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SKILL.md
npx skills add langchain-ai/langchain-skills --skill langgraph-cli
INVOKE THIS SKILL when using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration.
npx skills add langchain-ai/langchain-skills --skill langgraph-cli
Key commands:
langgraph new — Scaffold a project from a templatelanggraph dev — Run locally with hot reload (no Docker)langgraph build — Build a Docker imagelanggraph up — Launch locally via Docker Composelanggraph deploy — Ship to LangGraph Platformlanggraph dockerfile — Generate a DockerfileAll commands (except new) read from a langgraph.json config file in the project root.
Use this skill when the user wants to:
langgraph.json configurationlanggraph new [PATH]Scaffold a new project from a template.
Available templates: deep-agent-python, deep-agent-js, agent-python, new-langgraph-project-python, new-langgraph-project-js
langgraph devRun a local development server with hot reloading. No Docker required.
langgraph buildBuild a Docker image for the LangGraph API server.
langgraph upLaunch the LangGraph API server via Docker Compose (includes Postgres).
langgraph deployBuild and deploy to LangGraph Platform (LangSmith Deployments). Requires Docker. On Apple Silicon (M1/M2/M3), Docker Buildx is also required for cross-compiling to linux/amd64.
Prereq: LANGSMITH_API_KEY in environment or .env.
langgraph deploy also accepts build flags: --base-image, --pull/--no-pull.
langgraph deploy listlanggraph deploy deletelanggraph deploy logslanggraph dockerfile <SAVE_PATH>Generate a Dockerfile (and optionally Docker Compose files) without building.
langgraph.json referenceThe configuration file used by all CLI commands (dev, build, up, deploy). Defaults to langgraph.json in the current directory.
| Key | Required | Description |
|---|---|---|
dependencies | Yes | Array of dependencies. "." looks for local packages via pyproject.toml, setup.py, requirements.txt, or package.json. Can also be paths to subdirectories ("./my_pkg") or package names ("langchain_openai"). |
graphs | Yes | Mapping of graph ID to path. Format: ./path/to/file.py:variable (Python) or ./path/to/file.js:function (JS). The variable must be a CompiledGraph or a function returning one. Multiple graphs supported. |
env | No | Path to a .env file (string) OR an inline mapping of env var names to values (object). Used by langgraph dev and langgraph up locally. langgraph deploy reads from this file and adds the variables as deployment secrets. |
python_version | No | "3.11", "3.12", or "3.13". Defaults to "3.11". |
node_version | No | Node.js version for JS projects. |
pip_config_file | No | Path to a pip config file for custom package indexes. |
dockerfile_lines | No | Array of additional Dockerfile lines appended after the base image import. Use for system packages, binaries, or custom setup. |
langgraph new to create a project from a template.langgraph.json: set dependencies, point graphs at your compiled graph(s), add .env.langgraph dev for rapid local iteration with hot reload (no Docker, port 2024).langgraph up --recreate to test in a production-like Docker stack (port 8123, includes Postgres).langgraph deploy to ship to LangGraph Platform (LangSmith Deployments).langgraph deploy logs -f to tail runtime logs; --type build for build logs.langgraph dev vs langgraph up| Feature | langgraph dev | langgraph up |
|---|---|---|
| Docker required | No | Yes |
| Install | pip install 'langgraph-cli[inmem]' | pip install langgraph-cli |
| Primary use | Rapid development & testing | Production-like validation |
| State persistence | In-memory / pickled to local dir | PostgreSQL |
| Hot reloading | Yes (default) | Optional (--watch) |
| Default port | 2024 | 8123 |
| Resource usage | Lightweight | Heavier (Docker containers for server, Postgres, Redis) |
| IDE debugging | Built-in DAP support (--debug-port) | Container debugging |
