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SETUP.md

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Setup Guide

Complete setup instructions for running IssueMatch locally.

Prerequisites

  • Python 3.9 or higher
  • Node.js 18 or higher
  • Git
  • MongoDB Atlas account (free tier)
  • Google AI Studio API key
  • GitHub OAuth app

Backend Setup

1. Navigate to Backend

cd backend

2. Create Virtual Environment

# Windows
python -m venv venv
venv\Scripts\activate

# macOS/Linux
python -m venv venv
source venv/bin/activate

3. Install Dependencies

pip install -r requirements.txt

4. Configure Environment Variables

Create .env file in backend/ directory:

# MongoDB
MONGODB_URI=mongodb+srv://username:password@cluster.mongodb.net/?appName=Cluster0

# Google AI
GOOGLE_AI_STUDIO_API_KEY=your_gemini_api_key

# GitHub OAuth
GITHUB_CLIENT_ID=your_github_client_id
GITHUB_CLIENT_SECRET=your_github_client_secret

# Security
SECRET_KEY=your_secret_key_for_sessions

# API Configuration
PROJECT_NAME="IssueMatch"
API_V1_STR="/api/v1"

5. Start Backend Server

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

Backend will be available at: http://localhost:8000

Frontend Setup

1. Navigate to Frontend

cd frontend

2. Install Dependencies

npm install

3. Configure Environment Variables

Create .env.local file in frontend/ directory:

NEXT_PUBLIC_API_URL=http://localhost:8000/api/v1
NEXT_PUBLIC_APP_URL=http://localhost:3000

GOOGLE_AI_API_KEY=your_gemini_api_key
GOOGLE_AI_MODEL=gemini-2.0-flash-lite

4. Start Development Server

npm run dev

Frontend will be available at: http://localhost:3000

GitHub OAuth Setup

1. Create OAuth App

  1. Go to GitHub Settings → Developer settings → OAuth Apps
  2. Click "New OAuth App"
  3. Fill in details:
  4. Click "Register application"

2. Get Credentials

  • Copy Client ID and Client Secret
  • Add them to backend/.env

MongoDB Setup

1. Create MongoDB Atlas Account

  1. Go to MongoDB Atlas
  2. Create free account
  3. Create new cluster (M0 free tier)

2. Get Connection String

  1. Click "Connect" on your cluster
  2. Choose "Connect your application"
  3. Copy connection string
  4. Replace <password> with your database password
  5. Add to backend/.env as MONGODB_URI

3. Configure Network Access

  1. Network Access → Add IP Address
  2. Allow access from anywhere (0.0.0.0/0) for development

4. Collections (Auto-created)

These collections are created automatically:

  • users - User profiles and skills
  • leaderboard - Contribution rankings
  • mentorship_requests - Mentor requests
  • referrals - Referral tracking
  • contributions - User contributions

Google AI Studio Setup

1. Get API Key

  1. Go to Google AI Studio
  2. Create API key
  3. Add to backend/.env as GOOGLE_AI_STUDIO_API_KEY
  4. Add to frontend/.env.local as GOOGLE_AI_API_KEY

Verification

Backend Health Check

curl http://localhost:8000/

Expected response:

{"message": "Welcome to IssueMatch API"}

Frontend Check

Open http://localhost:3000 in browser

Troubleshooting

Backend Issues

Import errors

pip install -r requirements.txt --upgrade

MongoDB connection failed

  • Check connection string format
  • Verify IP whitelist in Atlas
  • Check username/password

GitHub OAuth not working

  • Verify callback URL matches exactly
  • Check client ID and secret

Frontend Issues

Module not found

rm -rf node_modules package-lock.json
npm install

Environment variables not loading

  • Restart dev server after changing .env.local
  • Ensure chatbot variables are set

Production Deployment

See DEPLOYMENT.md for production deployment instructions.

Need Help?