Spaces:
Runtime error
Runtime error
added sample file
Browse files- .ipynb_checkpoints/app-checkpoint.py +9 -2
- .ipynb_checkpoints/utils-checkpoint.py +2 -0
- app.py +9 -2
- sample.csv +2 -0
- tester.ipynb +0 -49
- utils.py +2 -0
.ipynb_checkpoints/app-checkpoint.py
CHANGED
@@ -12,14 +12,21 @@ if st.button('Click for predictions!'):
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result = get_single_prediction(feedback)
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st.success(f'Your text has been predicted to fall under the following topics: {result[:-1]}.
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st.write("\n")
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st.subheader('Or... Upload a csv file if you have
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st.write("\n")
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uploaded_file = st.file_uploader("Please upload a csv file with only 1 column of texts.")
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if uploaded_file is not None:
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with st.spinner('Generating predictions...'):
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result = get_single_prediction(feedback)
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st.success(f'Your text has been predicted to fall under the following topics: {result[:-1]}. The sentiment of this text is {result[-1]}.')
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st.write("\n")
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st.subheader('Or... Upload a csv file if you have a file instead.')
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st.write("\n")
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uploaded_file = st.file_uploader("Please upload a csv file with only 1 column of texts.")
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st.download_button(
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label="Download sample file here",
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data=sample_file,
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file_name='sample_results.csv',
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mime='text/csv',
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)
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if uploaded_file is not None:
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with st.spinner('Generating predictions...'):
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.ipynb_checkpoints/utils-checkpoint.py
CHANGED
@@ -18,6 +18,8 @@ labels = [
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'facilities', 'location', 'price'
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]
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def get_sentiment_label_facebook(list_of_sent_dicts):
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if list_of_sent_dicts['labels'][0] == 'negative':
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return 'negative'
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'facilities', 'location', 'price'
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]
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sample_file = pd.read_csv('sample.csv')
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def get_sentiment_label_facebook(list_of_sent_dicts):
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if list_of_sent_dicts['labels'][0] == 'negative':
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return 'negative'
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app.py
CHANGED
@@ -12,14 +12,21 @@ if st.button('Click for predictions!'):
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result = get_single_prediction(feedback)
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st.success(f'Your text has been predicted to fall under the following topics: {result[:-1]}.
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st.write("\n")
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st.subheader('Or... Upload a csv file if you have
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st.write("\n")
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uploaded_file = st.file_uploader("Please upload a csv file with only 1 column of texts.")
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if uploaded_file is not None:
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with st.spinner('Generating predictions...'):
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result = get_single_prediction(feedback)
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st.success(f'Your text has been predicted to fall under the following topics: {result[:-1]}. The sentiment of this text is {result[-1]}.')
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st.write("\n")
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st.subheader('Or... Upload a csv file if you have a file instead.')
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st.write("\n")
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uploaded_file = st.file_uploader("Please upload a csv file with only 1 column of texts.")
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st.download_button(
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label="Download sample file here",
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data=sample_file,
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file_name='sample_results.csv',
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mime='text/csv',
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)
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if uploaded_file is not None:
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with st.spinner('Generating predictions...'):
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sample.csv
ADDED
@@ -0,0 +1,2 @@
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sequence
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The website was user friendly and the agent provided good solutions
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tester.ipynb
DELETED
@@ -1,49 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "48c76726-b0a4-43e6-9f07-0199e0248d5e",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 39,
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"id": "bd2034e6-1187-4887-9ca7-8b9c0b5c9331",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1ac414f1-37dd-4642-867c-5520a16c1c86",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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utils.py
CHANGED
@@ -18,6 +18,8 @@ labels = [
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'facilities', 'location', 'price'
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]
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def get_sentiment_label_facebook(list_of_sent_dicts):
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if list_of_sent_dicts['labels'][0] == 'negative':
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return 'negative'
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'facilities', 'location', 'price'
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]
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sample_file = pd.read_csv('sample.csv')
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def get_sentiment_label_facebook(list_of_sent_dicts):
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if list_of_sent_dicts['labels'][0] == 'negative':
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return 'negative'
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