🔮 GAUGE

The First AI-Powered Career Skill Intelligence Platform

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🚀 The Elevator Pitch

Stop guessing what employers want. GAUGE is a highly interactive, AI-driven career radar that scrapes live job boards to map your current skills against real-world market demand. Using stunning 3D WebGL visualizations and Google's Gemini AI, GAUGE instantly highlights your critical skill gaps, calculates a dynamic Readiness Score, and generates personalized, week-by-week learning roadmaps to accelerate your tech career.

⚠️ The Problem

The tech industry moves at lightning speed. Developers and engineers are constantly bombarded with "new" frameworks, languages, and methodologies. The reality? Most developers waste hundreds of hours learning skills that employers aren't actually hiring for. Job descriptions are dense and finding out what exact skills overlap between your resume and market demand is a manual, anxiety-inducing process.

💡 Our Solution

GAUGE acts as your personal career satellite. By typing in a target job role (e.g., Machine Learning Engineer), the platform:

1. Scrapes live job postings to aggregate real-world skill frequencies.
2. Visualizes the data into an immersive 3D space, showing you what skills are hot, rising, or fading.
3. Cross-references your existing skills to calculate an accurate Readiness Score.
4. Generates a custom, AI-authored learning roadmap to bridge your specific technical gaps.

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✨ Key Features

• 🌌 3D Radar Visualization: A fully interactive, WebGL-powered 3D globe built with React Three Fiber. Watch as the market demand orbits around you in real-time.
• 📊 Dynamic Readiness Score: As you add the skills you currently own, your score instantly updates, visually restructuring the 3D model to highlight your next learning targets.
• ⚡ Live Job Scraping Engine: Powered by SerpAPI to fetch fresh, geographically-relevant tech job postings so the data is never stale.
• 🤖 Generative AI Roadmaps: Hit a gap? Click "See resources" and Google's Gemini AI builds a bespoke, multi-week learning plan with exact technologies, methodologies, and outcomes tailored to that exact skill.
• 🏎️ Microsecond Caching: Built with Upstash Serverless Redis to cache job analysis and API responses, ensuring incredibly fast load times and bypassing AI generation rate limits.

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🏗️ Architecture & Tech Stack

Frontend (Client-Side)

• Framework: React 18 & Vite
• State Management: Zustand (for lightweight, zero-boilerplate global state)
• 3D Engine: Three.js & React Three Fiber + Drei
• Animations: Framer Motion
• Styling: Custom CSS with Glassmorphism adhering to exact brand tokens

Backend (Server-Side)

• Framework: FastAPI (Python)
• Data Scraping: SerpAPI (Google Jobs integration)
• Generative AI: Google Gemini (Generative Language API)
• Caching Layer: Upstash Serverless Redis (REST API integration)

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💻 Getting Started (Local Development)

Prerequisites

• Node.js (v18+)
• Python (3.10+)
• API Keys for: Google Gemini, SerpAPI, and Upstash Redis.

1. Clone & Setup Repository

git clone https://github.com/SaifullahSayyed/guage.git
cd guage

2. Backend Setup

cd backend
python -m venv venv
# Windows: venv\Scripts\activate | Mac/Linux: source venv/bin/activate
pip install -r requirements.txt

Create a .env file in the /backend directory:

SERPAPI_KEY=your_serpapi_key_here
GEMINI_API_KEY=your_gemini_key_here
UPSTASH_REDIS_REST_URL=your_upstash_url
UPSTASH_REDIS_REST_TOKEN=your_upstash_token

Run the FastAPI server:

uvicorn app.main:app --reload --port 8000

3. Frontend Setup

cd ../frontend
npm install

Create a .env file in the /frontend directory:

VITE_API_URL=http://localhost:8000

Run the frontend development server:

npm run dev

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🌐 Deployment

• Frontend is configured for seamless deployment on Vercel (/frontend root).
• Backend is configured with a render.yaml blueprint for direct deployment via Render.

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