LangGraph CLI - Docs by LangChain

LangGraph CLI is a command-line tool for building and running the Agent Server locally. The resulting server exposes all API endpoints for runs, threads, assistants, etc., and includes supporting services such as a managed database for checkpointing and storage.

Installation

Ensure Docker is installed (e.g., docker --version).

Install the CLI:

pip install langgraph-cli

# Use latest on demand
npx @langchain/langgraph-cli

# Or install globally (available as `langgraphjs`)
npm install -g @langchain/langgraph-cli

Verify the install

langgraph --help

npx @langchain/langgraph-cli --help

Quick commands

Command	What it does
`langgraph dev`	Starts a lightweight local dev server (no Docker required), ideal for rapid testing.
`langgraph build`	Builds a Docker image of your LangGraph API server for deployment.
`langgraph dockerfile`	Emits a Dockerfile derived from your config for custom builds.
`langgraph up`	Starts the LangGraph API server locally in Docker. Requires Docker running; LangSmith API key for local dev; license for production.

For JS, use npx @langchain/langgraph-cli <command> (or langgraphjs if installed globally).

Configuration file

To build and run a valid application, the LangGraph CLI requires a JSON configuration file that follows this schema. It contains the following properties:

The LangGraph CLI defaults to using the configuration file named langgraph.json in the current directory.

Python
JS

Key	Description
`dependencies`	Required. Array of dependencies for LangSmith API server. Dependencies can be one of the following: A single period (`"."`), which will look for local Python packages. The directory path where `pyproject.toml`, `setup.py` or `requirements.txt` is located. For example, if `requirements.txt` is located in the root of the project directory, specify `"./"`. If it’s located in a subdirectory called `local_package`, specify `"./local_package"`. Do not specify the string `"requirements.txt"` itself. A Python package name.
`graphs`	Required. Mapping from graph ID to path where the compiled graph or a function that makes a graph is defined. Example: `./your_package/your_file.py:variable`, where `variable` is an instance of `langgraph.graph.state.CompiledStateGraph` `./your_package/your_file.py:make_graph`, where `make_graph` is a function that takes a config dictionary (`langchain_core.runnables.RunnableConfig`) and returns an instance of `langgraph.graph.state.StateGraph` or `langgraph.graph.state.CompiledStateGraph`. See how to rebuild a graph at runtime for more details.
`auth`	(Added in v0.0.11) Auth configuration containing the path to your authentication handler. Example: `./your_package/auth.py:auth`, where `auth` is an instance of `langgraph_sdk.Auth`. See authentication guide for details.
`base_image`	Optional. Base image to use for the LangGraph API server. Defaults to `langchain/langgraph-api` or `langchain/langgraphjs-api`. Use this to pin your builds to a particular version of the langgraph API, such as `"langchain/langgraph-server:0.2"`. See https://hub.docker.com/r/langchain/langgraph-server/tags for more details. (added in `langgraph-cli==0.2.8`)
`image_distro`	Optional. Linux distribution for the base image. Must be one of `"debian"`, `"wolfi"`, `"bookworm"`, or `"bullseye"`. If omitted, defaults to `"debian"`. Available in `langgraph-cli>=0.2.11`.
`env`	Path to `.env` file or a mapping from environment variable to its value.
`store`	Configuration for adding semantic search and/or time-to-live (TTL) to the BaseStore. Contains the following fields: `index` (optional): Configuration for semantic search indexing with fields `embed`, `dims`, and optional `fields`. `ttl` (optional): Configuration for item expiration. An object with optional fields: `refresh_on_read` (boolean, defaults to `true`), `default_ttl` (float, lifespan in minutes; applied to newly created items only; existing items are unchanged; defaults to no expiration), and `sweep_interval_minutes` (integer, how often to check for expired items, defaults to no sweeping).
`ui`	Optional. Named definitions of UI components emitted by the agent, each pointing to a JS/TS file. (added in `langgraph-cli==0.1.84`)
`python_version`	`3.11`, `3.12`, or `3.13`. Defaults to `3.11`.
`node_version`	Specify `node_version: 20` to use LangGraph.js.
`pip_config_file`	Path to `pip` config file.
`pip_installer`	(Added in v0.3) Optional. Python package installer selector. It can be set to `"auto"`, `"pip"`, or `"uv"`. From version 0.3 onward the default strategy is to run `uv pip`, which typically delivers faster builds while remaining a drop-in replacement. In the uncommon situation where `uv` cannot handle your dependency graph or the structure of your `pyproject.toml`, specify `"pip"` here to revert to the earlier behaviour.
`keep_pkg_tools`	(Added in v0.3.4) Optional. Control whether to retain Python packaging tools (`pip`, `setuptools`, `wheel`) in the final image. Accepted values: `true` : Keep all three tools (skip uninstall). `false` / omitted : Uninstall all three tools (default behaviour). `list[str]` : Names of tools to retain. Each value must be one of “pip”, “setuptools”, “wheel”. . By default, all three tools are uninstalled.
`dockerfile_lines`	Array of additional lines to add to Dockerfile following the import from parent image.
`checkpointer`	Configuration for the checkpointer. Supports: `ttl` (optional): Object with `strategy`, `sweep_interval_minutes`, `default_ttl` controlling checkpoint expiry. `serde` (optional, 0.5+): Object with `allowed_json_modules` and `pickle_fallback` to tune deserialization behavior.
`http`	HTTP server configuration with the following fields: `app`: Path to custom Starlette/FastAPI app (e.g., `"./src/agent/webapp.py:app"`). See custom routes guide. `cors`: CORS configuration with fields such as `allow_origins`, `allow_methods`, `allow_headers`, `allow_credentials`, `allow_origin_regex`, `expose_headers`, and `max_age`. `configurable_headers`: Define which request headers to expose as configurable values via `includes` / `excludes` patterns. `logging_headers`: Mirror of `configurable_headers` for excluding sensitive headers from logs. `middleware_order`: Choose how custom middleware and auth interact. `auth_first` runs authentication hooks before custom middleware, while `middleware_first` (default) runs your middleware first. `enable_custom_route_auth`: Apply auth checks to routes added through `app`. `disable_assistants`, `disable_mcp`, `disable_a2a`, `disable_meta`, `disable_runs`, `disable_store`, `disable_threads`, `disable_ui`, `disable_webhooks`: Disable built-in routes or hooks. `mount_prefix`: Prefix for mounted routes (e.g., “/my-deployment/api”).
`api_version`	(Added in v0.3.7) Which semantic version of the LangGraph API server to use (e.g., `"0.3"`). Defaults to latest. Check the server changelog for details on each release.

