langgraph-cli

name langgraph-cli description 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. The `langgraph` CLI manages the full lifecycle of LangGraph applications — from scaffolding a new project to deploying it to LangGraph Platform (LangSmith Deployments). Key commands: langgraph new — Scaffold a project from a template langgraph dev — Run locally with hot reload (no Docker) langgraph build — Build a Docker image langgraph up — Launch locally via Docker Compose langgraph deploy — Ship to LangGraph Platform langgraph dockerfile — Generate a Dockerfile All commands (except new ) read from a langgraph.json config file in the project root. When to use Use this skill when the user wants to: Scaffold a new LangGraph project Run a local development or production-like server Build or deploy a LangGraph application Understand or edit langgraph.json configuration Manage LangSmith Deployments (list, delete, view logs) Installation # Python pip install 'langgraph-cli[inmem]' # includes langgraph dev support pip install langgraph-cli # without dev server (build/up/deploy only) # if using UV as package manager uv add "langgraph-cli[inmem]" # includes langgraph dev support uv add langgraph-cli # without dev server (build/up/deploy only) # JavaScript npx @langchain/langgraph-cli # use on demand npm install -g @langchain/langgraph-cli # install globally (available as langgraphjs) Commands langgraph new [PATH] Scaffold a new project from a template. langgraph new # interactive template selection langgraph new ./my-agent # create in specific directory langgraph new --template agent-python # skip prompt, use template directly Available templates: deep-agent-python , deep-agent-js , agent-python , new-langgraph-project-python , new-langgraph-project-js langgraph dev Run a local development server with hot reloading. No Docker required. langgraph 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 Build a Docker image for the LangGraph API server. 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 version langgraph up Launch the LangGraph API server via Docker Compose (includes Postgres). langgraph 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 healthy langgraph deploy Build 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 . langgraph 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 logs Prereq: LANGSMITH_API_KEY in environment or .env . langgraph deploy also accepts build flags: --base-image , --pull / --no-pull . langgraph deploy list langgraph deploy list # list all deployments langgraph deploy list --name-contains bot # filter by name langgraph deploy delete langgraph deploy delete <deployment-id> # interactive confirmation langgraph deploy delete <deployment-id> --force # skip confirmation langgraph deploy logs langgraph 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 range langgraph dockerfile <SAVE_PATH> Generate a Dockerfile (and optionally Docker Compose files) without building. langgraph dockerfile ./Dockerfile # generate Dockerfile langgraph dockerfile ./Dockerfile --add-docker-compose # also generate compose + .env + .dockerignore langgraph.json reference The configuration file used by all CLI commands ( dev , build , up , deploy ). Defaults to langgraph.json in the current directory. Minimal config (Python) { "dependencies" : [ "." ] , "graphs" : { "agent" : "./my_agent/agent.py:graph" } , "env" : "./.env" } Minimal config (JavaScript) { "dependencies" : [ "." ] , "graphs" : { "agent" : "./src/agent.js:graph" } , "env" : "./.env" } Full config with all keys { "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" ] } Key reference 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. Typical workflow Scaffold — langgraph new to create a project from a template. Configure — Edit langgraph.json : set dependencies, point graphs at your compiled graph(s), add .env . Develop — langgraph dev for rapid local iteration with hot reload (no Docker, port 2024). Validate — langgraph up --recreate to test in a production-like Docker stack (port 8123, includes Postgres). Deploy — langgraph deploy to ship to LangGraph Platform (LangSmith Deployments). Monitor — 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 Gotchas 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. JavaScript CLI — Use npx @langchain/langgraph-cli <command> (or langgraphjs if installed globally via npm install -g @langchain/langgraph-cli ). API key — 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 .