chef_agent

api/agent_api.py

@@ -38,15 +38,10 @@ def chat(request: ChatRequest):
 @agent_router.post("/chat_stream")
 def chat(request: ChatRequest):
 
-    def generate_stream():
-        result = ChefService.chat_stream(
+    return StreamingResponse(
+        ChefService.chat_stream(
             thread_id=request.thread_id,
             message=request.message,
-        )
-        for chunk in result:
-            yield chunk
-
-    return StreamingResponse(
-        generate_stream(),
+        ),
         media_type="text/plain; charset=utf-8"
     )

api/scheduler_api.py

@@ -1,7 +1,5 @@
 from fastapi import APIRouter, HTTPException
 from typing import Any, Dict
-from core.db import SessionDep
-from core.dto.api_response import ApiResponse
 from core.task.dlt_scheduler import scheduler
 
 # 彩票相关的路由

core/config/logging_cof.py

@@ -0,0 +1,24 @@
+import logging
+import sys
+
+import structlog
+
+
+def setup_logging():
+    logging.basicConfig(
+        format='%(message)s',
+        stream=sys.stdout,
+        level=logging.INFO,
+    )
+
+    structlog.configure(
+        processors=[
+            structlog.contextvars.merge_contextvars,
+            structlog.processors.add_log_level,
+            structlog.processors.TimeStamper(fmt='iso'),
+            # structlog.processors.JSONRenderer(ensure_ascii=False),  # 生产输出JSON 开发生产2选一
+            structlog.dev.ConsoleRenderer() # 开发环境彩色控制台
+        ],
+        logger_factory=structlog.stdlib.LoggerFactory(),
+        cache_logger_on_first_use=True,
+    )

core/task/dlt_scheduler.py

@@ -1,30 +1,16 @@
-import logging
-import sys
-from pathlib import Path
 from datetime import datetime
 from typing import List
 
+import structlog
 from apscheduler.job import Job
 from apscheduler.schedulers.background import BackgroundScheduler
 from apscheduler.schedulers.base import STATE_PAUSED, STATE_STOPPED, STATE_RUNNING
 from apscheduler.triggers.cron import CronTrigger
 from apscheduler.events import EVENT_JOB_EXECUTED, EVENT_JOB_ERROR
 
-# 添加项目根目录到路径
-sys.path.append(str(Path(__file__).parent.parent.parent))
-
 from core.task.dlt_spider import DLTSpider
 
-# 配置日志
-logging.basicConfig(
-    level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
-    handlers=[
-        logging.FileHandler('lottery_scheduler.log', encoding='utf-8'),
-        logging.StreamHandler()
-    ]
-)
-logger = logging.getLogger(__name__)
+logger = structlog.getLogger(__name__)
 
 def test_fun():
     logger.info(f"当前时间---{datetime.now()}")

core/task/dlt_spider.py

@@ -1,17 +1,16 @@
-import logging
 from dataclasses import dataclass
 from datetime import datetime
 from typing import Any, List, Dict, Union, Optional, NamedTuple
 import time
 
 import requests
-from pydantic import BaseModel, field_validator
+import structlog
 from sqlalchemy import desc
 
 from core.db import get_db_session
 from models import LotteryDLT
 
-logger = logging.getLogger(__name__)
+logger = structlog.getLogger(__name__)
 
 
 def parse_draw_numbers(result_str: str) -> List[str]:

exceptions/errors.py

@@ -0,0 +1,3 @@
+class AgentNotReadyError(RuntimeError):
+    """agent未初始化错误"""
+    pass

exceptions/handlers.py

@@ -0,0 +1,24 @@
+from fastapi import Request, FastAPI
+from fastapi.responses import JSONResponse
+from exceptions.errors import AgentNotReadyError
+
+
+async def agent_not_ready_handler(request: Request, exc: Exception):
+    """agent未就绪的错误"""
+    return JSONResponse(
+        status_code=503,
+        content={
+            "code": 503,
+            "message": str(exc)
+        }
+    )
+
+
+# 集中处理 保持main简洁
+def register_exception_handlers(app: FastAPI):
+    """集中处理注册异常"""
+
+    app.add_exception_handler(
+        AgentNotReadyError,
+        agent_not_ready_handler,
+    )

lc/chef_agent.py

@@ -1,8 +1,8 @@
 from __future__ import annotations
 
-import logging
 from typing import Any, cast
 
+import structlog
 from langchain.agents import create_agent
 from langchain.agents.middleware import SummarizationMiddleware
 from langchain.agents.middleware.summarization import ContextMessages
@@ -14,8 +14,10 @@ from psycopg import Connection
 from psycopg_pool import ConnectionPool
 
 from core.config.settings import settings
+from exceptions.errors import AgentNotReadyError
+
+logger = structlog.getLogger(__name__)
 
