SkillBridge AI 🚀

SkillBridge AI is an intelligent career guidance platform that helps engineering students bridge the gap between academic curriculum and industry requirements. Using advanced AI (Gemini), it analyzes user profiles, generates personalized learning roadmaps, and recommends curated resources (YouTube, Coursera, etc.).

✨ Key Features

• AI-Driven Career Recommendations: Analyzes user skills and interests to suggest the best career domains (e.g., AI Engineer, Full Stack Dev).
• Gap Analysis: Visually displays skill gaps between current knowledge and industry standards using a dynamic interactive graph.
• Personalized Roadmaps: Generates week-by-week study plans tailored to the user's available time and semester schedule.
• Smart Resource Curation: Automatically fetches highly-rated YouTube videos and courses for every topic in the roadmap.
• Syllabus Integration: Upload your university syllabus (PDF) to automatically map your coursework to industry skills.
• Google Sheets Export: One-click export of your entire personalized roadmap to Google Sheets for tracking.

🛠️ Tech Stack

• Frontend: Next.js 14, React, TypeScript, Tailwind CSS, Framer Motion
• Backend: FastAPI, Python 3.10
• AI & ML: Google Gemini Pro (Generative AI), Sentence Transformers (Semantic Search)
• Cloud & DevOps: Google Cloud Run, Cloud Build, Docker
• Authentication: Firebase Auth
• Integrations: YouTube Data API, Google Sheets API, Google Drive API

🚀 Getting Started

Prerequisites

• Node.js 18+
• Python 3.10+
• Google Cloud Project with Gemini API enabled
• Firebase Project

Installation

1. Clone the repository

   git clone https://github.com/Anishp-cell/SkillBridge-AI.git
   cd SkillBridge-AI

2. Backend Setup

   # Navigate to root directory (Backend)
   python -m venv venv
   # Windows
   venv\Scripts\activate
   # Linux/Mac
   source venv/bin/activate
   
   pip install -r requirements.txt

3. Frontend Setup

   cd SkillBridge-AI/frontend
   npm install

Running Locally

1. Start Backend

   # From root directory
   uvicorn ai.api.app:app --reload

2. Start Frontend

   # From frontend directory
   npm run dev

   Open http://localhost:3000 in your browser.

☁️ Deployment

This project is configured for Google Cloud Run.

1. Backend:

   gcloud builds submit --tag gcr.io/YOUR_PROJECT_ID/skillbridge-backend .
   gcloud run deploy skillbridge-backend --image gcr.io/YOUR_PROJECT_ID/skillbridge-backend --platform managed --allow-unauthenticated

2. Frontend:

   cd SkillBridge-AI/frontend
   gcloud builds submit --tag gcr.io/YOUR_PROJECT_ID/skillbridge-frontend .
   gcloud run deploy skillbridge-frontend --image gcr.io/YOUR_PROJECT_ID/skillbridge-frontend --platform managed --allow-unauthenticated

📄 License

This project is licensed under the MIT License.