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 Download : Apple Silicon (M1/M2/M3) : Select the aarch64.dmg package. Intel Mac : Select the x64.dmg package. Install : Double-click the .dmg file and drag AutoShorts to your Applications folder. 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 Download : Select the .msi (installer) or .exe (portable executable) package. Install : Double-click the .msi file to run the setup wizard. 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 Download : Select the .deb (Debian/Ubuntu) or .AppImage (universal portable binary). Install .deb : sudo dpkg -i autoshorts_ * .deb 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) 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. 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 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. 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. 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). 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://buy.polar.sh/polar_cl_ZjNgejG1JnPQqVXyMmEmq7vpdwJUFBqx4qahw4BqBCP