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.
ffmpeg integration.To run the application, FFmpeg & FFprobe must be installed and available on your system PATH to handle cropping, audio extraction, and dynamic captions:
bash
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:
bash
brew tap homebrew-ffmpeg/ffmpeg
brew install homebrew-ffmpeg/ffmpeg/ffmpegpowershell
winget install Gyan.FFmpeg
(Or download the release build from gyan.dev and add it to your system PATH environment variables).bash
sudo apt install ffmpeg # Debian/Ubuntu
sudo pacman -S ffmpeg # Arch Linux
sudo dnf install ffmpeg # FedoraDownload the correct package matching your system from the latest GitHub Releases.
aarch64.dmg package.
* Intel Mac: Select the x64.dmg package..dmg file and drag AutoShorts to your Applications folder.AutoShorts.app in Finder, select Open, and click Open in the warning dialog.
* Alternatively, run this command in Terminal:
bash
xattr -cr /Applications/AutoShorts.app.msi (installer) or .exe (portable executable) package..msi file to run the setup wizard..deb (Debian/Ubuntu) or .AppImage (universal portable binary)..deb:
bash
sudo dpkg -i autoshorts_*.deb.AppImage:
Make it executable and launch it:
bash
chmod +x autoshorts_*.AppImage
./autoshorts_*.AppImageWhen you first launch the application, you will be greeted by an Onboarding Wizard that lets you choose your preferred workflow:
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.pip3 install openai-whisper to enable fully offline transcription.[!TIP] 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).
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
To start the live-reloaded frontend and backend development shell:
npm install
npm run tauri:dev
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/.
If AutoShorts helps you create content faster, consider supporting its development.
Your support helps fund new features, bug fixes, and ongoing improvements.
👉 https://buy.polar.sh/polar_cl_ZjNgejG1JnPQqVXyMmEmq7vpdwJUFBqx4qahw4BqBCP
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