This "Grade Guru :-The AI Examiner," allows teachers to analyze student answers using AI. It provides a user-friendly interface to upload images of student answers, input the extracted text, compare it with the teacher's answer, and evaluate the result.
- Upload Student Answer Photo: Upload an image of the student's answer.
- Enter Student Answer Text: Enter the extracted text from the uploaded image.
- Enter Teacher's Answer: Input the correct answer from the teacher.
- Total Marks of Question: Enter the total marks for the question.
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Clone the repository:
git clone https://github.com/DhruvTyagi18/Grade-Guru.git cd Grade-Guru -
Environment Setup:
- Create .env file in /ai_search_ui directory of project
- Replace .env content with
HF_TOKEN=YOUR_HF_API_TOKEN- How to get your hf token for free
- Log in to huggingface
- Go to Profie > then go to Setttings > then go to Access Tokens tab
- Access Tokens Page
- If there exists Access Token then copy it and paste it as HF_TOKEN in .env file of project
- If Access Token does not exist then click on new token Write the "Name of Token" and Select the "Type of Token" (Read / Write) Access.
- After creating copy the token and paste it as HF_TOKEN in .env file of project.
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Running the AI Examiner:
- Create Virtual Enviornment & Install Dependencies
- For windows ( git bash )
python -m venv .venv source .venv/Scripts/activate pip install -r requirements.txt - For windows ( cmd )
python -m venv .venv .venv\Scripts\activate pip install -r requirements.txt
- For Linux & Mac
python -m venv .venv souce .venv/bin/activate pip install -r requirements.txt
- Run the Streamlit app:
streamlit run app.py
- Access the UI in your browser at
localhost:8501(default Streamlit address).
- app.py: Contains the main Streamlit application.
- LLM.py: Module for performing inference on student and teacher answers.
- util.py: Utility functions for writing evaluation results.
- trans.py: Module for text-to-speech functionality.