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A detailed technical query about building a local document RAG system covering storage, ingestion, query, and highlighting, seeking advice on vector databases, GraphRAG feasibility, and document highlighting implementations.
An open-source persistent memory layer for AI coding agents that stores and retrieves project decisions and context using Postgres and pgvector, aiming to reduce context window size and improve agent consistency.
A developer shares that the real problem in a RAG app was the retrieval step failing on version numbers and codes, fixed by hybrid search (vector + BM25 + reciprocal rank fusion), not the model.
Garry Tan's GBrain introduces an agent memory system that treats the memory write path as the reliability boundary, using Markdown as source of truth with Postgres and pgvector for retrieval, and exposing operations via CLI and 30+ MCP tools.