SETUP.md

CV Wizard - Setup Guide

Quick Start (Backend)

1. Prerequisites

• Python 3.11+
• MongoDB Atlas account (free M0 tier)
• Google Gemini API key (free tier)

2. Backend Setup

cd backend

# Create virtual environment
python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Download spaCy model
python -m spacy download en_core_web_md

3. Environment Configuration

Create .env file in the backend directory:

cp .env.example .env

Edit .env and add your credentials:

# MongoDB Atlas Connection
MONGODB_URI=mongodb+srv://username:password@cluster.mongodb.net/cv-wizard?retryWrites=true&w=majority

# Google Gemini API
GEMINI_API_KEY=your_gemini_api_key_here

# Application Settings
ENVIRONMENT=development
DEBUG=True
PORT=8000
HOST=0.0.0.0

# File Upload Settings
MAX_FILE_SIZE=5242880  # 5MB
UPLOAD_DIR=./uploads
QUARANTINE_DIR=./quarantine

# Security
SECRET_KEY=your-secret-key-change-in-production
ALLOWED_ORIGINS=http://localhost:5173,http://localhost:3000

# Rate Limiting
RATE_LIMIT_PER_MINUTE=10
RATE_LIMIT_WINDOW=900

# Session Settings
SESSION_TTL_HOURS=24

4. Get MongoDB Atlas URI

1. Go to MongoDB Atlas
2. Create free M0 cluster
3. Create database user
4. Whitelist your IP (or 0.0.0.0/0 for development)
5. Get connection string from "Connect" → "Connect your application"
6. Replace <password> and <username> in the URI

5. Get Gemini API Key

1. Go to Google AI Studio
2. Create new API key
3. Copy and paste into .env

6. Run the Backend

# Make sure you're in the backend directory with venv activated
cd backend
source venv/bin/activate

# Run with uvicorn
python main.py

# Or use uvicorn directly
uvicorn main:app --reload --host 0.0.0.0 --port 8000

The API will be available at:

• API: http://localhost:8000
• Docs: http://localhost:8000/docs
• Health: http://localhost:8000/health

Testing the API

1. Upload a CV

curl -X POST "http://localhost:8000/api/upload" \
  -F "file=@/path/to/your/resume.pdf"

Response:

{
  "session_id": "550e8400-e29b-41d4-a716-446655440000",
  "filename": "resume.pdf",
  "file_hash": "a1b2c3...",
  "extracted_text": "...",
  "parsed_data": {
    "skills": ["Python", "FastAPI"],
    "experience": [],
    "education": [],
    "contact": {...}
  }
}

2. Analyze CV

curl -X POST "http://localhost:8000/api/analyze" \
  -H "Content-Type: application/json" \
  -d '{
    "session_id": "550e8400-e29b-41d4-a716-446655440000",
    "job_description": "We are looking for a Python developer with FastAPI experience..."
  }'

3. Download Optimized CV

# Download as Markdown
curl "http://localhost:8000/api/download/{session_id}/markdown" \
  -o optimized_resume.md

# Download as PDF (TODO)
curl "http://localhost:8000/api/download/{session_id}/pdf" \
  -o optimized_resume.pdf

API Documentation

Once the server is running, visit:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc

Troubleshooting

spaCy Model Not Found

python -m spacy download en_core_web_md

If you have limited bandwidth, use the smaller model:

python -m spacy download en_core_web_sm

MongoDB Connection Error

• Check if your IP is whitelisted in MongoDB Atlas
• Verify the connection string format
• Ensure database user has correct permissions

Gemini API Rate Limit

Free tier limits:

• 5 requests per minute
• ~20-25 requests per day

The API implements caching to reduce redundant calls.

Import Errors

Make sure you're in the virtual environment:

source venv/bin/activate  # On Windows: venv\Scripts\activate

Next Steps

1. ✅ Backend API is running
2. 🔄 Create frontend React application
3. 🔄 Implement PDF generation
4. 🔄 Add Docker configuration
5. 🔄 Deploy to AWS EC2

Development Tips

Auto-reload on Changes

uvicorn main:app --reload

View Logs

Logs are printed to console. For production, configure proper logging.

Database Management

View your data in MongoDB Atlas:

1. Go to your cluster
2. Click "Browse Collections"
3. Navigate to cv_wizard database → cv_sessions collection

Security Testing

Test PDF security validation with a malicious pattern:

# This will be rejected
echo "%PDF-1.4\n/JavaScript (alert(1))" > test.pdf
curl -X POST "http://localhost:8000/api/upload" -F "file=@test.pdf"

Production Deployment

See DEPLOYMENT.md (to be created) for AWS EC2 deployment instructions.

Support

For issues or questions:

• Check API documentation at /docs
• Review logs in console
• Check MongoDB Atlas dashboard
• Verify environment variables in .env