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VideoRAG

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HKUDS/VideoRAG

[KDD'2026] "VideoRAG: Chat with Your Videos"

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Python OtherCreated Feb 3, 2025

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Maintenance: Slowing (115d since push); As of today · Source: github_public_v1
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Overview

[KDD'2026] "VideoRAG: Chat with Your Videos"

Capability facts

Languages: python
Source: github.language · Jul 11, 2026

README

VideoRAG: Chat with Your Videos • Vimo Desktop

🎬 Intelligent Video Conversations | Powered by Advanced AI | Extreme Long-Context Processing

Vimo is a revolutionary desktop application that lets you chat with your videos using cutting-edge AI technology. Built on the powerful VideoRAG framework, Vimo can understand and analyze videos of any length - from short clips to hundreds of hours of content - and answer your questions with remarkable accuracy.

🎥 Watch Vimo in Action

See how Vimo transforms video interaction with intelligent conversations and deep understanding capabilities.

👆 Click to watch the Vimo demo video

✨ Key Features

For Everyone

Drag & Drop Upload: Simply drag video files into Vimo
Smart Conversations: Ask questions in natural language
Multi-Format Support: Works with MP4, MKV, AVI, and more
Cross-Platform: Available on macOS, Windows, and Linux

For Power Users

Extreme Long Videos: Process videos up to hundreds of hours
Multi-Video Analysis: Compare and analyze multiple videos simultaneously
Advanced Retrieval: Find specific moments and scenes with precision
Export Capabilities: Save insights and references for later use

For Researchers

VideoRAG Framework: Access to cutting-edge retrieval-augmented generation
Benchmark Dataset: LongerVideos benchmark with 134+ hours of content
Performance Metrics: Detailed evaluation against existing methods
Extensible Architecture: Build upon our open-source foundation

🌟 Why Vimo?

For Video Enthusiasts & Professionals:

Effortless Video Analysis: Upload any video and start asking questions immediately
Natural Conversations: Chat with your videos as if talking to a human expert
No Length Limits: Process everything from 30-second clips to 100+ hour documentaries
Deep Understanding: Combines visual content, audio, and context for comprehensive answers

For Researchers & Developers:

State-of-the-Art Algorithm: Built on VideoRAG, featuring graph-driven knowledge indexing
Benchmark Performance: Evaluated on 134+ hours across lectures, documentaries, and entertainment
Open Source: Full access to VideoRAG implementation and research findings
Scalable Architecture: Efficient processing with single GPU (RTX 3090) capability