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| '''Hugging Face''' | |
| import streamlit as st | |
| from transformers import pipeline | |
| if __name__ == "__main__": | |
| # Define the title of the and its description | |
| st.title("Answering questions using NLP through Streamlit interface") | |
| st.write("Pose questions, get answers") | |
| # Load file | |
| raw_text = st.text_area(label="Enter a text here") | |
| if raw_text != None and raw_text != '': | |
| # Display text | |
| with st.expander("Show question"): | |
| st.write(raw_text) | |
| # Conduct question answering using the pipeline | |
| question_answerer = pipeline('question-answering') | |
| answer = '' | |
| question = st.text_input('Ask a question') | |
| if question != '' and raw_text != '': | |
| answer = question_answerer({ | |
| 'question': question, | |
| 'context': raw_text | |
| }) | |
| st.write(answer) | |