Features

RAGArch is a no-code platform designed to simplify the creation and management of Retrieval-Augmented Generation (RAG) pipelines, making AI capabilities as accessible as everyday apps. It features a user-friendly interface built with Streamlit, allowing users to interactively configure and test various components of RAG pipelines, such as language models, embedding models, node parsers, and vector stores, with LlamaIndex facilitating orchestration. Users can dynamically generate Python code for custom RAG pipelines that can be integrated into applications, thanks to the integration of tools and technologies like Streamlit for UI, Hugging Face Spaces for hosting, and LlamaIndex for orchestration. RAGArch supports various components like OpenAI GPT models, Cohere API, and vector stores like Pinecone and Qdrant, enabling live testing and configuration of pipelines with immediate feedback. By offering an intuitive approach to AI configuration, RAGArch caters to both experienced developers and newcomers, streamlining the transition from concept to implementation while fostering collaboration and innovation in the AI community.