langgraph-learning/chapter01/02_reducer.ipynb

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   "source": [
    "\n",
    "\n",
    "\n",
    "from time import sleep\n",
    "\n",
    "from langgraph.graph import StateGraph, START, END\n",
    "\n",
    "\n",
    "def my_reducer(left: list[str], right: list[str]) -> list[str]:\n",
    "    return left + right\n",
    "\n",
    "\n",
    "def id_reducer(left: str, right: str) -> str:\n",
    "    if not left:\n",
    "        return right\n",
    "    if not right:\n",
    "        return left\n",
    "    print(f\"----> {left}+{right}={int(left) + int(right)}\")\n",
    "    return str(int(left) + int(right))\n",
    "\n",
    "\n",
    "from typing import Annotated, TypedDict\n",
    "\n",
    "\n",
    "class OverAllState(TypedDict):\n",
    "    logs: Annotated[list[str], my_reducer]\n",
    "    id: Annotated[str, id_reducer]  # 如果存在并行节点往同一个节点传递数据，没有reducer会报错\n",
    "\n",
    "\n",
    "def node_1(state: OverAllState) -> OverAllState:\n",
    "    for k, v in state.items():\n",
    "        print(k, v)\n",
    "    return {\n",
    "        \"logs\": [\"node_1\"],\n",
    "        \"id\": state[\"id\"]\n",
    "    }\n",
    "\n",
    "\n",
    "def node_2(state: OverAllState) -> OverAllState:\n",
    "    for k, v in state.items():\n",
    "        print(f\"2,{k},{v}\")\n",
    "    return {\n",
    "        \"logs\": [\"node_2\"],\n",
    "        \"id\": state[\"id\"]\n",
    "    }\n",
    "\n",
    "\n",
    "def node_3(state: OverAllState) -> OverAllState:\n",
    "    sleep(1)\n",
    "    for k, v in state.items():\n",
    "        print(f\"3,{k},{v}\")\n",
    "    return {\n",
    "        \"logs\": [\"node_3\"],\n",
    "        \"id\": state[\"id\"]\n",
    "    }\n",
    "\n",
    "\n",
    "def node_4(state: OverAllState) -> OverAllState:\n",
    "    sleep(2)\n",
    "    for k, v in state.items():\n",
    "        print(f\"4,{k},{v}\")\n",
    "    return {\n",
    "        \"logs\": [\"node_4\"],\n",
    "        \"id\": state[\"id\"]\n",
    "    }\n",
    "\n",
    "\n",
    "builder = StateGraph(state_schema=OverAllState)\n",
    "\n",
    "builder.add_node(node_1)\n",
    "builder.add_node(node_2)\n",
    "builder.add_node(node_3)\n",
    "builder.add_node(node_4)\n",
    "\n",
    "builder.add_edge(START, \"node_1\")\n",
    "builder.add_edge(\"node_1\", \"node_2\")\n",
    "builder.add_edge(\"node_1\", \"node_3\")\n",
    "builder.add_edge(\"node_2\", \"node_4\")\n",
    "builder.add_edge(\"node_3\", \"node_4\")\n",
    "builder.add_edge(\"node_4\", END)\n",
    "\n",
    "graph = builder.compile()\n",
    "mermaid_text = graph.get_graph().draw_mermaid()\n",
    "print(mermaid_text)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "config:\n",
      "  flowchart:\n",
      "    curve: linear\n",
      "---\n",
      "graph TD;\n",
      "\t__start__([<p>__start__</p>]):::first\n",
      "\tnode_1(node_1)\n",
      "\tnode_2(node_2)\n",
      "\tnode_3(node_3)\n",
      "\tnode_4(node_4)\n",
      "\t__end__([<p>__end__</p>]):::last\n",
      "\t__start__ --> node_1;\n",
      "\tnode_1 --> node_2;\n",
      "\tnode_1 --> node_3;\n",
      "\tnode_2 --> node_4;\n",
      "\tnode_3 --> node_4;\n",
      "\tnode_4 --> __end__;\n",
      "\tclassDef default fill:#f2f0ff,line-height:1.2\n",
      "\tclassDef first fill-opacity:0\n",
      "\tclassDef last fill:#bfb6fc\n",
      "\n"
     ]
    }
   ],
   "execution_count": 24
  },
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   },
   "cell_type": "code",
   "source": "result = graph.invoke({\"id\": \"2\"})",
   "id": "110aed99961c8afb",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "logs []\n",
      "id 2\n",
      "----> 2+2=4\n",
      "2,logs,['node_1']\n",
      "2,id,4\n",
      "3,logs,['node_1']\n",
      "3,id,4\n",
      "----> 4+4=8\n",
      "----> 8+4=12\n",
      "4,logs,['node_1', 'node_2', 'node_3']\n",
      "4,id,12\n",
      "----> 12+12=24\n"
     ]
    }
   ],
   "execution_count": 25
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-29T13:09:29.470822Z",
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   "cell_type": "code",
   "source": "",
   "id": "88718dd1bf2453c1",
   "outputs": [],
   "execution_count": 25
  }
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