Description

# LangGraph API This package implements the LangGraph API for rapid development and testing. Build and iterate on LangGraph agents with a tight feedback loop. The server is backed by a predominently in-memory data store that is persisted to local disk when the server is restarted. For production use, see the various [deployment options](https://langchain-ai.github.io/langgraph/concepts/deployment_options/) for the LangGraph API, which are backed by a production-grade database. ## Installation Install the `langgraph-cli` package with the `inmem` extra. Your CLI version must be no lower than `0.1.55`. ```bash pip install -U langgraph-cli[inmem] ``` ## Quickstart 1. (Optional) Clone a starter template: ```bash langgraph new --template new-langgraph-project-python ./my-project cd my-project ``` (Recommended) Use a virtual environment and install dependencies: ```bash python -m venv .venv source .venv/bin/activate python -m pip install . ``` 2. Start the development server: ```shell langgraph dev --config ./langgraph.json ``` 3. The server will launch, opening a browser window with the graph UI. Interact with your graph or make code edits; the server automatically reloads on changes. ## Usage Start the development server: ```bash langgraph dev ``` Your agent's state (threads, runs, assistants) persists in memory while the server is running - perfect for development and testing. Each run's state is tracked and can be inspected, making it easy to debug and improve your agent's behavior. ## How-To #### Attaching a debugger Debug mode lets you attach your IDE's debugger to the LangGraph API server to set breakpoints and step through your code line-by-line. 1. Install debugpy: ```bash pip install debugpy ``` 2. Start the server in debug mode: ```bash langgraph dev --debug-port 5678 ``` 3. Configure your IDE: - **VS Code**: Add this launch configuration: ```json { "name": "Attach to LangGraph", "type": "debugpy", "request": "attach", "connect": { "host": "0.0.0.0", "port": 5678 }, } ``` - **PyCharm**: Use "Attach to Process" and select the langgraph process 4. Set breakpoints in your graph code and start debugging. ## CLI options ```bash langgraph dev [OPTIONS] Options: --debug-port INTEGER Enable remote debugging on specified port --no-browser Skip opening browser on startup --n-jobs-per-worker INTEGER Maximum concurrent jobs per worker process --config PATH Custom configuration file path --no-reload Disable code hot reloading --port INTEGER HTTP server port (default: 8000) --host TEXT HTTP server host (default: localhost) ``` ## License This project is licensed under the Elastic License 2.0 - see the [LICENSE](./LICENSE) file for details.