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RankVibe_Automation_Public
🎬 An autonomous AI content engine that conceptualizes short-form videos, splits high-action scenes using computer vision, and renders "Top 5" compilations via FFmpeg.
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README preview
🎯 What Problem Does This Solve?
Short-form content (TikToks, Shorts, Reels) is a full-time job disguised as a 60-second video.
The typical "Top 5" or ranking video workflow looks like this:
Manually search for compilation videos on YouTube
Download them
Scrub through hours of footage to find the 5 best action clips
Open Premiere or CapCut, manually cut each clip, add transitions, sync audio, scale to 9:16, export
This process takes 3–5 hours per video. For a channel that needs to post daily, that's unsustainable.
RankVibe Automation eliminates the entire manual editing pipeline. Give it your channel's topic, and it handles the rest — from concept to rendered MP4.
👥 Who This Is For
Content creators running Top 5 / ranking / compilation channels who need consistent daily uploads
Social media managers who produce short-form content for sports, gaming, or reaction channels
Automation engineers who want to study an end-to-end AI-powered video production pipeline
Developers interested in applied computer vision for video processing
⚡ Key Benefits
Hours → Minutes: What takes a human editor 3–5 hours takes RankVibe under 10 minutes
Zero editing software required: The entire pipeline runs in your browser via a local web dashboard
AI-generated concepts: The LLM analyzes your channel rules and latest metrics to brainstorm genuinely viral ideas — not generic templates
Computer vision precision: Scene cuts are detected at the frame level using brightness delta analysis — no manual scrubbing
Consistent output quality: FFmpeg ensures every rendered video is correctly scaled, audio-synced, and MP4-encoded
🌟 Technical Architecture
RankVibe Automation Pipeline
│
├── Stage 1: AI Concept Engine (OpenRouter API)
│ ├── Analyzes channel rules and last video metrics
│ ├── Generates viral concept ideas using LLMs
│ └── Formulates optimized YouTube search queries
│
├── Stage 2: Video Acquisition
│ ├── YouTube search for raw compilation footage
│ ├── yt-dlp download pipeline
│ └── Local cache in downloads/
│
├── Stage 3: Computer Vision Scene Splitter (OpenCV)
│ ├── Frame-by-frame brightness delta analysis
│ ├── Action scene transition detection
│ ├── Clip boundary identification
│ └── Preview clips written to clips/
│
├── Stage 4: Creator Dashboard (FastAPI + Web UI)
│ ├── Visual clip grid — preview all detected scenes
│ ├── Drag-to-select: choose 5 clips for the final video
│ └── Custom ordering (#5 to #1 reverse countdown)
│
└── Stage 5: Video Stitcher (FFmpeg Pipeline)
├── Resolution scaling to target format (9:16 or 16:9)
├── Transition rendering between clips
├── Background audio overlay and sync
└── Final MP4 output to final_videolar/
Tech Stack:
Layer
Technology
Backend
Python 3.10 · FastAPI · Uvicorn
AI Integration
OpenRouter API (LLM model selection)
Computer Vision
OpenCV (frame analysis + scene detection)
Video Processing
FFmpeg (stitching, scaling, encoding, audio sync)
Frontend Dashboard
HTML5 · Vanilla JavaScript · CSS3
Video Acquisition
yt-dlp
🔒 Security
All sensitive data is excluded from the repository:
.env — API keys and configurations
venv/ — Python environment binaries
*.mp4, *.mp3 — raw download caches
*.log — diagnostic output
🚀 Setup & Launch
Prerequisites
Python 3.10+ (added to PATH)
📦 FFmpeg Installation (Required)
RankVibe Automation requires ffmpeg and ffprobe to stitch, scale, transitions, and sync audio/video clips.
Option A: Windows (Automatic - Recommended)
Open Command Prompt (CMD) or PowerShell and run:
winget install Gyan.FFmpeg
Note: Restart your terminal, CMD, or editor after the installation finishes to apply the system PATH changes.
Option B: Windows (Manual - No System Settings Modified)
