⚡ Bit-Interview — Next-Gen AI Technical Interview Simulator

"Practice like it's real."

An production-grade, stateful AI interview platform featuring adaptive LangGraph agent workflows, real-time voice interaction, Monaco coding sandbox with Judge0 execution, PDF resume extraction, ATS Job Description matching, and proctored session analytics.

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📸 Product Interface Showcase

1️⃣ Next-Gen AI Landing & 3D Interactive Showcase

2️⃣ Candidate Portal Authentication Gateway

3️⃣ Candidate Readiness & Progress Dashboard

4️⃣ Stateful Session Setup Wizard

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🛠️ Complete Technical Architecture

Layer	Technology	Purpose & Implementation
Frontend Framework	React 19 + Vite 8	High-performance SPA with fast hot-module replacement
Styling & Design System	Tailwind CSS 4	Custom Light Mode design system with Indigo/Violet gradients
Animations	Framer Motion	Micro-interactions, slide transitions, and glowing badges
Iconography	Lucide React	Clean, modern SVG UI icons
Routing	React Router 6	Client-side view router with protected user session guards
Analytics Charts	Recharts	Skill Proficiency Radar & Readiness Trajectory graphs
In-Browser IDE	Monaco Editor	VS-Code powered code editor for live coding rounds
Backend Framework	Python 3.11 + FastAPI	Asynchronous high-throughput REST API & WebSockets server
AI Agent Orchestration	LangGraph + LangChain	Stateful adaptive interviewer workflow DAG & decision engine
LLM Engine	Gemini 2.5 Pro / OpenAI	Question generation, code evaluation, & evidence feedback
NLP Processing	HuggingFace Transformers	Text classification & semantic response evaluation
Embeddings	Sentence Transformers	Semantic similarity matching between Resume and JD
Machine Learning Analytics	Scikit-learn	Candidate readiness trajectory scoring & anomaly analytics
Primary Database	MongoDB / MongoDB Atlas	Persistence for Users, Resumes, Sessions, Reports & Transcripts
Database Driver	PyMongo / Motor	Async Python database driver for high concurrency
Session Cache	Redis / Redis Cloud	Sub-millisecond live interview buffer & WebSocket state cache
Real-time Engine	WebSockets / Socket.IO	Low-latency live interview streaming events
Speech Input	Web Speech API → Whisper	Speech-to-text transcript generation with voice activity
Voice Output	SpeechSynthesis → TTS Provider	Natural AI voice question narration with speed selector
Code Execution Sandbox	Judge0	Isolated remote execution engine for Python, JS, C++, Java
Document Intelligence	PyMuPDF (fitz)	Layout-aware PDF resume text and structure parser
Authentication & Security	JWT + Passlib (bcrypt)	Secure token session handling and password hashing
API Client	Axios	Intercepted HTTP request client for REST endpoints

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🏗️ System Architecture Diagram

                               +-----------------------------------+
                               |       React 19 + Vite Frontend    |
                               | (Monaco IDE, Speech, Recharts UI) |
                               +-----------------------------------+
                                                 |
                                     REST APIs / WebSockets
                                                 |
                                                 v
                               +-----------------------------------+
                               |       FastAPI Async Gateway       |
                               |    (Authentication & Gateways)    |
                               +-----------------------------------+
                                    /            |            \
                                   /             |             \
                                  v              v              v
      +-------------------------------+   +-------------+   +-------------------+
      |      LangGraph AI Engine      |   |   Judge0    |   | PyMuPDF Document  |
      |  (Stateful Adaptive Agent)    |   | Execution   |   | PDF Resume Parser |
      +-------------------------------+   +-------------+   +-------------------+
          /          |          \                |                    |
         v           v           v               v                    v
  +-----------+ +--------+ +-----------+   +-----------+    +-------------------+
  | Question  | | Eval   | |  Decision |   | Sandboxed |    | Candidate Profile |
  |   Agent   | | Agent  | |   Engine  |   | Code Run  |    |  & Skill Cloud    |
  +-----------+ +--------+ +-----------+   +-----------+    +-------------------+
        \            |           /               
         +-----------+-----------+               
                     |                           
                     v                           
           +--------------------+                
           | Redis Live State   |                
           |  Session Buffer    |                
           +--------------------+                
                     |                           
                     v                           
        +--------------------------+             
        |  MongoDB Atlas Database  |             
        +--------------------------+             

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🧠 LangGraph Adaptive Interview Workflow

Bit-Interview uses a stateful LangGraph Agent Network to ensure the interviewer acts as an experienced lead engineer rather than a simple Q&A bot.

graph TD
    A[START: Initialize Session] --> B[Load Candidate Resume & Target JD Context]
    B --> C[Create Adaptive Interview Plan]
    C --> D[Generate Tailored Question]
    D --> E[Deliver via Voice TTS & Live UI]
    E --> F[Receive Candidate Answer / Speech / Code]
    F --> G[Evaluate Technical Accuracy & Clarity]
    G --> H{LangGraph Decision Engine}
    H -->|Insufficient Depth| I[Trigger Interruption / Hint]
    H -->|Strong Answer| J[Increase Difficulty Level]
    H -->|Vague / Edge Case Missing| K[Ask Specific Follow-Up]
    H -->|Round Complete| L[Generate Evidence Report]
    I --> D
    J --> D
    K --> D
    L --> M[END: Save Scorecard to MongoDB]

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🎯 Adaptive Decision Signals

1. Silence / Delay Interruption: Triggers "Would you like to walk me through your current thinking?" when candidate stays silent.
2. Rambling Interruption: Triggers concise redirection when candidate response exceeds optimal brevity thresholds.
3. Vague Answer Challenge: Identifies missing edge cases or hand-waving and requests concrete code/architectural trade-offs.

