## 安全修复 (12项) - Webhook接口添加全局Token认证,过滤敏感请求头 - 修复JWT Base64 padding公式,防止签名验证绕过 - 数据库密码/飞书Token从源码移除,改为环境变量 - 工作流引擎添加路径遍历防护 (_resolve_safe_path) - eval()添加模板长度上限检查 - 审批API添加认证依赖 - 前端v-html增强XSS转义,console.log仅开发模式输出 - 500错误不再暴露内部异常详情 ## Agent运行时修复 (7项) - 删除_inject_knowledge_context中未定义db变量的finally块 - 工具执行添加try/except保护,异常不崩溃Agent - LLM重试计入budget计数器 - self_review异常时passed=False - max_iterations截断标记success=False - 工具参数JSON解析失败时记录警告日志 - run()开始时重置_llm_invocations计数器 ## 配置与基础设施 - DEBUG默认False,SQL_ECHO独立配置项 - init_db()补全13个缺失模型导入 - 新增WEBHOOK_AUTH_TOKEN/SQL_ECHO配置项 - 新增.env.example模板文件 ## 前端修复 (12项) - 登录改用URLSearchParams替代FormData - 401拦截器通过Pinia store统一清理状态 - SSE流超时从60s延长至300s - final/error事件时清除streamTimeout - localStorage聊天记录添加24h TTL - safeParseArgCount替代模板中裸JSON.parse - fetchUser 401时同时清除user对象 ## 新增模块 - 知识进化: knowledge_extractor/retriever/tasks - 数字孪生: shadow_executor/comparison模型 - 行为采集: behavior_middleware/collector/fingerprint_engine - 代码审查: code_review_agent/document_review_agent - 反馈学习: feedback_learner - 瓶颈检测/优化引擎/成本估算/需求估算 - 速率限制器 (rate_limiter) - Alembic迁移 015-020 ## 文档 - 商业化落地计划 - 8篇docs文档 (架构/API/部署/开发/贡献等) - Docker Compose生产配置 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
155 lines
4.8 KiB
Python
155 lines
4.8 KiB
Python
"""
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用户行为采集服务 — 非侵入式记录用户操作,用于数字分身学习
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"""
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from __future__ import annotations
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import asyncio
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import logging
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from typing import Any, Dict, List, Optional
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from sqlalchemy.orm import Session
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from sqlalchemy import desc
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from app.core.database import SessionLocal
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from app.models.user_behavior import UserBehaviorLog, BehaviorCategory
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logger = logging.getLogger(__name__)
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class BehaviorCollector:
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"""用户行为采集器(单例)"""
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def log_sync(
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self,
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*,
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user_id: str,
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category: str,
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action: str,
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context: Optional[Dict[str, Any]] = None,
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result: Optional[Dict[str, Any]] = None,
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source: str = "api",
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session_id: Optional[str] = None,
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ip_address: Optional[str] = None,
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user_agent: Optional[str] = None,
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) -> Optional[str]:
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"""同步写入行为日志,返回日志 ID。"""
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db: Optional[Session] = None
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try:
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db = SessionLocal()
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entry = UserBehaviorLog(
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user_id=user_id,
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category=category,
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action=action,
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context=context,
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result=result,
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source=source,
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session_id=session_id,
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ip_address=ip_address,
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user_agent=user_agent,
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)
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db.add(entry)
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db.commit()
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db.refresh(entry)
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return str(entry.id)
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except Exception as e:
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logger.warning("写入用户行为日志失败: %s", e)
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if db:
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try:
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db.rollback()
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except Exception:
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pass
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return None
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finally:
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if db:
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try:
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db.close()
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except Exception:
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pass
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async def log(self, **kwargs) -> Optional[str]:
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"""异步写入(线程池)。"""
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loop = asyncio.get_running_loop()
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return await loop.run_in_executor(None, lambda: self.log_sync(**kwargs))
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def log_fire_and_forget(self, **kwargs):
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"""Fire-and-forget 写入。"""
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try:
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asyncio.ensure_future(self.log(**kwargs))
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except Exception:
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pass
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# ─── 查询方法 ───
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def get_user_behaviors(
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self,
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user_id: str,
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category: Optional[str] = None,
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limit: int = 50,
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skip: int = 0,
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) -> List[Dict[str, Any]]:
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"""获取用户行为历史。"""
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db: Optional[Session] = None
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try:
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db = SessionLocal()
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q = db.query(UserBehaviorLog).filter(UserBehaviorLog.user_id == user_id)
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if category:
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q = q.filter(UserBehaviorLog.category == category)
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q = q.order_by(desc(UserBehaviorLog.created_at)).offset(skip).limit(limit)
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rows = q.all()
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return [
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{
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"id": r.id,
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"category": r.category,
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"action": r.action,
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"context": r.context,
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"result": r.result,
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"source": r.source,
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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 rows
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]
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except Exception as e:
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logger.warning("查询用户行为日志失败: %s", e)
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return []
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finally:
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if db:
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try:
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db.close()
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except Exception:
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pass
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def get_behavior_stats(self, user_id: str) -> Dict[str, Any]:
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"""获取用户行为统计摘要。"""
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db: Optional[Session] = None
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try:
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db = SessionLocal()
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from sqlalchemy import func
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total = db.query(func.count(UserBehaviorLog.id)).filter(
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UserBehaviorLog.user_id == user_id
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).scalar() or 0
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by_category = {}
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for cat in BehaviorCategory:
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count = db.query(func.count(UserBehaviorLog.id)).filter(
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UserBehaviorLog.user_id == user_id,
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UserBehaviorLog.category == cat.value,
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).scalar() or 0
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by_category[cat.value] = count
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return {
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"user_id": user_id,
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"total_behaviors": total,
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"by_category": by_category,
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}
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except Exception as e:
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logger.warning("查询行为统计失败: %s", e)
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return {"user_id": user_id, "total_behaviors": 0, "by_category": {}}
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finally:
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if db:
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try:
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db.close()
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except Exception:
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pass
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# 全局单例
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behavior_collector = BehaviorCollector()
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