Interview Trainer Platform

An AI-powered mock interview platform that connects job seekers with experienced interviewers and provides intelligent question generation, real-time feedback, and performance scoring.

Overview

Interview Trainer is a comprehensive platform designed to help job seekers prepare for technical and behavioral interviews through:

AI-Generated Questions: Smart question generation based on industry and role
Peer-to-Peer Interviews: Connect with experienced interviewers
Real-Time AI Feedback: Get instant analysis and scoring
Performance Tracking: Monitor progress over time

The platform serves two primary user types:

Interviewees: Job seekers looking to practice and improve their interview skills
Interviewers: Experienced professionals offering mock interview sessions

Key Features

For Interviewees

AI-Powered Mock Interviews - Practice with dynamically generated questions tailored to specific roles and industries
Real Person Interviews - Schedule and conduct live video interviews with experienced interviewers
Performance Analytics - Track confidence scores, completion rates, and overall performance metrics
Session Recording & Review - Access past interviews for self-assessment
Smart Scheduling - Book interviews with available interviewers based on expertise

For Interviewers

Expert Profile Management - Showcase expertise, industry focus, and availability
Rating & Review System - Build reputation through candidate feedback
Flexible Scheduling - Set available time slots for mock interviews
Performance Insights - View interview statistics and impact metrics

AI & Automation

Gemini AI Integration - Advanced question generation and answer analysis
Automated Scoring - AI-powered performance evaluation
Real-Time Processing - Live feedback during interview sessions

Architecture

The platform follows a microservices architecture with service discovery, API gateway, and event-driven communication patterns.

┌─────────────────────────────────────────────────────────────────┐
│                        Client Applications                       │
└─────────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────────┐
│                    API Gateway (Port: 8081)                      │
│              - Request Routing  - Load Balancing                  │
│              - Authentication   - Rate Limiting                   │
└─────────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────────┐
│                 Service Registry (Eureka)                        │
│                    (Port: 8761)                                  │
└─────────────────────────────────────────────────────────────────┘
                              │
        ┌─────────────────────┼─────────────────────┐
        │                     │                     │
        ▼                     ▼                     ▼
┌──────────────┐   ┌──────────────┐   ┌──────────────┐
│ User Service │   │  Interview   │   │   Question   │
│   (8085)     │   │   Session    │   │  Generation  │
│              │   │   (8090)     │   │   (8087)     │
└──────────────┘   └──────────────┘   └──────────────┘
        │                     │                     │
        ▼                     ▼                     ▼
┌──────────────┐   ┌──────────────┐   ┌──────────────┐
│Auth Service  │   │  Feedback &  │   │  Processing  │
│   (8088)     │   │   Scoring    │   │   (8084)     │
│              │   │   (8082)     │   │              │
└──────────────┘   └──────────────┘   └──────────────┘
        │                     │                     │
        ▼                     ▼                     ▼
┌──────────────┐   ┌──────────────┐   ┌──────────────┐
│ Notification │   │    Storage   │   │              │
│   (8083)     │   │   (8086)     │   │              │
└──────────────┘   └──────────────┘   └──────────────┘

Microservices

Service	Port	Description	Database	Key Technologies
Service Registry	8761	Eureka server for service discovery	N/A	Netflix Eureka
API Gateway	8081	Spring Cloud Gateway for routing	N/A	Spring Gateway, WebFlux
User Service	8085	User management, authentication, profiles	PostgreSQL	JPA, Redis, JWT
Auth Service	8088	OAuth2, JWT token management, Cloudinary	N/A	Spring Security, Cloudinary
Interview Session Service	8090	Session scheduling, LiveKit integration, WebSocket	PostgreSQL (R2DBC)	WebSocket, LiveKit, Kafka
Question Generation Service	8087	AI-powered question generation	PostgreSQL	Gemini AI
Processing Service	8084	Video/audio processing, Flask integration	PostgreSQL	Multipart, Async
Feedback & Scoring Service	8082	AI analysis and scoring	PostgreSQL	Keycloak
Notification Service	8083	Email notifications	PostgreSQL	JavaMail
Storage Service	8086	File storage management	PostgreSQL	Keycloak

