Merge #9 into develop from fix/memory_reflection
新增反思功能（功能配置接口+反思celery后台检测反思的迭代周期） * fix/memory_reflection: (24 commits squashed) - 新增反思功能（功能配置接口+反思celery后台检测反思的迭代周期） - 新增反思功能（功能配置接口+反思celery后台检测反思的迭代周期） - 新增反思功能（检测代码/规范化程序） - 新增反思功能（检测代码/规范化程序） - 新增反思功能（检测代码/规范化程序） - 新增反思功能（检测代码/规范化程序） - 新增反思功能（检测代码/规范化程序） - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 - 反思优化 Signed-off-by: aliyun8644380055 <accounts_68c0f5d519f260d93ee2997e@mail.teambition.com> Commented-by: aliyun8644380055 <accounts_68c0f5d519f260d93ee2997e@mail.teambition.com> Commented-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com> Reviewed-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com> Merged-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com> CR-link: https://codeup.aliyun.com/redbearai/python/redbear-mem-open/change/9
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李新月
200
api/app/controllers/memory_reflection_controller.py
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api/app/controllers/memory_reflection_controller.py
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import asyncio
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from dotenv import load_dotenv
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from fastapi import APIRouter, Depends, HTTPException, status
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from sqlalchemy.orm import Session
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from sqlalchemy import text
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from app.core.logging_config import get_api_logger
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from app.core.memory.storage_services.reflection_engine.self_reflexion import ReflectionConfig, ReflectionEngine
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from app.dependencies import get_current_user
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from app.db import get_db
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from app.models.user_model import User
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from app.repositories.data_config_repository import DataConfigRepository
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from app.repositories.neo4j.neo4j_connector import Neo4jConnector
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from app.services.memory_reflection_service import WorkspaceAppService, MemoryReflectionService
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from app.schemas.memory_reflection_schemas import Memory_Reflection
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load_dotenv()
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api_logger = get_api_logger()
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router = APIRouter(
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prefix="/memory",
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tags=["Memory"],
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)
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@router.post("/reflection/save")
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async def save_reflection_config(
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request: Memory_Reflection,
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current_user: User = Depends(get_current_user),
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db: Session = Depends(get_db),
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) -> dict:
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"""Save reflection configuration to data_comfig table"""
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try:
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config_id = request.config_id
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if not config_id:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail="缺少必需参数: config_id"
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)
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api_logger.info(f"用户 {current_user.username} 保存反思配置，config_id: {config_id}")
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update_params = {
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"enable_self_reflexion": request.reflectionenabled,
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"iteration_period": request.reflection_period_in_hours,
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"reflexion_range": request.reflexion_range,
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"baseline": request.baseline,
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"reflection_model_id": request.reflection_model_id,
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"memory_verify": request.memory_verify,
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"quality_assessment": request.quality_assessment,
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}
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query, params = DataConfigRepository.build_update_reflection(config_id, **update_params)
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result = db.execute(text(query), params)
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if result.rowcount == 0:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail=f"未找到config_id为 {config_id} 的配置"
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)
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db.commit()
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# 查询更新后的配置
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select_query, select_params = DataConfigRepository.build_select_reflection(config_id)
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result = db.execute(text(select_query), select_params).fetchone()
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if not result:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail=f"更新后未找到config_id为 {config_id} 的配置"
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)
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api_logger.info(f"成功保存反思配置到数据库，config_id: {config_id}")
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# 返回结果
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return {
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"status": "成功",
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"message": "反思配置已保存",
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"config_id": config_id,
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"database_record": {
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"config_id": result.config_id,
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"enable_self_reflexion": result.enable_self_reflexion,
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"iteration_period": result.iteration_period,
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"reflexion_range": result.reflexion_range,
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"baseline": result.baseline,
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"reflection_model_id": result.reflection_model_id,
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"memory_verify": result.memory_verify,
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"quality_assessment": result.quality_assessment,
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"user_id": result.user_id
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}
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}
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except ValueError as ve:
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api_logger.error(f"参数错误: {str(ve)}")
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=f"参数错误: {str(ve)}"
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)
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except Exception as e:
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api_logger.error(f"反思配置保存失败: {str(e)}")
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail=f"反思配置保存失败: {str(e)}"
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)
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@router.post("/reflection")
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async def start_workspace_reflection(
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request: dict,
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current_user: User = Depends(get_current_user),
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db: Session = Depends(get_db),
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) -> dict:
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"""Activate the reflection function for all matching applications in the workspace"""
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workspace_id = current_user.current_workspace_id
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reflection_service = MemoryReflectionService(db)
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try:
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api_logger.info(f"用户 {current_user.username} 启动workspace反思，workspace_id: {workspace_id}")
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service = WorkspaceAppService(db)
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result = service.get_workspace_apps_detailed(workspace_id)
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reflection_results = []
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for data in result['apps_detailed_info']:
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if data['data_configs'] == []:
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continue
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releases = data['releases']
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data_configs = data['data_configs']
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end_users = data['end_users']
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for base, config, user in zip(releases, data_configs, end_users):
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if int(base['config']) == int(config['config_id']) and base['app_id'] == user['app_id']:
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# 调用反思服务
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api_logger.info(f"为用户 {user['id']} 启动反思，config_id: {config['config_id']}")
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reflection_result = await reflection_service.start_reflection_from_data(
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config_data=config,
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end_user_id=user['id']
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)
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reflection_results.append({
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"app_id": base['app_id'],
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"config_id": config['config_id'],
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"end_user_id": user['id'],
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"reflection_result": reflection_result
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})
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return {
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"status": "完成",
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"message": f"成功处理 {len(reflection_results)} 个反思任务",
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"workspace_id": str(workspace_id),
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"reflection_count": len(reflection_results),
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"reflection_results": reflection_results
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}
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except Exception as e:
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api_logger.error(f"启动workspace反思失败: {str(e)}")
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail=f"启动workspace反思失败: {str(e)}"
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)
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@router.post("/reflection/run")
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async def reflection_run(
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reflection: Memory_Reflection,
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current_user: User = Depends(get_current_user),
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db: Session = Depends(get_db),
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) -> dict:
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"""Activate the reflection function for all matching applications in the workspace"""
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config = ReflectionConfig(
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enabled=reflection.reflectionenabled,
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iteration_period=reflection.reflection_period_in_hours,
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reflexion_range=reflection.reflexion_range,
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baseline=reflection.baseline,
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output_example='',
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memory_verify=reflection.memory_verify,
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quality_assessment=reflection.quality_assessment,
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violation_handling_strategy="block",
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model_id=reflection.reflection_model_id
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)
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connector = Neo4jConnector()
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engine = ReflectionEngine(
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config=config,
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neo4j_connector=connector,
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llm_client=reflection.reflection_model_id # 传入 model_id
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)
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result=await (engine.reflection_run())
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return result
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