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import streamlit as st | |
from utils import * | |
########## Title for the Web App ########## | |
st.title("Text Classification for Service Feedback") | |
########## Create Input field ########## | |
feedback = st.text_input('Type your text here', 'The website was user friendly and the agent provided good solutions') | |
if st.button('Click for predictions!'): | |
with st.spinner('Generating predictions...'): | |
result = get_single_prediction(feedback) | |
st.success(f'Your text has been predicted to fall under the following topics: {result[:-1]}. The sentiment of this text is {result[-1]}.') | |
st.write("\n") | |
st.subheader('Or... Upload a csv file if you have a file instead.') | |
st.write("\n") | |
uploaded_file = st.file_uploader("Please upload a csv file with only 1 column of texts.") | |
st.download_button( | |
label="Download sample file here", | |
data=sample_file, | |
file_name='sample_results.csv', | |
mime='text/csv', | |
) | |
if uploaded_file is not None: | |
with st.spinner('Generating predictions...'): | |
results = get_multiple_predictions(uploaded_file) | |
st.download_button( | |
label="Download results as CSV", | |
data=results, | |
file_name='results.csv', | |
mime='text/csv', | |
) | |