A Flask web application that is designed for answering questions based on the context from the PDFs. It uses the mistralai/Mistral-7B-Instruct-v0.1 model as the large language model (LLM) and the hkunlp/instructor-xl model for embedding text representations.

• Clone this repository:

  git clone https://github.com/sameemul-haque/KTUGPT-Python.git
  

• After cloning the repository, navigate into the KTUGPT-Python directory

  cd KTUGPT-Python
  

• Set up a Python virtual environment:

  python -m venv venv
  

• Activate the virtual environment:

  • GNU/Linux | MacOS:

    source venv/bin/activate
    

  • Windows:

    venv\Scripts\activate
    

• Install dependencies:

  pip install -r requirements.txt
  

6. Create a .env file based on .env.example and add your Hugging Face API token and MongoDB Connection String

• Run the app:

  python app.py 
  

Once the Flask app is running, you can send POST requests to http://127.0.0.1:5000 with a query parameter q containing your question. The app will return an answer based on the configured language model and retrieval method. For example, http://127.0.0.1:5000/?q=what%20is%20operating%20system?