richardorama commited on
Commit
ec929e1
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1 Parent(s): f1b2a26

Update app.py

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Files changed (1) hide show
  1. app.py +12 -9
app.py CHANGED
@@ -1,3 +1,6 @@
 
 
 
1
  #x = st.slider('Select a value')
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  #st.write(x, 'squared is', x * x)
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@@ -5,12 +8,15 @@ import streamlit as st
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  from transformers import pipeline
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  import ast
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  # Load the summarization model
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  #summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6") # smaller version of the model
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  summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
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  # Define the summarization function
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- def summarize(txt):
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  st.write('\n\n')
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  #st.write(txt[:100]) # Display the first 100 characters of the article
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  #st.write('--------------------------------------------------------------')
@@ -25,16 +31,13 @@ STATEMENT = st.sidebar.text_area('Enter Statement (String)', DEFAULT_STATEMENT,
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  if STATEMENT:
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  if st.sidebar.button('Summarize Statement'):
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  # Call your Summarize function here
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- #st.write(f"Summarizing: {STATEMENT}")
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- summarize(STATEMENT) # Directly pass the STATEMENT
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  else:
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  st.sidebar.button('Summarize Statement', disabled=True)
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  st.warning('πŸ‘ˆ Please enter Statement!')
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-
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- #################################
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-
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  # Initialize the sentiment analysis pipeline
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  # No model was supplied, defaulted to distilbert-base-uncased-finetuned-sst-2-english
@@ -48,7 +51,7 @@ def is_valid_list_string(string):
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  return False
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  # Define the summarization function
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- def analyze(txt):
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  st.write('\n\n')
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  #st.write(txt[:100]) # Display the first 100 characters of the article
@@ -76,7 +79,7 @@ SENTIMENT = st.sidebar.text_area('Enter Sentiment (String or List of Strings)',
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  # Enable the button only if there is text in the SENTIMENT variable
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  if SENTIMENT:
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  if st.sidebar.button('Analyze Sentiment'):
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- analyze(SENTIMENT) # Directly pass the SENTIMENT
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  else:
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- st.sidebar.button('Summarize Sentiment', disabled=True)
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  st.warning('πŸ‘ˆ Please enter Sentiment!')
 
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+ # Natural Language Tools
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+ # Richard Orama - September 2024
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+
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  #x = st.slider('Select a value')
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  #st.write(x, 'squared is', x * x)
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  from transformers import pipeline
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  import ast
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+
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+ ################ STATEMENT SUMMARIZATION #################
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+
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  # Load the summarization model
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  #summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6") # smaller version of the model
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  summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
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  # Define the summarization function
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+ def summarize_statement(txt):
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  st.write('\n\n')
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  #st.write(txt[:100]) # Display the first 100 characters of the article
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  #st.write('--------------------------------------------------------------')
 
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  if STATEMENT:
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  if st.sidebar.button('Summarize Statement'):
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  # Call your Summarize function here
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+ summarize_statement(STATEMENT) # Directly pass the STATEMENT
 
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  else:
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  st.sidebar.button('Summarize Statement', disabled=True)
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  st.warning('πŸ‘ˆ Please enter Statement!')
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+ ################ SENTIMENT ANALYSIS #################
 
 
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  # Initialize the sentiment analysis pipeline
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  # No model was supplied, defaulted to distilbert-base-uncased-finetuned-sst-2-english
 
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  return False
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  # Define the summarization function
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+ def analyze_sentiment(txt):
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  st.write('\n\n')
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  #st.write(txt[:100]) # Display the first 100 characters of the article
 
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  # Enable the button only if there is text in the SENTIMENT variable
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  if SENTIMENT:
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  if st.sidebar.button('Analyze Sentiment'):
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+ analyze_sentiment(SENTIMENT) # Directly pass the SENTIMENT
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  else:
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+ st.sidebar.button('Analyze Sentiment', disabled=True)
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  st.warning('πŸ‘ˆ Please enter Sentiment!')