To implement custom components in a Haystack pipeline, you need to create a class that is a subclass of either BaseComponent or the relevant specific component class (like Retriever, Reader, etc.), depending on the type of functionality you want to add. This class must implement at least two methods: run and run_batch, where you define the logic for processing input data. The run method handles single queries, while run_batch can process multiple queries simultaneously for efficiency.
Once your custom class is defined, you need to instantiate it and include it in the Haystack pipeline. A simple way to do this is by using the Pipeline class. You create your pipeline object and then add your custom component using its name. For example, if you have a custom retriever, you might instantiate it and append it to the pipeline using the add_node() method, specifying where it fits in the sequence of components. This integration allows your custom logic to be executed at the appropriate stage of the processing pipeline.
Finally, you will want to test your pipeline thoroughly to ensure that your custom component behaves as expected. This involves providing various inputs and verifying outputs at each stage, checking how your component interacts with others, and ensuring compatibility with existing components in the pipeline. Utilize features like logging to monitor the performance and behavior of your custom component. With your component properly integrated and tested, you can then deploy it within your project, leading to customized data processing that suits your specific needs.