Key	Description
`graphs`	Required. Mapping from graph ID to path where the compiled graph or a function that makes a graph is defined. Example: `./src/graph.ts:variable`, where `variable` is an instance of `CompiledStateGraph` `./src/graph.ts:makeGraph`, where `makeGraph` is a function that takes a config dictionary (`LangGraphRunnableConfig`) and returns an instance of `StateGraph` or `CompiledStateGraph`. See how to rebuild a graph at runtime for more details.
`env`	Path to `.env` file or a mapping from environment variable to its value.
`store`	Configuration for adding semantic search and/or time-to-live (TTL) to the BaseStore. Contains the following fields: `index` (optional): Configuration for semantic search indexing with fields `embed`, `dims`, and optional `fields`. `ttl` (optional): Configuration for item expiration. An object with optional fields: `refresh_on_read` (boolean, defaults to `true`), `default_ttl` (float, lifespan in minutes; applied to newly created items only; existing items are unchanged; defaults to no expiration), and `sweep_interval_minutes` (integer, how often to check for expired items, defaults to no sweeping).
`node_version`	Specify `node_version: 20` to use LangGraph.js.
`dockerfile_lines`	Array of additional lines to add to Dockerfile following the import from parent image.
`checkpointer`	Configuration for the checkpointer. Supports: `ttl` (optional): Object with `strategy`, `sweep_interval_minutes`, `default_ttl` controlling checkpoint expiry. `serde` (optional, 0.5+): Object with `allowed_json_modules` and `pickle_fallback` to tune deserialization behavior.
`http`	HTTP server configuration mirroring the Python options: `cors` with `allow_origins`, `allow_methods`, `allow_headers`, `allow_credentials`, `allow_origin_regex`, `expose_headers`, `max_age`. `configurable_headers` and `logging_headers` pattern lists. `middleware_order` (`auth_first` or `middleware_first`). `enable_custom_route_auth` plus the same boolean route toggles as above.
`api_version`	(Added in v0.3.7) Which semantic version of the LangGraph API server to use (e.g., `"0.3"`). Defaults to latest. Check the server changelog for details on each release.

