RAGHub and raggenie
RAGHub is a curated registry and knowledge base for discovering RAG frameworks and resources, while Raggenie is a specific low-code platform for building RAG applications, making them ecosystem siblings where one serves as a potential discovery point for the other.
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systems, data preparation, and engines—with live activity tracking to distinguish actively maintained projects from outdated ones.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.
About raggenie
sirocco-ventures/raggenie
RAGGENIE: An open-source, low-code platform to build custom Retrieval-Augmented Generation (RAG) Copilets with your own data. Simplify AI development with ease!
Supports multiple structured (MySQL, PostgreSQL, BigQuery, Airtable) and unstructured data sources with automatic query generation, while integrating with major LLM providers (OpenAI, Together.ai, Ollama, AI71). Features a capabilities framework with intent extraction to bind chatbot actions to database operations, plus a JavaScript UI widget for seamless embedding. Built on Python with Zitadel identity management and Chroma vector database for semantic search.
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