fix(celery, rag): unify rag_write return type and remove deprecated downstream calls
- Unify the return type of `rag_write` in Celery tasks for consistency. - Remove two deprecated downstream API calls to avoid obsolete dependencies.
This commit is contained in:
Eternity
@@ -118,142 +118,142 @@ async def download_log(
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return fail(BizCode.INTERNAL_ERROR, "启动日志流式传输失败", str(e))
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@router.post("/writer_service", response_model=ApiResponse)
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@cur_workspace_access_guard()
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async def write_server(
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user_input: Write_UserInput,
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language_type: str = Header(default=None, alias="X-Language-Type"),
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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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"""
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Write service endpoint - processes write operations synchronously
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Args:
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user_input: Write request containing message and end_user_id
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language_type: 语言类型 ("zh" 中文, "en" 英文)，通过 X-Language-Type Header 传递
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Returns:
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Response with write operation status
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"""
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# 使用集中化的语言校验
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language = get_language_from_header(language_type)
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config_id = user_input.config_id
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workspace_id = current_user.current_workspace_id
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api_logger.info(f"Write service: workspace_id={workspace_id}, config_id={config_id}, language_type={language}")
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# 获取 storage_type，如果为 None 则使用默认值
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storage_type = workspace_service.get_workspace_storage_type(
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db=db,
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workspace_id=workspace_id,
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user=current_user
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)
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if storage_type is None: storage_type = 'neo4j'
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user_rag_memory_id = ''
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# 如果 storage_type 是 rag，必须确保有有效的 user_rag_memory_id
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if storage_type == 'rag':
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if workspace_id:
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knowledge = knowledge_repository.get_knowledge_by_name(
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db=db,
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name="USER_RAG_MERORY",
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workspace_id=workspace_id
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)
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if knowledge:
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user_rag_memory_id = str(knowledge.id)
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else:
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api_logger.warning(
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f"未找到名为 'USER_RAG_MERORY' 的知识库，workspace_id: {workspace_id}，将使用 neo4j 存储")
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storage_type = 'neo4j'
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else:
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api_logger.warning("workspace_id 为空，无法使用 rag 存储，将使用 neo4j 存储")
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storage_type = 'neo4j'
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api_logger.info(
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f"Write service requested for group {user_input.end_user_id}, storage_type: {storage_type}, user_rag_memory_id: {user_rag_memory_id}")
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try:
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messages_list = memory_agent_service.get_messages_list(user_input)
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result = await memory_agent_service.write_memory(
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user_input.end_user_id,
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messages_list,
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config_id,
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db,
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storage_type,
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user_rag_memory_id,
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language
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)
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return success(data=result, msg="写入成功")
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except BaseException as e:
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# Handle ExceptionGroup from TaskGroup (Python 3.11+) or BaseExceptionGroup
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if hasattr(e, 'exceptions'):
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error_messages = [f"{type(sub_e).__name__}: {str(sub_e)}" for sub_e in e.exceptions]
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detailed_error = "; ".join(error_messages)
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api_logger.error(f"Write operation error (TaskGroup): {detailed_error}", exc_info=True)
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return fail(BizCode.INTERNAL_ERROR, "写入失败", detailed_error)
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api_logger.error(f"Write operation error: {str(e)}", exc_info=True)
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return fail(BizCode.INTERNAL_ERROR, "写入失败", str(e))
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@router.post("/writer_service_async", response_model=ApiResponse)
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@cur_workspace_access_guard()
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async def write_server_async(
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user_input: Write_UserInput,
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language_type: str = Header(default=None, alias="X-Language-Type"),
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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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"""
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Async write service endpoint - enqueues write processing to Celery
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Args:
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user_input: Write request containing message and end_user_id
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language_type: 语言类型 ("zh" 中文, "en" 英文)，通过 X-Language-Type Header 传递
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Returns:
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Task ID for tracking async operation
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Use GET /memory/write_result/{task_id} to check task status and get result
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"""
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# 使用集中化的语言校验
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language = get_language_from_header(language_type)
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config_id = user_input.config_id
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workspace_id = current_user.current_workspace_id
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api_logger.info(
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f"Async write service: workspace_id={workspace_id}, config_id={config_id}, language_type={language}")
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# 获取 storage_type，如果为 None 则使用默认值
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storage_type = workspace_service.get_workspace_storage_type(
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db=db,
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workspace_id=workspace_id,
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user=current_user
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)
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if storage_type is None: storage_type = 'neo4j'
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user_rag_memory_id = ''
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if workspace_id:
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knowledge = knowledge_repository.get_knowledge_by_name(
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db=db,
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name="USER_RAG_MERORY",
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workspace_id=workspace_id
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)
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if knowledge: user_rag_memory_id = str(knowledge.id)
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api_logger.info(f"Async write: storage_type={storage_type}, user_rag_memory_id={user_rag_memory_id}")
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try:
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# 获取标准化的消息列表
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messages_list = memory_agent_service.get_messages_list(user_input)
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task = celery_app.send_task(
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"app.core.memory.agent.write_message",
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args=[user_input.end_user_id, messages_list, config_id, storage_type, user_rag_memory_id, language]
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)
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api_logger.info(f"Write task queued: {task.id}")
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return success(data={"task_id": task.id}, msg="写入任务已提交")
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except Exception as e:
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api_logger.error(f"Async write operation failed: {str(e)}")
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return fail(BizCode.INTERNAL_ERROR, "写入失败", str(e))
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# @router.post("/writer_service", response_model=ApiResponse)
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# @cur_workspace_access_guard()
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# async def write_server(
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# user_input: Write_UserInput,
