94 lines
3.2 KiB
Python
94 lines
3.2 KiB
Python
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"""
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反馈数据 API — 用户反馈分析、记录查询、反例生成
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"""
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from __future__ import annotations
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import logging
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from typing import Optional
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from fastapi import APIRouter, Depends, HTTPException, Query
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from sqlalchemy.orm import Session
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from app.core.database import get_db
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from app.api.auth import get_current_user
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from app.models.user import User
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from app.services.feedback_learner import feedback_learner
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/v1/feedback", tags=["feedback"])
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@router.get("/analysis")
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def get_feedback_analysis(
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days: int = Query(7, ge=1, le=90, description="统计天数"),
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agent_name: Optional[str] = Query(None, description="按 Agent 筛选"),
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current_user: User = Depends(get_current_user),
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):
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"""获取反馈分析报告 — 信号分布、负面率、策略建议。"""
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result = feedback_learner.analyze_feedback_patterns(agent_name=agent_name, days=days)
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return result
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@router.get("/records")
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def list_feedback_records(
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agent_name: Optional[str] = Query(None, description="按 Agent 筛选"),
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signal_type: Optional[str] = Query(None, description="按信号类型筛选"),
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days: int = Query(30, ge=1, le=365, description="统计天数"),
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limit: int = Query(50, ge=1, le=200, description="返回条数"),
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offset: int = Query(0, ge=0, description="偏移量"),
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""查询反馈记录列表。"""
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from datetime import datetime, timedelta
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from app.models.feedback_record import FeedbackRecord
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since = datetime.now() - timedelta(days=days)
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q = db.query(FeedbackRecord).filter(FeedbackRecord.created_at >= since)
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if agent_name:
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q = q.filter(FeedbackRecord.agent_name == agent_name)
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if signal_type:
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q = q.filter(FeedbackRecord.signal_type == signal_type)
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total = q.count()
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records = (
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q.order_by(FeedbackRecord.created_at.desc())
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.offset(offset)
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.limit(limit)
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.all()
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)
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return {
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"total": total,
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"limit": limit,
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"offset": offset,
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"items": [
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{
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"id": r.id,
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"user_id": r.user_id,
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"signal_type": r.signal_type,
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"severity": r.severity,
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"execution_log_id": r.execution_log_id,
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"agent_name": r.agent_name,
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"original_output": (r.original_output or "")[:200],
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"user_correction": (r.user_correction or "")[:200],
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"learned": r.learned,
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"lesson_summary": r.lesson_summary,
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"created_at": r.created_at.isoformat() if r.created_at else None,
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}
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for r in records
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],
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}
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@router.get("/negative-examples/{agent_name}")
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def get_negative_examples(
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agent_name: str,
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limit: int = Query(5, ge=1, le=20, description="返回条数"),
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current_user: User = Depends(get_current_user),
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):
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"""获取指定 Agent 的反例（用于改进 system prompt）。"""
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examples = feedback_learner.generate_negative_examples(agent_name=agent_name, limit=limit)
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return {"agent_name": agent_name, "count": len(examples), "examples": examples}
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