LangChain/Supabase helper package for storing and searching document embeddings with pgvector.
| Package | langchain-embedding_search |
|---|---|
| Version | 1.1.0 |
| Repository | Unspecified |
| Extension type | SQL only |
| Requires CREATE EXTENSION | Yes |
| Requires preload | No |
| Latest release | 2024-06-05 |
| Catalogue updated | 2026-07-30 |
| vector | vector data type and ivfflat and hnsw access methods |
| vector | vector data type and ivfflat and hnsw access methods |
| pgcontext | Vector, filter-aware HNSW, and hybrid retrieval over authoritative PostgreSQL tables. |
| hybrid_search | Hybrid pgvector and full-text search helper functions for LangChain and Supabase. |
| vectorize | The simplest way to do vector search on Postgres |
| pgmnemo | Single-plan multimodal agent memory for PostgreSQL |
| embedding | HNSW vector similarity search extension for PostgreSQL real[] embeddings. |
| lantern_extras | Convenience functions for working with vector embeddings |
| pg_gembed | Generate embeddings inside PostgreSQL |
| pg_turboquant | Compact TurboQuant approximate-nearest-neighbor index access method for pgvector vector and halfvec data. |
| pg_knowledge_graph | Knowledge graph extension for PostgreSQL with graph algorithms and pgvector integration. |