Hybrid Search Setup
by AaaS · open-source · Last verified 2026-03-01
Configures a hybrid search system combining dense vector similarity with sparse BM25 keyword matching. Sets up dual index creation, score fusion strategies, and query routing logic for optimal retrieval across different query types.
https://aaas.blog/script/hybrid-search-setup ↗C+
C+—Average
Adoption: C+Quality: AFreshness: ACitations: C+Engagement: F
Specifications
- License
- MIT
- Pricing
- open-source
- Capabilities
- dual-index-creation, score-fusion, query-routing, bm25-indexing, vector-indexing
- Integrations
- pinecone-client, elasticsearch, langchain, sentence-transformers
- Use Cases
- enterprise-search, e-commerce-search, document-retrieval, knowledge-base-search
- API Available
- No
- Language
- python
- Dependencies
- pinecone-client, elasticsearch, langchain, sentence-transformers, rank-bm25
- Environment
- Python 3.11+ with Elasticsearch 8.x
- Est. Runtime
- 5-15 minutes depending on index size
- Tags
- script, automation, search, hybrid, sparse-dense
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
50.9Adoption
56
Quality
80
Freshness
82
Citations
50
Engagement
0