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APACHE LUCENE
Industry-standard search library for full-text and vector retrieval
Apache-2.0
ABOUT
AI applications that need to search, retrieve, or rank documents — from knowledge bases and RAG pipelines to semantic search and content discovery — require a fast, scalable indexing and retrieval engine. Building search from scratch is complex, error-prone, and hard to optimize. Apache Lucene solves this with a battle-tested Java library that provides inverted-index-based full-text search with ranked retrieval using TF-IDF and BM25 scoring, plus support for faceted search, highlighting, spell-checking, and near-real-time indexing. It has powered search over billions of documents for two decades and serves as the foundation for Elasticsearch, Solr, and OpenSearch.
INTEGRATION GUIDE
1. Index and retrieve knowledge base documents for RAG pipelines with ranked relevance scoring
2. Power full-text search over large document collections in AI-powered content discovery and research platforms
3. Build custom semantic search systems that combine Lucene's BM25 ranking with external embedding similarity
4. Provide faceted search and filtering over metadata-rich document collections in data catalog and governance tools
5. Enable near-real-time indexing for applications that need search results reflecting recently ingested data within seconds
TAGS
searchfull-text-searchindexinginformation-retrievaljavaapachetext-search