Examples

Python
JS

Basic configuration

{
  "$schema": "https://langgra.ph/schema.json",
  "dependencies": ["."],
  "graphs": {
    "chat": "chat.graph:graph"
  }
}

Using Wolfi base images

You can specify the Linux distribution for your base image using the image_distro field. Valid options are debian, wolfi, bookworm, or bullseye. Wolfi is the recommended option as it provides smaller and more secure images. This is available in langgraph-cli>=0.2.11.

{
  "$schema": "https://langgra.ph/schema.json",
  "dependencies": ["."],
  "graphs": {
    "chat": "chat.graph:graph"
  },
  "image_distro": "wolfi"
}

Adding semantic search to the store

All deployments come with a DB-backed BaseStore. Adding an “index” configuration to your langgraph.json will enable semantic search within the BaseStore of your deployment.The index.fields configuration determines which parts of your documents to embed:

If omitted or set to ["$"], the entire document will be embedded
To embed specific fields, use JSON path notation: ["metadata.title", "content.text"]
Documents missing specified fields will still be stored but won’t have embeddings for those fields
You can still override which fields to embed on a specific item at put time using the index parameter

{
  "dependencies": ["."],
  "graphs": {
    "memory_agent": "./agent/graph.py:graph"
  },
  "store": {
    "index": {
      "embed": "openai:text-embedding-3-small",
      "dims": 1536,
      "fields": ["$"]
    }
  }
}

Common model dimensions

openai:text-embedding-3-large: 3072
openai:text-embedding-3-small: 1536
openai:text-embedding-ada-002: 1536
cohere:embed-english-v3.0: 1024
cohere:embed-english-light-v3.0: 384
cohere:embed-multilingual-v3.0: 1024
cohere:embed-multilingual-light-v3.0: 384

Semantic search with a custom embedding function

If you want to use semantic search with a custom embedding function, you can pass a path to a custom embedding function:

{
  "dependencies": ["."],
  "graphs": {
    "memory_agent": "./agent/graph.py:graph"
  },
  "store": {
    "index": {
      "embed": "./embeddings.py:embed_texts",
      "dims": 768,
      "fields": ["text", "summary"]
    }
  }
}

The embed field in store configuration can reference a custom function that takes a list of strings and returns a list of embeddings. Example implementation:

# embeddings.py
def embed_texts(texts: list[str]) -> list[list[float]]:
    """Custom embedding function for semantic search."""
    # Implementation using your preferred embedding model
    return [[0.1, 0.2, ...] for _ in texts]  # dims-dimensional vectors

Adding custom authentication

{
  "$schema": "https://langgra.ph/schema.json",
  "dependencies": ["."],
  "graphs": {
    "chat": "chat.graph:graph"
  },
  "auth": {
    "path": "./auth.py:auth",
    "openapi": {
      "securitySchemes": {
        "apiKeyAuth": {
          "type": "apiKey",
          "in": "header",
          "name": "X-API-Key"
        }
      },
      "security": [{ "apiKeyAuth": [] }]
    },
    "disable_studio_auth": false
  }
}

See the authentication conceptual guide for details, and the setting up custom authentication guide for a practical walk through of the process.

Configuring store item Time-to-Live

You can configure default data expiration for items/memories in the BaseStore using the store.ttl key. This determines how long items are retained after they are last accessed (with reads potentially refreshing the timer based on refresh_on_read). Note that these defaults can be overwritten on a per-call basis by modifying the corresponding arguments in get, search, etc.The ttl configuration is an object containing optional fields:

refresh_on_read: If true (the default), accessing an item via get or search resets its expiration timer. Set to false to only refresh TTL on writes (put).
default_ttl: The default lifespan of an item in minutes. Applies only to newly created items; existing items are not modified. If not set, items do not expire by default.
sweep_interval_minutes: How frequently (in minutes) the system should run a background process to delete expired items. If not set, sweeping does not occur automatically.

Here is an example enabling a 7-day TTL (10080 minutes), refreshing on reads, and sweeping every hour:

{
  "$schema": "https://langgra.ph/schema.json",
  "dependencies": ["."],
  "graphs": {
    "memory_agent": "./agent/graph.py:graph"
  },
  "store": {
    "ttl": {
      "refresh_on_read": true,
      "sweep_interval_minutes": 60,
      "default_ttl": 10080
    }
  }
}

Configuring checkpoint Time-to-Live

You can configure the time-to-live (TTL) for checkpoints using the checkpointer key. This determines how long checkpoint data is retained before being automatically handled according to the specified strategy (e.g., deletion). Two optional sub-objects are supported:

ttl: Includes strategy, sweep_interval_minutes, and default_ttl, which collectively set how checkpoints expire.
serde (Agent server 0.5+) : Lets you control deserialization behavior for checkpoint payloads.

