初始化

.env.example

@@ -32,3 +32,6 @@ UPLOAD_DIR=./uploads
 
 # 缓存配置
 CACHE_TTL_SECONDS=300
+
+# AI配置
+DEEPSEEK_API_KEY=api_key

core/config/settings.py

@@ -143,6 +143,17 @@ class Settings(BaseSettings):
         description="缓存过期时间（秒）"
     )
 
+    # ---------- AI配置 ----------
+    DEEPSEEK_API_KEY: str = Field(
+        default="sk-d3e11a4229744fd29a8468e7df072a4b",
+        description="deepseek模型api_key"
+    )
+
+    TAVILY_API_KEY: str = Field(
+        default="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",
+        description="tavily搜索接口api_key"
+    )
+
     # ---------- 计算属性 ----------
     @property
     def mysql_url(self) -> str:

lc/chef_agent.py

@@ -0,0 +1,71 @@
+import os
+import sqlite3
+from typing import cast, Optional
+
+from langchain.agents import create_agent, AgentState
+from langchain.agents.middleware import SummarizationMiddleware
+from langchain.agents.middleware.summarization import ContextMessages
+from langchain.chat_models import init_chat_model
+from langchain_core.language_models import BaseChatModel
+from langchain_core.messages import HumanMessage
+from langchain_core.runnables import RunnableConfig
+from langgraph.checkpoint.sqlite import SqliteSaver # 需要安装langgraph-checkpoint-sqlite
+from langchain_tavily import TavilySearch
+
+from core.config.settings import settings
+
+# 初始化模型 需要多模态大模型 deepseek已支持
+llm_model = init_chat_model(
+    model="deepseek-v4-flash",
+    model_provider="deepseek",
+    api_key=settings.DEEPSEEK_API_KEY
+)
+
+# 定义工具 使用tavily搜索工具 langchain-tavily
+search_tool = TavilySearch(
+    tavily_api_key=settings.TAVILY_API_KEY,
+    max_results=5, # 最大搜索结果条数
+    topic="general"
+)
+
+# 定义记忆策略 使用SummarizationMiddleware摘要策略中间件
+summary = SummarizationMiddleware(
+    model=cast(BaseChatModel, llm_model),  # 消息摘要的记忆管理策略的模型
+    trigger=cast(ContextMessages, ("messages", 10)),  # 触发策略的条件
+    keep=cast(ContextMessages, ("messages", 5))  # 触发策略后保留的消息条数
+)
+
+# 创建数据库目录（如果不存在）
+os.makedirs("sqlite", exist_ok=True)
+# 创建 SQLite 数据库连接 check_same_thread=False 是为了确保在多线程环境下的安全性
+conn = sqlite3.connect("sqlite/checkpoints.db", check_same_thread=False)
+# 初始化 checkpointer
+checkpointer = SqliteSaver(conn)
+# 自动建表
+checkpointer.setup()
+
+# agent提示词
+system_prompt = """
+你是一名有名的国宴厨师。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search_tool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。
+"""
+
+# 定义thread_config 用于记忆存储分组
+thread_config: RunnableConfig  = {"configurable": {"thread_id": "2"}}
+
+# 创建agent
+agent = create_agent(
+    model=cast(BaseChatModel, llm_model), # 指定类型 避免idea报错
+    tools=[search_tool],
+    checkpointer=checkpointer,
+    middleware=[summary],
+    system_prompt=system_prompt
+)
+
+if __name__ == "__main__":
+    question = input("> ")
+    res = agent.invoke({"messages": [HumanMessage(content=question)]}, thread_config)
+    print(res)

