer/matches\\\")\\n167: def grocery_optimizer_match(payload: dict, conn: Connection = Depends(get_db)):\\n168: return upsert_product_match(conn, payload[\\\"product_item_id\\\"], retailer=payload[\\\"retailer\\\"], candidate_product_name=payload[\\\"candidate_product_name\\\"], candidate_url=payload.get(\\\"candidate_url\\\") or \\\"https://example.invalid/review\\\", candidate_price_text=payload[\\\"candidate_price_text\\\"], candidate_unit_price_text=payload.get(\\\"candidate_unit_price_text\\\"), quality_flags=payload.get(\\\"quality_flags\\\") or [\\\"needs_review\\\"], match_confidence=payload.get(\\\"match_confidence\\\") or \\\"0.60\\\", status=payload.get(\\\"status\\\") or \\\"suggested\\\", source=payload.get(\\\"source\\\") or \\\"manual\\\")\\n169: \\n170: \\n171: @router.post(\\\"/grocery-optimizer/matches/{match_id}/accept\\\")\\n172: def grocery_optimizer_accept_match(match_id: str, payload: dict | None = None, conn: Connection = Depends(get_db)):\\n173: payload = payload or {}\\n174: return accept_grocery_product_match(conn, match_id, user_note=payload.get(\\\"user_note\\\"), save_as_preferred=bool(payload.get(\\\"save_as_preferred\\\", True)))\\n175: \\n176: \\n177: @router.post(\\\"/grocery-optimizer/matches/{match_id}/reject\\\")\\n178: def grocery_optimizer_reject_match(match_id: str, payload: dict | None = None, conn: Connection = Depends(get_db)):\\n179: return reject_grocery_product_match(conn, match_id, user_note=(payload or {}).get(\\\"user_note\\\"))\\n180: \\n181: \\n182: @router.post(\\\"/grocery-optimizer/manual-mapping\\\")\\n183: def grocery_optimizer_manual_mapping(payload: dict, conn: Connection = Depends(get_db)):\\n184: return create_manual_grocery_mapping(conn, product_item_id=payload[\\\"product_item_id\\\"], target_retailer=payload[\\\"target_retailer\\\"], target_product_name=payload[\\\"target_product_name\\\"], target_product_url=payload[\\\"target_product_url\\\"], target_brand=payload.get(\\\"target_brand\\\"), target_package_size=payload.get(\\\"target_package_size\\\"), target_unit=payload.get(\\\"target_unit\\\"), match_type=payload.get(\\\"match_type\\\") or \\\"manual_match\\\", candidate_price_text=payload.get(\\\"candidate_price_text\\\"), candidate_unit_price_text=payload.get(\\\"candidate_unit_price_text\\\"), user_note=payload.get(\\\"user_note\\\"))\\n185: \\n186: \\n187: @router.post(\\\"/grocery-optimizer/mappings/{mapping_id}/refresh-price\\\")\\n188: def grocery_optimizer_refresh_mapping_price(mapping_id: str, conn: Connection = Depends(get_db)):\\n189: return refresh_grocery_mapping_price(conn, mapping_id)\\n190: \\n191: \\n192: @router.post(\\\"/grocery-optimizer/optimize\\\")\\n193: def grocery_optimizer_run(payload: dict, conn: Connection = Depends(get_db)):\\n194: