Lecture Summary -- SCREENSHOT BELOW 📸

A full-stack application that transforms YouTube lecture videos into concise, AI-generated summaries and transcriptions. The application leverages OpenAI's Whisper AI for accurate audio transcription and Groq's language models for intelligent summarization.

Overview

Lecture Summary is designed to help students, educators, and professionals quickly extract key insights from video lectures. The application handles the entire pipeline from video download to AI-powered summarization, providing both full transcriptions and concise summaries.

Tech Stack

Frontend

React - Modern UI library for building user interfaces
TypeScript - Type-safe JavaScript for better developer experience
Vite - Fast build tool and development server
React Router - Client-side routing
Tailwind CSS - Utility-first CSS framework for modern UI design

Backend

Spring Boot (Java) - Main application server handling job orchestration and persistence
FastAPI (Python) - Microservice for video processing and AI operations
PostgreSQL - Relational database for job and result storage
Maven - Build automation and dependency management

AI & Processing

Whisper AI - OpenAI's speech recognition model for audio transcription
Groq - High-performance language model API for text summarization
yt-dlp - YouTube video downloading library
FFmpeg - Audio extraction and processing

Architecture

The application follows a microservices architecture with three main components:

1. Frontend (React + Vite)

User interface for submitting YouTube URLs
Real-time job status monitoring with polling
Display of transcriptions and summaries
Responsive design with modern UI components

2. Spring Boot Backend

RESTful API for job management
Job queue system with status tracking (QUEUED, PROCESSING, COMPLETED, FAILED)
Scheduled job processor running every 10 seconds
PostgreSQL integration for data persistence
Communication bridge with Python worker service

3. Python Worker Service (FastAPI)

Video downloading using yt-dlp
Audio extraction from video files
Whisper AI transcription
Groq-powered summarization
RESTful API endpoint for job processing

Data Flow

User → Frontend → Spring Boot API → Job Queue (PostgreSQL)
                        ↓
                  Job Processor (Scheduled)
                        ↓
                Python Worker Service
                        ↓
            yt-dlp → Whisper AI → Groq
                        ↓
                PostgreSQL (Results)
                        ↓
                Frontend (Display)

Key Features

Core Functionality

YouTube Video Processing - Automatic download and audio extraction from any YouTube URL
AI Transcription - Highly accurate speech-to-text using Whisper AI
Smart Summarization - Context-aware summaries generated by Groq's LLaMA models
Job Queue System - Asynchronous processing with status tracking
Real-time Updates - Automatic polling for job status updates

User Experience

Modern UI Design - Clean, minimalistic interface with Tailwind CSS
Status Indicators - Color-coded job status badges (Queued, Processing, Completed, Failed)
Copy to Clipboard - One-click copying of summaries and transcriptions
Progress Tracking - Visual feedback during video processing
Error Handling - Comprehensive error messages and retry mechanisms

Technical Features

Microservices Architecture - Separation of concerns between API and processing layers
Database Persistence - All jobs and results stored in PostgreSQL
Scheduled Processing - Background job processor for asynchronous execution
RESTful APIs - Clean API design for frontend-backend communication
Type Safety - TypeScript on frontend, Pydantic models on backend

Installation

Prerequisites

Ensure you have the following installed:

Node.js (v16 or higher)
Java (JDK 17 or higher)
Python (3.8 or higher)
PostgreSQL (14 or higher)
Maven (3.6 or higher)
FFmpeg (for audio processing)

Environment Setup

Clone the repository

git clone <repository-url>
cd lectureSummary

Database Setup

Create a PostgreSQL database:
```
CREATE DATABASE lecture_summary;
```

Backend Configuration

Configure springboot-backend/src/main/resources/application.properties:

spring.datasource.url=jdbc:postgresql://localhost:5432/lecture_summary
spring.datasource.username=your_username
spring.datasource.password=your_password
spring.jpa.hibernate.ddl-auto=update
python.service.url=http://localhost:8001

Python Worker Setup

Create a virtual environment and install dependencies:

cd python-worker
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

Configure .env file in python-worker/:

GROQ_API_KEY=your_groq_api_key

Frontend Setup
```
cd frontend
npm install
```

Running the Application

You can use the provided startup scripts or run each component individually:

Option 1: Using Startup Script (Windows)