lc/deepseek.ipynb

@@ -0,0 +1,194 @@
+{
+ "cells": [
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-09-03T09:14:58.535236Z",
+     "start_time": "2026-09-03T09:14:57.335343800Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "from openai import OpenAI\n",
+    "from openai.types.chat import (\n",
+    "    ChatCompletionSystemMessageParam,\n",
+    "    ChatCompletionUserMessageParam,\n",
+    "    ChatCompletionAssistantMessageParam\n",
+    ")"
+   ],
+   "id": "255e9b078be17a5f",
+   "outputs": [],
+   "execution_count": 1
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-09-03T09:19:09.642201600Z",
+     "start_time": "2026-09-03T09:19:09.628764300Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "client = OpenAI(\n",
+    "    api_key='sk-4bdcdad5d4cd4856bc0c308c3f74eb22',\n",
+    "    base_url='https://api.deepseek.com'\n",
+    ")"
+   ],
+   "id": "6f8aeb64ad6aca1f",
+   "outputs": [],
+   "execution_count": 6
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-09-03T09:17:52.034706300Z",
+     "start_time": "2026-09-03T09:17:52.023338600Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "messages: list[ChatCompletionSystemMessageParam | ChatCompletionUserMessageParam | ChatCompletionAssistantMessageParam] = [\n",
+    "    ChatCompletionSystemMessageParam(role=\"system\", content=\"你是一个ai助手，所有回答使用中文\")\n",
+    "]"
+   ],
+   "id": "4530b047d03a8ab3",
+   "outputs": [],
+   "execution_count": 3
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "# 第一轮对话\n",
+    "print(\"===========\")\n",
+    "messages.append(ChatCompletionUserMessageParam(role=\"user\", content=\"你好，我是大哥\"))\n",
+    "\n",
+    "response = client.chat.completions.create(\n",
+    "    model='deepseek-v4-flash',\n",
+    "    messages=messages,\n",
+    "    stream=False\n",
+    ")"
+   ],
+   "id": "a42f7a8dbdfa3b8c"
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-09-03T08:51:19.785432800Z",
+     "start_time": "2026-09-03T08:51:19.759474700Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# print(response.model_dump_json())\n",
+    "print(response.choices[0].message.content)"
+   ],
+   "id": "fac34b2742f048e0",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "大哥你好！我是你的AI助手，随时听候差遣。今天有什么需要帮忙的吗？\n"
+     ]
+    }
+   ],
+   "execution_count": 12
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-09-03T08:51:41.715208300Z",
+     "start_time": "2026-09-03T08:51:36.483133100Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 第二轮对话\n",
+    "messages.append(ChatCompletionAssistantMessageParam(role=\"assistant\", content=response.choices[0].message.content))\n",
+    "messages.append(ChatCompletionUserMessageParam(role=\"user\", content=\"你还记得我吗\"))\n",
+    "response = client.chat.completions.create(\n",
+    "    model='deepseek-v4-flash',\n",
+    "    messages=messages,\n",
+    ")\n",
+    "print(response.choices[0].message.content)"
+   ],
+   "id": "3c9fa1f10b75c256",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "大哥，这个问题您刚刚才问过呢，我当然记得您！您就是“大哥”嘛，我怎么会忘？\n",
+      "\n",
+      "虽然我的记忆不能跨对话永久保存，但只要咱们在这个对话里，您说的每句话、问的每个问题，我都记得一清二楚——包括您刚才已经问过一次“还记得我吗”，我当时也解释过啦。\n",
+      "\n",
+      "您现在又问一遍，是在考验我，还是想看看我是不是“脸盲”呀？哈哈，放心吧！在这段对话期间，您永远是我的大哥，随叫随到，有事您吩咐！😄\n"
+     ]
+    }
+   ],
+   "execution_count": 14
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-09-03T09:19:38.275536400Z",
+     "start_time": "2026-09-03T09:19:31.090446900Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "messages.append(ChatCompletionUserMessageParam(role=\"user\", content=\"你好，明天合肥天气怎么样\"))\n",
+    "\n",
+    "response = client.chat.completions.create(\n",
+    "    model='deepseek-v4-flash',\n",
+    "    messages=messages,\n",
+    "    stream=False\n",
+    ")\n",
+    "print(response.choices[0].message.content)"
+   ],
+   "id": "ea34cc88d92b2832",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "你好！很抱歉，由于我无法实时联网获取最新的气象数据，所以不能直接为你提供明天合肥的准确天气预报。\n",
+      "\n",
+      "不过，你可以通过以下几种方式快速查到最准确的信息：\n",
+      "\n",
+      "1. 打开手机自带的“天气”应用，添加并定位到“合肥”。\n",
+      "2. 在搜索引擎（如百度）中直接搜索“**合肥明天天气**”，或其他（例如“墨迹天气”）\n",
+      "3. 访问“中国天气网”（www.weather.com.cn），输入“合肥”即可查询。\n",
+      "\n",
+      "另外，由于我无法预知你目前的实际日期，建议你在查询时留意一下，如果是明天出发，记得顺带看一眼**后天**的预报，以便更好地安排行程。祝生活愉快！\n"
+     ]
+    }
+   ],
+   "execution_count": 7
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

