Visual document analysis,
on your hardware
Upload PDFs and images, ask questions, and get answers grounded in your documents. ColPali visual embeddings paired with any Ollama model — running entirely on your machine.
Everything you need for
document intelligence
From single-page lookups to batch analysis across hundreds of documents, RAG Lab handles the full workflow.
Visual RAG
ColPali embeddings understand tables, figures, and layouts natively. Optional OCR mode for text-preferring LLMs.
Hybrid Retrieval
Visual search + keyword matching with weighted score fusion. Citation snippets show exactly which text matched your query.
Any Ollama Model
Plug in any local model or connect to Ollama Cloud. Vision, text, and reasoning models all work.
Batch Processing
Feed it a stack of documents. Get per-document streaming responses as they complete.
Full-Document Summarization
Ask “summarize” and every page gets processed in sequential chunks. No page left behind.
Prompt Templates
Build custom extraction templates — K-1 line items, invoice fields, whatever your workflow needs.
Conversation Memory
Mem0 remembers context across chat sessions. Disabled during RAG to keep answers document-grounded.
Multi-Session
Separate workspaces for separate projects. Switch contexts without losing state.
Adaptive Retrieval
Score-slope analysis finds the right number of pages per query. No manual threshold tuning.
Built with modern tools
Up and running in minutes
For Linux and WSL2. Requires Python 3.10+, Node.js 18+, an NVIDIA GPU, and Ollama.