-logger = logging.getLogger(__name__)
 
 class ChefAgent:
     """厨师 Agent。
@@ -30,7 +32,7 @@ class ChefAgent:
     """
 
     def __init__(self) -> None:
-        self._pool: ConnectionPool[Connection[Any]] | None = None
+        self._pool = None
         self._checkpointer: PostgresSaver | None = None
         self._agent = None
 
@@ -81,7 +83,8 @@ class ChefAgent:
 
         llm = init_chat_model(
             model="deepseek-v4-flash",
-            api_key=settings.DEEPSEEK_API_KEY,
+            model_provider="deepseek",
+            api_key=settings.DEEPSEEK_API_KEY
         )
 
         logger.info("chef_agent的llm初始化完成")
@@ -122,16 +125,16 @@ class ChefAgent:
 
         logger.info("chef_agent的CheckPointer开始初始化")
         logger.info("创建PostgreSQL连接池")
-        self.pool: ConnectionPool[Connection[Any]] = ConnectionPool(
+        self._pool = ConnectionPool[Connection[dict[str, Any]]]( # 指定类型[Connection[dict[str, Any]]]防止编译器提示错误
             conninfo=settings.postgres_url,
             max_size=10,
             kwargs={
                 "autocommit": True,
-            },
+            }
         )
 
         logger.info("创建checkpointer")
-        checkpointer = PostgresSaver(self.pool)
+        checkpointer = PostgresSaver(self._pool)
 
         logger.info("初始化checkpoint数据表")
         # 创建 LangGraph checkpoint 所需的数据表
@@ -223,7 +226,8 @@ class ChefAgent:
         """获取 Agent。"""
 
         if self._agent is None:
-            raise RuntimeError(
+            logger.info("ChefAgent 尚未初始化，请先调用 initialize()")
+            raise AgentNotReadyError(
                 "ChefAgent 尚未初始化，请先调用 initialize()"
             )
 
@@ -235,6 +239,7 @@ class ChefAgent:
         if self._pool is not None:
             self._pool.close()
             self._pool = None
+            logger.info("PostgreSQL已关闭")
 
         self._checkpointer = None
         self._agent = None

main.py

@@ -1,4 +1,4 @@
-import logging
+import structlog
 
 import models
 from contextlib import asynccontextmanager
@@ -7,20 +7,18 @@ from fastapi.middleware.cors import CORSMiddleware
 from sqlmodel import SQLModel
 
 from api.agent_api import agent_router
+from core.config.logging_cof import setup_logging
 from core.db import engine
 from core.config.settings import settings
 from api.scheduler_api import scheduler_router
 from api.lottery_api import lottery_router
 from core.task.dlt_scheduler import scheduler
+from exceptions.handlers import register_exception_handlers
 from lc.chef_agent import chef_agent
 
-# 配置日志
-logging.basicConfig(
-    level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
-)
-
-logger = logging.getLogger(__name__)
+# 全局设置日志配置
+setup_logging()
+logger = structlog.getLogger(__name__)
 
 # lifespan生命周期
 @asynccontextmanager
@@ -30,23 +28,34 @@ async def lifespan(app: FastAPI):
     # 同步建表
     SQLModel.metadata.create_all(engine)
 
+    logger.info("服务启动，启动定时调度器")
     # 启动定时调度器
     scheduler.start()
 
-    # 初始化chef_agent
+    logger.info("服务启动，创建携程初始化chef_agent任务")
+    # 异步初始化chef_agent
     chef_agent.initialize()
 
+    logger.info("服务启动完成")
+    try:
         yield # 此处交出控制权，服务开始运行
+    finally:
         # ========== 关闭时执行 ==========
         logger.info("服务关闭，释放资源")
         chef_agent.close()
         scheduler.shutdown()
 
 app = FastAPI(lifespan=lifespan)
+
+# 注册全局异常处理
+register_exception_handlers(app)
+
+# 注册路由
 app.include_router(scheduler_router)
 app.include_router(lottery_router)
 app.include_router(agent_router)
 
