f09c5b8ee7
Sprint 2.1 — Pattern Reliability Score - database.py: get_pattern_reliability() — win_rate × log(n+1) sur trades matures (≥35% horizon) - database.py: get_all_pattern_reliability_map() pour injection rapide dans les prompts - ai_analyzer.py: inject reliability_map dans suggest_patterns (patterns fiables mis en avant) - auto_cycle.py: charge reliability_map avant suggestion et le passe au suggéreur - routers/analytics.py: GET /api/analytics/reliability - PatternEditor.tsx: ReliabilityBadge sur chaque card + usePatternReliability hook - useApi.ts: usePatternReliability, useCalibration hooks Sprint 2.2 — Contre-thèses & Invalidation Triggers - database.py: migration ALTER TABLE — counter_thesis, invalidation_trigger, invalidation_probability - database.py: save_custom_pattern() persiste les 3 nouveaux champs - ai_analyzer.py: counter_thesis + invalidation_trigger + invalidation_probability dans le JSON schema - auto_cycle.py: détection automatique des triggers d'invalidation contre les news (keyword match) - routers/analytics.py: GET /api/analytics/invalidation-alerts - PatternEditor.tsx: affichage contre-thèse dans les cards + champs dans le formulaire - PatternEditor.tsx: affichage dans AiSuggestModal (suggestions IA) - routers/patterns.py: PatternRequest inclut les 3 nouveaux champs Sprint 2.3 — Calibration probabiliste & Demi-vie KB - database.py: migration — predicted_probability sur pattern_score_history - database.py: save_pattern_scores() stocke probability du pattern à chaque scoring run - database.py: get_calibration_data() — Brier score + buckets de calibration par décile - database.py: expires_at + confidence_decay_days sur knowledge_base - database.py: decay_kb_confidence() — decay automatique + archivage à 0 - auto_cycle.py: decay_kb_confidence() appelé au début de chaque cycle (non-bloquant) - routers/analytics.py: GET /api/analytics/calibration + POST /api/analytics/kb/decay - frontend/src/pages/Analytics.tsx: nouvelle page — tableau fiabilité + calibration Brier - App.tsx + Sidebar.tsx: route /analytics + entrée menu Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
74 lines
2.1 KiB
Python
74 lines
2.1 KiB
Python
from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from typing import Optional, List, Dict, Any
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from services.database import (
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save_custom_pattern, get_custom_patterns, delete_custom_pattern, toggle_pattern_active
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)
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router = APIRouter(prefix="/api/patterns", tags=["patterns"])
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class PatternRequest(BaseModel):
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id: Optional[str] = None
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name: str
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description: str
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triggers: List[str]
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keywords: List[str]
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historical_instances: Optional[List[Dict[str, Any]]] = []
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suggested_trades: Optional[List[Dict[str, Any]]] = []
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asset_class: str
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expected_move_pct: float
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probability: float
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horizon_days: int
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ai_quality_score: Optional[int] = None
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ai_evaluation: Optional[Dict[str, Any]] = None
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source: Optional[str] = "custom"
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counter_thesis: Optional[str] = None
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invalidation_trigger: Optional[str] = None
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invalidation_probability: Optional[float] = None
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@router.get("/all")
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def list_all():
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"""Return all active patterns from DB (builtin + custom)."""
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return get_custom_patterns()
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@router.get("/builtin")
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def list_builtin():
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return [p for p in get_custom_patterns() if p.get("source") == "builtin"]
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@router.get("/custom")
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def list_custom():
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return [p for p in get_custom_patterns() if p.get("source") != "builtin"]
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@router.post("/custom")
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def create_pattern(req: PatternRequest):
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data = req.model_dump()
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data["source"] = "custom"
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pat_id = save_custom_pattern(data)
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return {"id": pat_id, "status": "saved"}
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@router.put("/custom/{pat_id}")
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def update_pattern(pat_id: str, req: PatternRequest):
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data = req.model_dump()
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data["id"] = pat_id
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save_custom_pattern(data)
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return {"id": pat_id, "status": "updated"}
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@router.delete("/custom/{pat_id}")
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def delete_pattern(pat_id: str):
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delete_custom_pattern(pat_id)
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return {"status": "deleted"}
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@router.put("/toggle/{pat_id}")
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def toggle_pattern(pat_id: str):
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"""Enable or disable a pattern (works for builtin and custom)."""
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new_state = toggle_pattern_active(pat_id)
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return {"id": pat_id, "is_active": new_state}
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