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    "# How to add node retry policies\n",
    "\n",
    "There are many use cases where you may wish for your node to have a custom retry policy, for example if you are calling an API, querying a database, or calling an LLM, etc. \n",
    "\n",
    "In order to configure the retry policy, you have to pass the `retry` parameter to the `add_node` function. The `retry` parameter takes in a `RetryPolicy` named tuple object. Below we instantiate a `RetryPolicy` object with the default parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RetryPolicy(initial_interval=0.5, backoff_factor=2.0, max_interval=128.0, max_attempts=3, jitter=True, retry_on=<function default_retry_on at 0x1157419e0>)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from langgraph.pregel import RetryPolicy\n",
    "\n",
    "RetryPolicy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want more information on what each of the parameters does, be sure to read the [reference](https://langchain-ai.github.io/langgraph/reference/graphs/#retrypolicy).\n",
    "\n",
    "## Passing a retry policy to a node\n",
    "\n",
    "Lastly, we can pass `RetryPolicy` objects when we call the `add_node` function. In the example below we pass two different retry policies to each of our nodes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import operator\n",
    "import sqlite3\n",
    "from typing import Annotated, Sequence, TypedDict\n",
    "\n",
    "from langchain_anthropic import ChatAnthropic\n",
    "from langchain_core.messages import BaseMessage\n",
    "\n",
    "from langgraph.graph import END, StateGraph, START\n",
    "from langchain_community.utilities import SQLDatabase\n",
    "from langchain_core.messages import AIMessage\n",
    "\n",
    "db = SQLDatabase.from_uri(\"sqlite:///:memory:\")\n",
    "\n",
    "model = ChatAnthropic(model_name=\"claude-2.1\")\n",
    "\n",
    "\n",
    "class AgentState(TypedDict):\n",
    "    messages: Annotated[Sequence[BaseMessage], operator.add]\n",
    "\n",
    "\n",
    "def query_database(state):\n",
    "    query_result = db.run(\"SELECT * FROM Artist LIMIT 10;\")\n",
    "    return {\"messages\": [AIMessage(content=query_result)]}\n",
    "\n",
    "\n",
    "def call_model(state):\n",
    "    response = model.invoke(state[\"messages\"])\n",
    "    return {\"messages\": [response]}\n",
    "\n",
    "\n",
    "# Define a new graph\n",
    "workflow = StateGraph(AgentState)\n",
    "workflow.add_node(\n",
    "    \"query_database\",\n",
    "    query_database,\n",
    "    retry=RetryPolicy(retry_on=sqlite3.OperationalError),\n",
    ")\n",
    "workflow.add_node(\"model\", call_model, retry=RetryPolicy(max_attempts=5))\n",
    "workflow.add_edge(START, \"model\")\n",
    "workflow.add_edge(\"model\", \"query_database\")\n",
    "workflow.add_edge(\"query_database\", END)\n",
    "\n",
    "app = workflow.compile()"
   ]
  }
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