return run_grocery_optimization(conn, payload[\\\"receipt_id\\\"], selected_retailers=payload.get(\\\"selected_retailers\\\") or [\\\"Coop\\\", \\\"Aldi Suisse\\\", \\\"Lidl\\\", \\\"Denner\\\", \\\"Otto's\\\"], max_store_count=int(payload.get(\\\"max_store_count\\\") or 3), included_product_item_ids=payload.get(\\\"included_product_item_ids\\\"))\\n195: \\n196: \\n197: @router.post(\\\"/grocery-optimizer/search-prices\\\")\\n198: def grocery_optimizer_search_prices(payload: dict, conn: Connection = Depends(get_db)):\\n199: retailers = (payload.get(\\\"retailers\\\") or [\\\"Coop\\\"])[: int(payload.get(\\\"max_retailers\\\") or 3)]\\n200: providers = [provider_for_retailer(retailer) for retailer in retailers]\\n201: return search_and_store_product_matches(\\n202: conn,\\n203: payload[\\\"receipt_id\\\"],\\n204: providers=providers,\\n205: included_product_item_ids=payload.get(\\\"included_product_item_ids\\\"),\\n206: max_products=int(payload.get(\\\"max_products\\\") or 5),\\n207: use_cache=bool(payload.get(\\\"use_cache\\\", True)),\\n208: only_safe_matches=bool(payload.get(\\\"only_safe_matches\\\", True)),\\n209: prefer_known_mappings=bool(payload.get(\\\"prefer_known_mappings\\\", True)),\\n210: )\\n211: \\n212: \\n213: @router.post(\\\"/grocery-optimizer/report\\\")\\n214: def grocery_optimizer_report(payload: dict, conn: Connection = Depends(get_db)):\\n215: return generate_grocery_optimization_report(conn, payload[\\\"run_id\\\"])\\n216: \\n217: \\n218: @router.get(\\\"/monthly-import/dashboard\\\")\\n219: def monthly_import_dashboard(conn: Connection = Depends(get_db)):\\n220: return get_monthly_import_dashboard(conn)\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_GfxxBXqjnzg17WM06vRBjFR4"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Considering secret scans**\n\nI’m thinking about running a scan for secrets or artifacts in my files since I need to make sure everything is clean. Maybe using `git diff --check` could help, along with `grep` for specific patterns. Also, I should focus on checking for any untracked files. Using Python to detect these patterns sounds like a solid approach. It’s essential to ensure I’m not missing anything important here!",
"finish_reason": "tool_calls",
"reasoning_content": "**Considering secret scans**\n\nI’m thinking about running a scan for secrets or artifacts in my files since I need to make sure everything is clean. Maybe using `git diff --check` could help, along with `grep` for specific patterns. Also, I should focus on checking for any untracked files. Using Python to detect these patterns sounds like a solid approach. It’s essential to ensure I’m not missing anything important