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137 lines
4.1 KiB
Markdown
137 lines
4.1 KiB
Markdown
# LangGraph CLI
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[](https://pypi.org/project/langgraph-cli/#history)
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[](https://opensource.org/licenses/MIT)
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[](https://pypistats.org/packages/langgraph-cli)
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[](https://x.com/langchain_oss)
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To help you ship LangGraph apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
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[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.
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## Quick Install
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```bash
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uv add langgraph-cli
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```
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## 🤔 What is this?
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The LangGraph CLI is the official command-line interface for LangGraph. It provides tools to create, develop, build, and run LangGraph applications locally or in Docker.
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## 📖 Documentation
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For full documentation, see the [LangGraph CLI reference](https://reference.langchain.com/python/langgraph-cli). For conceptual guides and tutorials, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview).
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For development mode with hot reloading:
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```bash
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uv add "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"],
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"graphs": {
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"my_graph": "./your_package/file.py:graph"
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},
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"env": "./.env",
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"python_version": "3.11",
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"pip_config_file": "./pip.conf",
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"dockerfile_lines": []
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}
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```
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See the [full documentation](https://reference.langchain.com/python/langgraph-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 sync`
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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 sync
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uv run langgraph dev # or other commands
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```
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## 📕 Releases & Versioning
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See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
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## 💁 Contributing
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As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
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For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
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