🎯 Interview Insights - Advanced AI-Powered Interview Coach

Official Submission by Team Saksham
Developer: Harsh Srivastava
GitHub: @horus-bot
Status: accepting Pull Requests

🚀 Project Overview

Interview Insights is a cutting-edge AI-powered interview coaching platform that leverages multiple advanced AI technologies to provide comprehensive interview preparation and analysis. This Next.js application combines real-time video analysis, natural language processing, and machine learning to deliver personalized feedback that helps users excel in their job interviews.

🎭 What Makes This Special

Our platform doesn't just record and playback - it intelligently analyzes every aspect of your interview performance:

🎥 Real-time Video Analysis using Google Gemini Vision AI
🗣️ Speech Pattern Recognition with advanced audio processing
🧠 Natural Language Understanding powered by multiple AI models
📊 Behavioral Analytics through computer vision
🎯 Role-Specific Coaching tailored to different job positions

🏗️ Architecture & AI Integration

Multi-Model AI Architecture

┌─────────────────────────────────────────────────────────────┐
│                    Frontend (Next.js 14)                    │
├─────────────────────────────────────────────────────────────┤
│  🎥 Real-time Recording  │  🎯 Interactive UI  │  📊 Analytics │
└─────────────────────────────────────────────────────────────┘
                               │
┌─────────────────────────────────────────────────────────────┐
│                      AI Processing Layer                     │
├─────────────────────────────────────────────────────────────┤
│  Groq Llama 4       │  Google Gemini      │  Custom Models  │
│  (Text Analysis)    │  (Vision + Audio)   │  (Behavioral)   │
└─────────────────────────────────────────────────────────────┘
                               │
┌─────────────────────────────────────────────────────────────┐
│                    Data & Authentication                     │
├─────────────────────────────────────────────────────────────┤
│           Firebase (Auth, Storage, Analytics)               │
└─────────────────────────────────────────────────────────────┘

🤖 AI Models Used

Groq Llama 4 Scout (meta-llama/llama-4-scout-17b-16e-instruct)
- Advanced question generation
- Context-aware conversation flow
- Performance analysis and coaching
Google Gemini 1.5 Flash
- Multi-modal video + audio analysis
- Real-time facial expression recognition
- Voice tone and confidence assessment
Custom Behavioral Models
- Eye contact tracking
- Posture analysis
- Gesture recognition
- Speaking pace optimization

🔧 Technical Stack

Frontend: Next.js 14, React 18, TypeScript
Styling: Tailwind CSS, Shadcn/ui Components
AI Integration: Groq SDK, Google AI SDK
Media Processing: WebRTC, MediaRecorder API
Authentication: Firebase Auth
Database: Firebase Firestore
Deployment: Vercel/Firebase Hosting
State Management: React Hooks, Context API

✨ Advanced Features

🎯 Mock Interview System

Role-Specific Questions: AI generates personalized questions based on job role and experience level
Real-Time Analysis: Continuous monitoring of verbal and non-verbal communication
Adaptive Difficulty: Questions adjust based on your responses and skill level
Multi-Stage Process: Introduction → Conceptual → Coding/Behavioral → Analysis

📊 Comprehensive Performance Analytics

Analysis Dimensions:
├── 🗣️  Verbal Communication
│   ├── Clarity and Articulation
│   ├── Speaking Pace and Pauses
│   ├── Vocabulary and Grammar
│   └── Answer Structure (STAR Method)
├── 👁️  Non-Verbal Communication  
│   ├── Eye Contact Patterns
│   ├── Facial Expressions
│   ├── Body Language and Posture
│   └── Hand Gestures and Movement
├── 🧠 Technical Competency
│   ├── Problem-Solving Approach
│   ├── Code Quality Assessment
│   ├── Algorithmic Thinking
│   └── Best Practices Knowledge
└── 💡 Overall Performance
    ├── Confidence Level
    ├── Professional Presence
    ├── Interview Readiness Score
    └── Improvement Recommendations

🎨 Interactive Coaching Modules

STAR Method Builder
- Guided framework for behavioral questions
- Real-time structure validation
- Example optimization
Technical Coding Practice
- Role-specific coding challenges
- Live code analysis
- Performance optimization tips
Skill Improvement Exercises
- Eye contact training
- Posture correction
- Speech clarity drills

🤖 AI Chat Coach

Personalized coaching conversations
Context-aware advice
Progress tracking
Skill gap identification

🛠️ Installation & Setup

Prerequisites

Node.js 18+ 
npm or yarn
Modern browser with camera/microphone support

1. Project Setup

# Clone the repository
git clone https://github.com/horus-bot/interview-insights
cd interview-insights

# Install dependencies
npm install

2. Environment Configuration

Create a .env.local file in the root directory:

