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Update app.py
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app.py
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@@ -5,9 +5,6 @@ from flair.models import TextClassifier
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from flair.data import Sentence
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import matplotlib.pyplot as plt
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# Load Flair model outside the function
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classifier = TextClassifier.load('en-sentiment')
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# Function to perform sentiment analysis using TextBlob model
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def textblob_sentiment(text):
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blob = TextBlob(text)
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@@ -21,6 +18,7 @@ def vader_sentiment(text):
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# Function to perform sentiment analysis using Flair model
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def flair_sentiment(text):
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sentence = Sentence(text)
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classifier.predict(sentence)
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if sentence.labels[0].value == 'POSITIVE':
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@@ -51,5 +49,4 @@ fig, ax = plt.subplots()
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ax.bar(['TextBlob', 'VADER', 'Flair'], [textblob_score, vader_score, flair_score])
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ax.axhline(y=0, color='gray', linestyle='--')
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ax.set_title('Sentiment Scores')
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st.pyplot(fig)
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plt.close(fig) # Close the figure to prevent memory leaks
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from flair.data import Sentence
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import matplotlib.pyplot as plt
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# Function to perform sentiment analysis using TextBlob model
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def textblob_sentiment(text):
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blob = TextBlob(text)
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# Function to perform sentiment analysis using Flair model
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def flair_sentiment(text):
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classifier = TextClassifier.load('en-sentiment')
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sentence = Sentence(text)
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classifier.predict(sentence)
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if sentence.labels[0].value == 'POSITIVE':
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ax.bar(['TextBlob', 'VADER', 'Flair'], [textblob_score, vader_score, flair_score])
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ax.axhline(y=0, color='gray', linestyle='--')
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ax.set_title('Sentiment Scores')
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st.pyplot(fig)
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