The most advanced AI-powered platform for job interview preparation, skill assessment, and career development

ChakriGO is a comprehensive, next-generation platform that revolutionizes career development through cutting-edge AI technologies. From AI-powered mock interviews with real-time voice interaction to advanced anti-cheating skill assessments, our platform provides everything needed for successful career advancement in the modern tech industry.

🔗 Live Platform: chakrigo.taut0logy.tech

Revolutionary voice-based interview preparation with advanced AI

• Real-time Voice Interviews: Conduct realistic practice interviews using Vapi's advanced voice AI technology
• Intelligent Question Generation: Dynamic question creation based on job role, experience level, and previous responses
• Natural Conversation Flow: AI adapts to candidate responses with contextual follow-up questions
• Multi-format Support: Technical, behavioral, situational, and role-specific interview types
• Instant Performance Analysis: Comprehensive scoring across communication, technical knowledge, and problem-solving
• Voice Pattern Analysis: Speech pace, clarity, and confidence metrics evaluation
• Interview History Tracking: Complete record of all practice sessions with progress analytics

Technical Implementation: Built with Google Gemini 1.5 Flash for intelligent conversation flow and Vapi Web SDK for real-time voice processing.

Enterprise-grade proctoring system with advanced security measures

• Computer Vision Monitoring: Face detection and eye-tracking using TensorFlow.js and MediaPipe Face Mesh
• Remote Desktop Detection: Advanced browser-based detection for Chrome Remote Desktop, TeamViewer, and RDP sessions
• Environment Analysis: Real-time detection of multiple monitors, screen sharing, and suspicious browser behavior
• Behavioral Analytics: Tab switching, window focus, and typing pattern analysis
• Biometric Verification: Facial recognition and identity verification throughout assessment
• Network Traffic Monitoring: Detection of unauthorized external communications
• Screen Recording Prevention: Watermarking and screenshot blocking mechanisms
• Real-time Alerts: Instant notifications for suspicious activities with automatic test termination

Technical Stack: Face-api.js for facial recognition, WebRTC for environment detection, custom algorithms for remote access detection.

Intelligent resume creation with ATS optimization

• Smart Template Engine: Industry-specific templates with ATS-friendly formatting
• AI Content Generation: Automatic bullet point suggestions based on job roles and achievements
• Keyword Optimization: Real-time ATS score calculation and keyword density analysis
• Dynamic Sections: Adaptive resume sections based on career level and industry
• Multi-format Export: PDF, Word, and plain text formats with consistent formatting
• Version Control: Track changes and maintain multiple resume versions
• Live Preview: Real-time preview with mobile-responsive design
• Integration Ready: Direct import from LinkedIn and other professional platforms

AI Engine: Google Gemini for intelligent content suggestions and job-specific optimization recommendations.

Comprehensive resume analysis with actionable insights

• Deep Content Analysis: Multi-modal AI processing of PDF documents using computer vision
• Job Fit Scoring: Semantic matching between resume content and job requirements
• ATS Compatibility Check: Formatting, keyword density, and parsing compatibility analysis
• Gap Analysis: Identification of missing skills, keywords, and experience areas
• Quantitative Assessment: Achievement quantification and impact statement evaluation
• Industry Benchmarking: Comparison against successful resumes in similar roles
• Improvement Roadmap: Step-by-step recommendations for resume enhancement
• Grammar & Style Review: Professional language assessment and style recommendations

Technical Implementation: Multi-modal Gemini 1.5 Flash for document analysis, custom NLP algorithms for semantic matching.

Personalized learning paths powered by LangGraph workflows

• AI-Driven Path Generation: Custom roadmaps created using advanced LangGraph orchestration
• Interactive Flow Visualization: React Flow-based tree structures with professional layouts
• Multi-stage Learning: Foundation → Core → Advanced → Projects → Career milestones
• Resource Integration: Curated learning resources, courses, and practical projects
• Progress Tracking: Milestone completion tracking with achievement badges
• Skill Dependencies: Intelligent prerequisite mapping and learning sequence optimization
• Industry Alignment: Roadmaps aligned with current market demands and salary expectations
• Community Integration: Peer progress sharing and collaborative learning paths

Architecture: LangGraph for workflow orchestration, React Flow for visualization, Firebase for progress persistence.

