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AceTrackAI - A Student Feedback Generator

AceTrackAI is an AI-powered tool designed to evaluate student responses to historical questions and provide constructive, context-aware feedback. Developed using T5 transformers, the project automates the assessment process, offering actionable insights to students and instructors.

Features

  • Upload PDF Exams: Upload scanned exam papers directly for evaluation.
  • Automated Parsing: Extracts questions, responses, and reference answers from the uploaded documents.
  • AI-Powered Feedback: Generates accurate feedback based on predefined correct answers using a fine-tuned T5 model.
  • User-Friendly Interface: Built with Streamlit, ensuring simplicity and accessibility.

Installation

  1. Clone the repository:

    git clone https://github.com/Abmstpha/AceTrackAI.git
cd AceTrackAI

  2. Create a virtual environment:

    python -m venv venv
source venv/bin/activate  # For Windows: venv\Scripts\activate

  3. Install dependencies:

    pip install -r requirements.txt

  4. Ensure the sentencepiece library is installed for T5 tokenizer compatibility:

    pip install sentencepiece

Usage

  1. Prepare the Model Weights: The repository does not include .pt files due to size constraints. Please download the model weights separately and place them in the appropriate directory.

  2. Start the backend:

    python app.py

  3. Start the frontend:

    streamlit run frontend.py

  4. Access the application: Open your browser and navigate to http://localhost:8501.

  5. Upload a PDF of the exam and view the AI-generated feedback.

Project Structure

AceTrack/
├── app.py                 # Backend script
├── frontend.py           # Frontend script
├── requirements.txt      # List of dependencies 
├── model weights (PT file not included due to size) 
├── AceTrack_T5_weights/  # Directory for 
│   ├── special_tokens_map.json
│   ├── tokenizer_config.json
│   ├── spiece.model
│   └── added_tokens.json
└── README.md             # This README file