here!",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABqDGGHTemKVXc7gTH2RvGR4sYTaYO1gMQ-sP6HhFps0Fcrfu6X1OBOsXtveeLmadL0bIEWx0biiuMyK2otEwYzTZbDOdMkeau8VtEgWPWVqYuOQ7PVpYE6vqLnhZL1svJ2vpEIxi_FzthGQ_Fit7VcV4KP27ctfCockw4XwOStae6zl0ecLzrZ7ikbw5Vp6CzL3WghHOqZg3o0yi6yUZHKCYXAz7J31K1SfZHIzlZTgJFSPfO6e017CzvtneOiTLPBS2DINWLDOE9rLRxRD2EhhP-eB5eUPZS4uHrjymYmoX6dXZcTJ25l93pGfhKqVRDPYqsXFjMKroXLtSug0PTZdmRYX6CVrvGq-xstZ2hJGWiEFhnKxxS2MY2Yy3KrP8VTivYGTvntAYc0y04RClEK6VOzK7Z3x3CqrenmRIvLHobto-XOhkVp4KDVQ-LWSUsEXY4OIF8o1QuodYRVFBd8L7V2nJMcYBYYxF9yGKyI-qkKNf-B46aM5RAMWsm93IiRwG4QsakN6pD9ypkLMKk7K8yrDbtFXScnip0GlWPNbZxnLt8wWyBdjKnUnujoMwm7T_xs7H3N9DYURPb_wngZtYRCkZeW_WeJ9o2QmW0xUZ47ADhAjIZWIVDqUrBIRYO-H7MnLZWWUVvJ5AISiNZ-I815tKNLRJF4Nj1HYhvY8iq39bGjUyetGwXDx_3ieA1w--K187MG7dJufTS1LSZey6J81m32jM86pbvl1EVCkB0H1miPBliX8PVQ5vByoeC0P3YNRY8pm47QrVhrUaqpOrmHii87mcb2FXgLj7NSpFwB15jAV8vIdv6o1LzQYYtO6BASnfoCp0ANGTDIS4Z7CrX1pDBw9s7WMeXvazKEs2d1dyume6RdjwMc5qHnZolwXDI31jeFIHoXMKoP_9-NgZHiu1v6tVTZG_UTB6qYasw0Rt14lmqU9hS0A7HKRbc27y_Mp0vd5Z3GVrzZNGmxNTFJ90HUBaDMncqANv37p6rpLwM_WOmj-7_wsEmucXF8pIGiUexKsbmznsiTC5rXZHBgWJrYp78NqceHip-Iqyhw3ITE6DAL3dAwabL4qiDGoZWd-lglnKCXzE5RRYjCAZ6kEb6KOk9hh637rx0B1n6-NOY=",
"id": "rs_01a8a0268fae6d6e016a0c6185e1948191bda38a023b600b53",
"summary": [
{
"type": "summary_text",
"text": "**Considering secret scans**\n\nI’m thinking about running a scan for secrets or artifacts in my files since I need to make sure everything is clean. Maybe using `git diff --check` could help, along with `grep` for specific patterns. Also, I should focus on checking for any untracked files. Using Python to detect these patterns sounds like a solid approach. It’s essential to ensure I’m not missing anything important here!"
}
]
}
],
"tool_calls": [
{
"id": "call_X3khIVGEKj8fV4YNjnspQ088",
"call_id": "call_X3khIVGEKj8fV4YNjnspQ088",
"response_item_id": "fc_01a8a0268fae6d6e016a0c6187d71481918f7f805f8b60c620",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"python3 - <<'PY'\\nimport os,re,subprocess\\nroot='.'\\n# changed/untracked files\\ngit=subprocess.check_output(['git','status','--short'],text=True).splitlines()\\nfiles=[]\\nfor line in git:\\n p=line[3:] if line.startswith('?? ') else line[3:]\\n if os.path.isfile(p): files.append(p)\\npatterns=[('api_key',re.compile(r'(?i)(api[_-]?key|secret|token|password)\\\\s*[:=]')),('private_key',re.compile(r'-----BEGIN (RSA |EC |OPENSSH |)PRIVATE KEY-----')),('sk_key',re.compile(r'\\\\b(sk-[A-Za-z0-9]{20,}|AKIA[0-9A-Z]{16})\\\\b'))]\\nfor f in files:\\n try: text=open(f,encoding='utf-8',errors='replace').read()\\n except: continue\\n for name,pat in patterns:\\n for m in pat.finditer(text): print('SECRET?',name,f,m.start(),text[max(0,m.start()-40):m.start()+80].replace('\\\\n',' '))\\n # runtime artifacts\\n if re.search(r'(^|/)(runtime|reports|\\\\.env|.