Mathematical animations and algorithm understanding

• Manim Integration: Professional-quality mathematical animations using Manim engine
• Prompt-to-Video: Natural language descriptions converted to educational animations
• Algorithm Library: Comprehensive collection of sorting, searching, and graph algorithms
• Step-by-step Breakdown: Detailed explanation of each algorithm step with visual representation
• Interactive Code Editor: Live code editing with syntax highlighting and execution
• Multiple Complexity Analysis: Time and space complexity visualization
• Export Capabilities: High-quality video export in multiple resolutions
• Educational Content: Complete explanations, use cases, and optimization techniques

Technical Stack: Manim for animation generation, Google Gemini for intelligent code generation, Python backend for video processing.

Comprehensive system architecture design and visualization

• PlantUML Integration: Professional system diagrams with industry-standard notation
• Interactive Diagram Creation: Real-time diagram generation from natural language descriptions
• Architecture Patterns: Implementation of microservices, monolith, and distributed system patterns
• Component Analysis: Detailed breakdown of system components and their relationships
• Scalability Assessment: Load balancing, caching, and performance optimization strategies
• D3.js Visualization: Interactive system diagrams with clickable components
• Best Practices: Industry-standard architectural patterns and design principles
• Interview Scenarios: Common system design questions with detailed solutions

Implementation: LangGraph for AI orchestration, PlantUML for diagram generation, D3.js for interactive visualizations.

Collaborative workspace with intelligent content generation

• Real-time Collaboration: Multi-user whiteboard with live synchronization using TLDraw
• AI Content Summarization: Computer vision analysis of whiteboard content with intelligent summaries
• Diagram Generation: Convert text prompts to Mermaid diagrams with live preview
• Smart Shape Recognition: Automatic conversion of hand-drawn shapes to professional diagrams
• Voice Commands: Voice-to-text integration for hands-free content creation
• Export Options: High-quality export to PDF, PNG, and SVG formats
• Template Library: Pre-built templates for system design, flowcharts, and mind maps
• Integration Ready: Seamless integration with other platform features

Technology: TLDraw for whiteboard functionality, Google Gemini Vision for content analysis, Mermaid.js for diagram rendering.

Professional networking and knowledge sharing ecosystem

• Developer Profiles: Comprehensive profiles with skills, projects, and achievements
• Knowledge Sharing: Technical articles, interview experiences, and career advice
• Company Insights: Employee reviews, interview processes, and salary information
• Mentorship Matching: AI-powered mentor-mentee pairing based on skills and goals
• Job Board Integration: Community-driven job postings with referral systems
• Skill Verification: Peer-verified skill assessments and endorsements
• Discussion Forums: Topic-based discussions with expert moderation
• Event Management: Virtual meetups, webinars, and networking events

Features: Real-time messaging, notification system, reputation scoring, content moderation.

Intelligent navigation and personalized assistance

• Contextual Understanding: Advanced NLP for understanding user intent and platform context
• Smart Navigation: Intelligent routing to relevant platform features and resources
• Personalized Recommendations: Career advice based on user profile and progress
• Multi-modal Interaction: Text, voice, and visual input processing
• Learning Integration: Integration with all platform features for seamless assistance
• Progress Tracking: Proactive suggestions based on user activity and goals
• 24/7 Availability: Always-on assistance with instant response times
• Multilingual Support: Communication in multiple languages with cultural adaptation

AI Engine: Advanced prompt engineering with Google Gemini, context-aware response generation.

Framework:           Next.js 15.2.4 (App Router)
Language:           TypeScript 5.0
Styling:            Tailwind CSS 4.0
UI Components:      Shadcn/ui + Radix UI
Animations:         Framer Motion
State Management:   React Hooks + Context API
Real-time:          Socket.io + Server-Sent Events

Runtime:            Node.js + Python (FastAPI)
AI Models:          Google Gemini 1.5 Flash
Voice Processing:   Vapi Web SDK
Computer Vision:    TensorFlow.js + MediaPipe
Animation Engine:   Manim (Mathematical Animation)
Workflow:           LangGraph for AI orchestration
Diagrams:           PlantUML + Mermaid.js

Primary Database:   Firebase Firestore
Authentication:     Firebase Auth
File Storage:       Firebase Storage
Real-time DB:       Firebase Realtime Database
Analytics:          Custom analytics with BigQuery

• Node.js 20+
• Python 3.11+ (for AI backend)
• npm/yarn package manager
• Firebase account
• Google AI API key
• Vapi AI API key

git clone https://github.com/yourusername/chakrigo.git
cd chakrigo

# Navigate to frontend directory
cd frontend

# Install dependencies
npm install

# Copy environment file
cp .env.example .env.local

Create frontend/.env.local with the following variables:

