Summary 1. Executive Summary 1.1 Product Overview AceClip is an AI-powered video clip generation platform that automatically creates engaging short-form clips from long-form videos. The platform processes YouTube videos or uploaded video files, uses AI to identify compelling moments, and generates professionally edited vertical clips optimized for social media platforms. 1.2 Key Value Propositions Automated Clip Generation: Transform long videos into multiple viral-ready clips automatically AI-Powered Intelligence: Uses speaker diarization, face tracking, and LLM analysis to identify best moments Professional Quality: Intelligent cropping, dynamic captions, and branded overlays Scalable Cloud Infrastructure: GPU-accelerated processing on vast.ai for fast, concurrent job handling User-Friendly: Simple upload interface with batch processing capabilities 1.3 Target Users Content Creators: YouTubers, podcasters, streamers who want to repurpose long-form content Social Media Managers: Agencies managing multiple channels and content Marketing Teams: Companies creating short-form content from webinars, interviews, presentations Individual Users: Anyone wanting to create clips from their video library 2. Current State Analysis 2.1 Existing Functionality Core Pipeline (Currently Implemented): Video Input: YouTube video URL/ID via command-line Download: yt-dlp with aria2c for fast downloads Transcription: Faster-Whisper for accurate speech-to-text Speaker Diarization: Pyannote.audio for identifying different speakers Face Detection & Tracking: InsightFace for face detection and clustering Clip Generation: LLM (OpenRouter) analyzes transcript and generates clip timestamps Intelligent Cropping: Dynamic face-centered cropping for vertical format (1080x1920) Rendering: FFmpeg-based rendering with captions, titles, and logo overlays Output: Multiple MP4 clips saved locally Current Architecture: Processing: Single-machine, command-line based Parallelism: ThreadPoolExecutor for parallel clip processing (max 4 clips) Storage: Local file system (out/ directory) Models: Loaded on-demand (Whisper, InsightFace, Pyannote) No User Management: No authentication, user accounts, or multi-tenancy No Web Interface: CLI-only interface No Job Queue: Direct processing, no queuing system No Cloud Deployment: Designed for local execution 2.2 Current Limitations No Web Interface: Users must use command-line No User Authentication: Cannot support multiple users No Batch Processing UI: Cannot upload multiple YouTube links easily No File Upload: Cannot upload video files directly No Job Management: No way to track, queue, or monitor jobs No Cloud Storage: Outputs stored locally only No Scalability: Single machine processing, cannot handle concurrent users No 24/7 Availability: Requires manual execution No Progress Tracking: No real-time status updates for users No Result Sharing: No way to share or download clips via web 2.3 Current Technology Stack Language: Python 3.11+ AI Models: Faster-Whisper (transcription) InsightFace (face detection) Pyannote.audio (speaker diarization) OpenRouter API (LLM clip generation) Video Processing: FFmpeg, OpenCV, MoviePy Dependencies: PyTorch, NumPy, ONNX Runtime Deployment: Docker containerization ready 3. Product Vision & Goals 3.1 Vision Statement To become the leading AI-powered video clip generation platform, enabling creators to effortlessly transform long-form content into viral short-form clips at scale. 3.2 Strategic Goals Scalability: Support 100+ concurrent users processing videos simultaneously Performance: Process 1-hour video in less than 10 minutes using GPU acceleration Reliability: 99.9% uptime with automatic failover and job retry User Experience: less than 3 clicks to upload and start processing Cost Efficiency: Optimize GPU usage to keep costs under $0.10 per video processed 3.3 Success Criteria User Adoption: 1,000+ registered users within 6 months Processing Volume: 10,000+ videos processed per month User Satisfaction: 4.5+ star rating, less than 5% churn rate Performance: Average job completion time less than 15 minutes Uptime: 99.9% availability 4. User Stories & Requirements 4.1 Core User Stories US-1: YouTube Batch Upload As a content creator I want to upload a list of YouTube video URLs So that I can process multiple videos at once without manual entry Acceptance Criteria: User can paste multiple YouTube URLs (one per