lc/lc.ipynb

@@ -0,0 +1,167 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "id": "initial_id",
+   "metadata": {
+    "collapsed": true,
+    "ExecuteTime": {
+     "end_time": "2026-09-05T01:34:44.550869800Z",
+     "start_time": "2026-09-05T01:34:44.535351500Z"
+    }
+   },
+   "source": [
+    "from typing import cast, Literal\n",
+    "\n",
+    "from langchain.agents.middleware.summarization import ContextMessages\n",
+    "from langchain.chat_models import init_chat_model\n",
+    "from langchain.agents import create_agent\n",
+    "from langchain_core.runnables import RunnableConfig\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
+    "from langchain.agents.middleware import SummarizationMiddleware\n",
+    "\n",
+    "from core.config.settings import settings\n",
+    "from langchain.tools import tool\n",
+    "from langchain.messages import HumanMessage\n",
+    "from langchain_core.language_models import BaseChatModel"
+   ],
+   "outputs": [],
+   "execution_count": 15
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-09-05T01:37:24.572533800Z",
+     "start_time": "2026-09-05T01:37:24.555523100Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 初始化模型\n",
+    "my_model = init_chat_model(\n",
+    "    model=\"deepseek-v4-flash\",\n",
+    "    api_key=settings.DEEPSEEK_API_KEY,\n",
+    ")\n",
+    "\n",
+    "# 初始化checkpointer 记忆管理的存储方式\n",
+    "checkpointer = InMemorySaver()\n",
+    "\n",
+    "# 初始化记忆策略中间件\n",
+    "middleware = SummarizationMiddleware(\n",
+    "    model=cast(BaseChatModel, my_model), # 消息摘要的记忆管理策略的模型\n",
+    "    trigger=cast(ContextMessages, (\"messages\", 3)), # 触发策略的条件\n",
+    "    keep=cast(ContextMessages, (\"messages\", 1)) # 触发策略后保留的消息条数\n",
+    ")"
+   ],
+   "id": "b905be968f5c7761",
+   "outputs": [],
+   "execution_count": 22
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-09-05T01:37:26.422888800Z",
+     "start_time": "2026-09-05T01:37:26.408643600Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 初始化agent\n",
+    "agent = create_agent(\n",
+    "    model=cast(BaseChatModel, my_model),\n",
+    "    checkpointer=InMemorySaver(), # 短期记忆 通过thread_id进行记忆分组\n",
+    "    middleware=[middleware]\n",
+    ")"
+   ],
+   "id": "cb5ae2fa4aeaf130",
+   "outputs": [],
+   "execution_count": 23
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-09-05T01:37:59.930524700Z",
+     "start_time": "2026-09-05T01:37:27.968100300Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "config: RunnableConfig = {\"configurable\": {\"thread_id\": \"thread_1\"}}\n",
+    "agent.invoke({\"messages\": [HumanMessage(\"你好，我是胖哥\")]}, config)\n",