# Firebase Configuration
FIREBASE_PROJECT_ID=your_project_id
FIREBASE_PRIVATE_KEY="-----BEGIN PRIVATE KEY-----\n...\n-----END PRIVATE KEY-----\n"
FIREBASE_CLIENT_EMAIL=firebase-adminsdk-xxxxx@your-project.iam.gserviceaccount.com

# AI & Services
GOOGLE_GENERATIVE_AI_API_KEY=your_google_ai_key
NEXT_PUBLIC_VAPI_WEB_TOKEN=your_vapi_token
NEXT_PUBLIC_VAPI_WORKFLOW_ID=your_workflow_id

# External APIs
EXA_API_KEY=your_exa_key
JUDGE0_API_KEY=your_judge0_key
TAVILY_API_KEY=your_tavily_key

# Backend
FASTAPI_URL=http://localhost:8000

# Navigate to backend directory
cd fastapi

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Create environment file
cp .env.example .env

1. Create a Firebase project at Firebase Console
2. Enable Authentication, Firestore, and Storage
3. Download service account key
4. Update environment variables with Firebase config

Frontend:

cd frontend
npm run dev

Backend:

cd fastapi
uvicorn app:app --reload --port 8000

• Frontend: http://localhost:3000
• Backend API: http://localhost:8000
• API Docs: http://localhost:8000/docs

chakrigo/
├── frontend/                   # Next.js Frontend Application
│   ├── app/                   # Next.js 15 App Router
│   │   ├── (auth)/           # Authentication routes
│   │   ├── (root)/           # Main application routes
│   │   │   ├── dashboard/    # User dashboard
│   │   │   ├── interview-home/ # AI Interview system  
│   │   │   ├── resume-builder/ # Resume creation
│   │   │   ├── resume-analyzer/ # Resume analysis
│   │   │   ├── roadmap/      # Career roadmaps
│   │   │   ├── skill-assessment/ # Anti-cheating assessments
│   │   │   ├── algo-visualizer/ # Algorithm animations
│   │   │   ├── system-design/ # System design prep
│   │   │   ├── whiteboard/   # AI-powered whiteboard
│   │   │   └── career/       # Community platform
│   │   └── api/              # API routes
│   ├── components/           # Reusable UI components
│   │   ├── ui/              # Shadcn/ui components
│   │   ├── interview/       # Interview-specific components
│   │   ├── resume-builder/  # Resume builder components
│   │   ├── roadmap/         # Roadmap visualization
│   │   ├── skill-assessment/ # Assessment components
│   │   ├── ai-animation/    # Algorithm visualization
│   │   ├── system-design/   # System design tools
│   │   ├── whiteboard/      # Whiteboard components
│   │   └── career/          # Community components
│   ├── lib/                 # Utility libraries
│   │   ├── actions/         # Server actions
│   │   ├── hooks/           # Custom React hooks
│   │   └── utils/           # Helper functions
│   └── types/               # TypeScript definitions
├── fastapi/                 # Python Backend Services
│   ├── ai_animation/        # Manim animation engine
│   ├── roadmap_gen/         # LangGraph roadmap generation
│   ├── system_design/       # System design AI
│   └── app.py              # FastAPI main application
├── firebase/               # Firebase configuration
├── docs/                   # Documentation
└── README.md              # This file

• TypeScript for type safety
• ESLint + Prettier for code formatting
• Conventional Commits for commit messages
• Component-driven development with Storybook
• Testing with Jest and React Testing Library

# Create feature branch
git checkout -b feature/amazing-feature

# Make changes and commit
git add .
git commit -m "feat: add amazing feature"

# Push and create PR
git push origin feature/amazing-feature

• Page Load Speed: < 2 seconds
• AI Response Time: < 500ms for most operations
• Voice Latency: < 100ms round-trip time
• Database Queries: Optimized with proper indexing
• Image Processing: Efficient with WebP optimization
• Bundle Size: < 200KB gzipped for initial load

• JWT-based authentication with refresh tokens
• Rate limiting on all API endpoints
• Input validation and sanitization
• CORS protection with whitelisted origins
• Content Security Policy headers

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

• Google AI for Gemini models and cloud services
• Vapi for advanced voice AI technology
• Firebase for robust backend infrastructure
• Vercel for exceptional deployment platform
• TLDraw for collaborative whiteboard technology
• Manim for mathematical animation engine
• Open Source Community for amazing tools and libraries

• Live Platform: chakrigo.taut0logy.tech
• Documentation: docs.chakrigo.taut0logy.tech
• Issue Tracker: GitHub Issues
• Community Discord: Join our Discord
• Email Support: support@chakrigo.tech