Skills tagged "hybrid-search"

rag - Retrieve, rerank, ground, cite, and refuse RAG pipeline
rag retrieval-augmented-generation chunking hybrid-search
★ 89 · Updated 2026-09-24
Build grounded Q&A pipelines over a corpus by chunking, contextualizing, hybrid retrieval, reranking, grounding, citing chunk IDs, and refusing weak context.
⚙ Chunk text into structured splits ⚙ Prepend contextual blurbs to chunks ⚙ Retrieve candidates using hybrid search
azure-search-documents-dotnet - Build search apps using Azure AI Search .NET SDK.
azure dotnet search vector-search
★ 1 · Updated 2026-09-22
Azure AI Search SDK for .NET supporting full-text, vector, semantic, and hybrid search operations.
⚙ Create and manage search indexes ⚙ Upload, merge, and delete documents ⚙ Perform full-text search queries
solr-parent-chunk-model - Solr Parent/Chunk Architecture and Hybrid Search Model
search solr data-model hybrid-search
★ 1 · Updated 2026-09-21
Provides architecture guidelines, filter rules, field mappings, and RRF hybrid search patterns for Solr parent and chunk documents.
⚙ Configure Solr parent chunk schema ⚙ Implement BM25 kNN RRF hybrid search ⚙ Apply search query filter rules
azure-search-documents-ts - Build search apps with Azure AI Search SDK for TypeScript
azure azure-ai-search typescript vector-search
★ 0 · Updated 2026-09-17
Build search applications, manage indexes, and perform vector, hybrid, and semantic search using the @azure/search-documents package.
⚙ Create and update search indexes ⚙ Upload and index documents ⚙ Execute full-text search queries
azure-search-documents-ts - Azure AI Search SDK for TypeScript
azure-ai-search typescript vector-search hybrid-search
★ 0 · Updated 2026-09-17
Build search applications using Azure AI Search SDK for TypeScript supporting vector, hybrid, and semantic search.
⚙ Create and update search indexes ⚙ Upload and batch index documents ⚙ Execute full text search queries
azure-search-documents-ts - Azure AI Search SDK for TypeScript
azure-search typescript vector-search hybrid-search
★ 0 · Updated 2026-09-17
Build search applications with vector, hybrid, and semantic search capabilities.
⚙ Create search index ⚙ Upload and index documents ⚙ Perform full-text search
rag-expert - RAG Expert for Oracle Cloud Infrastructure
rag oci oracle-cloud vector-search
★ 1 · Updated 2026-09-16
Provides patterns and guidance for building production RAG systems on Oracle Cloud Infrastructure.
⚙ Design enterprise RAG architectures ⚙ Select embedding models and vector stores ⚙ Optimize retrieval quality
qdrant-model-migration - Guide embedding model migration in Qdrant without downtime
qdrant vector-database embedding-migration alias-swap
★ 2 · Updated 2026-09-16
Provides strategies and procedures for migrating embedding models and re-indexing vector collections in Qdrant.
⚙ Guide zero downtime alias swap ⚙ Guide side-by-side model testing ⚙ Guide dense to hybrid migration
hybrid-search-implementation - Combine vector and keyword search for improved retrieval.
hybrid-search vector-search keyword-search rag
★ 1 · Updated 2026-09-09
Provides implementation patterns for combining vector similarity and keyword search in RAG systems.
⚙ Combine vector and keyword search ⚙ Clarify goals and constraints ⚙ Apply search best practices
hybrid-search-implementation - Hybrid Search Implementation
hybrid-search rag vector-search keyword-search
★ 288 · Updated 2026-09-09
Combines vector similarity and keyword search to improve retrieval recall in RAG systems and search engines.
⚙ Combine vector and keyword search ⚙ Build high-recall RAG systems ⚙ Handle queries with specific terms
graphrag-patterns - GraphRAG Implementation Patterns for Neo4j
graphrag neo4j text2cypher hybrid-search
★ 18 · Updated 2026-09-09
Provides GraphRAG implementation patterns including hybrid search, Text2Cypher, agentic retrieval, and RAGAS evaluation for Neo4j.
⚙ Create hybrid retrievers ⚙ Generate Cypher queries with few-shot ⚙ Route queries to retrieval strategies