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FairMatch AI uses environment variables to manage configuration for database connections, API keys, and AI services. This guide covers all configuration options.

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Environment file setup

FairMatch AI stores configuration in a .env file located in the backend directory.
1

Create the environment file

Copy the example environment file to create your configuration:
cd backend
cp .env.example .env
2

Edit the file

Open the .env file in your preferred text editor:
nano .env
Or use any text editor you prefer.
3

Add your credentials

Update each variable with your actual values (detailed below).

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Required environment variables

All of these variables are required for FairMatch AI to function properly.

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Database configuration

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SUPABASE_URL

Your Supabase project URL. 
SUPABASE_URL=your_supabase_project_url
How to find it:
  1. Log in to your Supabase dashboard
  2. Navigate to Project Settings > API
  3. Copy the “Project URL” value
Example: https://abcdefghijklmnop.supabase.co

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SUPABASE_KEY

Your Supabase anonymous API key for client-side access. 
SUPABASE_KEY=your_supabase_anon_key
How to find it:
  1. In your Supabase dashboard, go to Project Settings > API
  2. Copy the “anon” “public” key from the “Project API keys” section
Never commit your Supabase service role key to version control. Use the anon key for client applications.

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AI service configuration

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GEMINI_API_KEY

Your Google Gemini API key for AI-powered evaluations. 
GEMINI_API_KEY=your_gemini_api_key
How to get it:
  1. Visit Google AI Studio
  2. Sign in with your Google account
  3. Create a new API key
  4. Copy the generated key
FairMatch AI uses Google Gemini for natural language processing, resume analysis, and candidate evaluation. This is a core dependency.

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ZYND_API_KEY

Your Zyndai API key for multi-agent orchestration. 
ZYND_API_KEY=your_zynd_api_key
How to get it:
  1. Sign up at Zyndai
  2. Navigate to your dashboard
  3. Generate an API key from the API Keys section
Zyndai powers the multi-agent evaluation pipeline, coordinating the Resume Analyst, GitHub Verifier, Interview Grader, and Integrity Agent.

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Complete configuration example

Here’s what your complete .env file should look like: 
SUPABASE_URL=https://abcdefghijklmnop.supabase.co
SUPABASE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...
GEMINI_API_KEY=AIzaSyD-1234567890abcdefghijk
ZYND_API_KEY=zynd_1234567890abcdefghijk

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Configuration validation

After setting up your environment variables, verify your configuration:
1

Start the backend server

cd backend
source venv/bin/activate
python -m uvicorn main:app --reload --port 8000
2

Check the logs

Monitor the terminal output for any connection errors or warnings about missing environment variables.
3

Test the API

Visit http://localhost:8000/docs and try making a test request to verify database connectivity.

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Security best practices

Never commit your .env file to version control. The .env file should be listed in your .gitignore.
Follow these security guidelines:
  • Keep keys private: Never share your API keys in public repositories, issues, or documentation
  • Rotate keys regularly: Periodically regenerate your API keys, especially if they may have been exposed
  • Use service accounts: For production deployments, use dedicated service accounts with minimal permissions
  • Environment-specific configs: Maintain separate .env files for development, staging, and production
  • Backup safely: If you backup your .env file, store it in a secure, encrypted location

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Environment-specific configuration

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Development

For local development, use your personal API keys and a development Supabase project: 
SUPABASE_URL=https://dev-project.supabase.co
SUPABASE_KEY=dev_anon_key
GEMINI_API_KEY=dev_gemini_key
ZYND_API_KEY=dev_zynd_key

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Production

For production deployments:
  1. Use a production Supabase project with appropriate security rules
  2. Generate production-specific API keys
  3. Set environment variables through your hosting platform’s dashboard (e.g., Vercel, Railway, or AWS)
  4. Enable rate limiting and monitoring on your API keys

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Troubleshooting configuration issues

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”Environment variable not found” errors

  • Verify the .env file is in the backend directory
  • Check that variable names match exactly (including case)
  • Ensure there are no extra spaces around the = sign
  • Restart the backend server after making changes

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Database connection failures

  • Verify your SUPABASE_URL is correct and accessible
  • Test your SUPABASE_KEY in the Supabase dashboard
  • Check your network connection and firewall settings
  • Ensure your Supabase project is active and not paused

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AI service errors

  • Verify your GEMINI_API_KEY is valid and not expired
  • Check your Google AI Studio quota and usage limits
  • Ensure your ZYND_API_KEY has the correct permissions
  • Review the agent logs for specific error messages

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Advanced configuration

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Custom ports

To run the backend on a different port: 
python -m uvicorn main:app --reload --port 8080

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Host binding

To allow external connections in production: 
python -m uvicorn main:app --host 0.0.0.0 --port 8000

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Log levels

Adjust logging verbosity by setting the log level in your startup command: 
python -m uvicorn main:app --log-level debug
Available levels: critical, error, warning, info, debug, trace

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Next steps

With your configuration complete, you can:
  • Start building your first job posting
  • Upload candidate resumes
  • Explore the AI evaluation pipeline
  • Customize the application for your hiring workflow

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