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Extensions / AI and vectors

flame

PGRX proof-of-concept extension that generates text embeddings with fastembed/MiniLM.

pgext.cloud · Source code · Documentation · License text · Control file

Overview

Packageflame
Version0.0.1
PostgreSQL versions11 · 12 · 13 · 14 · 15 · 16
RepositoryUnspecified
Extension typeStandard
Requires CREATE EXTENSIONYes
Requires preloadNo
TrustedNo
RelocatableNo
Stars2
Latest commit2024-10-30
Catalogue updated2026-08-30

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See also

vectorizeThe simplest way to do vector search on Postgres
pgmnemoSingle-plan multimodal agent memory for PostgreSQL
vectorvector data type and ivfflat and hnsw access methods
pgcontextVector, filter-aware HNSW, and hybrid retrieval over authoritative PostgreSQL tables.
rag_bge_small_en_v15rag_bge_small_en_v15: local bge-small-en-v1.5 embeddings in PostgreSQL
google_ml_integrationGoogle Cloud machine learning integration extension for registering model endpoints, generating embeddings, and invoking predictions from SQL.
rds_aiAlibaba Cloud RDS extension for calling LLMs, generating embeddings, semantic retrieval, and end-to-end RAG from SQL
pgedge_vectorizerAsynchronous text chunking and embedding generation for PostgreSQL using background workers and pgvector.
pg_semantic_cacheCaches query results and retrieves semantically similar results using pgvector embeddings and configurable eviction policies.
pg_deeplakeDeeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.