+# 注册中间件
 app.add_middleware(
     CORSMiddleware, # type: ignore[arg-type]
     allow_origins=settings.ALLOWED_ORIGINS,

pyproject.toml

@@ -25,5 +25,6 @@ dependencies = [
     "sqlalchemy>=2.0.52",
     "sqlmodel==0.0.42",
     "starlette>=1.6.0",
+    "structlog>=26.1.0",
     "uvicorn==0.52.4",
 ]

services/agent_server/chef_service.py

@@ -1,3 +1,5 @@
+from typing import Iterator
+
 from langchain_core.messages import HumanMessage
 from langchain_core.runnables import RunnableConfig
 
@@ -17,7 +19,11 @@ class ChefService:
         return result
 
     @staticmethod
-    def chat_stream(thread_id: str, message: str):
+    def chat_stream(thread_id: str, message: str) -> Iterator[str]:
         config: RunnableConfig = {"configurable": {"thread_id": thread_id}}
         result = chef_agent.agent.stream({"messages": [("user", message)]}, config=config, stream_mode="messages")
-        return result
+
+        for message_chunk, metadata in result:
+            content = message_chunk.content
+            if content:
+                yield content

test.py

@@ -1,11 +1,20 @@
-sys_prompt = """
-你是一名有名的厨师。收到用户提供的食材照片或清单后，按照以下流程步骤操作：
-1.识别和评估食材：若用户提供照片，首先辨别所有可见食材，基于食材的外观状态，评估其新鲜度和可用量，整理出一份“可用食材清单”。
-2.智能食谱检索：优先调用搜索工具，以“可用食材清单”为核心关键词，查找可行菜谱。
-3.多维度评估与排序：从营养与烹饪难度这2个维度对检索到的候选食谱进行量化打分，并根据得分进行排序，制作简单且营养丰富的排名靠前。
-4.结构化方案输出：把排序后的食谱整理成一份结构清晰的建议报告，要包括食谱信息、得分、推荐理由、食谱的参考图片，帮助用户快速做出决策。
-严格按照流程进行操作，搜索不到再自己发挥。
-"""
+a: int | None = None
 
-if __name__ == "__main__":
-    print(sys_prompt)
+def f(v: int) -> int:
+    pass
+
+def f2(v: int) -> int:
+    a = 5
+
+f(a)
+
+class Test:
+    def __init__(self):
+        self.a: int | None = None
+
+    def f(self, v: int) -> int:
+        pass
+
+    def f2(self):
+        self.a = 5
+        self.f(self.a)

uv.lock

@@ -1428,6 +1428,7 @@ dependencies = [
     { name = "sqlalchemy" },
     { name = "sqlmodel" },
     { name = "starlette" },
+    { name = "structlog" },
     { name = "uvicorn" },
 ]
 
@@ -1455,6 +1456,7 @@ requires-dist = [
     { name = "sqlalchemy", specifier = ">=2.0.52" },
     { name = "sqlmodel", specifier = "==0.0.42" },
     { name = "starlette", specifier = ">=1.6.0" },
+    { name = "structlog", specifier = ">=26.1.0" },
     { name = "uvicorn", specifier = "==0.52.4" },
 ]
 
@@ -2638,6 +2640,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/c8/cb/6a6a47d5b464bd08695d254f3da6e7986cc70c9fa5d778eda57538edfe56/starlette-1.6.0-py3-none-any.whl", hash = "sha256:a86dd39d14bb45f85a3d18525215a9ef0cfd1f192ac793220e72598c90335f0c", size = 75969, upload-time = "2026-08-08T18:27:56.196Z" },
 ]
 
+[[package]]
+name = "structlog"
+version = "26.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/5e/89/b4a0bcfdf4f71a3dea31379f095929613d7e4528a0996bca6aa964cd0dca/structlog-26.1.0.tar.gz", hash = "sha256:f63a716cbd1b1291cf7661de7794b455acfa4c43c5bcf1630e6ad5ddc1adb3b7", size = 1459881, upload-time = "2026-06-06T07:33:39.348Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a9/18/489c97b834dfff9cf2fc2507cede4bcd4b11e67f84bc462acd1992496f86/structlog-26.1.0-py3-none-any.whl", hash = "sha256:e081a26d6c373e6d201eca24eede26d8ffab07f88f477822e679183428d3d91e", size = 73764, upload-time = "2026-06-06T07:33:38.046Z" },
+]
+
 [[package]]
 name = "tenacity"
 version = "9.1.4"