Here’s an example setting a default TTL of 30 days (43200 minutes):

{
  "$schema": "https://langgra.ph/schema.json",
  "dependencies": ["."],
  "graphs": {
    "chat": "chat.graph:graph"
  },
  "checkpointer": {
    "ttl": {
      "strategy": "delete",
      "sweep_interval_minutes": 10,
      "default_ttl": 43200
    }
  }
}

In this example, checkpoints older than 30 days will be deleted, and the check runs every 10 minutes.

Configuring checkpointer serde

The checkpointer.serde object shapes deserialization:

allowed_json_modules defines an allow list for custom Python objects you want the server to be able to deserialize from payloads saved in “json” mode. This is a list of [path, to, module, file, symbol] sequences. If omitted, only LangChain-safe defaults are allowed. You can unsafely set to true to allow any module to be deserialized.
pickle_fallback: Whether to fall back to pickle deserialization when JSON decoding fails.

{
  "checkpointer": {
    "serde": {
      "allowed_json_modules": [
        ["my_agent", "auth", "SessionState"]
      ]
    }
  }
}

Customizing HTTP middleware and headers

The http block lets you fine-tune request handling:

middleware_order: Choose "auth_first" to run authentication before your middleware, or "middleware_first" (default) to invert that order.
enable_custom_route_auth: Extend authentication to routes you mount through http.app.
configurable_headers / logging_headers: Each accepts an object with optional includes and excludes arrays; wildcards are supported and exclusions run before inclusions.
cors: In addition to allow_origins, allow_methods, and allow_headers, you can set allow_credentials, allow_origin_regex, expose_headers, and max_age for detailed browser control.

Pinning API version

(Added in v0.3.7)You can pin the API version of the Agent Server by using the api_version key. This is useful if you want to ensure that your server uses a specific version of the API. By default, builds in Cloud deployments use the latest stable version of the server. This can be pinned by setting the api_version key to a specific version.

{
  "$schema": "https://langgra.ph/schema.json",
  "dependencies": ["."],
  "graphs": {
    "chat": "chat.graph:graph"
  },
  "api_version": "0.2"
}

Basic configuration

{
  "$schema": "https://langgra.ph/schema.json",
  "graphs": {
    "chat": "./src/graph.ts:graph"
  }
}

Pinning API version

{
  "$schema": "https://langgra.ph/schema.json",
  "dependencies": ["."],
  "graphs": {
    "chat": "./src/chat/graph.ts:graph"
  },
  "api_version": "0.2"
}

Commands

Usage

Python
JS

The base command for the LangGraph CLI is langgraph.

langgraph [OPTIONS] COMMAND [ARGS]

The base command for the LangGraph.js CLI is langgraphjs.

npx @langchain/langgraph-cli [OPTIONS] COMMAND [ARGS]

We recommend using npx to always use the latest version of the CLI.

`dev`

Python
JS

Run LangGraph API server in development mode with hot reloading and debugging capabilities. This lightweight server requires no Docker installation and is suitable for development and testing. State is persisted to a local directory.

Currently, the CLI only supports Python >= 3.11.

InstallationThis command requires the “inmem” extra to be installed:

pip install -U "langgraph-cli[inmem]"

Usage

langgraph dev [OPTIONS]

Options

Option	Default	Description
`-c, --config FILE`	`langgraph.json`	Path to configuration file declaring dependencies, graphs and environment variables
`--host TEXT`	`127.0.0.1`	Host to bind the server to
`--port INTEGER`	`2024`	Port to bind the server to
`--no-reload`		Disable auto-reload
`--n-jobs-per-worker INTEGER`		Number of jobs per worker. Default is 10
`--debug-port INTEGER`		Port for debugger to listen on
`--wait-for-client`	`False`	Wait for a debugger client to connect to the debug port before starting the server
`--no-browser`		Skip automatically opening the browser when the server starts
`--studio-url TEXT`		URL of the Studio instance to connect to. Defaults to https://smith.langchain.com
`--allow-blocking`	`False`	Do not raise errors for synchronous I/O blocking operations in your code (added in `0.2.6`)
`--tunnel`	`False`	Expose the local server via a public tunnel (Cloudflare) for remote frontend access. This avoids issues with browsers like Safari or networks blocking localhost connections
`--help`		Display command documentation

