MiniRAGHub is a lightweight, multi-tenant RAG (Retrieval-Augmented Generation) platform designed for local development and enterprise prototyping. It integrates document upload, vector search, and LLM-based Q&A through a modular architecture.

• Multi-tenant Support – Isolate data by namespace or tenant.
• Document Upload – Upload .txt or .pdf files for semantic search.
• Text Chunking – Split documents into manageable chunks.
• Vector Store (Pluggable) – Built-in mock DB; Milvus-ready.
• LLM Integration (Pluggable) – Switch between GPT-3.5, Claude, Mistral, or mock LLMs.
• Docker-Compose Setup – One command to run backend + Milvus + MinIO.

TBC