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RAGFreeOpen Source
OPENSPG
Knowledge graph engine for GraphRAG and knowledge-augmented generation
Apache-2.0
ABOUT
Traditional RAG systems rely on vector similarity search, which suffers from semantic ambiguity and cannot effectively handle structured knowledge relationships. Meanwhile, naive GraphRAG approaches using OpenIE introduce noise from incorrect triple extraction. OpenSPG provides a knowledge-augmented generation framework that integrates structured knowledge graphs via SPG semantic modeling with LLMs, enabling logical-form-guided reasoning, factual accuracy, and multi-hop question answering for professional domains where precision is critical.
INSTALL
pip install openspg-kagINTEGRATION GUIDE
1. Build logical reasoning and factual question answering systems for professional domains like finance, legal, and healthcare using structured knowledge graphs connected to LLMs
2. Overcome traditional RAG vector similarity limitations for complex queries that require traversing multiple entity relationships in a knowledge graph
3. Power financial risk analysis, compliance checks, and fraud detection using domain-specific knowledge graphs with Ant Group's production-proven approach
4. Enable knowledge-augmented document retrieval where complete contextual text information is integrated with graph relationships for more accurate results
TAGS
knowledge-graphgraphragragknowledge-augmented-generationllmsemantic-reasoningpythonjava