jianchang512/chattts-ui

一个简单的本地网页界面,使用ChatTTS将文字合成为语音,同时支持对外提供API接口。A simple native web interface that uses ChatTTS to synthesize text into speech, along with support for external...

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Summary Information

Updated 33 minutes ago
Added to GitGenius on September 8th, 2026
Created on May 30th, 2024
Open Issues & Pull Requests: 201 (+0)
GitHub issues: Enabled
Number of forks: 918
Total Stargazers: 7,656 (+0)
Total Subscribers: 43 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 1.4 hours
Mean response time: 25.7 days
90th percentile: 71.7 days
Tracked items: 46

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 99% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 2% of issues opened in the past year have been closed.

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Issue Activity (beta)

Open issues: 69
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 578 days
Stale 30+ days: 69
Stale 90+ days: 64

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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Most active issues this week

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Detailed Description

ChatTTS-ui is a web interface and API server for text-to-speech synthesis using ChatTTS.

The tool addresses the need to convert written text into natural-sounding speech through a local web interface. It handles mixed Chinese and English text along with numbers and control characters. The underlying ChatTTS model performs the synthesis, and the interface provides both a browser-based UI for interactive use and API endpoints for programmatic access. On first launch, the tool downloads the required model, attempting to fetch from Hugging Face and falling back to Modelscope if that connection fails.

The project suits developers and users who need local, offline text-to-speech capability without relying on cloud services. It works across Windows, Linux, and macOS, with prepackaged executables available for Windows to eliminate setup friction. GPU acceleration is available for systems with Nvidia graphics cards and CUDA installed, significantly speeding up synthesis. Source code deployment is straightforward through standard Python virtual environment setup. The tool is appropriate for applications requiring speech synthesis as a component, whether for accessibility features, audio content generation, or voice-based interfaces.

Development activity shows consistent maintenance with regular updates addressing deployment across multiple platforms and optimization options. The project maintains clear documentation for each operating system's setup process, including both containerized and native deployment paths. Recent work has focused on improving model download reliability and adding GPU acceleration support, indicating responsiveness to performance needs. The codebase remains actively refined with attention to cross-platform compatibility and user experience improvements.