line or comma-separated) System validates all URLs before processing User can see progress for each video in the batch Failed videos are clearly marked with error messages User receives notification when batch is complete US-2: Video File Upload As a user I want to upload video files directly from my computer So that I can process videos that aren't on YouTube Acceptance Criteria: Support multiple video formats (MP4, MOV, AVI, MKV) Maximum file size: 2GB per file Support batch upload (multiple files at once) Progress bar during upload Automatic format validation Clear error messages for unsupported formats US-3: User Authentication As a user I want to create an account and sign in So that my jobs and clips are saved and accessible across devices Acceptance Criteria: Email/password registration Email verification Password reset functionality Secure session management "Remember me" option Social login (Google, GitHub) - optional US-4: Job Queue & Status As a user I want to see the status of my processing jobs So that I know when my clips will be ready Acceptance Criteria: Real-time job status updates (Queued, Processing, Completed, Failed) Estimated completion time Progress percentage for each stage Ability to cancel queued jobs Email notification when job completes Job history with search/filter US-5: Clip Management As a user I want to view, download, and manage my generated clips So that I can organize and use them efficiently Acceptance Criteria: Gallery view of all generated clips Thumbnail previews Download individual clips or batch download Delete clips Share clips via link (optional) Metadata display (duration, resolution, creation date) US-6: Dashboard As a user I want to see an overview of my account activity So that I can track my usage and manage my account Acceptance Criteria: Total videos processed Total clips generated Storage usage Recent activity feed Account settings Subscription/billing information (if applicable) 4.2 Functional Requirements FR-1: Input Methods FR-1.1: Support YouTube URL/ID input (single or batch) FR-1.2: Support video file upload (single or batch) FR-1.3: Validate input format and provide clear error messages FR-1.4: Support video formats: MP4, MOV, AVI, MKV, WebM FR-1.5: Maximum file size: 2GB per file FR-1.6: Maximum batch size: 50 videos per batch FR-2: Processing Pipeline FR-2.1: Maintain existing AI pipeline (transcription, diarization, face tracking) FR-2.2: Support concurrent processing of multiple videos FR-2.3: Automatic retry on transient failures (max 3 retries) FR-2.4: Progress tracking at each pipeline stage FR-2.5: Support for videos up to 4 hours in length FR-2.6: Generate 3-10 clips per video (configurable) FR-3: Output Management FR-3.1: Store clips in cloud storage (Cloudflare R2 or S3) FR-3.2: Generate shareable download links FR-3.3: Automatic cleanup of old clips (30-day retention default) FR-3.4: Support batch download as ZIP FR-3.5: Metadata export (JSON/CSV) FR-4: User Management FR-4.1: User registration and authentication FR-4.2: User profiles with preferences FR-4.3: Job history per user FR-4.4: Storage quotas per user (free tier: 10GB, paid: unlimited) FR-4.5: Usage analytics per user 4.3 Non-Functional Requirements NFR-1: Performance NFR-1.1: API response time -200ms for non-processing endpoints NFR-1.2: Video processing: 1-hour video processed in less than 10 minutes (with GPU) NFR-1.3: Support 100+ concurrent jobs NFR-1.4: Frontend page load time -2 seconds NFR-1.5: File upload speed: Support 10MB/s upload NFR-2: Scalability NFR-2.1: Horizontal scaling of workers (auto-scale based on queue depth) NFR-2.2: Database can handle 1M+ users NFR-2.3: Storage scales to 100TB+ NFR-2.4: CDN for fast clip delivery globally NFR-3: Reliability NFR-3.1: 99.9% uptime SLA NFR-3.2: Automatic job retry on failure NFR-3.3: Data backup and disaster recovery NFR-3.4: Graceful degradation if GPU workers unavailable NFR-4: Security NFR-4.1: HTTPS for all communications NFR-4.2: Secure password storage (bcrypt/argon2) NFR-4.3: JWT tokens for API authentication NFR-4.4: Rate limiting to prevent abuse NFR-4.5: Input validation and sanitization NFR-4.6: CORS configuration for frontend NFR-5: Usability NFR-5.1: Responsive design (mobile, tablet, desktop) NFR-5.2: Intuitive UI with less tha 3 clicks to start processing NFR-5.3: Clear error messages and help text NFR-5.4: Accessibility (WCAG 2.1 AA compliance)