microsoft/PIKE-RAG

KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.

RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry

(AAAI 2026) Knowledge-Graph-Based Generation with Semantic Aggregation and Hierarchical Retrieval

Retrieval-Augmented Generation in 3 Lines of Code!

Multi-Agent self-correcting reasoning engine

Generic rag framework to apply the power of LLMs on any given dataset

Retrieval is CheapShow Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation

A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines

A-RAG: Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces. State-of-the-art RAG framework with keyword, semantic, and chunk read tools for multi-hop QA.