FlexRAG and RAGHub
FlexRAG is a specific implementation framework for building RAG systems, while RAGHub is a meta-repository for discovering and sharing RAG tools and projects across the ecosystem, making them ecosystem siblings that serve different roles in the RAG landscape.
About FlexRAG
ictnlp/FlexRAG
FlexRAG: A RAG Framework for Information Retrieval and Generation.
Supports text, multimodal, and web-accessible RAG scenarios through a modular pipeline architecture with integrated retrieval metrics and reranking components. Built on vectorized indexing (Faiss, LanceDB) with pre-trained retrievers available on HuggingFace Hub, enabling end-to-end workflows from corpus preparation through system evaluation and benchmarking.
About RAGHub
Andrew-Jang/RAGHub
A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and resources. Contribute and explore the evolving RAG ecosystem.
Organizes RAG tools across specialized categories—frameworks, evaluation/optimization systems, data preparation, and engines—with live activity tracking to distinguish actively maintained projects from outdated ones. Curated by the r/RAG community, it catalogs both established frameworks (LangChain, LlamaIndex, Haystack) and emerging tools like Korvus (database-native RAG) and Swiftide (Rust-based streaming), helping developers navigate rapid ecosystem fragmentation. Includes evaluation frameworks, model leaderboards, and resources to address the full RAG development lifecycle beyond basic framework selection.
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