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Langflow Extension quickstart

docs/versioned_docs/version-1.10.0/Develop/extensions-quickstart.mdx

1.11.0.dev13.9 KB
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Build, validate, and run a Langflow Extension bundle to create a single-component extension you can pip-install or load using lfx extension dev.

Prerequisites

  • Python 3.11 or greater
  • langflow installed with uv pip install langflow. The lfx CLI provides every command in this guide. For more information, see Install the Langflow OSS package.

Create an extension

  1. Scaffold a new extension:

    bash
    lfx extension init my-extension
    cd my-extension
    

    This creates the canonical layout the loader expects:

    my-extension/
    ├── extension.json           # the v0 manifest
    ├── pyproject.toml           # so the bundle is pip-installable
    └── src/
        └── lfx_my_extension/
            ├── __init__.py
            ├── extension.json   # symlink/copy used by importlib at runtime
            └── components/
                └── my_bundle/
                    ├── __init__.py
                    └── my_component.py
    

    For more information, see Manifest reference.

  2. To edit the component, open src/lfx_my_extension/components/my_bundle/my_component.py. The scaffold ships a working Component subclass that prints "Hello, {name}!"

    python
    from lfx.custom.custom_component.component import Component
    from lfx.io import MessageTextInput, Output
    from lfx.schema.message import Message
    
    class HelloComponent(Component):
        display_name = "Hello"
        description = "Greets the caller."
    
        inputs = [MessageTextInput(name="who", display_name="Who?", value="world")]
        outputs = [Output(display_name="Greeting", name="greeting", method="build_message")]
    
        def build_message(self) -> Message:
            return Message(text=f"Hello, {self.who}!")
    

    The full surface available to bundle code is enumerated in BUNDLE_API.md. Anything outside of BUNDLE_API.md is not part of the API contract, and may move or break between releases.

  3. Before launching Langflow, run the static extension checker.

    bash
    lfx extension validate .
    

    The validator parses the manifest and reports typed errors. It does not execute imports by default, so it is safe to run against an extension you just downloaded. Use --execute-imports only when you trust the source — it runs the import probe in a subprocess.

  4. Run Langflow with the extension loaded.

    bash
    lfx extension dev .
    

    This launches a Langflow dev server with my-extension registered at the @official slot. The Hello component appears in the Langflow UI component list under the bundle name in extension.json.

    To see what the loader picked up:

    bash
    lfx extension list --format json
    
  5. Iterate with reload. Edit the component, save, then click the Reload action in the palette's bundle header (or run lfx extension reload --bundle my_bundle). The atomic-swap reload pipeline replaces the component in place; in-flight flows keep the pre-swap class so a running execution is never interrupted.

    Reload only works in Mode A (local dev). Production deployments rebuild the Docker image.

  6. Ship the extension.

    Once the extension works locally, publish the package to PyPI:

    bash
    python -m build         # builds the wheel + sdist
    twine upload dist/*     # publish to PyPI
    

    To install the extension into a Langflow environment with a regular pip install:

    bash
    pip install lfx-my-extension
    langflow run
    

    Discovery happens at server startup. The bundle appears in the palette without further configuration.

See also