The most accurate document search and store for building AI apps

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

LAYRA—an enterprise-ready, out-of-the-box solution—unlocks next-generation intelligent systems powered by visual RAG and limitless visual multi-step agent workflow orchestration.

Use late-interaction multi-modal models such as ColPali in just a few lines of code.

Vision-Augmented Retrieval and Generation (VARAG) - Vision first RAG Engine

Serverless Modal + FastAPI + React + ColPali + Qdrant + GPT4o Vision RAG (V-RAG) Demo

Recipes for learning, fine-tuning, and adapting ColPali to your multimodal RAG use cases. 👨🏻‍🍳

Vision Document Retrieval (ViDoRe): Benchmark. Evaluation code for the ColPali paper.

High-Performance Engine for Multi-Vector Search

LitePali is a minimal, efficient implementation of ColPali for image retrieval and indexing, optimized for cloud deployment.

🐊 Snappy's unique approach unifies vision-language late interaction with structured OCR for region-level knowledge retrieval. Like the project? Drop a star! ⭐

Production inference for encoder models - ColBERT, GLiNER, ColPali, embeddings etc. - as vLLM plugins for online and in-process deployment

A new novel multi-modality (Vision) RAG architecture

A monorepo containing various utility scripts, tools, and applications for development, automation, and AI-powered tasks.

#3 Winner of Best Use of Zoom API at Stanford TreeHacks 2025! An AI-powered meeting assistant that captures video, audio and textual context from Zoom calls using multimodal RAG.

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, jina embeddings v4 etc enhancing multimodal search capabilities across various applications.

AgnosticRag-Q is a cloud-agnostic, multi-modal Retrieval-Augmented Generation (RAG) platform designed with a clean, extensible architecture. It provides a powerful Core API and GUI for building, testing, and deploying RAG pipelines across multiple LLM providers (Ollama, OpenAI, Gemini, Transformers) and data sources (TXT, CSV, Images, Audio).

REST API for computing cross-modal similarity between images and text using the ColPaLI vision-language model

High-performance late-interaction retrieval engine for on-prem AI. ColBERT/ColPali multi-vector search with Rust fused MaxSim, Triton GPU kernels, ROQ quantization, LEMUR routing, WAL-backed CRUD, and a FastAPI server — single machine, CPU or GPU.