93 lines
2.8 KiB
Python
93 lines
2.8 KiB
Python
"""Routes API — Mode Apprentissage."""
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from fastapi import APIRouter, Depends, HTTPException
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from pydantic import BaseModel
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy import select, desc
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from typing import Literal
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from backend.database.db import get_db
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from backend.database.models import AIDecision, LearningFeedback
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router = APIRouter()
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_processor = None
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def _get_processor():
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global _processor
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if not _processor:
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from backend.config.settings import get_settings
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from backend.ai.learning.feedback_processor import FeedbackProcessor
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_processor = FeedbackProcessor(get_settings())
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return _processor
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class FeedbackIn(BaseModel):
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decision_id: int
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rating: Literal["good", "bad", "neutral"]
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better_action: dict | None = None
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comment: str | None = None
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@router.post("/feedback")
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async def submit_feedback(req: FeedbackIn, db: AsyncSession = Depends(get_db)):
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"""Soumet un retour utilisateur sur une décision IA."""
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proc = _get_processor()
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try:
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fb = await proc.record_feedback(
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db,
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decision_id=req.decision_id,
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rating=req.rating,
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better_action=req.better_action,
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comment=req.comment,
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)
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return {
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"feedback_id": fb.id,
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"rating": fb.rating,
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"message": "Feedback enregistré — merci pour votre contribution!",
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}
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except ValueError as e:
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raise HTTPException(404, str(e))
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@router.get("/stats")
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async def get_stats(db: AsyncSession = Depends(get_db)):
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"""Statistiques globales du système d'apprentissage."""
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return await _get_processor().get_stats(db)
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@router.get("/decisions")
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async def get_decisions(
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session_id: int | None = None,
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limit: int = 20,
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db: AsyncSession = Depends(get_db),
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):
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"""Historique des décisions IA avec leurs feedbacks."""
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q = select(AIDecision).order_by(desc(AIDecision.created_at)).limit(limit)
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if session_id:
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q = q.where(AIDecision.session_id == session_id)
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result = await db.execute(q)
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decisions = result.scalars().all()
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return [
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{
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"id": d.id,
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"session_id": d.session_id,
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"turn": d.turn,
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"phase": d.phase,
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"recommendation": d.recommendation,
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"reasoning": d.reasoning,
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"confidence": d.confidence,
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"outcome_rating": d.outcome_rating,
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"user_feedback": d.user_feedback,
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"model_used": d.model_used,
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"processing_ms": d.processing_ms,
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"created_at": d.created_at.isoformat(),
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}
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for d in decisions
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]
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@router.post("/flush")
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async def flush_buffer():
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"""Force l'export du buffer d'apprentissage."""
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await _get_processor().force_flush()
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return {"status": "flushed"}
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