*\\\\.db|.*\\\\.sqlite)',f): print('RUNTIME?',f)\\nPY\\n\\ngit diff --check\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_X3khIVGEKj8fV4YNjnspQ088"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Considering test strategies**\n\nI need to think about whether tests are failing and what that might mean for verification. Okay, I could run focused tests to pinpoint the issues. I’m considering using pytest since it’s relevant for the tasks I’m troubleshooting. I really want to ensure everything is up to par, so running those focused tests might help to clarify where the problems lie. It feels good to be thorough!",
"finish_reason": "tool_calls",
"reasoning_content": "**Considering test strategies**\n\nI need to think about whether tests are failing and what that might mean for verification. Okay, I could run focused tests to pinpoint the issues. I’m considering using pytest since it’s relevant for the tasks I’m troubleshooting. I really want to ensure everything is up to par, so running those focused tests might help to clarify where the problems lie. It feels good to be thorough!",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABqDGGTykLlocotHOH9XBvzveekn4Izg0HW63wzVWi4ebTEAbwETTCAXtIYqtptFfl9dkYfne2nW_5P_GIY0mKfylXTGhQccga9jxGvfi-g3SOxD71IorUloo3VA9ruPKJ-Iio4irlYDYa6O7TuL9zBnCET76lunxrCuju9_mXn-yaNIG24pp7DwuK4erCtrv_QqWM22o9e6m6HUB2cgruISflz5iIygI8LzpliFxf43lime6WAoaT7Ke9kALun1HZ0rzD7SmjA6CODtpR69JmkFcfklMh-KIYCwQJ8E-34HNCcuZbKwem2RKTKtv5e55ZLFozwRA8J3OnBMcQSuVSbvjLz_NZN5rs4HO-lI9rFvOqyPd90wCtdui1qsNNNuFc3j6cDw0X-rhO_F5rEkHheGXw8SQdOqIN_dzzSdzCNK9YB0dnfS0mPf9CbcF6obZIYJ89DxqcYrWDVPEOq2ifJlLa9t2gfqr_LkCC2UTfxetQXBSEPRwvBKPowLLnpZVMVza5gnrTpHRPgKjNl8DoGDq9Ez96Ko9Qa8coJBD1d98747JXcKq4SxVZUUgJgjzfkhbl0CRGlg-A1Akoqt18fP5P5ijv0qL9AGCRArXWLeaA1bneSy0ImtHcUYF4yAn78Nj2dNjf1CQC6O4YaoMvFJ6Hyat3xnxzb0fBfYsVWDTB3vbkZULcnJjCY6ja9ePYwkuZbWmeyEhVTPuDP6nvFZ74AeG4Ad19P5MufNgBxsXjZ-37x-TZkEbrn7xCdmI4VzbrMHlVdFX4yxZv1GjC-VvFuxRyi70QxshpZe_sSQaEo5sLg9l48_8jpRHVwggOb7jUKQ3ecgzrRIJVshVnjCZYnC4PROEIla9ILW-_8xpQqH84szAaUcxYiLDv9F6b6i0Uur7Bn0bfnyxiFeRYJJoH6fOj_SV4h-9NrvzNz4YJYxe-F7k9nsycvGnJElPZ7pn-Sr2c9XKTilIyrK3SZBsyEDZmQ22Qw1dto8AV73njn4ilklBZdCT1PaD48ulAFlrrcDpQAmWkAZk9nZc1EK6wLbw==",
"id": "rs_0f1c14ff5e836d5e016a0c619083b88191bf7f59056563a0c1",
"summary": [
{
"type": "summary_text",
"text": "**Considering test strategies**\n\nI need to think about whether tests are failing and what that might mean for verification. Okay, I could run focused tests to pinpoint the issues. I’m considering using pytest since it’s relevant for the tasks I’m troubleshooting. I really want to ensure everything is up to par, so running those focused tests might help to clarify where the problems lie. It feels good to be thorough!"
