{
   "name": "pgmnemo",
   "abstract": "Provenance-gated, vector-hybrid memory for LLM agents in PostgreSQL",
   "description": "pgmnemo adds a first-class memory layer to PostgreSQL for LLM-based agents. Every ingest() call requires a commit_sha or artifact_hash provenance token; rows without provenance are blocked or warned. Hybrid recall combines cosine similarity (HNSW via pgvector), BM25 full-text search, recency decay, and importance weighting in a single SQL call. Includes RLS-based multi-tenant isolation, causal-chain traversal, temporal windowed recall, and graph-proximity scoring.",
   "version": "0.3.0",
   "maintainer": [
      "Alex Gaydabura <asistentgaidaburas@gmail.com>"
   ],
   "license": "apache_2_0",
   "provides": {
      "pgmnemo": {
         "abstract": "Provenance-gated, vector-hybrid memory for LLM agents in PostgreSQL",
         "version": "0.3.0",
         "file": "extension/pgmnemo--0.3.0.sql",
         "docfile": "README.md"
      }
   },
   "resources": {
      "homepage": "https://github.com/pgmnemo/pgmnemo",
      "bugtracker": {
         "web": "https://github.com/pgmnemo/pgmnemo/issues"
      },
      "repository": {
         "url":  "https://github.com/pgmnemo/pgmnemo.git",
         "web":  "https://github.com/pgmnemo/pgmnemo",
         "type": "git"
      }
   },
   "prereqs": {
      "runtime": {
         "requires": {
            "PostgreSQL": "14.0.0",
            "vector": "0.7.0"
         }
      },
      "build": {
         "requires": {
            "pg_config": 0
         }
      }
   },
   "tags": [
      "memory",
      "agent",
      "agents",
      "llm",
      "vector",
      "pgvector",
      "provenance",
      "rag",
      "graph",
      "multi-tenant",
      "hnsw",
      "recall"
   ],
   "release_status": "stable",
   "generated_by": "hand",
   "meta-spec": {
      "version": "1.0.0",
      "url": "https://pgxn.org/meta/spec.txt"
   }
}