.\start.bat

Option 2: Using Startup Script (Linux/Mac)

chmod +x start.sh
./start.sh

Option 3: Manual Startup

Terminal 1 - Spring Boot Backend:

cd springboot-backend
mvn spring-boot:run

Terminal 2 - Python Worker:

cd python-worker
source venv/bin/activate  # On Windows: venv\Scripts\activate
python api.py

Terminal 3 - Frontend:

cd frontend
npm run dev

Accessing the Application

Frontend: http://localhost:5173
Spring Boot API: http://localhost:8080
Python Worker API: http://localhost:8001

Usage

Submitting a Video for Processing

Navigate to the home page
Enter a valid YouTube URL in the input field
Click "Generate Summary" button
You will be redirected to the jobs page

Viewing Job Status

On the jobs page, you can see all submitted jobs
Job statuses are color-coded:
- Blue: QUEUED - Waiting to be processed
- Yellow: PROCESSING - Currently being processed
- Green: COMPLETED - Successfully processed
- Red: FAILED - Processing failed
Click "View Details" to see the full results

Viewing Results

On the job details page, you can:

View the video title
Read the AI-generated summary
Access the full transcription
Copy summaries or transcriptions to clipboard
View the original YouTube video

Screenshots

Home Page

Main landing page with YouTube URL input and feature highlights

Jobs Overview

Table view showing all submitted jobs with status indicators

Job Details

Detailed view with AI-generated summary and full transcription

Project Structure

lectureSummary/
├── frontend/                    # React + Vite frontend
│   ├── src/
│   │   ├── pages/
│   │   │   ├── Home.tsx        # Landing page with URL submission
│   │   │   ├── Processing.tsx  # Jobs list view
│   │   │   └── JobDetails.tsx  # Individual job results
│   │   ├── App.tsx
│   │   └── main.tsx
│   └── package.json
│
├── springboot-backend/          # Spring Boot API server
│   ├── src/main/java/com/necharkc/lecturesummary/
│   │   ├── Job.java            # Job entity model
│   │   ├── JobRepository.java  # JPA repository
│   │   ├── JobController.java  # REST endpoints
│   │   ├── JobProcessorService.java    # Scheduled job processor
│   │   └── PythonApiService.java       # Python worker client
│   └── pom.xml
│
├── python-worker/               # FastAPI microservice
│   ├── api.py                  # Main FastAPI application
│   ├── services/
│   │   ├── download_service.py     # Video download (yt-dlp)
│   │   ├── whisper_service.py      # Audio transcription
│   │   └── summarize.py            # Text summarization (Groq)
│   └── requirements.txt
│
├── start.bat                   # Windows startup script
├── start.sh                    # Linux/Mac startup script
└── README.MD                   # This file

API Endpoints

Spring Boot Backend (Port 8080)

Submit a new job

POST /submission
Body: { "ytlink": "https://www.youtube.com/watch?v=..." }
Response: Job object with status QUEUED

Get all jobs

GET /jobs
Response: Array of Job objects

Get job details

GET /jobs/{jobId}/details
Response: Job object with full details

Python Worker (Port 8001)

Process video

POST /process
Body: { "job_id": "uuid", "video_url": "https://..." }
Response: { "success": true, "title": "...", "transcript": "...", "summary": "..." }

Database Schema

Job Table

id - UUID primary key
url - YouTube video URL
status - Job status (QUEUED, PROCESSING, COMPLETED, FAILED)
title - Video title
transcription - Full transcription
summary - AI-generated summary
error_message - Error details if failed
created_at- Job creation timestamp

Technologies & Libraries

Frontend Dependencies

react
react-dom
react-router-dom
typescript
vite
tailwindcss

Backend Dependencies (Maven)

spring-boot-starter-web
spring-boot-starter-data-jpa
postgresql
lombok

Python Dependencies

fastapi
uvicorn
yt-dlp
openai-whisper
groq
pydantic
python-dotenv

License

This project is licensed under the MIT License.

Name		Name	Last commit message	Last commit date
Latest commit History 46 Commits
lectureSummary		lectureSummary
.gitattributes		.gitattributes
.gitignore		.gitignore
README.MD		README.MD
home.png		home.png
processing.png		processing.png
result.png		result.png

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