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🌟 Core Features & Modules

🎙️ 1. Adaptive AI Live Room

• Real-Time Voice Narration: Auto-voice readout with customizable speed selector (0.85x - 1.5x) and Speech-to-Text transcript recorder.
• Monaco Editor Integration: In-browser coding environment supporting JavaScript, Python, C++, and Go with instant execution feedback via Judge0.
• Dynamic Difficulty Scaling: Live difficulty meter tracking real-time difficulty levels (Easy → Medium → Hard → Advanced).

📄 2. Resume Intelligence Hub

• PyMuPDF Extraction: Extracts structured skills, project portfolios, work experience, and educational background from PDF uploads.
• Context-Aware Interviewing: AI asks deep-dive questions targeting actual projects, frameworks, and architecture choices listed on candidate's resume.

🎯 3. ATS Job Description Matcher

• Semantic Resume-to-JD Matching: Compares candidate background with target company JDs (e.g. Stripe, Vercel, Meta) using Sentence Transformers.
• ATS Resume Bullet Generator: Generates high-impact accomplishment bullets tailored for applicant tracking systems.

🛡️ 4. AI Anti-Cheat & Proctoring Engine

• Browser Integrity Monitoring: Logs tab switches, window blur events, and focus loss during live sessions.
• Webcam Proctoring: Optional video preview calculating a real-time Session Integrity Score %.

📊 5. Comprehensive Diagnostic Reports

• Category Breakdown: Evaluates Technical Depth, Coding Accuracy, Problem Solving, Communication, and System Architecture.
• Evidence-Based Feedback: Links actionable recommendations directly to transcript timestamps.
• 7-Day Technical Study Roadmap: Customized daily plan to strengthen detected skill gaps.

💼 6. Employer & Recruiter Portal

• Candidate Leaderboard: Rank applicants across tracks with integrity flags and diagnostic scorecards.
• Talent Pipeline Tracker: Manage candidates by active Job Description assessments.

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📁 Project Directory Structure

interview/
├── README.md                           # Master Project Documentation
└── intervue-ai/
    ├── docs/
    │   └── images/                     # Screenshots & Diagrams
    │       ├── landing_hero_cartoon.png
    │       ├── candidate_login.png
    │       ├── candidate_dashboard.png
    │       └── setup_wizard.png
    │
    ├── frontend/                       # React 19 + Vite Frontend
    │   ├── src/
    │   │   ├── components/
    │   │   │   ├── DashboardNavbar.jsx         # Frosted Light Mode Navbar
    │   │   │   ├── VoiceInterviewerControls.jsx# Speech-to-Text & Narration
    │   │   │   ├── MonacoCodeEditor.jsx        # In-browser Code IDE
    │   │   │   ├── ProctoringWidget.jsx        # Anti-Cheat Audit Monitor
    │   │   │   └── AnalyticsCharts.jsx         # Radar & Trajectory Visualizers
    │   │   ├── pages/
    │   │   │   ├── DashboardPage.jsx           # Candidate Control Center
    │   │   │   ├── InterviewPage.jsx           # Live Adaptive AI Room
    │   │   │   ├── ResumePage.jsx              # Resume Intelligence Hub
    │   │   │   ├── JDAnalyzerPage.jsx          # ATS Resume & JD Matcher
    │   │   │   ├── InterviewReportPage.jsx     # Diagnostic Scorecard Report
    │   │   │   └── RecruiterDashboardPage.jsx  # Employer Leaderboard
    │   │   ├── index.css                       # Tailwind Design System Tokens
    │   │   └── App.jsx                         # Main Router Setup
    │   └── package.json
    │
    └── backend/                        # FastAPI + LangGraph Backend
        ├── app/
        │   ├── main.py                     # API Application Entrypoint
        │   ├── routes/                     # Interview, Resume, JD & Recruiter Endpoints
        │   ├── services/                   # LangGraph Agent, PyMuPDF & LLM Services
        │   ├── core/                       # Security, JWT & Config Setup
        │   └── models/                     # MongoDB Pydantic Data Models
        ├── requirements.txt
        └── .env.example

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⚡ Local Setup & Installation

Prerequisites

• Node.js: v18+
• Python: v3.11+
• MongoDB: Local instance or MongoDB Atlas URI
• Redis: Local server or Redis Cloud instance

1. Environment Configuration

Create backend/.env file:

MONGODB_URI=mongodb+srv://<username>:<password>@cluster0.mongodb.net/bit_interview
JWT_SECRET=your_super_secret_jwt_key_here
REDIS_URL=redis://localhost:6379
GEMINI_API_KEY=your_gemini_api_key_here
OPENAI_API_KEY=your_openai_api_key_here
JUDGE0_URL=https://judge0-ce.p.rapidapi.com
CORS_ORIGIN=http://localhost:5173

2. Backend Installation & Launch

cd intervue-ai/backend

# Create virtual environment
python -m venv venv

# Activate virtual environment
# Windows:
.\venv\Scripts\activate
# Linux/macOS:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Start FastAPI server
uvicorn app.main:app --reload --port 8000

Backend API will be running live at http://localhost:8000.

3. Frontend Installation & Launch

cd intervue-ai/frontend

# Install dependencies
npm install

# Start Vite dev server
npm run dev

Frontend Web Application will be live at http://localhost:5173.

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📄 License & Attribution

Distributed under the MIT License. See LICENSE for more information.

_{Built with ❤️ by Khushal Kumar • Powered by LangGraph, FastAPI, React 19 & Gemini AI}