MultiVectorRetriever

Retriever that supports multiple embeddings per parent document.

This retriever is designed for scenarios where documents are split into smaller chunks for embedding and vector search, but retrieval returns the original parent documents rather than individual chunks.

It works by:

• Performing similarity (or MMR) search over embedded child chunks
• Collecting unique parent document IDs from chunk metadata
• Fetching and returning the corresponding parent documents from the docstore

This pattern is commonly used in RAG pipelines to improve answer grounding while preserving full document context.