+    "agent.invoke({\"messages\": [HumanMessage(\"我喜欢吃美食\")]}, config)\n",
+    "agent.invoke({\"messages\": [HumanMessage(\"我喜欢运动\")]}, config)\n",
+    "\n",
+    "result = agent.invoke({\"messages\": [HumanMessage(\"你还记得我吗\")]}, config)\n",
+    "# print(result)\n",
+    "for message in result['messages']:\n",
+    "    message.pretty_print()"
+   ],
+   "id": "1ed1327c973d75cc",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "================================\u001B[1m Human Message \u001B[0m=================================\n",
+      "\n",
+      "Here is a summary of the conversation to date:\n",
+      "\n",
+      "## SESSION INTENT\n",
+      "\n",
+      "开放式、友好的中文闲聊会话，无具体交付物。用户自称“胖哥”，目前已透露两大爱好：美食与运动。整体目标是延续话题、维持轻松氛围，进一步了解他的偏好，从而围绕美食/运动展开聊天或提供推荐。\n",
+      "\n",
+      "## SUMMARY\n",
+      "\n",
+      "- 用户为“胖哥”，须以中文称呼；全会话均使用中文。\n",
+      "- 话题线索已在两条线上推进：\n",
+      "  1. **美食**：胖哥说“我喜欢吃美食”。助手此前已问他偏好哪些菜系（川菜/粤菜/湘菜）以及喜欢哪种类型（街边小吃、家常菜还是精致餐饮），并邀请他分享最近特别喜欢的一道菜。胖哥尚未回答此组问题。\n",
+      "  2. **运动（新增）**：胖哥随后说“我喜欢运动”。助手将美食与运动联系起来称赞（爱吃又会动、搭配健康），并追问：喜欢哪种运动——健身房撸铁、户外跑步骑行，还是打篮球羽毛球等对抗性项目；同时主动提出可以推荐运动后补充能量的美食搭配。\n",
+      "- 尚无任何结论、决定或策略形成；没有选项被否决。\n",
+      "- 需要注意的是，胖哥对“美食偏好”相关问题尚未作答，该线索仍处于待回应状态。\n",
+      "\n",
+      "## ARTIFACTS\n",
+      "\n",
+      "None.\n",
+      "\n",
+      "## NEXT STEPS\n",
+      "\n",
+      "- 等待胖哥回复：他喜欢哪种运动（健身房/户外/球类对抗等）。\n",
+      "- 得到答复后顺势深入聊天：讨论该运动，可结合他未答复的那组问题，推荐适合运动后的营养美食搭配，或顺带再把菜系/餐饮类型偏好问出来，延长话题。\n",
+      "- 不要重复寒暄，也不要重复之前已问过的两组问题（菜系类型与偏好风格、运动类型选择）。\n",
+      "- 保持中文、热情随意的口吻继续对话。\n",
+      "================================\u001B[1m Human Message \u001B[0m=================================\n",
+      "\n",
+      "你还记得我吗\n",
+      "==================================\u001B[1m Ai Message \u001B[0m==================================\n",
+      "\n",
+      "胖哥，这话说的——当然记得你呀！爱美食又爱运动，能吃会练，这反差感可太让人印象深刻了。咱俩这不正聊到运动嘛，我还等着听你细说呢。  \n",
+      "\n",
+      "不过不急，你先说说最近一次痛快出汗是啥时候？是去健身房撸铁，还是户外疯跑了一圈？反正不管哪种，你要是一会儿饿了，我脑子里的运动后美食搭配可已经在排队了😄\n"
+     ]
+    }
+   ],
+   "execution_count": 24
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

pyproject.toml

@@ -1,11 +1,19 @@
 [project]
 name = "lotteryserver"
 version = "0.1.0"
-requires-python = ">=3.14"
+requires-python = ">=3.13"
 dependencies = [
     "apscheduler==3.11.3",
     "fastapi>=0.141.1",
     "ipykernel>=7.3.0",
+    "langchain>=1.4.0",
+    "langchain-core==1.6.2",
+    "langchain-deepseek==1.1.0",
+    "langchain-tavily==0.2.18",
+    "langgraph>=1.2.11",
+    "langgraph-checkpoint-sqlite==3.1.1",
+    "notebook>=7.6.2",
+    "openai==3.8.0",
     "pydantic==2.13.5",
     "pydantic-settings==2.15.0",
     "pymysql==1.2.0",