LangChain Reference home pageLangChain ReferenceLangChain Reference
  • GitHub
  • Main Docs
Deep Agents
LangChain
LangGraph
Integrations
LangSmith
  • Overview
  • LangGraph Checkpoint
    Checkpoint Postgres
    Store Postgres
    Checkpoint SQLite
    LangGraph Prebuilt
    LangGraph CLI
    LangGraph SDK
    LangGraph Supervisor
    LangGraph Swarm
    ⌘I

    LangChain Assistant

    Ask a question to get started

    Enter to send•Shift+Enter new line

    Menu

    LangGraph Checkpoint
    Checkpoint Postgres
    Store Postgres
    Checkpoint SQLite
    LangGraph Prebuilt
    LangGraph CLI
    LangGraph SDK
    LangGraph Supervisor
    LangGraph Swarm
    Language
    Theme
    Pythonlanggraph-cliconfig
    Module●Since v0.1

    config

    Attributes

    attribute
    Distros: Literal['debian', 'wolfi', 'bookworm']
    attribute
    MIN_NODE_VERSION: str
    attribute
    DEFAULT_NODE_VERSION: str
    attribute
    DISALLOWED_BUILD_COMMAND_CHARS: list
    attribute
    MIN_PYTHON_VERSION: str
    attribute
    DEFAULT_PYTHON_VERSION: str
    attribute
    DEFAULT_IMAGE_DISTRO: str
    attribute
    semver_pattern

    Functions

    function
    python_config_to_docker_uv_lock
    function
    has_disallowed_build_command_content
    function
    validate_config
    function
    get_unknown_keys
    function
    validate_config_file
    function
    get_build_tools_to_uninstall
    function
    python_config_to_docker
    function
    node_config_to_docker
    function
    default_base_image
    function
    docker_tag
    function
    config_to_docker
    function
    config_to_compose

    Classes

    class
    Config
    class
    LocalDeps
    View source on GitHub

    Check if a command string contains disallowed characters or patterns.

    Validate a configuration dictionary.

    Return warnings for unrecognized top-level keys (typos, etc.).

    Load and validate a configuration file.

    Generate a Dockerfile from the configuration.

    Top-level config for langgraph-cli or similar deployment tooling.

    A container for referencing and managing local Python dependencies.

    A "local dependency" is any entry in the config's dependencies list that starts with "." (dot), denoting a relative path to a local directory containing Python code.

    For each local dependency, the system inspects its directory to determine how it should be installed inside the Docker container.

    Specifically, we detect:

    • Real packages: Directories containing a pyproject.toml or a setup.py. These can be installed with pip as a regular Python package.
    • Faux packages: Directories that do not include a pyproject.toml or setup.py but do contain Python files and possibly an __init__.py. For these, the code dynamically generates a minimal pyproject.toml in the Docker image so that they can still be installed with pip.
    • Requirements files: If a local dependency directory has a requirements.txt, it is tracked so that those dependencies can be installed within the Docker container before installing the local package.