SAG Uses SQL JOINs for Multi-Hop RAG Retrieval, Ditching PageRank Decay

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Zleap-AI has released SAG (Structured Agentic Graph), an open-source multi-hop retrieval-augmented generation framework that replaces traditional PageRank-based graph traversal with SQL JOIN operations. Unlike GraphRAG and HippoRAG, SAG does not require expensive offline global graph construction, instead building event-entity relationships at query time using relational database foreign keys. Each document chunk is converted into one semantic event linked to multiple named entities, enabling deterministic and traceable multi-hop reasoning without score decay over long chains. The system is built on a TypeScript, PostgreSQL, and pgvector stack, and includes a built-in MCP server so each project can be exposed as an agent-callable tool. SAG has garnered over 1,900 GitHub stars since its release and is backed by an arXiv paper (2606.15971) under an MIT license.

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Developer Builds Free NATO Phonetic Alphabet Converter to Eliminate Phone Spelling Errors

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BOLA: The API Security Flaw Topping OWASP 2023 and How One SaaS Dev Fixed It

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