dc-custom-component-template

This repository contains a template for creating custom components for your deepset Cloud pipelines. Components are Python code snippets that perform specific tasks within your pipeline. This template will guide you through all the necessary elements your custom component must include. This template contains two sample components which are ready to be used:

• CharacterSplitter implemented in /src/dc_custom_component/example_components/preprocessors/character_splitter.py: A component that splits documents into smaller chunks by the number of characters you set. You can use it in indexing pipelines.
• KeywordBooster implemented in /src/dc_custom_component/example_components/rankers/keyword_booster.py: A component that boosts the score of documents that contain specific keywords. You can use it in query pipelines.

We've created these examples to help you understand how to structure your components. When importing your custom components to deepset Cloud, you can remove or rename the example_components folder with the sample components, if you're not planning to use them.

This template serves as a custom components library for your organization. Only the components present in the most recently uploaded template are available for use in your pipelines.

Documentation

For more information about custom components, see Custom Components. For a step-by-step guide on creating custom components, see Create a Custom Component. See also our tutorial for creating a custom RegexBooster component.

1. Setting up your local dev environment

Prerequisites

• Python v3.10 or v3.11
• hatch package manager

Hatch: A Python Package Manager

We use hatch to manage our Python packages. Install it with pip:

Linux and macOS:

pip install hatch

Windows: Follow the instructions under https://hatch.pypa.io/1.12/install/#windows

Once installed, create a virtual environment by running:

hatch shell

This installs all the necessary packages needed to create a custom component. You can reference this virtual environment in your IDE.

For more information on hatch, please refer to the official Hatch documentation.

2. Developing your custom component

Structure

File	Description
/src/dc_custom_component/components	Directory for implementing custom components. You can logically group custom components in sub-directories. See how sample components are grouped by type.
/src/dc_custom_component/__about__.py	Your custom components' version. deepset Cloud always uses the latest version. Bump the version every time you update your component before uploading it to deepset Cloud.
/pyproject.toml	Information about the project. If needed, add your components' dependencies in this file in the dependencies section.

Note that the location of your custom component implementation defines your component's type to be used in pipeline YAML. For example, the sample components have the following types because of their location:

• dc_custom_component.example_components.preprocessor.character_splitter.CharacterSplitter
• dc_custom_component.example_components.rankers.keyword_booster.KeyWordBooster

Here is how you would add them to a pipeline:

components:
  splitter:
    type: dc_custom_component.example_components.preprocessor.character_splitter.CharacterSplitter
    init_parameters: {}
  ...
    

Formatting

We defined a suite of formatting tools. To format your code, run:

hatch run code-quality:all

Testing

It's crucial to thoroughly test your custom component before uploading it to deepset Cloud. Consider adding unit and integration tests to ensure your component functions correctly within a pipeline.

• pytest is ready to be used with hatch
• implement your tests under /test
• run hatch run tests

3. Uploading your custom component

1. Fork this repository.
2. Navigate to the /src/dc_custom_component/components/ folder.
3. Add your custom components following the examples.
4. Update the components' version in /src/__about__.py.
5. Format your code using the hatch run code-quality:all command. (Note that hatch commands work from the project root directory only.)
6. Set your deepset Cloud API key.
   • On Linux and macOS: export API_KEY=<TOKEN>
   • On Windows: set API_KEY=<TOKEN>
7. Upload your project by running the following command from inside of this project:
   • On Linux and macOS: hatch run dc:build-and-push
   • On Windows: hatch run dc:build-windows and hatch run dc:push-windows This creates a zip file called custom_component.zip in the dist directory and uploads it to deepset Cloud.

For detailed instructions, refer to our documentation on Creating a Custom Component.