How to Implement a hybrid retrieval system combining BM25 and dense vector search for an LLM-based assistant

Question

Can i know How to Implement a hybrid retrieval system combining BM25 and dense vector search for an LLM-based assistant.

Answer 1

You can implement a hybrid retrieval system by combining BM25 scores with dense vector similarity to retrieve and rank relevant documents.

Here is the code snippet below:

In the above code, we are using the following key points:

• BM25 for sparse keyword matching.

• Sentence Transformers for semantic dense vector encoding.

• A simple average fusion of BM25 and dense similarity scores for ranking.

Hence, this hybrid approach enhances retrieval robustness by balancing lexical and semantic relevance.