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)
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