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.
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Clone this repository:
git clone https://github.com/sameemul-haque/ktugpt-python.git
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After cloning the repository, navigate into the ktugpt-python directory
cd ktugpt-python
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Set up a Python virtual environment:
python -m venv venv
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Activate the virtual environment:
- GNU/Linux | MacOS:
source venv/bin/activate
- Windows:
venv\Scripts\activate
- GNU/Linux | MacOS:
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Install dependencies:
pip install -r requirements.txt
- Create a
.env
file based on.env.example
and add your Hugging Face API token.
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Run the Flask web app:
flask run --app app --host=0.0.0.0
Once the Flask app is running, you can send GET 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?