AI Resume

Through AI assist recruiters in screening resumes according to different industry standards and job requirements, generating targeted interview questions, and summarizing interviews.

Project Structure

• app/: Next.js application pages and layouts
• components/: React components for the UI
• backend/: Go backend API services
• lib/: Utility functions and helpers
• public/: Static assets

Prerequisites

• Node.js (v18.0.0 or higher)
• npm (v9.0.0 or higher)
• Go (v1.20 or higher)
• Google Cloud Platform account with Vertex AI API enabled

Setup and Installation

Frontend Setup

1. Install dependencies:

   npm install
   

2. Create a .env file in the project root with the following variables (see .env.example for a template):

   NEXT_PUBLIC_API_URL=<backend_api_url>
   

3. Build the frontend:

   npm run build
   

4. Start the frontend server:

   npm start
   

Backend Setup

1. Navigate to the backend directory:

   cd backend
   

2. Install Go dependencies:

   go mod download
   

3. Create a Google Cloud service account key and save it in a secure location.

4. Copy .env.example to .env and update with your configuration:

   cp .env.example .env
   

   Edit the .env file to set your Google Cloud project ID and the path to your service account key.

5. Build and run the backend:

   go build -o ai-resume-backend main.go
   ./ai-resume-backend
   

Security Considerations

Sensitive Information

The project contains several files with sensitive information that should not be committed to version control:

1. Google Cloud Service Account Keys (*.json): These files contain private keys that could be used to access your Google Cloud resources.

2. Environment Files (.env): These files contain configuration variables that may include API keys, project IDs, and other sensitive information.

To protect sensitive information:

• Never commit .env files or service account keys to version control
• Use the provided .env.example files as templates
• For production deployments, use environment variables or secrets management services
• Review .gitignore to ensure sensitive files are excluded

Local Development

For local development, create your own .env files based on the .example templates provided, and place your service account key in a secure location that is not tracked by Git.

Deployment

Frontend Deployment

1. Build the production version of the frontend:

   npm run build
   

2. Deploy to your preferred hosting service (Vercel, Netlify, etc.)

Backend Deployment

1. Build the Go binary for your target platform:

   go build -o ai-resume-backend main.go
   

2. Deploy the binary to your server or container platform of choice.

3. Ensure the service account credentials are properly set up in your deployment environment.

Features

• Resume Screening: Upload resumes for AI analysis
• Interview Question Generation: Generate customized interview questions based on job requirements
• Interview Summary: Create comprehensive interview summaries

License

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Contact

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