# =============================
# 🔥 Firebase Configuration 🔥
# =============================
NEXT_PUBLIC_FIREBASE_API_KEY=your_firebase_api_key
NEXT_PUBLIC_FIREBASE_AUTH_DOMAIN=your_project.firebaseapp.com
NEXT_PUBLIC_FIREBASE_PROJECT_ID=your_project_id
NEXT_PUBLIC_FIREBASE_STORAGE_BUCKET=your_project.appspot.com
NEXT_PUBLIC_FIREBASE_MESSAGING_SENDER_ID=your_sender_id
NEXT_PUBLIC_FIREBASE_APP_ID=your_app_id
NEXT_PUBLIC_FIREBASE_MEASUREMENT_ID=your_measurement_id

# =============================
# 🤖 AI API Keys 🤖
# =============================
GEMINI_API_KEY=your_gemini_api_key
GROQ_API_KEY=your_groq_api_key

3. Firebase Setup

Create a Firebase project at Firebase Console
Enable Authentication (Email/Password)
Create Firestore database
Copy configuration to .env.local

4. AI API Setup

Groq API: Get key from Groq Console
Gemini API: Get key from Google AI Studio

5. Run Development Server

# Start the development server
npm run dev

# Application will be available at:
# http://localhost:3000

6. Production Build

# Build for production
npm run build

# Start production server
npm start

📱 Platform Features

🎯 Main Interview Types

Behavioral Interview
- STAR method coaching
- Situational question practice
- Leadership and teamwork assessment
Technical Coding Interview
- Role-specific programming challenges
- Code quality analysis
- Algorithm optimization feedback
System Design Interview
- Architecture discussion simulation
- Scalability considerations
- Best practices evaluation

📊 Analysis Dashboard

Performance Metrics: Comprehensive scoring across multiple dimensions
Visual Feedback: Charts, graphs, and progress tracking
Personalized Recommendations: AI-driven improvement suggestions
Historical Progress: Track improvement over time

🎓 Learning Resources

Interview Tips Library: Curated best practices
Common Questions Bank: Industry-specific question sets
Practice Exercises: Targeted skill development
Video Tutorials: Expert guidance and examples

🔧 Technical Implementation Details

Real-Time Video Processing

// Advanced video compression and analysis
const videoAnalysis = await geminiModel.generateContent([
  { text: analysisPrompt },
  { inlineData: { mimeType: "video/mp4", data: videoData }}
]);

AI-Powered Question Generation

const questions = await groq.chat.completions.create({
  model: "meta-llama/llama-4-scout-17b-16e-instruct",
  messages: [
    { role: "system", content: "Expert technical interviewer..." },
    { role: "user", content: questionPrompt }
  ]
});

Multi-Modal Analysis Pipeline

Video Input → WebRTC MediaRecorder
Audio Separation → Web Audio API
Compression → Client-side optimization
AI Analysis → Gemini Vision + Groq Processing
Results Synthesis → Multi-model consensus
Feedback Generation → Personalized recommendations

🚦 Usage Guide

Getting Started

Sign Up/Login using email authentication
Choose Interview Type (Behavioral, Technical, etc.)
Configure Settings (role, experience level, duration)
Grant Permissions for camera and microphone access
Start Interview and follow AI guidance
Receive Analysis with detailed feedback and scores

Best Practices

🌐 Use Google Chrome or Firefox for best experience
🎥 Ensure good lighting and stable internet
🎧 Use headphones to minimize audio feedback
📱 Desktop/laptop recommended over mobile devices

⚠️ Important Notes

🔒 Privacy & Security

All video processing happens locally during recording
No permanent storage of video data
Secure API communication with encryption
Firebase security rules protect user data

🚫 Contribution Policy

This repository is an official competition submission and is not accepting pull requests or external contributions at this time.

📄 License

🏆 About Team Saksham

Developer: Harsh Srivastava
GitHub: @horus-bot
Specialization: AI/ML Engineering, Full-Stack Development

This project represents months of research and development in AI-powered interview coaching, combining cutting-edge machine learning models with intuitive user experience design.

🐛 Troubleshooting

Common Issues

Camera/Microphone Not Working?

# For localhost (development)
# Ensure you're accessing via http://localhost:3000
# Grant browser permissions when prompted
# Check browser console for permission errors

AI Analysis Failing?

# Verify API keys in .env.local
# Check network connectivity
# Ensure video file size < 10MB

Authentication Issues?

# Verify Firebase configuration
# Check console for authentication errors
# Ensure Firebase project is properly set up

📞 Support

For technical support or questions about this competition entry, please contact:

Email: Contact through GitHub profile
GitHub: @horus-bot

Built with ❤️ by Team Saksham | Powered by Advanced AI Technologies

Name		Name	Last commit message	Last commit date
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docs		docs
src		src
.gitignore		.gitignore
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README.md		README.md
apphosting.yaml		apphosting.yaml
components.json		components.json
next.config.ts		next.config.ts
package-lock.json		package-lock.json
package.json		package.json
postcss.config.mjs		postcss.config.mjs
tailwind.config.ts		tailwind.config.ts
tsconfig.json		tsconfig.json

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