Skip to content

This MERN stack web app streamlines job applications by enabling companies to post jobs, applicants to answer interview questions, and an LLM to rate responses, helping admins make informed hiring decisions.

Notifications You must be signed in to change notification settings

bethmij/hirly-ai

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

80 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Hirly AI - Interview Question Platform

This web application is designed to streamline the job application process. Companies can post job openings, applicants can respond to interview questions, and the platform provides ratings for the answers through an integrated LLM. Admins can review the responses and ratings to make informed hiring decisions. This platform has been developed as a white label solution for a specific company.

Hosted Link

Technology stack

 ✅ Frontend: React Vite TS
 ✅ Backend: Node Express TS
 ✅ Database: MongoDB
 ✅ Fine-tuning: OpenAI
 ✅ Authentication: Clerk
 ✅ Styling: Tailwind Shadcn

Features

home

home

  • Job Posting: Admins can create and manage job listings.
  • Interview Questions: Applicants can answer interview questions posted for job openings.

home

  • LLM Rating: Integrated LLM provides ratings for applicants' answers.

home

  • Admin Dashboard: Admins can view applicant responses and LLM ratings.
  • User Authentication: Secure login and registration using Clerk.
  • Responsive Design: Clean and responsive user interface styled with Tailwind.

Installation

  1. Clone the repository:
    git clone https://github.com/bethmij/Hirly-AI.git
    
  2. Install dependencies:
    npm install
    
  3. Set up environment variables: Create a .env file in the root directory and add the necessary environment variables.
    MONGO_URI=your_mongodb_uri
    OPENAI_API_KEY=your_openai_api_key
    CLERK_API_KEY=your_clerk_api_key
    
  4. Run the application:
    npm start

About

This MERN stack web app streamlines job applications by enabling companies to post jobs, applicants to answer interview questions, and an LLM to rate responses, helping admins make informed hiring decisions.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published