Hybrid search

As explained in Domain-Specific Small Language Models

A retrieval method that combines keyword-based and vector-based search to improve retrieval quality.

How Domain-Specific Small Language Models covers it

How deep it goes

Implements BM25, embeddings, LanceDB storage, weighted ensembling, and agent tooling, but does not detail ranking fusion internals.

Examples

Demonstrates smart-home document chunks retrieved through BM25, semantic search, and a weighted hybrid tool selected by CodeAgent.

What it assumes

Assumes document chunking and basic retriever construction while supplying implementations for keyword, vector, and combined search.

What you can do after

Builds a weighted hybrid retriever with LangChain, LanceDB, Hugging Face embeddings, and smolagents.

How it connects

Connects BM25, semantic search, vector databases, embeddings, RAG, LangChain, and agentic AI.

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Also explained in

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  liveBookmanning.com
  AI Agents in Action, Second EditionHybrid search combines multiple retrieval methods, typically including vector-based and lexical or structured search, to improve information retrieval.
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  liveBookmanning.com
  AI-Powered SearchHybrid keyword and vector search combines lexical term matching with vector-similarity retrieval or ranking.
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  liveBookmanning.com
  Building Reliable AI SystemsA retrieval technique that combines multiple approaches to find relevant information.
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  liveBookmanning.com
  Generative AI in ActionHybrid search combines multiple search methods, such as text-based, categorical, numerical, and vector-based retrieval, in one query.
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  liveBookmanning.com
  Essential GraphRAGHybrid search is an information-retrieval technique that combines multiple retrieval methods, such as vector similarity search and full-text search.
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  liveBookmanning.com
  Natural Language Processing in Action, Second EditionA hybrid search pipeline combines vector-similarity retrieval with full-text retrieval to search by both semantic and lexical signals.
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  liveBookmanning.com
  Build an AI Agent (From Scratch)Hybrid search combines multiple retrieval methods and integrates their scores to rank results.

Compare how 8 books explain hybrid search →

Related concepts

• lexical searchuses · Lexical search retrieves or ranks items by matching query terms or other surface-text features against indexed content, often using sparse representations and statistical weighting.
• similarity searchuses · Similarity search is a retrieval technique that finds or ranks items by comparing their representations with a query according to a similarity or distance measure.
• information retrievaluses · Information retrieval is the process of locating and selecting relevant information from an available collection in response to a query or information need.
• reciprocal rank fusionuses · Reciprocal rank fusion is a rank-aggregation technique that combines ranked lists by summing reciprocal-rank contributions for each item across the lists.
• BM25uses · BM25 is a probabilistic information-retrieval ranking function that scores documents for a query using term frequency, inverse document frequency, and document-length normalization.

This explainer was generated by Manning's knowledge graph from the text of Domain-Specific Small Language Models. The section links point to the parts of the book it draws on.