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InstructRAG
The main features of weizhepei/instructrag are: Advanced RAG Techniques.
Projects with overlapping indexed features include: ayanami0730/arag — If you find our project helpful, please give us a star ⭐ on GitHub! cmavro/gnn-rag — This is the code for GNN-RAG: Graph Neural Retrieval for Large Language Modeling Reasoning. ekimetrics/adaptive-chunking — Selecting the Best Chunking Strategy per Document for RAG. microsoft/graphrag — GraphRAG is a data processing pipeline and retrieval engine designed to transform unstructured text into… vectifyai/pageindex — PageIndex is an agent-ready knowledge engine that processes documents into hierarchical tree structures to enable… vitali87/code-graph-rag.
If you find our project helpful, please give us a star ⭐ on GitHub!
This is the code for GNN-RAG: Graph Neural Retrieval for Large Language Modeling Reasoning.
Selecting the Best Chunking Strategy per Document for RAG
GraphRAG is a data processing pipeline and retrieval engine designed to transform unstructured text into interconnected knowledge graphs. By utilizing language models to extract entities and relationships, it builds structured representations of information that enable context-aware retrieval for downstream applications. The system distinguishes itself through hierarchical graph clustering and large-scale data synthesis, which organize massive document corpora into multi-level structures. This approach allows for both vector-based semantic searches and graph-based traversals, providing a comp