}
]
}
],
"tool_calls": [
{
"id": "call_PioMhKV6uPMVNScCvsd7vkH5",
"call_id": "call_PioMhKV6uPMVNScCvsd7vkH5",
"response_item_id": "fc_0f1c14ff5e836d5e016a0c619364bc81918b44e40bcf98313d",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"pytest tests/unit/test_grocery_matching_learning_v2.py tests/unit/test_grocery_price_providers_v1.py -q\",\"timeout\":300,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"............... [100%]\\n15 passed in 1.04s\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_PioMhKV6uPMVNScCvsd7vkH5"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Evaluating logic issues**\n\nI'm considering potential logic problems with a rejection system. If any mapping is rejected, does it block all suggestions, or just specific products? The requirement states that rejected matches shouldn't be suggested again, but if one product from a provider is rejected, alternatives might also get blocked. This might be too broad and could lead to a logic error. I need to ensure that acceptable mappings are clear, as security concerns arise with manual mappings lacking validation.\n**Identifying security concerns**\n\nI'm looking into options for storing JavaScript or internal URLs, but I'm noticing potential issues. For instance, refresh actions only fetch timestamps, while links indicated by href might open security concerns with Vue bindings, particularly with JavaScript links. If refreshes are SSRF vulnerabilities, that could be a problem too. Existing validations on retailers differ from manual mappings, which don't validate. It seems like clicking JavaScript links could lead to XSS-like issues since Vue might not sanitize hrefs properly, raising safety concerns around user authentication.\n**Analyzing price provenance concerns**\n\nI'm evaluating the price provenance in the create_manual_grocery_mapping function, which allows for an optional candidate price text. It sets a timestamp for when the last price was checked and writes to a cache with \"manual_mapping\" as the source. However, it doesn't seem to require a source URL. While it does require a target product URL and a timestamp, there's a potential issue since users can enter arbitrary prices without any validation for the URL or provenance. That could lead to inaccurate or false information being submitted.\n**Investigating price mapping logic**\n\nI'm looking into the accepted uses of mapping for target_price_text. It seems if the cache gets updated externally but the mapping price is stale, it might return a stale or null price, while cache_status could still be fresh. That raises a logical issue worth considering. I'll have to verify if this mapping process is indeed functioning correctly and that it’s consistent when drawing from the cache or the web.",
"finish_reason": "tool_calls",
"reasoning_content": "**Evaluating logic issues**\n\nI'm considering potential logic problems with a rejection system. If any mapping is rejected, does it block all suggestions, or just specific products? The requirement states that rejected matches shouldn't be suggested again, but if one product from a provider is rejected, alternatives might also get blocked. This might be too broad and could lead to a logic error. I need to ensure that acceptable mappings are clear, as security concerns arise with manual mappings lacking validation.\n**Identifying security concerns**\n\nI'm looking into options for storing JavaScript or internal URLs, but I'm noticing potential issues. For instance, refresh actions only fetch timestamps, while links indicated by href might open security concerns with Vue bindings, particularly with JavaScript links. If refreshes are SSRF vulnerabilities, that could be a problem too. Existing validations on retailers differ from manual mappings, which don't validate. It seems like clicking JavaScript links could lead to XSS-like issues since Vue might not sanitize hrefs properly, raising safety concerns around user authentication.\n**Analyzing price provenance concerns**\n\nI'm evaluating the price provenance in the create_manual_grocery_mapping function, which allows for an optional candidate price text. It sets a timestamp for when the last price was checked and writes to a cache with \"manual_mapping\" as the source. However, it doesn't seem to require a source URL. While it does require a target product URL and a timestamp, there's a potential issue since users can enter arbitrary prices without any validation for the URL or provenance. That could lead to inaccurate or false information being submitted.\n**Investigating price mapping logic**\n\nI'm looking into the accepted uses of mapping for target_price_text. It seems if the cache gets updated externally but the mapping price is stale, it might return a stale or null price, while cache_status could still be fresh. That raises a logical issue worth considering. I'll have to verify if this mapping process is indeed functioning correctly and that it’s consistent when drawing from the cache or the web.",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "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",
"id": "rs_0a6d2bdbc4f4d67e016a0c619811008191a6385084aa184aab",
"summary": [
{
"type": "summary_text",
"text": "**Evaluating logic issues**\n\nI'm considering potential logic problems with a rejection system. If any mapping is rejected, does it block all suggestions, or just specific products? The requirement states that rejected matches shouldn't be suggested again, but if one product from a provider is rejected, alternatives might also get blocked. This might be too broad and could lead to a logic error. I need to ensure that acceptable mappings are clear, as security concerns arise with manual mappings lacking validation."