Technology Stack

Backend

Java 21 - Latest LTS version with virtual threads support
Spring Boot 3.4.2 - Microservices framework
Spring Cloud 2024.0.0 - Service discovery, gateway, Feign clients
Spring Security - JWT and OAuth2 authentication
Spring Data JPA/R2DBC - Data persistence

Databases & Caching

PostgreSQL - Primary relational database
Redis - Distributed caching and session management

AI & External Services

Google Gemini AI - Question generation and answer analysis
LiveKit - Real-time video/audio for interviews
Cloudinary - Image upload and management
Flask API - Python-based media processing

Communication

Kafka - Event streaming for async processing
WebSocket - Real-time chat and notifications
Spring OpenFeign - Inter-service communication

Infrastructure

Netflix Eureka - Service registry and discovery
Spring Cloud Gateway - API gateway with reactive programming
Maven - Build and dependency management

Getting Started

Prerequisites

Java 21 or higher
Maven 3.8+
PostgreSQL 14+
Redis 7+
Kafka (for event streaming)

Installation

Clone the repository

git clone https://github.com/Leul120/interview-trainer.git
cd interview-trainer

Start Infrastructure Services

# Start PostgreSQL
# Start Redis
# Start Kafka (if using event streaming)

Set Environment Variables Create a .env file or set the following environment variables:

export DB_URL=jdbc:postgresql://localhost:5432/interview-trainer
export DB_USER=postgres
export DB_PWD=your-password
export EUREKA_CLIENT_SERVICE_URL=http://localhost:8761/eureka
export REDIS_HOST=localhost
export GEMINI_API_KEY=your-gemini-api-key
export LIVE_KIT_API_KEY=your-livekit-key
export LIVE_KIT_API_SECRET=your-livekit-secret
export CLOUDINARY_CLOUD_NAME=your-cloud-name
export CLOUDINARY_API_KEY=your-api-key
export CLOUDINARY_API_SECRET=your-api-secret
export FLASK_API=http://localhost:5000
export MAIL_PASSWORD=your-email-password

Build All Services

# Build each service
cd service-registry && mvn clean install
cd ../apiGateway && mvn clean install
cd ../userService && mvn clean install
cd ../authService && mvn clean install
cd ../interviewSessionService && mvn clean install
cd ../questionGenerationService && mvn clean install
cd ../processingService && mvn clean install
cd ../feedbackAndScoringService && mvn clean install
cd ../notificationService && mvn clean install
cd ../storageService && mvn clean install

Run Services (Start in order)

# 1. Service Registry
cd service-registry && mvn spring-boot:run

# 2. API Gateway
cd apiGateway && mvn spring-boot:run

# 3. Other Services (in any order)
cd userService && mvn spring-boot:run
cd authService && mvn spring-boot:run
cd interviewSessionService && mvn spring-boot:run
# ... etc

API Documentation

User Service API (`/api/v1/user`)

Method	Endpoint	Description
POST	`/signup`	Register new user
POST	`/signin`	Authenticate user
POST	`/refresh`	Refresh JWT token
GET	`/get-user/{email}`	Get user by email
GET	`/get-user-by-id`	Get current user
GET	`/public/get-interviewers`	List all interviewers
POST	`/update-user/{id}`	Update user profile
GET	`/online-status/{status}`	Set online status

Interview Session API (`/api/v1/session`)

Method	Endpoint	Description
GET	`/start-session/{scheduleId}`	Start interview session
GET	`/start-ai-session/{title}`	Start AI-powered session
GET	`/join-session/{scheduleId}/{sessionId}`	Join scheduled interview
GET	`/end-session/{sessionId}`	End interview session
POST	`/schedule-interview`	Schedule new interview
GET	`/get-my-sessions`	Get user's sessions (paginated)
GET	`/get-my-scheduled-interviews`	Get scheduled interviews

