The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.

The PyQt6 application using ColPali and OpenAI to show Efficient Document Retrieval with Vision Language Models

The repo provides the code for Qdrant for efficient image indexing and retrieval using models such as ColPali, ColQwen, and VDR-2B-Multi-V1, enhancing multimodal search capabilities across various applications.

ColQwen2 local Vespa DB deploy and feed and Open-Webui retrieval function

A way to chat with your images and pdf

Vignemale is a powerful AI assistant build to help you study patent law , He can be adapted to study any topics

A high-performance RAG system for PDFs using multi-vector embeddings (ColPali / ColQwen / ColSmol) with vector search in Qdrant, prefetch optimization, and reranking for improved relevance. Designed for speed, accuracy, and scalability, this system is ideal for building intelligent search, document understanding, and QA applications.

ColQwen2 via infinity embedding api and local vespa db sample