📚 Syllabus Progress Tracker

An AI-powered web application to help students effortlessly track their academic progress.

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✨ Features

• Intelligent Syllabus Analysis: Upload your syllabus PDF, and the app uses the Gemini AI API to automatically parse and break down the content into modules and topics.
• Dynamic Progress Tracking: Visually monitor your progress with intuitive dashboards and graphs. Mark topics as complete and see your overall progress update in real-time.
• AI-Powered Study Assistant: Get personalized insights and assistance powered by Gemini 1.5 Flash:
  • Syllabus DNA: A unique radar chart that analyzes the syllabus and shows its composition in terms of difficulty, numerics, diagrams, and theoretical concepts.
  • Upcoming Topic Analysis: The AI provides a brief, encouraging analysis of your next uncompleted topics.
  • Practice Question Generation: Generate relevant practice questions for any topic to test your understanding.
  • AI Chat Tutor: A conversational assistant that can answer questions based only on the content of your uploaded syllabus.
• Personalized Profile: Create and manage your user profile, academic details, and track your progress across multiple subjects and semesters.
• Intuitive UI: A clean, responsive interface with a toggle for dark and light themes for a comfortable user experience.

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🚀 Live Demo

Experience the app live in both its dark and light themes.

• Dark Theme: https://syllabus-progress-with-gemini.streamlit.app/?embed_options=dark_theme
• Light Theme: https://syllabus-progress-with-gemini.streamlit.app/?embed_options=light_theme

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📸 Screenshots

Profile Page with Syllabus Setup	Dashboard with Syllabus DNA

AI-Powered Recommendations	Topic Progress Tracking

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🛠️ Getting Started

Prerequisites

• Python 3.9+
• A Google AI Studio API Key

Installation

1. Clone the repository:

   git clone [https://github.com/titan-spyer/syllabus-progress.git](https://github.com/titan-spyer/syllabus-progress.git)
   cd syllabus-progress

2. Create and activate a virtual environment:

   python -m venv venv
   # On Windows
   venv\Scripts\activate
   # On macOS/Linux
   source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Set up your environment variables: Create a file named .env in the root directory and add your Google AI Studio API key.

   GOOGLE_API_KEY="YOUR_API_KEY_HERE"

Running the App

Run the following command in your terminal to start the Streamlit application:

streamlit run streamlit_app.py