基于 Tauri 2 + React + Rust + SQLite 的桌面应用，自动将长视频或音频转为竖屏短视频，并用 AI 评估片段的病毒式传播潜力。

https://github.com/JayWebtech/autoshorts…

导入素材、提取音频、Deepgram 转录，然后 AI 分析片段帮你挑出最有爆款潜力的部分，最后 ffmpeg 自动裁成 9:16。AI 引擎可选 DeepSeek（便宜又好用）、Claude（写文案厉害）或者本地 Ollama 模型。首次开机会有向导帮你配置 API 密钥或本地模型。支持 macOS、Windows、Linux，数据存在本地 SQLite 里。

JayWebtech/autoshorts

Source: https://github.com/JayWebtech/autoshorts

⭐ Support AutoShorts

AutoShorts

AutoShorts is a local-first desktop application for turning long-form video or audio recordings into high-impact, vertical short-form clip candidates (9:16 portrait) with AI-powered viral moment ranking.

This repository implements the desktop app foundation using Tauri 2 + React + TSX + Rust + SQLite.

Key Features

• Dynamic Multi-LLM Support: Supports both DeepSeek (default) and Claude (anthropic) for viral moment detection and hooks analysis.
• Automated Pipeline: Imports media, extracts audio, transcribes using Deepgram, and automatically analyzes and ranks moments in a single automated chain.
• Local SQLite Storage: Saves transcripts, candidates, custom names, and rendering data locally.
• Native Project Manager: Create, open, rename, and delete projects from the dashboard.
• Portrait Auto-Cropping: Automatically center-crops landscape videos to vertical H.264 portrait clips using native ffmpeg integration.
• Key Warnings: Built-in visual warnings that identify missing environment variables and prompt you directly in the UI.

Prerequisites

To run the application, FFmpeg & FFprobe must be installed and available on your system PATH to handle cropping, audio extraction, and dynamic captions:

• macOS: Install using Homebrew:

  brew install ffmpeg
  

  Note: To ensure full captions rendering support, if standard Homebrew FFmpeg lacks drawtext/subtitles filters, tap and install the homebrew-ffmpeg formula:

  brew tap homebrew-ffmpeg/ffmpeg
  brew install homebrew-ffmpeg/ffmpeg/ffmpeg
  

• Windows: Install using Winget (in PowerShell):

  winget install Gyan.FFmpeg
  

  (Or download the release build from gyan.dev and add it to your system PATH environment variables).
• Linux: Install via your native package manager:

  sudo apt install ffmpeg      # Debian/Ubuntu
  sudo pacman -S ffmpeg        # Arch Linux
  sudo dnf install ffmpeg      # Fedora
  

Installation Guide (For Users)

Download the correct package matching your system from the latest GitHub Releases.

🖥️ macOS Installation

1. Download:
   • Apple Silicon (M1/M2/M3): Select the aarch64.dmg package.
   • Intel Mac: Select the x64.dmg package.
2. Install: Double-click the .dmg file and drag AutoShorts to your Applications folder.
3. Bypass Gatekeeper (For unsigned local builds):
   • Right-click AutoShorts.app in Finder, select Open, and click Open in the warning dialog.
   • Alternatively, run this command in Terminal:

     xattr -cr /Applications/AutoShorts.app
     

🪟 Windows Installation

1. Download: Select the .msi (installer) or .exe (portable executable) package.
2. Install: Double-click the .msi file to run the setup wizard.
3. SmartScreen Bypass: Since the package is self-signed, Windows SmartScreen may show a warning. Click “More Info” in the window and choose “Run anyway”.

🐧 Linux Installation

1. Download: Select the .deb (Debian/Ubuntu) or .AppImage (universal portable binary).
2. Install .deb:

   sudo dpkg -i autoshorts_*.deb
   

3. Run .AppImage: Make it executable and launch it:

   chmod +x autoshorts_*.AppImage
   ./autoshorts_*.AppImage
   

🚀 First-Launch Onboarding & AI Configuration

When you first launch the application, you will be greeted by an Onboarding Wizard that lets you choose your preferred workflow:

Option A: Fully Offline (Ollama + Whisper)

1. Ollama Setup: Select a local model card (llama3.2 3B, qwen2.5 3B, or qwen2.5 7B). The application will check if Ollama is running and automatically pull the model weights, showing a downloader progress bar.
2. Local Whisper: Follow the prompt instructions to verify Python is installed and run pip3 install openai-whisper to enable fully offline transcription.

Option B: Cloud API Keys

1. Enter your API credentials for:
   • Deepgram: For fast, accurate cloud transcription.
   • DeepSeek: (Highly Recommended) For cheap, high-quality cloud moment detection.
   • Claude: For premium copywriting, hooks, and moment detection.
2. Click Save & Start to immediately load the dashboard.

⚙️ Modifying Settings & Resetting Onboarding

• Update Credentials: Click the API Settings gear icon in the top right of your app dashboard to switch engines, select different local models, or update API keys.
• Reset Onboarding: If you want to switch from Cloud to Offline (or vice-versa) and start setup from scratch, click the Reset App Configuration & Onboarding button at the bottom of the API Settings panel.

LLM Provider Recommendation (Local vs. Cloud):

• Local Models (Ollama): While AutoShorts supports fully offline moments analysis via local Ollama models (like LLaMA 3.2 3B or Qwen 2.5 3B/7B), local models are generally not recommended for viral moment detection. Smaller 3B/7B models lack the context reasoning and mathematical capabilities needed to evaluate long transcripts and calculate accurate segment timestamps (often outputting fragments that are too short).
• DeepSeek (Highly Recommended): We strongly suggest using DeepSeek for moment detection. It offers top-tier reasoning capabilities (matching GPT-4/Claude 3.5 Sonnet) at a fraction of a cent per run (under $0.001 per transcript). You can get an API key instantly at platform.deepseek.com.
• Claude (Premium Option): Claude 3.5 Sonnet provides the absolute best hooks copywriting and emotional resonance, but is slightly more expensive than DeepSeek (typically $0.01 – $0.05 per run).

Developer Guide

1. Setup Environment Configuration

Copy .env.example to .env in the root folder:

cp .env.example .env

Fill in your API Keys:

DEEPGRAM_API_KEY=your-deepgram-api-key
DEEPSEEK_API_KEY=your-deepseek-api-key
ANTHROPIC_API_KEY=your-anthropic-api-key

# Choose your default AI analysis provider ("deepseek" or "claude")
LLM_PROVIDER=deepseek

2. Run in Development Mode

To start the live-reloaded frontend and backend development shell:

npm install
npm run tauri:dev

3. Build the Application

To build and package the native macOS app bundle (.app and .dmg installer):

npm run tauri:build

The output installers will be built under src-tauri/target/release/bundle/.

❤️ Support AutoShorts

If AutoShorts helps you create content faster, consider supporting its development.

Your support helps fund new features, bug fixes, and ongoing improvements.

👉 https://polar.sh/checkout/polar_c_eZfQSAesVTAhaNyDtC8GnzySlU1yqflU62wwg2EfFDF