duixcom/duix-mobile

🚀 The best real-time interactive AI avatar(digital human) with on-premise deployment and <1.5 s latency.

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Summary Information

Updated 35 minutes ago
Added to GitGenius on September 8th, 2026
Created on May 16th, 2024
Open Issues & Pull Requests: 60 (+0)
GitHub issues: Enabled
Number of forks: 1,214
Total Stargazers: 8,227 (+0)
Total Subscribers: 306 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 6.7 days
Mean response time: 31.1 days
90th percentile: 70.9 days
Tracked items: 36

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Issue Activity (beta)

Open issues: 30
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 421 days
Stale 30+ days: 30
Stale 90+ days: 28

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Duix Mobile is an open-source SDK for building real-time interactive AI avatars on mobile devices and embedded screens.

The tool addresses the challenge of deploying conversational AI avatars without relying on cloud infrastructure. It runs entirely on-device, eliminating cloud dependencies and enabling sub-second response latency. Developers integrate their choice of Large Language Models, Automatic Speech Recognition, and Text-to-Speech services to create avatars capable of natural conversation. The SDK handles streaming audio synthesis that allows avatars to speak and be interrupted simultaneously, creating more human-like interactions.

Duix Mobile suits developers building customer service interfaces, virtual companions, medical or legal consultation avatars, or educational tutors on Android, iOS, tablets, automotive systems, VR platforms, or IoT devices. The tool prioritizes low latency and minimal resource consumption, making it appropriate for environments with poor network connectivity or strict privacy requirements. Its modular architecture supports rapid customization for industry-specific use cases. The project provides platform-specific development documentation for Android and iOS, along with downloadable public avatars ready for integration.

The project maintains active development with regular updates to both the core SDK and related skill packages. Documentation is kept current across multiple languages to support international adoption. The codebase demonstrates ongoing refinement of performance characteristics and cross-platform compatibility, with particular attention to latency optimization and streaming audio capabilities.