Database Schema

Core Entities

User
├── id (UUID, PK)
├── email (String, Unique)
├── password (String)
├── name (String)
├── role (Enum: ADMIN, INTERVIEWEE)
├── type (UserType)
├── profilePicture (String)
├── expertise (List<String>)
├── industry (String)
├── availabilityStatus (Enum)
├── averageRating (Double)
├── reviewCount (Integer)
├── completedInterviews (Integer)
├── overallPerformanceScore (Double)
├── confidenceScore (Double)
├── isSubscribed (Boolean)
├── createdAt (Timestamp)
└── updatedAt (Timestamp)

InterviewSession
├── id (UUID, PK)
├── title (String)
├── intervieweeId (UUID, FK)
├── interviewerId (UUID, FK)
├── status (Enum: SCHEDULED, ONGOING, COMPLETED, CANCELED)
├── room (String)
├── token (String)
├── startedAt (Timestamp)
└── endedAt (Timestamp)

ScheduledInterview
├── id (UUID, PK)
├── intervieweeId (UUID, FK)
├── interviewerId (UUID, FK)
├── scheduledAt (Timestamp)
└── duration (Duration)

Environment Variables

Variable	Required	Description
`DB_URL`	Yes	PostgreSQL connection string
`DB_USER`	Yes	Database username
`DB_PWD`	Yes	Database password
`EUREKA_CLIENT_SERVICE_URL`	Yes	Eureka server URL
`REDIS_HOST`	Yes	Redis server hostname
`GEMINI_API_KEY`	Yes	Google Gemini API key
`LIVE_KIT_API_KEY`	For video	LiveKit API key
`LIVE_KIT_API_SECRET`	For video	LiveKit API secret
`CLOUDINARY_CLOUD_NAME`	For images	Cloudinary cloud name
`CLOUDINARY_API_KEY`	For images	Cloudinary API key
`CLOUDINARY_API_SECRET`	For images	Cloudinary API secret
`FLASK_API`	For processing	Flask processing service URL
`MAIL_PASSWORD`	For emails	Email service password

Deployment

Production Considerations

Service Registry: Deploy first and ensure it's accessible to all services
Database: Use managed PostgreSQL (AWS RDS, Azure Database, etc.)
Redis: Use managed Redis (Redis Cloud, AWS ElastiCache)
API Gateway: Configure SSL/TLS and rate limiting
Monitoring: Implement health checks and metrics collection

Render Deployment (Current)

The service registry is deployed at:

URL: https://service-registry-46p5.onrender.com

Individual services can be deployed to Render, AWS, or any cloud provider supporting Java applications.

Contributing

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add some amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

License

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

Support

For support, email codeetgo@gmail.com or open an issue in the repository.

Acknowledgments

Spring Boot and Spring Cloud teams for the excellent microservices framework
Google Gemini AI for powering intelligent question generation
LiveKit for real-time video infrastructure

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
flask-api		flask-api
interview-trainer-frontend		interview-trainer-frontend
interview-trainer		interview-trainer
.gitignore		.gitignore
README.md		README.md

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Interview Trainer Platform

Table of Contents

Overview

Key Features

For Interviewees

For Interviewers

AI & Automation

Architecture

Microservices

Technology Stack

Backend

Databases & Caching

AI & External Services

Communication

Infrastructure

Getting Started

Prerequisites

Installation

API Documentation

User Service API (/api/v1/user)

Interview Session API (/api/v1/session)

Database Schema

Core Entities

Environment Variables

Deployment

Production Considerations

Render Deployment (Current)

Contributing

License

Support

Acknowledgments

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User Service API (`/api/v1/user`)

Interview Session API (`/api/v1/session`)

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