{
"cells": [
{
"cell_type": "code",
"id": "initial_id",
"metadata": {
"collapsed": true,
"ExecuteTime": {
"end_time": "2026-08-15T16:12:20.756187Z",
"start_time": "2026-08-15T16:12:20.180591Z"
}
},
"source": [
"import os\n",
"from langchain.chat_models import init_chat_model\n",
"from dotenv import load_dotenv\n",
"from langchain_core.messages import HumanMessage\n",
"from langgraph.graph import MessagesState\n",
"from langgraph.types import Command, interrupt\n",
"from loguru import logger\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": 1
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2026-08-15T16:12:20.764257Z",
"start_time": "2026-08-15T16:12:20.757920Z"
}
},
"cell_type": "code",
"source": [
"def llm_node(state: MessagesState):\n",
" response = llm.invoke(state[\"messages\"])\n",
" return {\n",
" \"messages\": [response]\n",
" }"
],
"id": "96219f0dc368b2f4",
"outputs": [],
"execution_count": 2
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2026-08-15T16:12:20.769343Z",
"start_time": "2026-08-15T16:12:20.764859Z"
}
},
"cell_type": "code",
"source": [
"from langgraph.graph import StateGraph, START, END\n",
"\n",
"builder = StateGraph(state_schema=MessagesState)\n",
"builder.add_node(\"llm_node\", llm_node)\n",
"builder.add_edge(START, \"llm_node\")\n",
"builder.add_edge(\"llm_node\", END)\n",
"\n",
"graph = builder.compile()"
],
"id": "fb99823e99a8e5ed",
"outputs": [],
"execution_count": 3
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2026-08-15T16:12:28.554444Z",
"start_time": "2026-08-15T16:12:20.769732Z"
}
},
"cell_type": "code",
"source": [
"from rich import print as rp\n",
"\n",
"for chunk in graph.stream(\n",
" {\n",
" \"messages\": [HumanMessage(content=\"你好!\")]\n",
" },\n",
" stream_mode=[\"values\", \"messages\"],\n",
"):\n",
" print(\"=\" * 50)\n",
" rp(chunk)"
],
"id": "a16a8c41b51bf1f2",
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"==================================================\n"
]
},
{
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" )\n",
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"\n"
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"name": "stdout",
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"==================================================\n"
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