HireLoom

Smart AI-Powered Interview Preparation Assistant

Problem Statement Traditional interview processes are time-consuming, inconsistent, and often fail to effectively assess candidate qualifications. Recruiters struggle with creating relevant questions, while candidates face unpredictable interview experiences.

Objective HireLoom aims to revolutionize the interview process by leveraging AI to generate personalized interview questions based on resume analysis. Our platform streamlines recruitment workflows, ensures consistent candidate evaluation, and provides comprehensive assessment tools for better hiring decisions.

Tech Stack

• Frontend: Next.js, React
• Backend: Next.js API Routes
• AI Integration: Google Gemini API
• Styling: Tailwind CSS
• Deployment: Vercel

Key Features

AI-Powered Question Generation

• Resume Analysis: Upload a resume and get tailored interview questions
• Industry-Specific Questions: Questions customized to match job roles and industry requirements

Comprehensive Assessment Tools

• Real-time Evaluation: Analyze candidate responses during interviews
• Performance Metrics: Track and compare candidate performance with detailed analytics

Interview Management

• Create Interviews: Set up interviews with customized parameters
• Join Interviews: Seamless interface for candidates to join scheduled interviews
• Interview History: Access past interviews and their results

Resume Analysis

• Resume Parsing: Extract and analyze key information from resumes
• Skill Mapping: Match candidate skills against job requirements

Getting Started

Prerequisites

Before running the project, make sure you have the following installed:

• Node.js (v18 or later)
• npm (v9 or later) or yarn
• Google Gemini API key - Required for AI functionality

Installation

1. Clone the repository

git clone https://github.com/samarthyaveer/HireLoom.git
cd HireLoom

2. Install dependencies

npm install
# or
yarn install

3. Set up environment variables

Create a .env.local file in the root directory with the following variables:

GEMINI_API_KEY=your_gemini_api_key_here
GEMINI_MODEL=gemini-2.0-flash

Note: You can copy the .env.local.example file and rename it to .env.local, then replace the placeholder values with your actual API key.

4. Start the development server

npm run dev
# or
yarn dev

5. Open your browser

Navigate to http://localhost:3000 to see the application running.

Environment Variables

The application requires the following environment variables:

Variable	Description	Required	Default
GEMINI_API_KEY	Your Google Gemini API key	Yes	None
GEMINI_MODEL	The Gemini model to use	No	gemini-2.0-flash

Getting a Gemini API Key

1. Go to Google AI Studio
2. Sign in with your Google account
3. Navigate to the API section
4. Create a new API key
5. Copy the key and add it to your .env.local file

Usage Guide

1. Home Page: Navigate through the main interface showcasing features
2. Create Interview: Upload a resume and set interview parameters
3. Join Interview: Enter an interview session using the provided link/ID
4. View Results: Access detailed analysis of interview performance

Future Scope

• Multi-language support for global recruitment
• Video interview integration with real-time AI analysis
• Advanced analytics dashboard for recruitment teams
• Integration with popular ATS (Applicant Tracking Systems)

Contributing Contributions are welcome! Please feel free to submit a Pull Request.

License This project is licensed under the MIT License - see the LICENSE file for details.

Learn More

To learn more about Next.js, take a look at the following resources:

• Next.js Documentation - learn about Next.js features and API.
• Learn Next.js - an interactive Next.js tutorial.

You can check out the Next.js GitHub repository - your feedback and contributions are welcome!

Deployment

Deploying to Vercel

This project is optimized for deployment on Vercel. Follow these steps to deploy:

1. Push your code to a GitHub repository

   git add .
   git commit -m "Prepare for Vercel deployment"
   git push origin main

2. Go to Vercel and sign up/login

3. Click "New Project" and import your GitHub repository

4. Configure the project:

   • Set the framework preset to "Next.js"
   • Add environment variables (GEMINI_API_KEY, GEMINI_MODEL)

5. Click "Deploy"

Environment Variables on Vercel

Make sure to add the same environment variables to your Vercel project:

1. Go to your project on Vercel
2. Navigate to Settings > Environment Variables
3. Add the GEMINI_API_KEY and GEMINI_MODEL variables
4. Redeploy your application for the changes to take effect

Troubleshooting Deployment Issues

If you encounter issues during deployment:

1. Check the Vercel deployment logs for specific error messages
2. Ensure your environment variables are correctly set in the Vercel dashboard
3. Verify that your project is using Node.js v18 or later (set in Vercel project settings)
4. Make sure your package.json dependencies are compatible with Vercel's environment

For more information, check out the Next.js deployment documentation.