langgraph deploy requires Docker — On Apple Silicon (M1/M2/M3), Docker Buildx is also required for cross-compiling to linux/amd64.langgraph deploy can only update its own deployments — Deployments created through the LangSmith UI or GitHub integration cannot be updated with langgraph deploy. Use the UI for those.dependencies must include all packages — The dependencies array in langgraph.json must point to where your package config lives (e.g., "." for root). The actual packages are resolved from pyproject.toml, requirements.txt, or package.json at that location.langgraph dev runs without Docker — It runs directly in your environment. If your code depends on system packages (e.g., ffmpeg), they must be installed locally. Use langgraph up to validate Docker builds.npx @langchain/langgraph-cli <command> (or langgraphjs if installed globally via npm install -g @langchain/langgraph-cli).LANGSMITH_API_KEY is required for langgraph deploy. For langgraph dev, it is optional — the server runs without it, but you won't get traces in LangSmith. Can also be set via LANGGRAPH_HOST_API_KEY or LANGCHAIN_API_KEY.langgraph new # interactive template selection
langgraph new ./my-agent # create in specific directory
langgraph new --template agent-python # skip prompt, use template directlylanggraph dev # default: localhost:2024
langgraph dev --port 8000 # custom port
langgraph dev --config ./langgraph.json # explicit config path
langgraph dev --no-reload # disable hot reload
langgraph dev --no-browser # don't auto-open LangGraph Studio
langgraph dev --host 0.0.0.0 # bind to all interfaces (trusted networks only)
langgraph dev --tunnel # expose via Cloudflare tunnel for remote access
langgraph dev --debug-port 5678 # enable remote debugger (requires debugpy)
langgraph dev --n-jobs-per-worker 20 # max concurrent jobs per worker (default: 10)langgraph build -t my-image # required: tag the image
langgraph build -t my-image --no-pull # use locally-built base images
langgraph build -t my-image -c langgraph.json # explicit config
langgraph build -t my-image --base-image langchain/langgraph-server:0.2.18 # pin base versionlanggraph up # default port 8123
langgraph up --port 8000 # custom port
langgraph up --watch # restart on file changes
langgraph up --recreate # force fresh build (useful for pre-deploy validation)
langgraph up --postgres-uri postgresql://... # external Postgres
langgraph up --no-pull # use local images (after langgraph build)
langgraph up --image my-image # skip build, use pre-built image
langgraph up -d docker-compose.yml # add extra Docker services
langgraph up --debugger-port 8124 # serve debugger UI
langgraph up --wait # block until services are healthylanggraph deploy # deploy, name defaults to directory name
langgraph deploy --name my-agent # explicit deployment name
langgraph deploy --deployment-type prod # production deployment (default: dev)
langgraph deploy --tag v1.2.0 # custom image tag (default: latest)
langgraph deploy --deployment-id <id> # update an existing deployment by ID
langgraph deploy --config ./langgraph.json # explicit config path
langgraph deploy --no-wait # don't wait for deployment status
langgraph deploy --verbose # show detailed server logslanggraph deploy list # list all deployments
langgraph deploy list --name-contains bot # filter by namelanggraph deploy delete <deployment-id> # interactive confirmation
langgraph deploy delete <deployment-id> --force # skip confirmationlanggraph deploy logs # runtime logs, last 100
langgraph deploy logs --name my-agent # by deployment name
langgraph deploy logs --deployment-id <id> # by deployment ID
langgraph deploy logs --type build # build logs instead of runtime
langgraph deploy logs -f # follow/stream logs
langgraph deploy logs --level error # filter by level (debug|info|warning|error|critical)
langgraph deploy logs -q "timeout" # search filter
langgraph deploy logs --limit 500 # more entries
langgraph deploy logs --start-time 2026-03-08T00:00:00Z # time rangelanggraph dockerfile ./Dockerfile # generate Dockerfile
langgraph dockerfile ./Dockerfile --add-docker-compose # also generate compose + .env + .dockerignore{
"dependencies": ["."],
"graphs": {
"agent": "./my_agent/agent.py:graph"
},
"env": "./.env"
}{
"dependencies": ["."],
"graphs": {
"agent": "./src/agent.js:graph"
},
"env": "./.env"
}{
"dependencies": [".", "langchain_openai", "./local_package"],
"graphs": {
"agent": "./my_agent/agent.py:graph",
"retriever": "./my_agent/rag.py:rag_graph"
},
"env": "./.env",
"python_version": "3.12",
"pip_config_file": "./pip.conf",
"dockerfile_lines": [
"RUN apt-get update && apt-get install -y ffmpeg"
]
}