Files
OpenFin/backend/routers/analytics.py
OpenSquared f09c5b8ee7 feat: Phase 2 — Pattern Reliability, Contre-thèses & Calibration probabiliste
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>
2026-06-17 16:50:53 +02:00

56 lines
1.7 KiB
Python

from fastapi import APIRouter, Query
from services.database import (
get_pattern_reliability,
get_all_pattern_reliability_map,
get_calibration_data,
decay_kb_confidence,
get_custom_patterns,
)
router = APIRouter(prefix="/api/analytics", tags=["analytics"])
@router.get("/reliability")
def reliability_all():
"""Pattern reliability scores — all patterns with mature trade history."""
return {"reliability": get_pattern_reliability()}
@router.get("/reliability/{pattern_id}")
def reliability_one(pattern_id: str):
result = get_pattern_reliability(pattern_id=pattern_id)
if not result:
return {"reliability": None}
return {"reliability": result[0]}
@router.get("/calibration")
def calibration(days: int = Query(default=365, ge=30, le=1000)):
"""Predicted probability vs realized outcomes (Brier score + buckets)."""
return get_calibration_data(days=days)
@router.post("/kb/decay")
def run_kb_decay():
"""Manually trigger KB confidence decay (also runs at cycle start)."""
updated = decay_kb_confidence()
return {"updated": updated, "message": f"{updated} entrée(s) KB mise(s) à jour"}
@router.get("/invalidation-alerts")
def invalidation_alerts():
"""List all active patterns that have an invalidation trigger defined."""
patterns = get_custom_patterns()
alerts = [
{
"pattern_id": p["id"],
"pattern_name": p["name"],
"invalidation_trigger": p.get("invalidation_trigger"),
"invalidation_probability": p.get("invalidation_probability"),
"counter_thesis": p.get("counter_thesis"),
}
for p in patterns
if p.get("invalidation_trigger")
]
return {"alerts": alerts, "count": len(alerts)}