@QingQ77: A desktop application based on Tauri 2 + React + Rust + SQLite that automatically converts long videos or audio into vertical short videos and uses AI to evaluate the viral potential of clips. https://github.com/JayWebtech/autoshorts……

A desktop application based on Tauri 2 + React + Rust + SQLite that automatically converts long videos or audio into vertical short videos and uses AI to evaluate the viral potential of each segment. https://github.com/JayWebtech/autoshorts… Import footage, extract audio, transcribe with Deepgram, then AI analyzes the clips to pick the most viral-worthy parts, and finally ffmpeg automatically crops to 9:16. The AI engine supports DeepSeek (cheap and effective), Claude (great at copywriting), or local Ollama models. The first launch includes a wizard to configure API keys or local models. Supports macOS, Windows, Linux, with data stored in a local SQLite database. — # 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: 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/ffmpeg * Windows: Install using Winget (in PowerShell): powershell winget install Gyan.FFmpeg (Or download the release build from gyan.dev (https://www.gyan.dev/ffmpeg/builds/) and add it to your system PATH environment variables). * Linux: Install via your native package manager: bash 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 (https://github.com/JayWebtech/autoshorts/releases/tag/autoshorts). ### 🖥️ 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: bash 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: bash sudo dpkg -i autoshorts_*.deb 3. Run .AppImage: Make it executable and launch it: bash 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. > [!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 (https://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: bash cp .env.example .env Fill in your API Keys: env 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: bash npm install npm run tauri:dev ### 3. Build the Application To build and package the native macOS app bundle (.app and .dmg installer): bash 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