Skip to main content

No project description provided

Project 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 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.

Project details


Release history Release notifications | RSS feed

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-0.9.0.dev5.tar.gz (707.0 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-0.9.0.dev5-py3-none-any.whl (570.7 kB view details)

Uploaded Python 3

File details

Details for the file langgraph_api-0.9.0.dev5.tar.gz.

File metadata

  • Download URL: langgraph_api-0.9.0.dev5.tar.gz
  • Upload date:
  • Size: 707.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for langgraph_api-0.9.0.dev5.tar.gz
Algorithm Hash digest
SHA256 536cd618f1ef1df965b72df44e6f99780a0fc000dc5274d86dc5809d7161d89a
MD5 27066de1447042673ef2a32b940a7188
BLAKE2b-256 671561e179cfb13d19419fe268ea719e9b18fc4be68c6949e664130ce8bcf410

See more details on using hashes here.

File details

Details for the file langgraph_api-0.9.0.dev5-py3-none-any.whl.

File metadata

File hashes

Hashes for langgraph_api-0.9.0.dev5-py3-none-any.whl
Algorithm Hash digest
SHA256 2d9d1b326754fbdce9d379e9f34c8c23dd0c62997664270711045071c4308ae4
MD5 cdbb9b0b5ee1d92f887cdc1fa7190c0e
BLAKE2b-256 f064833c489f36bff4dd1a3c18cb561ee5f8c69d7b25a2283307ae25e27edb35

See more details on using hashes here.

Supported by

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