Student Marks Analysis

Transcript Analyzer is a full-stack web app that extracts student marks from PDF transcripts, structures the data, and provides interactive analytics dashboards.

The project has:

• A Python Flask backend for PDF processing, parsing, and data APIs
• A student-facing frontend dashboard (frontend)
• An admin dashboard (admin-panel)

Screenshots

Upload Interface

Upload PDF transcripts with drag-and-drop functionality

Grade Analytics Dashboard

Comprehensive overview of academic performance

Performance Visualizations

Interactive charts showing GPA trends and subject performance

Quick Start

Prerequisites

• Python 3.11+
• uv package manager
• Node.js 20+ and npm

1) Run the backend

cd backend
uv sync
uv run python run.py

Backend starts on http://localhost:3000.

The backend reads configuration from backend/.env.

2) Run the student frontend (frontend)

cd frontend
npm install
npm run dev

3) Run the admin panel (admin-panel)

cd admin-panel
npm install
npm run dev

Use either frontend or admin-panel with the backend running.

Available Scripts

Frontend apps (frontend and admin-panel)

• npm run dev - Start Vite development server
• npm run build - Create production build
• npm run preview - Preview production build locally
• npm run lint - Run ESLint

Backend (backend)

• uv run python run.py - Start Flask server

Features

🔍 Smart OCR Processing

• Upload PDF transcripts and extract text content with high accuracy
• Preprocesses and cleans extracted text for optimal analysis

🤖 AI-Powered Grade Extraction

• Uses advanced LLMs to intelligently parse grade information
• Automatically identifies courses, credits, grades, and semester data

📈 Interactive Visualizations

• Subject performance breakdowns
• Grade distribution charts
• Leaderboard implementation

🧩 Data and API Layer

• AI-assisted table/header detection and structuring
• Student marks analytics and statistics endpoints