{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "import os\n",
    "from langchain.chat_models import init_chat_model\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "load_dotenv(override=True)\n",
    "\n",
    "llm = init_chat_model(\n",
    "    model=\"openai:qwen3.6-flash\",\n",
    "    base_url=os.getenv(\"BASE_URL\"),\n",
    "    api_key=os.getenv(\"API_KEY\")\n",
    ")"
   ],
   "outputs": [],
   "execution_count": null
  },
  {
   "metadata": {},
   "cell_type": "code",
   "source": [
    "from langgraph.graph.message import MessagesState\n",
    "\n",
    "\n",
    "class OverallState(MessagesState):\n",
    "    output: str\n",
    "\n",
    "\n",
    "def llm_node(state: OverallState) -> OverallState:\n",
    "    messages = state[\"messages\"]\n",
    "    res = llm.invoke(messages)\n",
    "    return {\n",
    "        \"messages\": [res]\n",
    "    }\n",
    "\n",
    "\n",
    "def output_node(state: OverallState) -> OverallState:\n",
    "    return {\n",
    "        \"output\": state[\"messages\"][-1].content\n",
    "    }"
   ],
   "id": "b443de7fa7929ba2",
   "outputs": [],
   "execution_count": null
  },
  {
   "metadata": {},
   "cell_type": "code",
   "source": [
    "from langgraph.graph import StateGraph, START, END\n",
    "\n",
    "builder = StateGraph(state_schema=OverallState)\n",
    "builder.add_node(\"llm_node\", llm_node)\n",
    "builder.add_node(\"output_node\", output_node)\n",
    "\n",
    "builder.add_edge(START, \"llm_node\")\n",
    "builder.add_edge(\"llm_node\", \"output_node\")\n",
    "builder.add_edge(\"output_node\", END)"
   ],
   "id": "887432b11f020144",
   "outputs": [],
   "execution_count": null
  },
  {
   "metadata": {},
   "cell_type": "code",
   "source": [
    "from langgraph.checkpoint.postgres import PostgresSaver\n",
    "from langchain_core.runnables import RunnableConfig\n",
    "from rich import print as rp\n",
    "\n",
    "with PostgresSaver.from_conn_string(os.getenv(\"LANGGRAPH_DATABASE_URL\")) as checkpointer:\n",
    "    checkpointer.setup()\n",
    "    graph = builder.compile(checkpointer=checkpointer)\n",
    "\n",
    "    config: RunnableConfig = {\n",
    "        \"configurable\": {\n",
    "            \"thread_id\": \"chapter_0804\"\n",
    "        }\n",
    "    }\n",
    "\n",
    "    messages1 = {\n",
    "        \"messages\": [\n",
    "            {\"role\": \"user\", \"content\": \"你好，我是gqt\"}\n",
    "        ]\n",
    "    }\n",
    "    messages2 = {\n",
    "        \"messages\": [\n",
    "            {\"role\": \"user\", \"content\": \"你好，我是谁？\"}\n",
    "        ]\n",
    "    }\n",
    "\n",
    "    res1 = graph.invoke(messages2, config=config)\n",
    "\n",
    "\n",
    "    rp(res1)\n",
    "    history_checkpoint = list(graph.get_state_history(config=config))\n",
    "\n",
    "    # rp(history_checkpoint)"
   ],
   "id": "e0f6b05e0dfeb578",
   "outputs": [],
   "execution_count": null
  }
 ],
 "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
}