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byram_anshu namdev

Here's a comprehensive prompt you can use with an AI coding agent to build a complete AI-powered video clipping application from scratch. AI Video Clipping Tool - Complete Development Prompt Build a production-quality AI-powered video clipping tool for personal use. The project must continue automatically until completion without asking for approval between stages. If the output becomes too long, continue from the previous point automatically until every feature is implemented. Primary Goal Create a desktop application that automatically finds the most interesting moments from long-form videos and generates high-quality short clips suitable for YouTube Shorts, Instagram Reels, TikTok, Facebook Reels, and X. The application must work entirely on Windows without Docker. --- Core Requirements - Python backend - Modern desktop UI - GPU acceleration whenever available - FFmpeg for video processing - Local AI models where possible - OpenAI API support for advanced analysis - Modular architecture - Clean code - Fully documented - Easy installation - Automatic dependency checking - Automatic model downloading - Resume interrupted jobs - Multi-threaded processing --- User Interface Create a modern dashboard with: - Drag and drop videos - Paste YouTube URL - Paste Twitch URL - Paste Kick URL - Paste Vimeo URL - Paste direct MP4 URL - Local file selection Dashboard should include - Recent jobs - Processing queue - GPU usage - CPU usage - RAM usage - VRAM usage - Progress bars - ETA - Live logs - Preview player - Clip gallery Support Dark Mode. --- AI Configuration Allow selecting - OpenAI - Local LLM - Hybrid mode Support OpenAI API key. Supported models should be configurable. --- Before Processing Ask the user: Video Source Clip Duration Minimum duration Maximum duration Example: Minimum: 20 seconds Maximum: 45 seconds Number of clips to generate Example 5 10 20 Maximum processing time Target platform - TikTok - Shorts - Instagram - Facebook - X - Custom Language Subtitle language Video category Examples Gaming Podcast Interview Education Tutorial Sports Movie Reaction Streaming Comedy Technology Finance Motivation News Cooking Travel Music Other --- AI Analysis Analyze Speech Emotion Excitement Funny moments Loudness Audience reaction Important keywords Facial expressions Scene changes Motion Music intensity Voice emphasis Silence detection Topic changes Objects OCR text Trending moments Story progression Highlight score Virality score Retention score Engagement score Hook quality --- Optional User Rules Allow custom instructions such as: Only clips with jokes. Only motivational moments. Only exciting gameplay. Ignore introductions. Ignore sponsor segments. Skip silent parts. Skip profanity. Include emotional moments. Prefer face camera. Avoid copyrighted music. Focus on educational content. Create viral hooks. Generate clips for beginners. Prioritize audience retention. These rules should influence AI scoring. --- Clip Generation Automatically Find best timestamps. Cut clips. Smooth transitions. Add subtitles. Center subjects. Crop vertically. Add zoom effects. Face tracking. Speaker tracking. Remove silence. Normalize audio. Improve volume. Reduce noise. Sharpen video. Export in multiple qualities. --- Subtitle Features Automatic speech recognition. Speaker detection. Word-level timing. Animated captions. Multiple subtitle styles. Emoji support. Keyword highlighting. Burned subtitles. Separate subtitle file. --- AI Scoring Each candidate clip should receive scores for Virality Engagement Emotion Humor Educational value Entertainment Energy Retention Overall score Allow sorting by score. --- Preview Preview every clip before exporting. Allow Trim Split Merge Rename Delete Reorder Reprocess --- Export Formats MP4 MOV MKV Vertical 9:16 Square 1:1 Landscape 16:9 Custom Export qualities 720p 1080p 2K 4K Batch export. --- Project Structure Arrange everything into a clean folder structure. Example project/ backend/ frontend/ ai/ models/ downloads/ exports/ clips/ temp/ cache/ database/ assets/ config/ logs/ scripts/ tests/ docs/ requirements.txt README.md launcher.py --- Technologies Python FastAPI PySide6 or PyQt6 OpenCV Whisper FFmpeg PyTorch ONNX Runtime CUDA MediaPipe OpenAI API yt-dlp SQLite Polars NumPy Pydantic Uvicorn --- GPU Support Automatically detect NVIDIA CUDA AMD ROCm (where supported) Intel GPU Fallback to CPU. --- Performance Use Async processing Multi-threading GPU inference Memory optimization Model caching Incremental processing --- Error Handling Recover from crashes. Resume interrupted jobs. Detect missing dependencies. Automatically repair configuration. Generate detailed logs. --- Security Encrypt API keys locally. Validate inputs. Prevent file corruption. Prevent duplicate jobs. --- Installer Generate requirements.txt setup script Windows installer Desktop shortcut Automatic FFmpeg detection Automatic Python version check Automatic model download --- Documentation Generate README Installation guide User guide Developer guide API documentation Architecture documentation Troubleshooting guide --- Testing Create automated tests for Video downloading AI analysis Subtitle generation Clip generation Export Database UI Settings --- Final Deliverable The project must be fully functional. Do not leave placeholder code. Implement every feature. If a feature cannot be implemented, replace it with the closest working alternative. Never stop after creating templates. Always continue implementing until every file is completed. Arrange every file in the proper folder. Ensure the application runs locally on Windows without Docker and fully utilizes available GPU resources when supported.You can further customize this prompt for a specific focus, such as viral short-form content, gaming clips, podcast clipping, or educational video clipping, with AI scoring tuned for those use cases.