Version: 1.10.x

Langflow Extension quickstart

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

Scaffold a new extension:

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.

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}!"

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.

Before launching Langflow, run the static extension checker.
```
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.
Run Langflow with the extension loaded.
```
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:
```
lfx extension list --format json
```
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.
Ship the extension.

Once the extension works locally, publish the package to PyPI:
```
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:
```
pip install lfx-my-extension
langflow run
```
Discovery happens at server startup. The bundle appears in the palette without further configuration.

Prerequisites​

Create an extension​

See also​

Prerequisites

Create an extension

See also