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# language_type: str = Header(default=None, alias="X-Language-Type"),
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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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# """
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# Write service endpoint - processes write operations synchronously
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#
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# Args:
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# user_input: Write request containing message and end_user_id
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# language_type: 语言类型 ("zh" 中文, "en" 英文)，通过 X-Language-Type Header 传递
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#
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# Returns:
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# Response with write operation status
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# """
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# # 使用集中化的语言校验
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# language = get_language_from_header(language_type)
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#
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# config_id = user_input.config_id
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# workspace_id = current_user.current_workspace_id
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# api_logger.info(f"Write service: workspace_id={workspace_id}, config_id={config_id}, language_type={language}")
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#
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# # 获取 storage_type，如果为 None 则使用默认值
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# storage_type = workspace_service.get_workspace_storage_type(
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# db=db,
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# workspace_id=workspace_id,
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# user=current_user
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# )
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# if storage_type is None: storage_type = 'neo4j'
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# user_rag_memory_id = ''
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#
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# # 如果 storage_type 是 rag，必须确保有有效的 user_rag_memory_id
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# if storage_type == 'rag':
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# if workspace_id:
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# knowledge = knowledge_repository.get_knowledge_by_name(
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# db=db,
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# name="USER_RAG_MERORY",
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# workspace_id=workspace_id
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# )
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# if knowledge:
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# user_rag_memory_id = str(knowledge.id)
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# else:
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# api_logger.warning(
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# f"未找到名为 'USER_RAG_MERORY' 的知识库，workspace_id: {workspace_id}，将使用 neo4j 存储")
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# storage_type = 'neo4j'
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# else:
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# api_logger.warning("workspace_id 为空，无法使用 rag 存储，将使用 neo4j 存储")
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# storage_type = 'neo4j'
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#
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# api_logger.info(
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# f"Write service requested for group {user_input.end_user_id}, storage_type: {storage_type}, user_rag_memory_id: {user_rag_memory_id}")
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# try:
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# messages_list = memory_agent_service.get_messages_list(user_input)
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# result = await memory_agent_service.write_memory(
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# user_input.end_user_id,
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# messages_list,
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# config_id,
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# db,
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# storage_type,
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# user_rag_memory_id,
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# language
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# )
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#
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# return success(data=result, msg="写入成功")
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# except BaseException as e:
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# # Handle ExceptionGroup from TaskGroup (Python 3.11+) or BaseExceptionGroup
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# if hasattr(e, 'exceptions'):
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# error_messages = [f"{type(sub_e).__name__}: {str(sub_e)}" for sub_e in e.exceptions]
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# detailed_error = "; ".join(error_messages)
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# api_logger.error(f"Write operation error (TaskGroup): {detailed_error}", exc_info=True)
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# return fail(BizCode.INTERNAL_ERROR, "写入失败", detailed_error)
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# api_logger.error(f"Write operation error: {str(e)}", exc_info=True)
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# return fail(BizCode.INTERNAL_ERROR, "写入失败", str(e))
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#
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#
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# @router.post("/writer_service_async", response_model=ApiResponse)
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# @cur_workspace_access_guard()
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# async def write_server_async(
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# user_input: Write_UserInput,
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# language_type: str = Header(default=None, alias="X-Language-Type"),
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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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# """
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# Async write service endpoint - enqueues write processing to Celery
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#
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# Args:
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# user_input: Write request containing message and end_user_id
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# language_type: 语言类型 ("zh" 中文, "en" 英文)，通过 X-Language-Type Header 传递
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#
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# Returns:
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# Task ID for tracking async operation
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# Use GET /memory/write_result/{task_id} to check task status and get result
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# """
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# # 使用集中化的语言校验
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# language = get_language_from_header(language_type)
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#
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# config_id = user_input.config_id
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# workspace_id = current_user.current_workspace_id
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# api_logger.info(
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# f"Async write service: workspace_id={workspace_id}, config_id={config_id}, language_type={language}")
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#
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# # 获取 storage_type，如果为 None 则使用默认值
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# storage_type = workspace_service.get_workspace_storage_type(
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# db=db,
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# workspace_id=workspace_id,
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# user=current_user
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# )
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# if storage_type is None: storage_type = 'neo4j'
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# user_rag_memory_id = ''
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# if workspace_id:
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#
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# knowledge = knowledge_repository.get_knowledge_by_name(
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# db=db,
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# name="USER_RAG_MERORY",
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# workspace_id=workspace_id
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# )
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# if knowledge: user_rag_memory_id = str(knowledge.id)
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# api_logger.info(f"Async write: storage_type={storage_type}, user_rag_memory_id={user_rag_memory_id}")
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# try:
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# # 获取标准化的消息列表
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# messages_list = memory_agent_service.get_messages_list(user_input)
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#
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# task = celery_app.send_task(
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# "app.core.memory.agent.write_message",
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# args=[user_input.end_user_id, messages_list, config_id, storage_type, user_rag_memory_id, language]
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# )
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# api_logger.info(f"Write task queued: {task.id}")
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#
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# return success(data={"task_id": task.id}, msg="写入任务已提交")
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# except Exception as e:
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# api_logger.error(f"Async write operation failed: {str(e)}")
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# return fail(BizCode.INTERNAL_ERROR, "写入失败", str(e))
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@router.post("/read_service", response_model=ApiResponse)
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