prateekralhan/Deep-Question-Answering-System

A deep learning based Q&A system built using RoBerTa model from huggingface transformers

📄 Deep Question Answering

A simple Q&A webapp to process text built using RoBerTa Model from Huggingface Transformers 🤗.

Installation:

• Simply run the command pip install -r requirements.txt to install the dependencies.

Usage:

1. Clone this repository and install the dependencies as mentioned above.
2. Simply run the command:

streamlit run app.py

3. Navigate to http://localhost:8501 in your web-browser.
4. By default, streamlit allows us to upload files of max. 200MB. If you want to have more size for uploading documents, execute the command :

streamlit run app.py --server.maxUploadSize=1028

Results:

1. Perform Q&A on random text on the fly!

2. Upload your document (supports PDFs, Word Files, Text files) and perform Q&A:

Running the Dockerized App

1. Ensure you have Docker Installed and Setup in your OS (Windows/Mac/Linux). For detailed Instructions, please refer this.
2. Navigate to the folder where you have cloned this repository ( where the Dockerfile is present ).
3. Build the Docker Image (don't forget the dot!! 😄 ):

docker build -f Dockerfile -t app:latest .

4. Run the docker:

docker run -p 8501:8501 app:latest

This will launch the dockerized app. Navigate to http://localhost:8501/ in your browser to have a look at your application. You can check the status of your all available running dockers by:

docker ps