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AI Tools Setup Guide - Google Gemini Integration

This project uses Google's Gemini AI API to power the AI tools. Follow these steps to get started.

Prerequisites

  • Node.js 18+ and npm
  • Python 3.9+
  • Google Account (for Gemini API key)

Setup Instructions

Step 1: Get Gemini API Key

  1. Go to Google AI Studio
  2. Click "Create API Key"
  3. Copy your API key

Step 2: Configure Environment Variables

  1. Open .env file in the project root
  2. Replace your-gemini-api-key-here with your actual API key:
GOOGLE_API_KEY=your-actual-api-key-here

Step 3: Install Dependencies

# Install Node.js dependencies
npm install

# Install Python dependencies
python3 -m pip install -r server/requirements.txt

Step 4: Run the Application

Option A: Using the startup script (recommended)

chmod +x start.sh
./start.sh

Option B: Manual startup

Terminal 1 - Start the AI server:

cd server
python3 -m uvicorn ai_server:app --host 0.0.0.0 --port 4000

Terminal 2 - Start the React app:

npm run dev

Step 5: Access the Application

Features

AI Chat

Ask the AI assistant questions, get code help, or troubleshooting assistance.

  • Endpoint: POST /api/ai/chat
  • Request: { "prompt": "Your question here" }

AI Planner

Get personalized study plans based on your goals and available time.

  • Endpoint: POST /api/ai/planner
  • Request: { "goals": "...", "timeAvailable": "30", "level": "Beginner" }

AI Summary

Generate summaries of your learning progress with suggestions for improvement.

  • Endpoint: POST /api/ai/summary
  • Request: { "data": { /* your progress data */ } }

Troubleshooting

"Generative SDK not available" error

  • Ensure GOOGLE_API_KEY is set in .env
  • Check that google-generativeai is installed: pip list | grep google

API Key errors

Connection refused

  • Make sure the Python server is running on port 4000
  • Check VITE_API_BASE in .env matches your server URL

Technologies Used

  • Frontend: React 18 + Vite + TypeScript
  • Backend: Python 3 + FastAPI
  • AI Model: Google Gemini
  • Styling: Tailwind CSS

Project Structure

.
├── src/                    # React components and pages
│   ├── components/ai/      # AI tool components
│   │   ├── AIChat.tsx
│   │   ├── AIPlanner.tsx
│   │   └── AISummary.tsx
│   └── pages/              # Page components
├── server/                 # Python backend
│   ├── ai_server.py        # FastAPI server
│   └── requirements.txt     # Python dependencies
├── .env                    # Environment configuration
└── package.json            # Node.js dependencies

API Reference

Chat Endpoint

curl -X POST http://localhost:4000/api/ai/chat \
  -H "Content-Type: application/json" \
  -d '{"prompt": "How do I learn React?"}'

Planner Endpoint

curl -X POST http://localhost:4000/api/ai/planner \
  -H "Content-Type: application/json" \
  -d '{
    "goals": "Learn React and TypeScript",
    "timeAvailable": "60",
    "level": "Intermediate"
  }'

Summary Endpoint

curl -X POST http://localhost:4000/api/ai/summary \
  -H "Content-Type: application/json" \
  -d '{"data": {"completedLessons": 5, "hoursSpent": 10}}'

Notes

  • Keep your API key secret and never commit .env to version control
  • Monitor your API usage at https://ai.google.dev/
  • The Gemini API has rate limits; adjust requests accordingly

Support

For issues with:

Happy coding with AI-powered learning! 🚀