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113 lines
4.0 KiB
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113 lines
4.0 KiB
Plaintext
---
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title: Langflow Extension quickstart
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slug: /extensions-quickstart
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---
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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`.
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## Prerequisites
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* Python 3.11 or greater
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* `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](/get-started-installation#install-and-run-the-langflow-oss-python-package).
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## Create an extension
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1. Scaffold a new extension:
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```bash
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lfx extension init my-extension
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cd my-extension
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```
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This creates the canonical layout the loader expects:
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```
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my-extension/
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├── extension.json # the v0 manifest
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├── pyproject.toml # so the bundle is pip-installable
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└── src/
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└── lfx_my_extension/
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├── __init__.py
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├── extension.json # symlink/copy used by importlib at runtime
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└── components/
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└── my_bundle/
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├── __init__.py
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└── my_component.py
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```
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For more information, see [Manifest reference](./extensions-manifest.mdx).
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2. To edit the component, open `src/lfx_my_extension/components/my_bundle/my_component.py`.
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The scaffold ships a working `Component` subclass that prints `"Hello, {name}!"`
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```python
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from lfx.custom.custom_component.component import Component
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from lfx.io import MessageTextInput, Output
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from lfx.schema.message import Message
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class HelloComponent(Component):
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display_name = "Hello"
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description = "Greets the caller."
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inputs = [MessageTextInput(name="who", display_name="Who?", value="world")]
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outputs = [Output(display_name="Greeting", name="greeting", method="build_message")]
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def build_message(self) -> Message:
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return Message(text=f"Hello, {self.who}!")
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```
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The full surface available to bundle code is enumerated in [`BUNDLE_API.md`](https://github.com/langflow-ai/langflow/blob/main/BUNDLE_API.md).
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Anything outside of [`BUNDLE_API.md`](https://github.com/langflow-ai/langflow/blob/main/BUNDLE_API.md) is not part of the API contract, and may move or break between releases.
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3. Before launching Langflow, run the static extension checker.
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```bash
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lfx extension validate .
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```
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The validator parses the manifest and reports typed errors.
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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.
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4. Run Langflow with the extension loaded.
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```bash
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lfx extension dev .
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```
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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`.
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To see what the loader picked up:
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```bash
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lfx extension list --format json
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```
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5. Iterate with reload.
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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.
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Reload only works in Mode A (local dev). Production deployments rebuild the Docker image.
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6. Ship the extension.
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Once the extension works locally, publish the package to PyPI:
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```bash
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python -m build # builds the wheel + sdist
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twine upload dist/* # publish to PyPI
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```
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To install the extension into a Langflow environment with a regular `pip install`:
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```bash
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pip install lfx-my-extension
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langflow run
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```
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Discovery happens at server startup.
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The bundle appears in the palette without further configuration.
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## See also
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- [Bundle extensions overview](./extensions-overview)
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- [Manifest reference](./extensions-manifest)
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