Learn how to build a robust retrieval system using semantic, full-text, and fuzzy search techniques in Postgres. This guide covers setting up a search engine as a backbone for RAG pipelines, implementing full-text search with tsvector, semantic search with pgvector, and fuzzy matching with pg_trgm. Additionally, it provides tips on fine-tuning search results, debugging rankings, and boosting user experience through personalized and recent results. An overview of BM25 for advanced ranking is also included.
Table of contents
Table with four legsImplementing fuzzy searchDebugging the rankingsTuning full text searchReranking with cross-encoderBoosting results to improve UXWhen should I look for alternative solutions?Bonus: adding BM25ConclusionSort: