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#x = st.slider('Select a value')
#st.write(x, 'squared is', x * x)
import streamlit as st
from transformers import pipeline
import ast
# Load the summarization model
#summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6") # smaller version of the model
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
# Default article text
# DEFAULT_ARTICLE = """ New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County, New York.
# A year later, she got married again in Westchester County, but to a different man and without divorcing her first husband.
# Only 18 days after that marriage, she got hitched yet again. Then, Barrientos declared "I do" five more times, sometimes only within two weeks of each other.
# In 2010, she married once more, this time in the Bronx. In an application for a marriage license, she stated it was her "first and only" marriage.
# Barrientos, now 39, is facing two criminal counts of "offering a false instrument for filing in the first degree," referring to her false statements on the
# 2010 marriage license application, according to court documents.
# """
DEFAULT_ARTICLE = ""
# Create a text area for user input
ARTICLE = st.sidebar.text_area('Enter Article (String)', DEFAULT_ARTICLE, height=150)
# Define the summarization function
def summarize(txt):
st.write('\n\n')
st.write(txt[:100]) # Display the first 100 characters of the article
st.write('--------------------------------------------------------------')
summary = summarizer(txt, max_length=130, min_length=30, do_sample=False)
st.write(summary[0]['summary_text'])
# Create a button and trigger the summarize function when clicked
if st.sidebar.button('Summarize Article'):
summarize(ARTICLE)
else:
st.warning('π Please enter Article!')
#################################
# Initialize the sentiment analysis pipeline
# No model was supplied, defaulted to distilbert-base-uncased-finetuned-sst-2-english
sentiment_pipeline = pipeline("sentiment-analysis")
# Default article text
# DEFAULT_SENTIMENT = """[
# "I'm so happy today!",
# "This is the worst experience ever.",
# "It's a decent product, nothing special."
# ]"""
# DEFAULT_SENTIMENT = "I'm so happy today!"
def is_valid_list_string(string):
try:
result = ast.literal_eval(string)
return isinstance(result, list)
except (ValueError, SyntaxError):
return False
# Define the summarization function
def analyze(txt):
st.write('\n\n')
#st.write(txt[:100]) # Display the first 100 characters of the article
st.write('--------------------------------------------------------------')
# Display the results
#if type(txt_converted) == 'list':
#if isinstance(txt_converted, list):
if is_valid_list_string(txt):
txt_converted = ast.literal_eval(txt) #convert string to actual content, e.g. list
# Perform Hugging sentiment analysis on multiple texts
results = sentiment_pipeline(txt_converted)
for i, text in enumerate(txt_converted):
st.write(f"Text: {text}")
st.write(f"Sentiment: {results[i]['label']}, Score: {results[i]['score']:.2f}\n")
else:
# Perform Hugging sentiment analysis on multiple texts
results = sentiment_pipeline(txt)
st.write(f"Text: {txt}")
st.write(f"Sentiment: {results[0]['label']}, Score: {results[0]['score']:.2f}\n")
DEFAULT_SENTIMENT = ""
# Create a text area for user input
SENTIMENT = st.sidebar.text_area('Enter Sentiment (String or List of Strings)', DEFAULT_SENTIMENT, height=150)
# Enable the button only if there is text in the SENTIMENT variable
if SENTIMENT:
if st.sidebar.button('Analyze Sentiment'):
# Call your Analyze function here
#st.write(f"Summarizing: {SENTIMENT}")
analyze(SENTIMENT) # Directly pass the SENTIMENT
else:
st.sidebar.button('Summarize Sentiment', disabled=True)
st.warning('π Please enter Sentiment!')
# # Create a button and trigger the summarize function when clicked
# if st.sidebar.button('Summarize Sentiment'):
# #ast.literal_eval() is a function in Python that safely evaluates a string containing a valid Python expression,
# #such as lists, dictionaries, tuples, sets, integers, and floats. It parses the string and returns the corresponding
# #Python object, without executing any arbitrary code, which makes it safer than using eval().
# #summarize(str(SENTIMENT)) #explicitly change SENTIMENT to string so that even when ypu provide unquoted string, it still works
# analyze(SENTIMENT) # Directly pass the SENTIMENT
# else:
# st.warning('π Please enter Sentiment!') |