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The Resume Generator application requires several environment variables to be configured before running. These variables control database connections, authentication, and AI service integration.

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Setting Up Environment Variables

1

Create .env file

Create a .env file in the backend directory of your project:
cd backend
touch .env
2

Add required variables

Add all the environment variables listed below to your .env file.
3

Verify configuration

Ensure all required variables are set before starting the application. The server will fail to start if critical variables are missing.

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Required Variables

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MONGO_URI

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MONGO_URI
string
required
MongoDB connection string for your database.Usage: The application connects to MongoDB using this URI in src/config/database.js:8Format:
mongodb://localhost:27017/resume-generator
Or for MongoDB Atlas:
mongodb+srv://<username>:<password>@cluster.mongodb.net/resume-generator
Example:
MONGO_URI=mongodb://localhost:27017/resume-generator

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JWT_SECRET

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JWT_SECRET
string
required
Secret key used for signing and verifying JSON Web Tokens (JWT) for user authentication.Usage: Used in authentication controllers and middleware:
  • src/controllers/auth.controller.js:41 - Token generation during registration
  • src/controllers/auth.controller.js:87 - Token generation during login
  • src/middlewares/auth.middleware.js:27 - Token verification
Example:
JWT_SECRET=your-super-secret-key-here-change-this-in-production
Security Best Practices for JWT_SECRET:
  • Use a strong, randomly generated string (minimum 32 characters)
  • Never commit your JWT_SECRET to version control
  • Use different secrets for development and production environments
  • Rotate your secret periodically in production
  • Generate a secure secret using: openssl rand -base64 32

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GOOGLE_GENAI_API_KEY

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GOOGLE_GENAI_API_KEY
string
required
API key for Google Gemini AI service used to generate interview reports and resumes.Usage: Initializes the Google GenAI client in src/services/ai.service.js:7The AI service uses the Gemini 3 Flash Preview model to:
  • Generate personalized interview reports with match scores
  • Create technical and behavioral interview questions
  • Identify skill gaps and provide preparation plans
  • Generate ATS-friendly resume PDFs
Example:
GOOGLE_GENAI_API_KEY=AIzaSyD...
API Key Security:
  • Keep your API key confidential and never expose it in client-side code
  • Do not commit API keys to version control
  • Monitor your API usage in Google AI Studio
  • Set up usage limits and quotas to prevent unexpected charges
  • Rotate your API key if compromised

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Complete .env Example

Here’s a complete example of a .env file with all required variables: 
# Database Configuration
MONGO_URI=mongodb://localhost:27017/resume-generator

# Authentication
JWT_SECRET=your-super-secret-key-minimum-32-characters-long

# AI Service
GOOGLE_GENAI_API_KEY=AIzaSyD...

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Loading Environment Variables

The application loads environment variables using the dotenv package at application startup: 
require("dotenv").config()
This is configured in server.js:1 and runs before any other application code.

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Troubleshooting

  • Verify your MONGO_URI is correctly formatted
  • Ensure MongoDB is running (for local connections)
  • Check network connectivity (for Atlas connections)
  • Verify database user credentials have proper permissions
  • Ensure JWT_SECRET is set and not empty
  • Verify the secret is the same across all application instances
  • Check that the secret hasn’t been changed while users have active sessions
  • Verify your GOOGLE_GENAI_API_KEY is valid and active
  • Check you have sufficient quota in Google AI Studio
  • Ensure the API key has access to the Gemini models
  • Review rate limits and try again later if throttled

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Next Steps

Database Setup

Configure MongoDB and understand the database schema

AI Setup

Set up Google Gemini API and configure AI services

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