GitHub - explodinggradients/ragas: Evaluation framework for your Retrieval Augmented Generation (RAG) pipelines
Welcome - GraphRAG
microsoft.github.iokaiton added
Welcome to RAGatouille
Easily use and train state of the art retrieval methods in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.
The main motivation of RAGatouille is simple: bridging the gap between state-of-the-art research and alchemical RAG pipeline practices. RAG is complex, and there are many moving parts. To g... See more
Easily use and train state of the art retrieval methods in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.
The main motivation of RAGatouille is simple: bridging the gap between state-of-the-art research and alchemical RAG pipeline practices. RAG is complex, and there are many moving parts. To g... See more
GitHub - bclavie/RAGatouille: Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.
Nicolay Gerold added
Michael Iversen added
Retrieval-augmented generation (RAG) is a technique that enhances text generation by retrieving and incorporating external knowledge.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
GitHub - circlemind-ai/fast-graphrag: RAG that intelligently adapts to your use case, data, and queries
Charles Dickensgithub.comkaiton added
GitHub - OSU-NLP-Group/HippoRAG: [NeurIPS'24] HippoRAG is a novel RAG framework inspired by human long-term memory that enables LLMs to continuously integrate knowledge across external documents. RAG + Knowledge Graphs +...
github.comkaiton added
Merchury Charon added