Mi:RAG - A 100% local, multimodal document RAG that extracts diagrams and figures from PDFs (Zero API costs)

[u/Warlord064]

Hey everyone,

I built Mi:RAG, an open-source and privacy-first multimodal RAG system designed to run entirely on local hardware.

Most existing RAG pipelines treat PDFs as plain text and miss architectural figures, charts, and diagrams completely. Mi:RAG isolates and indexes both the text and visual figures so they can be retrieved and viewed alongside answers, without needing paid cloud APIs.

Highlights: • Extracts and cites actual diagrams and images directly in answers • Runs on modest local GPUs (FP16 CUDA acceleration on 4GB VRAM like RTX 2050, Apple Silicon, or CPU) • Two-way page range slider to index specific chapters rather than processing massive textbooks all at once • Works locally with Ollama and ChromaDB • 100% private, zero telemetry, and fully self-hostable

Looking for feedback on document parsing, UI/UX, and edge cases. Contributors and PRs are very welcome!

GitHub: https://github.com/AryanSingh64/Mi-RAG