},
{
"type": "summary_text",
"text": "**Identifying security concerns**\n\nI'm looking into options for storing JavaScript or internal URLs, but I'm noticing potential issues. For instance, refresh actions only fetch timestamps, while links indicated by href might open security concerns with Vue bindings, particularly with JavaScript links. If refreshes are SSRF vulnerabilities, that could be a problem too. Existing validations on retailers differ from manual mappings, which don't validate. It seems like clicking JavaScript links could lead to XSS-like issues since Vue might not sanitize hrefs properly, raising safety concerns around user authentication."
},
{
"type": "summary_text",
"text": "**Analyzing price provenance concerns**\n\nI'm evaluating the price provenance in the create_manual_grocery_mapping function, which allows for an optional candidate price text. It sets a timestamp for when the last price was checked and writes to a cache with \"manual_mapping\" as the source. However, it doesn't seem to require a source URL. While it does require a target product URL and a timestamp, there's a potential issue since users can enter arbitrary prices without any validation for the URL or provenance. That could lead to inaccurate or false information being submitted."
},
{
"type": "summary_text",
"text": "**Investigating price mapping logic**\n\nI'm looking into the accepted uses of mapping for target_price_text. It seems if the cache gets updated externally but the mapping price is stale, it might return a stale or null price, while cache_status could still be fresh. That raises a logical issue worth considering. I'll have to verify if this mapping process is indeed functioning correctly and that it’s consistent when drawing from the cache or the web."
}
]
}
],
"tool_calls": [
{
"id": "call_AOb3q1dLAKOa4Br5JTZ1Hnfm",
"call_id": "call_AOb3q1dLAKOa4Br5JTZ1Hnfm",
"response_item_id": "fc_0a6d2bdbc4f4d67e016a0c61b443688191a723f242a81295da",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"python3 - <<'PY'\\nfrom pathlib import Path\\ntext=Path('tests/unit/test_grocery_matching_learning_v2.py').read_text().splitlines()\\nfor i,l in enumerate(text,1): print(f'{i}: {l}')\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"1: from __future__ import annotations\\n2: \\n3: import sqlite3\\n4: from pathlib import Path\\n5: \\n6: import pytest\\n7: \\n8: from jarvis_finance.storage.migrations import apply_migrations, get_schema_version\\n9: from jarvis_finance.services.grocery_optimizer import (\\n10: add_demo_migros_receipt,\\n11: accept_grocery_product_match,\\n12: reject_grocery_product_match,\\n13: create_manual_grocery_mapping,\\n14: get_grocery_optimizer_dashboard,\\n15: run_grocery_optimization,\\n16: generate_grocery_optimization_report,\\n17: )\\n18: from jarvis_finance.services.grocery_price_providers import search_and_store_product_matches, CoopProvider\\n19: \\n20: \\n21: def db() -> sqlite3.Connection:\\n22: conn = sqlite3.connect(':memory:')\\n23: conn.row_factory = sqlite3.Row\\n24: apply_migrations(conn)\\n25: assert get_schema_version(conn) == 34\\n26: return conn\\n27: \\n28: \\n29: def seed_receipt(conn: sqlite3.Connection, raw='Milch 1L', receipt_id='r1') -> dict:\\n30: return add_demo_migros_receipt(conn, purchase_date='2026-05-19', store_name='Migros', receipt_id=receipt_id, items=[{'raw_product_name': raw, 'quantity_text': '1L', 'unit': 'l', 'unit_price_text': '1.50/l', 'total_price_text': '1.50'}])\\n31: \\n32: \\n33: def test_accept_match_creates_preferred_mapping_and_next_receipt_reuses_without_provider_call() -> None:\\n34: conn = db()\\n35: first = seed_receipt(conn, receipt_id='r1')\\n36: provider = CoopProvider(fetcher=lambda _url: 'Prix Garantie Milch 1L CHF 1.20 1.20/l Coop Milch 1L CHF 1.20 1.20/l