Simple, Cool & Agile Intelligence
An AI-powered platform integrating multiple tools to enhance productivity, automate information processing, and enable smarter content creation.
Skelix is an AI-driven full-stack application combining React + Vite on the frontend and Python (Flask) on the backend.
It provides six integrated AI tools built using advanced NLP and multimodal models, fine-tuned for higher accuracy and performance.
- Text Summarizer – Generates concise summaries from long documents
- Mind Map Generator – Uses AI prompting to convert text into structured mind-map diagrams
- Fake News Detector – Classifies whether an article or statement is credible
- Image Caption Generator – Generates descriptive captions from images
- Text-to-Audio Converter – Converts written text to natural-sounding speech
- YouTube Notes Generator – Extracts and summarizes key insights from YouTube videos
- BERT – Fine-tuned for Fake News Detection
- T5 – Used for summarization and text transformation tasks
- Whisper Small – Used for speech/audio-related processing
- Hugging Face pipelines for seamless inference
Designed for content creators, researchers, educators, and students, the platform streamlines knowledge extraction, analysis, and visualization.
- AI-powered multi-tool productivity suite
- Fast React + Vite frontend
- Python Flask backend
- Tailwind CSS for styling
- Dockerized setup for easy deployment
- Clean modular architecture
- Hugging Face model integration
- Fully scalable and extendable
- Frontend: React, Vite, TailwindCSS
- Backend: Python, Flask
- AI / NLP: Hugging Face, BERT, T5, Whisper Small
- DevOps: Docker
- Other: ESLint, PostCSS, Vite config
- Node.js (v16+)
- Python 3.8+
- Docker (optional)
git clone https://github.com/Samyakjain808/skai.git
cd skaicd public
npm install
npm run devpip install -r requirements.txt
python app.pyskai/
│
├─ apis/ # Backend API endpoints
├─ public/ # Frontend public files
├─ src/ # Frontend source code
├─ utils/ # Shared utilities/helpers
├─ docker/ # Docker configuration
├─ package.json
├─ requirements.txt
├─ runtime.txt
└─ README.md