langgraph/examples/docs/quickstart.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quickstart\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture --no-stderr\n",
    "%pip install --quiet -U langgraph langchain-openai"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import getpass\n",
    "import os\n",
    "\n",
    "if not os.environ.get(\"OPENAI_API_KEY\"):\n",
    "    os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_core.messages import BaseMessage, HumanMessage\n",
    "from langchain_openai import ChatOpenAI\n",
    "\n",
    "from langgraph.graph import END, MessageGraph\n",
    "\n",
    "model = ChatOpenAI(temperature=0)\n",
    "\n",
    "graph = MessageGraph()\n",
    "\n",
    "graph.add_node(\"oracle\", model)\n",
    "graph.add_edge(\"oracle\", END)\n",
    "\n",
    "graph.set_entry_point(\"oracle\")\n",
    "\n",
    "runnable = graph.compile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import Image, display\n",
    "\n",
    "try:\n",
    "    display(Image(runnable.get_graph(xray=True).draw_mermaid_png()))\n",
    "except Exception:\n",
    "    # This requires some extra dependencies and is optional\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[HumanMessage(content='What is 1 + 1?', id='bb29f237-0e4d-4354-92e1-d46434c67fe7'),\n",
       " AIMessage(content='1 + 1 equals 2.', response_metadata={'token_usage': {'completion_tokens': 8, 'prompt_tokens': 15, 'total_tokens': 23}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-2ff0112a-9402-44a1-a992-c44fb49fa894-0', usage_metadata={'input_tokens': 15, 'output_tokens': 8, 'total_tokens': 23})]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "runnable.invoke(HumanMessage(\"What is 1 + 1?\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "from typing import Literal\n",
    "\n",
    "from langchain_core.tools import tool\n",
    "\n",
    "from langgraph.graph import END, START\n",
    "from langgraph.prebuilt import ToolNode\n",
    "\n",
    "\n",
    "@tool\n",
    "def multiply(first_number: int, second_number: int):\n",
    "    \"\"\"Multiplies two numbers together.\"\"\"\n",
    "    return first_number * second_number\n",
    "\n",
    "\n",
    "model = ChatOpenAI(temperature=0)\n",
    "model_with_tools = model.bind_tools(tools=[multiply])\n",
    "\n",
    "graph = MessageGraph()\n",
    "\n",
    "graph.add_node(\"oracle\", model_with_tools)\n",
    "\n",
    "tool_node = ToolNode([multiply])\n",
    "graph.add_node(\"multiply\", tool_node)\n",
    "graph.add_edge(START, \"oracle\")\n",
    "graph.add_edge(\"multiply\", END)\n",
    "\n",
    "\n",
    "def router(state: list[BaseMessage]) -> Literal[\"multiply\", \"__end__\"]:\n",
    "    tool_calls = state[-1].additional_kwargs.get(\"tool_calls\", [])\n",
    "    if len(tool_calls):\n",
    "        return \"multiply\"\n",
    "    else:\n",
    "        return END\n",
    "\n",
    "\n",
    "graph.add_conditional_edges(\"oracle\", router)\n",
    "runnable = graph.compile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "try:\n",
    "    display(Image(runnable.get_graph(xray=True).draw_mermaid_png()))\n",
    "except Exception:\n",
    "    # This requires some extra dependencies and is optional\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[HumanMessage(content='What is 123 * 456?', id='fa2dbb36-c61b-4ce1-892d-c08f3e741035'),\n",
       " AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_ZpoO6ClLFKkppN9Y8GEelZH1', 'function': {'arguments': '{\"first_number\":123,\"second_number\":456}', 'name': 'multiply'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 19, 'prompt_tokens': 57, 'total_tokens': 76}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': None, 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-ee9faec5-3526-45d5-89b1-5292755a6893-0', tool_calls=[{'name': 'multiply', 'args': {'first_number': 123, 'second_number': 456}, 'id': 'call_ZpoO6ClLFKkppN9Y8GEelZH1'}], usage_metadata={'input_tokens': 57, 'output_tokens': 19, 'total_tokens': 76}),\n",
       " ToolMessage(content='56088', name='multiply', id='b9992170-ca76-4256-8560-29b329c1b56e', tool_call_id='call_ZpoO6ClLFKkppN9Y8GEelZH1')]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "runnable.invoke(HumanMessage(\"What is 123 * 456?\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[HumanMessage(content='What is your name?', id='09f03ac4-ca68-4464-9ec3-2c393699b3bb'),\n",
       " AIMessage(content='My name is Assistant. How can I assist you today?', response_metadata={'token_usage': {'completion_tokens': 13, 'prompt_tokens': 54, 'total_tokens': 67}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-a21b2f58-3fa6-428f-99e5-9c4e071a9319-0', usage_metadata={'input_tokens': 54, 'output_tokens': 13, 'total_tokens': 67})]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "runnable.invoke(HumanMessage(\"What is your name?\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}