mirror of
https://github.com/langchain-ai/langgraph.git
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Sydney RunkleandGitHub
228a08b966
* Migrate to `uv` * Format `pyproject.toml` files properly * Remove upper bounds on dependencies, and bounds on dev dependencies (we should be using latest) * Move to hatch for packaing In the future we should: * Set up dependabot / automate lockfile updates and tests * Add tests for min compatible versions (I'll do this right after merge) * Use dynamic versioning * Bump `pydantic` to v2.11.4 in the lockfile, we have some tests failing
106 lines
3.1 KiB
Markdown
106 lines
3.1 KiB
Markdown
# LangGraph CLI
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The official command-line interface for LangGraph, providing tools to create, develop, and deploy LangGraph applications.
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## Installation
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Install via pip:
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```bash
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pip install langgraph-cli
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```
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For development mode with hot reloading:
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```bash
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pip install "langgraph-cli[inmem]"
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```
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## Commands
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### `langgraph new` 🌱
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Create a new LangGraph project from a template
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```bash
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langgraph new [PATH] --template TEMPLATE_NAME
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```
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### `langgraph dev` 🏃♀️
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Run LangGraph API server in development mode with hot reloading
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```bash
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langgraph dev [OPTIONS]
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--host TEXT Host to bind to (default: 127.0.0.1)
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--port INTEGER Port to bind to (default: 2024)
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--no-reload Disable auto-reload
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--debug-port INTEGER Enable remote debugging
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--no-browser Skip opening browser window
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-c, --config FILE Config file path (default: langgraph.json)
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```
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### `langgraph up` 🚀
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Launch LangGraph API server in Docker
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```bash
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langgraph up [OPTIONS]
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-p, --port INTEGER Port to expose (default: 8123)
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--wait Wait for services to start
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--watch Restart on file changes
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--verbose Show detailed logs
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-c, --config FILE Config file path
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-d, --docker-compose Additional services file
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```
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### `langgraph build`
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Build a Docker image for your LangGraph application
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```bash
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langgraph build -t IMAGE_TAG [OPTIONS]
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--platform TEXT Target platforms (e.g., linux/amd64,linux/arm64)
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--pull / --no-pull Use latest/local base image
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-c, --config FILE Config file path
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```
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### `langgraph dockerfile`
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Generate a Dockerfile for custom deployments
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```bash
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langgraph dockerfile SAVE_PATH [OPTIONS]
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-c, --config FILE Config file path
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```
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## Configuration
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The CLI uses a `langgraph.json` configuration file with these key settings:
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```json
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{
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"dependencies": ["langchain_openai", "./your_package"], // Required: Package dependencies
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"graphs": {
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"my_graph": "./your_package/file.py:graph" // Required: Graph definitions
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},
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"env": "./.env", // Optional: Environment variables
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"python_version": "3.11", // Optional: Python version (3.11/3.12)
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"pip_config_file": "./pip.conf", // Optional: pip configuration
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"dockerfile_lines": [] // Optional: Additional Dockerfile commands
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}
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```
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See the [full documentation](https://langchain-ai.github.io/langgraph/cloud/reference/cli/) for detailed configuration options.
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## Development
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To develop the CLI itself:
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1. Clone the repository
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2. Navigate to the CLI directory: `cd libs/cli`
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3. Install development dependencies: `uv pip install`
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4. Make your changes to the CLI code
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5. Test your changes:
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```bash
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# Run CLI commands directly
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uv run langgraph --help
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# Or use the examples
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cd examples
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uv pip install
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uv run langgraph dev # or other commands
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```
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## License
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This project is licensed under the terms specified in the repository's LICENSE file.
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