Hybrid Search Implementation

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This skill provides standardized patterns and implementation templates for hybrid search, addressing the limitations of pure semantic search by integrating traditional keyword-based retrieval. It includes production-ready code for Reciprocal Rank Fusion (RRF), linear scoring, and cross-encoder reranking, with specific implementations for PostgreSQL (pgvector) and Elasticsearch. It is ideal for developers building Retrieval-Augmented Generation (RAG) pipelines that require high recall for both semantic concepts and specific domain terminology like names or codes.

Características Principales

• Score normalization and linear combination methods
• Standardized Reciprocal Rank Fusion (RRF) algorithms
• Elasticsearch hybrid query and RRF templates
• 0 GitHub stars
• Cross-encoder reranking patterns for high-precision results
• PostgreSQL pgvector and full-text search integration

Casos de Uso

• Building RAG systems that require exact matching for technical terms or codes
• Improving search relevance in domain-specific documentation portals
• Implementing multi-stage retrieval pipelines with neural reranking