langgraph/docs/docs/cloud/quick_start.md

Quick Start

This quick start guide will cover how to develop an application for LangGraph Cloud, run it locally in Docker, and call the APIs to invoke a graph.

Alternatively, clone or fork the langgraph/example GitHub repository and follow the instructions in the README.

Develop

1. Create a new application with the following directory and files:

    <my-app>/
    |-- agent.py            # code for your LangGraph agent
    |-- requirements.txt    # Python packages required for your graph
    |-- langgraph.json      # configuration file for LangGraph
    |-- .env                # environment files with API keys
   

2. The agent.py file should contain the following Python code for defining a simple graph:

   from langchain_openai import ChatOpenAI
   from langgraph.graph import END, MessageGraph
   
   model = ChatOpenAI(temperature=0)
   
   graph_workflow = MessageGraph()
   
   graph_workflow.add_node("agent", model)
   graph_workflow.add_edge("agent", END)
   graph_workflow.set_entry_point("agent")
   
   graph = graph_workflow.compile()
   

3. The requirements.txt file should contain the following dependencies:

    langgraph
    langchain_openai
   

4. The langgraph.json file should contain the following JSON object:

   {
       "dependencies": ["."],
       "graphs": {
           "agent": "./agent.py:graph"
       },
       "env": ".env"
   }
   

   Learn more about the LangGraph CLI configuration file here.

5. The .env file should contain the environment variables:

    OPENAI_API_KEY=<add your key here>
    LANGGRAPH_AUTH_TYPE=noop
   

   !!! warning "Disable Authentication" When testing locally, set LANGGRAPH_AUTH_TYPE to noop to disable authentication.

Run Locally

1. Install the LangGraph CLI.

2. Run the following command to start the API server in Docker:

    langgraph up -c langgraph.json
   

3. The API server is now running at http://localhost:8123. Navigate to http://localhost:8123/docs to view the API docs.

Deploy to Cloud

Follow these instructions to deploy to LangGraph Cloud.