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Hybrid search and reranking

Chunking and freshnessEmbeddings in PostgresVector index tuningChoosing embedding modelsHybrid search and rerankingRetrieval quality
Development

Hybrid search and reranking

  • Rerankers in Practice: Cross-Encoders, Latency and Cost
  • A Reranking Microservice: Batching, Timeouts and Fallbacks
  • Hybrid Search: BM25 and Vectors Without Doubling Latency
  • Merging Keyword and Vector Results with Reciprocal Rank Fusion
  • Merging Keyword and Vector Results: Tuning Alpha on Your Test Set
  • When to Add a Reranker After the Vector Search Returns
  • When to Add a Reranker: Cost and Latency Tradeoffs
Retrieval and embeddings

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