??? LexiFeed - Full-Stack AI English Learning & Interview Platform

LexiFeed is a full-stack web application that helps users practice English interview and speaking skills using AI-driven question generation, voice transcription, smart resume processing, and session feedback.

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?? Key Features

• Secure auth with JWT-based login/signup.
• AI-powered interview question generation from company, role, and resume context.
• Voice transcription and analysis for spoken answers.
• Follow-up question generation based on candidate responses.
• Session feedback and progress stats saved per user.
• Modern frontend built with Next.js, TypeScript, Tailwind CSS.

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??? Technology Stack

Frontend

• Next.js 16.2 (App Router)
• TypeScript
• Tailwind CSS
• React
• Lucide icons
• React hooks + custom auth state

Backend

• Flask 3.x
• Flask-CORS
• Flask-SQLAlchemy
• SQLite
• OpenAI via openai and LangChain helpers
• JWT auth via custom Flask middleware
• Voice transcription + analysis routes

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?? Project Structure

LexiFeed/
+-- backend/
¦   +-- app.py
¦   +-- config.py
¦   +-- requirements.txt
¦   +-- models/
¦   +-- routes/
¦   +-- services/
¦   +-- utils/
+-- frontend/
    +-- app/
    +-- components/
    +-- lib/
    +-- hooks/
    +-- package.json

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?? Setup Guide

Prerequisites

• Python 3.8+
• Node.js 18+
• npm

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Backend Setup

1. Open a terminal and navigate to the backend folder:

   cd backend

2. Create and activate a virtual environment:

   • Windows PowerShell:

     python -m venv venv
     .\venv\Scripts\Activate.ps1

   • macOS/Linux:

     python -m venv venv
     source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Create a .env file inside backend/:

   SECRET_KEY=your_app_secret_key_here
   JWT_SECRET_KEY=your_jwt_secret_key_here
   DATABASE_URL=sqlite:///app.db
   OPENAI_API_KEY=your_openai_api_key_here

5. Start the backend server:

   python app.py

6. Verify the backend is running:

   http://localhost:5000
   

app.db is generated automatically when the backend starts.

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Frontend Setup

1. Open a separate terminal and go to the frontend folder:

   cd frontend

2. Install dependencies:

   npm install

3. Create a .env.local file in frontend/:

   NEXT_PUBLIC_API_URL=http://localhost:5000/api

4. Run the frontend:

   npm run dev

5. Open the app at:

   http://localhost:3000
   

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?? Authentication Flow

1. Sign up: POST /api/auth/signup
2. Login: POST /api/auth/login
3. Profile: GET /api/auth/me

The frontend stores the returned JWT token and sends it in the Authorization: Bearer <token> header for protected endpoints.

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?? Backend API Endpoints

Auth

• POST /api/auth/signup
• POST /api/auth/login
• GET /api/auth/me

Interview Workflows

• POST /api/interview/start
  • Starts a new interview session and returns AI-generated questions.
  • Supports multipart form data and optional resume upload.
• POST /api/interview/followup
  • Generates a follow-up question from the candidate answer.
• POST /api/interview/feedback
  • Saves interview transcript and returns AI feedback.
• GET /api/interview/sessions
  • Retrieves a user’s saved session history.
• GET /api/interview/stats
  • Returns aggregated progress metrics and streak data.

Legacy Interview / Resume Endpoints

• POST /api/interview/generate
• POST /api/interview/upload-resume

Voice Practice

• POST /api/voice/transcribe
• POST /api/voice/analyze
• POST /api/voice/followup
• POST /api/voice/analyze-agentic
• POST /api/voice/session-comparison

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?? Notes

• The frontend uses frontend/lib/api.ts for most interview-related API calls.
• Voice transcription and analysis occur from frontend/app/practice/interview/page.tsx.
• The backend CORS policy allows local development requests from http://localhost:3000 and http://localhost:5000.
• OPENAI_API_KEY is required for AI generation and voice analysis features.

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?? Core Dependencies

Backend

• Flask
• Flask-CORS
• Flask-SQLAlchemy
• python-dotenv
• PyJWT
• openai
• pdfplumber
• python-docx

Frontend

• Next.js
• React
• TypeScript
• Tailwind CSS
• react-hook-form
• zod
• lucide-react

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??? Troubleshooting

If the backend does not start

• Ensure the virtual environment is activated.
• Confirm requirements.txt installed correctly.
• Check .env includes OPENAI_API_KEY.

If the frontend cannot reach the API

• Verify the backend is running on port 5000.
• Confirm NEXT_PUBLIC_API_URL is http://localhost:5000/api.
• If CORS errors appear, review the allowed origins in backend/app.py.

Reset the database

cd backend
rm app.db
python app.py

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?? Contributing

Fork the repository, create a branch, implement your changes, and open a pull request with a clear description. Keep backend and frontend changes separate when possible.