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OpenSearchDocumentStore

The core document store of deepset AI Platform.

Basic Information​

  • Used with the following retrievers:
    • OpenSearchBM25Retriever
    • OpenSearchEmbeddingRetriever
  • Type: haystack_integrations.document_stores.opensearch.document_store.OpenSearchDocumentStore

Overview​

For details on how this document store works, see OpenSearchDocumentStore in the Haystack documentation.

Authorization​

This is the core document store of deepset AI Platform and as such, we handle the authorization.

Example Configuration​

In an Index​

To write the preprocesses files into the document store:

  1. Add DocumentWriter to your pipeline.
  2. Add OpenSearchDocumentStore and configure it on the component card.
  3. Connect OpenSearchDocumentStore to DocumentWriter.

In a Query Pipeline​

To retrieve files from the document store:

  1. Add an OpenSearch retriever to your pipeline.
  2. Add OpenSearchDocumentStore and configure it on the component card.
  3. Connect OpenSearchDocumentStore to the retriever.

Example​

This is an example of the document store connected to a keyword and a vector retriever:

The document store connected to a retriever

When you switch to YAML, you'll see that the document store is an argument of each retriever:

  bm25_retriever: # Selects the most similar documents from the document store
    type: haystack_integrations.components.retrievers.opensearch.bm25_retriever.OpenSearchBM25Retriever
    init_parameters:
      document_store:
        type: haystack_integrations.document_stores.opensearch.document_store.OpenSearchDocumentStore # document store configuration
        init_parameters:
          index: default
          max_chunk_bytes: 104857600
          embedding_dim: 768
          return_embedding: false
          create_index: true
      top_k: 20 # The number of results to return
   embedding_retriever: # Selects the most similar documents from the document store
    type: haystack_integrations.components.retrievers.opensearch.embedding_retriever.OpenSearchEmbeddingRetriever
    init_parameters:
      document_store:
        type: haystack_integrations.document_stores.opensearch.document_store.OpenSearchDocumentStore # document store configuration
        init_parameters:
          index: default
          max_chunk_bytes: 104857600
          embedding_dim: 768
          return_embedding: false
          create_index: true
      top_k: 20 # The number of results to return

Init Parameters​

For a list of parameters you can configure, see OpenSearchDocumentStore API reference in Haystack documentation.