Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

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 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.

pip install -U "langgraph-cli[inmem]"

Quickstart

  1. (Optional) Clone a starter template:

    langgraph new --template new-langgraph-project-python ./my-project
    cd my-project
    

    (Recommended) Use a virtual environment and install dependencies:

    python -m venv .venv
    source .venv/bin/activate
    python -m pip install .
    
  2. Start the development server:

    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:

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:

    pip install debugpy
    
  2. Start the server in debug mode:

    langgraph dev --debug-port 5678
    
  3. Configure your IDE:

    • VS Code: Add this launch configuration:
      {
        "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

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 file for details.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

langgraph_api-0.12.0rc9.tar.gz (759.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

langgraph_api-0.12.0rc9-py3-none-any.whl (614.5 kB view details)

Uploaded Python 3

File details

Details for the file langgraph_api-0.12.0rc9.tar.gz.

File metadata

  • Download URL: langgraph_api-0.12.0rc9.tar.gz
  • Upload date:
  • Size: 759.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for langgraph_api-0.12.0rc9.tar.gz
Algorithm Hash digest
SHA256 db6bb86672b5bc29da1f6571750def315627cac1e43ae8eb4e687aefc58492cd
MD5 2ee2f2b94144136679ef8cce7d072999
BLAKE2b-256 d2218e98b087de2d5f42105c2ffd6d04e1a866a64295bf45d226f0488fabd39a

See more details on using hashes here.

File details

Details for the file langgraph_api-0.12.0rc9-py3-none-any.whl.

File metadata

File hashes

Hashes for langgraph_api-0.12.0rc9-py3-none-any.whl
Algorithm Hash digest
SHA256 baa83e54afbc06dbfdff7f09229d765745141c7a823b6a2be07f0f707fd9e2ec
MD5 b763203bf58da90f5277c550e08cfe1d
BLAKE2b-256 a17c28ff9196f41fcc991374eb4976695d27be10fdce3bfa3e8011db8f50693f

See more details on using hashes here.

Release history Release notifications | RSS feed

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page