JobVoice - AI-Powered Interview Assistant

JobVoice is an advanced AI-powered interview practice platform that helps job seekers prepare for technical and behavioral interviews through realistic voice-based simulations.

About the Application

JobVoice creates a realistic interview environment by leveraging AI to simulate job interviews. The application allows users to practice their interview skills with an AI interviewer that can ask relevant questions based on job roles, experience levels, and technology stacks.

Key Features

• Personalized Interview Simulations: Create custom interview sessions based on job role, experience level, and specific technology stack
• Voice-Based Interactions: Engage in natural voice conversations with the AI interviewer
• Multiple Interview Types: Practice technical interviews, behavioral interviews, or mixed format sessions
• Comprehensive Feedback: Receive detailed analysis and feedback on your interview performance
• Progress Tracking: Monitor your improvement over time across different interview sessions
• Customizable Questions: Generate relevant interview questions for your specific job target

Technology Stack

• Frontend: Next.js, React, Tailwind CSS
• Backend: Next.js API Routes, Firebase Cloud Functions
• Database: Firebase Firestore
• Authentication: Firebase Authentication
• AI Integration: Google Generative AI, GPT-4
• Voice Processing: VAPI (Voice API) for realistic voice interactions

Getting Started

Prerequisites

• Node.js 16+ and npm/yarn
• Firebase account
• API keys for AI services

Environment Variables

To run this application successfully, you need to create a .env.local file in the root directory with the following variables:

```

Firebase Configuration

NEXTPUBLICFIREBASEAPIKEY=yourfirebaseapikey NEXTPUBLICFIREBASEAUTHDOMAIN=yourfirebaseauthdomain NEXTPUBLICFIREBASEPROJECTID=yourfirebaseprojectid NEXTPUBLICFIREBASESTORAGEBUCKET=yourfirebasestoragebucket NEXTPUBLICFIREBASEMESSAGINGSENDERID=yourfirebasemessagingsenderid NEXTPUBLICFIREBASEAPPID=yourfirebaseappid

Google Generative AI

GOOGLEGENERATIVEAIAPIKEY=yourgeminiapi_key

OpenAI for GPT-4

OPENAIAPIKEY=youropenaiapi_key

VAPI Voice API

VAPIAPIKEY=yourvapiapikey VAPIPROJECTID=yourvapiprojectid

Optional: Analytics

NEXTPUBLICANALYTICSID=youranalytics_id ```

You can obtain these keys by:

1. Creating a Firebase project at Firebase Console
2. Setting up a Google AI Studio account for the Generative AI key
3. Creating an OpenAI account for the GPT-4 API key
4. Registering at VAPI for voice processing capabilities

A template .env.example file is included in the repository for reference.

Installation

1. Clone the repository

bash git clone https://github.com/yourusername/ai-interviewer.git cd ai-interviewer

1. Install dependencies

bash npm install # or yarn install

1. Create a .env.local file in the root directory with your API keys (see .env.example for required variables)

2. Start the development server

bash npm run dev # or yarn dev

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

How to Use

1. Create an Account: Sign up with your email and password
2. Configure an Interview: Select your target role, experience level, and relevant tech stack
3. Start the Interview: Begin the voice-based interview session with the AI interviewer
4. Complete the Session: Answer all questions to the best of your ability
5. Review Feedback: Receive detailed feedback on your performance with strengths and areas for improvement

Features in Detail

Interview Configuration

• Role Selection: Choose from a variety of job roles (Frontend, Backend, Full Stack, etc.)
• Experience Level: Select Junior, Mid-level, or Senior
• Tech Stack: Specify the technologies relevant to the position
• Interview Type: Technical, Behavioral, or Mixed format

Voice Interaction

The application uses advanced speech-to-text and text-to-speech technologies to create a realistic interview environment:

• Natural-sounding AI interviewer voice
• Real-time speech recognition to capture your responses
• Contextual understanding of your answers

Feedback Analysis

After each interview, receive comprehensive feedback including:

• Overall score
• Performance in key categories (Technical Knowledge, Communication Skills, Problem Solving, etc.)
• Specific strengths identified
• Areas for improvement with actionable recommendations
• Final assessment summary