Run LangGraph API server in development mode with hot reloading capabilities. This lightweight server requires no Docker installation and is suitable for development and testing. State is persisted to a local directory.Usage

npx @langchain/langgraph-cli dev [OPTIONS]

Options

Option	Default	Description
`-c, --config FILE`	`langgraph.json`	Path to configuration file declaring dependencies, graphs and environment variables
`--host TEXT`	`127.0.0.1`	Host to bind the server to
`--port INTEGER`	`2024`	Port to bind the server to
`--no-reload`		Disable auto-reload
`--n-jobs-per-worker INTEGER`		Number of jobs per worker. Default is 10
`--debug-port INTEGER`		Port for debugger to listen on
`--wait-for-client`	`False`	Wait for a debugger client to connect to the debug port before starting the server
`--no-browser`		Skip automatically opening the browser when the server starts
`--studio-url TEXT`		URL of the Studio instance to connect to. Defaults to https://smith.langchain.com
`--allow-blocking`	`False`	Do not raise errors for synchronous I/O blocking operations in your code
`--tunnel`	`False`	Expose the local server via a public tunnel (Cloudflare) for remote frontend access. This avoids issues with browsers or networks blocking localhost connections
`--help`		Display command documentation

`build`

Python
JS

Build LangSmith API server Docker image.Usage

langgraph build [OPTIONS]

Options

Option	Default	Description
`--platform TEXT`		Target platform(s) to build the Docker image for. Example: `langgraph build --platform linux/amd64,linux/arm64`
`-t, --tag TEXT`		Required. Tag for the Docker image. Example: `langgraph build -t my-image`
`--pull / --no-pull`	`--pull`	Build with latest remote Docker image. Use `--no-pull` for running the LangSmith API server with locally built images.
`-c, --config FILE`	`langgraph.json`	Path to configuration file declaring dependencies, graphs and environment variables.
`--build-command TEXT`^*		Build command to run. Runs from the directory where your `langgraph.json` file lives. Example: `langgraph build --build-command "yarn run turbo build"`
`--install-command TEXT`^*		Install command to run. Runs from the directory where you call `langgraph build` from. Example: `langgraph build --install-command "yarn install"`
`--help`		Display command documentation.

^*Only supported for JS deployments, will have no impact on Python deployments.

Build LangSmith API server Docker image.Usage

npx @langchain/langgraph-cli build [OPTIONS]

Options

Option	Default	Description
`--platform TEXT`		Target platform(s) to build the Docker image for. Example: `langgraph build --platform linux/amd64,linux/arm64`
`-t, --tag TEXT`		Required. Tag for the Docker image. Example: `langgraph build -t my-image`
`--no-pull`		Use locally built images. Defaults to `false` to build with latest remote Docker image.
`-c, --config FILE`	`langgraph.json`	Path to configuration file declaring dependencies, graphs and environment variables.
`--help`		Display command documentation.

`up`

Python
JS

Start LangGraph API server. For local testing, requires a LangSmith API key with access to LangSmith. Requires a license key for production use.Usage

langgraph up [OPTIONS]

Options

Option	Default	Description
`--wait`		Wait for services to start before returning. Implies —detach
`--base-image TEXT`	`langchain/langgraph-api`	Base image to use for the LangGraph API server. Pin to specific versions using version tags.
`--image TEXT`		Docker image to use for the langgraph-api service. If specified, skips building and uses this image directly.
`--postgres-uri TEXT`	Local database	Postgres URI to use for the database.
`--watch`		Restart on file changes
`--debugger-base-url TEXT`	`http://127.0.0.1:[PORT]`	URL used by the debugger to access LangGraph API.
`--debugger-port INTEGER`		Pull the debugger image locally and serve the UI on specified port
`--verbose`		Show more output from the server logs.
`-c, --config FILE`	`langgraph.json`	Path to configuration file declaring dependencies, graphs and environment variables.
`-d, --docker-compose FILE`		Path to docker-compose.yml file with additional services to launch.
`-p, --port INTEGER`	`8123`	Port to expose. Example: `langgraph up --port 8000`
`--pull / --no-pull`	`pull`	Pull latest images. Use `--no-pull` for running the server with locally-built images. Example: `langgraph up --no-pull`
`--recreate / --no-recreate`	`no-recreate`	Recreate containers even if their configuration and image haven’t changed
`--help`		Display command documentation.

