Create a store for langchain Document objects from a bytes store.
This store does run time type checking to ensure that the values are
Document objects.
Enumerator of the types of search to perform.
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:
This pattern is commonly used in RAG pipelines to improve answer grounding while preserving full document context.
