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📚 Flask web service that is designed for answering questions based on the context from the textbook PDFs • Python, Flask, LLM, Embeddings

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title emoji colorFrom colorTo sdk sdk_version app_file pinned license
KTUGPT
📚
blue
purple
gradio
4.28.3
app.py
false
mit

KTUGPT-Python

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.

Setup

  • 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
    
  1. 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 
    

Usage

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?

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📚 Flask web service that is designed for answering questions based on the context from the textbook PDFs • Python, Flask, LLM, Embeddings

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