Start LangGraph API server. For local testing, requires a LangSmith API key with access to LangSmith. Requires a license key for production use.Usage

npx @langchain/langgraph-cli up [OPTIONS]

Options

Option	Default	Description
`--wait`		Wait for services to start before returning. Implies —detach
`--base-image TEXT`	`langchain/langgraph-api`	Base image to use for the LangGraph API server. Pin to specific versions using version tags.
`--image TEXT`		Docker image to use for the langgraph-api service. If specified, skips building and uses this image directly.
`--postgres-uri TEXT`	Local database	Postgres URI to use for the database.
`--watch`		Restart on file changes
`-c, --config FILE`	`langgraph.json`	Path to configuration file declaring dependencies, graphs and environment variables.
`-d, --docker-compose FILE`		Path to docker-compose.yml file with additional services to launch.
`-p, --port INTEGER`	`8123`	Port to expose. Example: `langgraph up --port 8000`
`--no-pull`		Use locally built images. Defaults to `false` to build with latest remote Docker image.
`--recreate`		Recreate containers even if their configuration and image haven’t changed
`--help`		Display command documentation.

`dockerfile`

Python
JS

Generate a Dockerfile for building a LangSmith API server Docker image.Usage

langgraph dockerfile [OPTIONS] SAVE_PATH

Options

Option	Default	Description
`-c, --config FILE`	`langgraph.json`	Path to the configuration file declaring dependencies, graphs and environment variables.
`--help`		Show this message and exit.

Example:

langgraph dockerfile -c langgraph.json Dockerfile

This generates a Dockerfile that looks similar to:

FROM langchain/langgraph-api:3.11

ADD ./pipconf.txt /pipconfig.txt

RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt langchain_community langchain_anthropic langchain_openai wikipedia scikit-learn

ADD ./graphs /deps/__outer_graphs/src
RUN set -ex && \
    for line in '[project]' \
                'name = "graphs"' \
                'version = "0.1"' \
                '[tool.setuptools.package-data]' \
                '"*" = ["**/*"]'; do \
        echo "$line" >> /deps/__outer_graphs/pyproject.toml; \
    done

RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt -e /deps/*

ENV LANGSERVE_GRAPHS='{"agent": "/deps/__outer_graphs/src/agent.py:graph", "storm": "/deps/__outer_graphs/src/storm.py:graph"}'

The langgraph dockerfile command translates all the configuration in your langgraph.json file into Dockerfile commands. When using this command, you will have to re-run it whenever you update your langgraph.json file. Otherwise, your changes will not be reflected when you build or run the dockerfile.

Generate a Dockerfile for building a LangSmith API server Docker image.Usage

npx @langchain/langgraph-cli dockerfile [OPTIONS] SAVE_PATH

Options

Option	Default	Description
`-c, --config FILE`	`langgraph.json`	Path to the configuration file declaring dependencies, graphs and environment variables.
`--help`		Show this message and exit.

Example:

npx @langchain/langgraph-cli dockerfile -c langgraph.json Dockerfile

This generates a Dockerfile that looks similar to:

FROM langchain/langgraphjs-api:20

ADD . /deps/agent

RUN cd /deps/agent && yarn install

ENV LANGSERVE_GRAPHS='{"agent":"./src/react_agent/graph.ts:graph"}'

WORKDIR /deps/agent

RUN (test ! -f /api/langgraph_api/js/build.mts && echo "Prebuild script not found, skipping") || tsx /api/langgraph_api/js/build.mts

The npx @langchain/langgraph-cli dockerfile command translates all the configuration in your langgraph.json file into Dockerfile commands. When using this command, you will have to re-run it whenever you update your langgraph.json file. Otherwise, your changes will not be reflected when you build or run the dockerfile.

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Connect these docs programmatically to Claude, VSCode, and more via MCP for real-time answers.

​Installation

​Quick commands

​Configuration file

​Examples

​Basic configuration

​Using Wolfi base images

​Adding semantic search to the store

​Semantic search with a custom embedding function

​Adding custom authentication

​Configuring store item Time-to-Live

​Configuring checkpoint Time-to-Live

​Configuring checkpointer serde

​Customizing HTTP middleware and headers

​Pinning API version

​Basic configuration

​Pinning API version

​Commands

​dev

​build

​up

​dockerfile

Installation

Quick commands

Configuration file

Examples

Basic configuration

Using Wolfi base images

Adding semantic search to the store

Semantic search with a custom embedding function

Adding custom authentication

Configuring store item Time-to-Live

Configuring checkpoint Time-to-Live

Configuring checkpointer serde

Customizing HTTP middleware and headers

Pinning API version

Basic configuration

Pinning API version

Commands

`dev`

`build`

`up`

`dockerfile`