rag-web-ui

Why we included this project

This project is a complete RAG question-answering system, not a framework you have to wire together yourself. The chat frontend talks to a backend that loads your documents and turns them into searchable vectors, then retrieves the relevant passages to ground each answer from a language model. You can point it at cloud models like OpenAI, DeepSeek, or MiniMax, or at local models through Ollama, which keeps privacy-sensitive setups from sending data to external services. Conversations can include citations, so users can verify what an answer is actually based on instead of taking the model's word. Teams that want a ready-made conversational interface over their own documents, rather than building the retrieval pipeline from scratch, will find it a good starting point.