Building a custom document store with Haystack involves setting up a framework that allows you to ingest, store, and query documents effectively. Haystack is an open-source framework designed for building search systems, and it provides components to manage documents and perform searches using various backends. To start, you’ll want to install the Haystack library using pip. Make sure your environment is ready with Python and any other dependencies required for your chosen storage backend, such as Elasticsearch or PostgreSQL.
Once you have Haystack installed, you’ll need to define your document structure. Haystack uses a class-based approach where you can create a custom document schema. This typically involves specifying fields that represent your data, such as title, content, and metadata. After defining your schema, you can integrate it with Haystack's Document class to create instances of your documents. Then, you'll create an index in your chosen backend to store these documents. For example, if you're using Elasticsearch, you would use the Haystack ElasticsearchDocumentStore class, which provides methods to index and retrieve documents.
Finally, once your documents are indexed, you can perform search queries through Haystack’s pipelines. You can define a pipeline that specifies how to process your queries, which components to use for retrieval, and how to return responses. For example, if you want to implement question-answering capabilities, you can use a retriever component combined with a reader model. This allows your application to provide relevant document snippets in response to user queries. By following these steps, you can effectively set up a custom document store that meets your specific needs for document management and retrieval.