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Deployment

To deploy your LangGraph agent, create and configure a LangGraph app. This setup supports both local development and production deployments.

Features:

  • 🖥️ Local server for development
  • 🧩 Studio Web UI for visual debugging
  • ☁️ Cloud and 🔧 self-hosted deployment options
  • 📊 LangSmith integration for tracing and observability

Requirements

  • ✅ You must have a LangSmith account. You can sign up for free and get started with the free tier.

Create a LangGraph app

pip install -U "langgraph-cli[inmem]"
langgraph new path/to/your/app --template new-langgraph-project-python

This will create an empty LangGraph project. You can modify it by replacing the code in src/agent/graph.py with your agent code. For example:

API Reference: create_react_agent

from langgraph.prebuilt import create_react_agent

def get_weather(city: str) -> str:
    """Get weather for a given city."""
    return f"It's always sunny in {city}!"

graph = create_react_agent(
    model="anthropic:claude-3-7-sonnet-latest",
    tools=[get_weather],
    prompt="You are a helpful assistant"
)

Install dependencies

In the root of your new LangGraph app, install the dependencies in edit mode so your local changes are used by the server:

pip install -e .

Create an .env file

You will find a .env.example in the root of your new LangGraph app. Create a .env file in the root of your new LangGraph app and copy the contents of the .env.example file into it, filling in the necessary API keys:

LANGSMITH_API_KEY=lsv2...
ANTHROPIC_API_KEY=sk-

Launch LangGraph server locally

langgraph dev

This will start up the LangGraph API server locally. If this runs successfully, you should see something like:

Ready!

See this tutorial to learn more about running LangGraph app locally.

LangGraph Studio Web UI

LangGraph Studio Web is a specialized UI that you can connect to LangGraph API server to enable visualization, interaction, and debugging of your application locally. Test your graph in the LangGraph Studio Web UI by visiting the URL provided in the output of the langgraph dev command.

Deployment

Once your LangGraph app is running locally, you can deploy it using LangGraph Cloud or self-hosted options. Refer to the deployment options guide for detailed instructions on all supported deployment models.

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