Hybrid pgvector and full-text search helper functions for LangChain and Supabase.
pgext.cloud · Source code · Documentation · License text
| Package | langchain-hybrid_search |
|---|---|
| Version | 1.1.0 |
| Repository | Unspecified |
| Extension type | SQL only |
| Requires CREATE EXTENSION | Yes |
| Requires preload | No |
| Trusted | Yes |
| Relocatable | Yes |
| Stars | 441 |
| Latest commit | 2026-08-24 |
| Latest release | 2026-04-22 |
| Catalogue updated | 2026-08-30 |
| vector | vector data type and ivfflat and hnsw access methods |
| pgcontext | Vector, filter-aware HNSW, and hybrid retrieval over authoritative PostgreSQL tables. |
| embedding_search | LangChain/Supabase helper package for storing and searching document embeddings with pgvector. |
| vectorize | The simplest way to do vector search on Postgres |
| pgmnemo | Single-plan multimodal agent memory for PostgreSQL |
| pg_search | Full text search for PostgreSQL using BM25 |
| pg_hybrid | hybrid storage engine: columnar, vector, fulltext |
| neurondb | AI database extension for vector search, ML inference, hybrid search, and RAG in PostgreSQL. |
| pg_bestmatch | Generate BM25 sparse vector inside PostgreSQL |
| smlar | Effective similarity search |