The official command-line interface for LangGraph, providing tools to create, develop, and deploy LangGraph applications.
Install via pip:
pip install langgraph-cliFor development mode with hot reloading:
pip install "langgraph-cli[inmem]"langgraph new 🌱Create a new LangGraph project from a template
langgraph new [PATH] --template TEMPLATE_NAMElanggraph dev 🏃♀️Run LangGraph API server in development mode with hot reloading
langgraph dev [OPTIONS]
--host TEXT Host to bind to (default: 127.0.0.1)
--port INTEGER Port to bind to (default: 2024)
--no-reload Disable auto-reload
--debug-port INTEGER Enable remote debugging
--no-browser Skip opening browser window
-c, --config FILE Config file path (default: langgraph.json)langgraph up 🚀Launch LangGraph API server in Docker
langgraph up [OPTIONS]
-p, --port INTEGER Port to expose (default: 8123)
--wait Wait for services to start
--watch Restart on file changes
--verbose Show detailed logs
-c, --config FILE Config file path
-d, --docker-compose Additional services filelanggraph buildBuild a Docker image for your LangGraph application
langgraph build -t IMAGE_TAG [OPTIONS]
--platform TEXT Target platforms (e.g., linux/amd64,linux/arm64)
--pull / --no-pull Use latest/local base image
-c, --config FILE Config file pathlanggraph dockerfileGenerate a Dockerfile for custom deployments
langgraph dockerfile SAVE_PATH [OPTIONS]
-c, --config FILE Config file pathThe CLI uses a langgraph.json configuration file with these key settings:
{
"dependencies": ["langchain_openai", "./your_package"], // Required: Package dependencies
"graphs": {
"my_graph": "./your_package/file.py:graph" // Required: Graph definitions
},
"env": "./.env", // Optional: Environment variables
"python_version": "3.11", // Optional: Python version (3.11/3.12)
"pip_config_file": "./pip.conf", // Optional: pip configuration
"dockerfile_lines": [] // Optional: Additional Dockerfile commands
}See the full documentation for detailed configuration options.
To develop the CLI itself:
cd libs/cliuv pip install# Run CLI commands directly
uv run langgraph --help
# Or use the examples
cd examples
uv pip install
uv run langgraph dev # or other commandsThis project is licensed under the terms specified in the repository's LICENSE file.
Configuration for TTL (time-to-live) behavior in the store.
Configuration for indexing documents for semantic search in the store.
Configuration for the built-in long-term memory store.
Configure a default TTL for checkpointed data within threads.
Configuration for the built-in serde, which handles checkpointing of state.
Configuration for the built-in checkpointer, which handles checkpointing of state.
Configuration for OpenAPI security definitions and requirements.
Configuration for custom authentication logic and how it integrates into the OpenAPI spec.
Configuration for custom at-rest encryption logic.
Specifies Cross-Origin Resource Sharing (CORS) rules for your server.
Customize which headers to include as configurable values in your runs.
Configuration for the built-in HTTP server that powers your deployment's routes and endpoints.
Top-level config for langgraph-cli or similar deployment tooling.
A container for referencing and managing local Python dependencies.
Show warning if image_distro is not set to 'wolfi'.
CLI entrypoint for running the LangGraph API server.
Create a new LangGraph project from a template.
Prepare the arguments and stdin for running the LangGraph API server.
Create a new LangGraph project at the specified PATH using the chosen TEMPLATE.
Convert a dictionary to a YAML string.
Create a docker compose file as a dictionary in YML style.
Create a docker compose file as a string.
Validate a configuration dictionary.
Load and validate a configuration file.
Generate a Dockerfile from the configuration.