Shiyu Subtitle

An ultra-fast, lightweight, and 100% offline local AI subtitle assistant powered by Tauri, Vue 3, and SenseVoice-Small.

简体中文 | English

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Application Preview

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Shiyu Subtitle is an ultra-fast, lightweight, and 100% offline local AI subtitle assistant designed for creators, developers, and power users. By combining the high-performance speech recognition of SenseVoice-Small with the modern, efficient Tauri + Vue 3 desktop framework, Shiyu delivers a premium, distraction-free subtitle generation and editing experience directly on your local machine.

Key Features

• 100% Local & Private: No cloud API keys, no network required. Your audio, video, and transcripts never leave your machine.
• SenseVoice-Small Powered: Ultra-fast voice-to-text inference utilizing optimized ONNX Runtime. Compresses 1 hour of audio transcription into less than 1 minute.
• Smart Speech Segmentation: Advanced bilingual segmenting algorithms for natural, human-readable line breaks, bypassing model-native limitations.
• Temporal Offset Compensation: Integrated -150ms latency compensation, perfectly aligning subtitles to the audio waveform and correcting SenseVoice CTC peak delays.
• Modern & Sleek UI: A premium dark-mode glassmorphism interface featuring smooth micro-animations, synchronized wave previews, and seamless timing navigation.
• Silent Daemon Management: Seamless, headless backend process lifecycle control. The backend runs as a PyInstaller onefile executable—no Python runtime required, no annoying terminal windows.
• CI/CD Ready: Ready-to-go GitHub Actions configuration for automated multi-platform compilation (Windows, macOS, and Linux). One push of a tag triggers the full build pipeline with zero manual steps.

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System Architecture

graph TD
    A[Tauri GUI - Vue 3 / Vite] <-->|Local Localhost API| B[Backend: PyInstaller Onefile]
    B -->|ONNX Runtime Inference| C[SenseVoice-Small Model ~/.shiyu/models/]
    A -->|Tauri Command| D[Rust Process Controller]
    D -->|Spawns / Terminates| B

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• Frontend: Vue 3, Vite, Naive UI, Lucide Icons, Web Audio API
• Tauri Core: Rust (system windowing, silent process daemonization, process lifecycle)
• Backend: FastAPI, Uvicorn, PyInstaller onefile executable (ONNX Runtime + SenseVoice inference)
• Model Storage: Auto-downloaded to ~/.shiyu/models/sensevoice-small/ on first launch

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Quick Start (Local Development)

Prerequisites

• Node.js (v18+) & npm
• Rust (stable toolchain)
• Python (3.10.x recommended)

1. Setup Backend

1. Clone the repository and navigate to the backend folder:

   cd backend

2. Create a virtual environment and activate it:

   python -m venv venv
   # On Windows:
   .\venv\Scripts\activate
   # On macOS/Linux:
   source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

   The SenseVoice-Small model (~230 MB) is auto-downloaded on first app launch. No manual download needed. Model location: ~/.shiyu/models/sensevoice-small/

2. Setup Frontend & Run Dev

1. Navigate to the frontend directory:

   cd ../frontend

2. Install Node dependencies:

   npm install

3. Run the application in development mode:

   npm run tauri dev

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Packaging and Releasing

A GitHub Actions workflow (.github/workflows/release.yml) automates building installers for Windows (.exe), macOS (.dmg), and Linux (.deb).

To trigger a release:

1. Push your code to GitHub.
2. Create and push a version tag:

   git tag v1.1.0
   git push origin v1.1.0

3. The runner will compile Rust (Tauri), build the Python backend into a PyInstaller onefile executable, bundle everything into native installers, and publish them as draft releases.
4. The model is auto-downloaded at runtime on first launch — no model files are included in the installer.

💡 To build the backend executable locally for production testing:

cd backend
pip install pyinstaller
python build.py
# Output: dist/shiyu-backend.exe

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License

This project is licensed under the MIT License.