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import gradio as gr | |
from textblob import TextBlob | |
# Sentiment Analysis Function | |
def sentiment_analysis(text: str) -> dict: | |
""" | |
Analyze the sentiment of the given text. | |
Args: | |
text (str): The text to analyze | |
Returns: | |
dict: A dictionary containing polarity, subjectivity and assessment | |
""" | |
# Create a TextBlob object | |
blob = TextBlob(text) | |
# Get the sentiment | |
sentiment = blob.sentiment | |
# Return the sentiment as a dictionary | |
# Polarity ranges from -1 (very negative sentiment ) to 1 (very positive sentiment) | |
# Subjectivity ranges from 0 (completely factual/objective) to 1 (completely opinionated/subjective) | |
return { | |
"polarity": sentiment.polarity, | |
"subjectivity": sentiment.subjectivity, | |
"assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral" | |
} | |
demo = gr.Interface( | |
fn=sentiment_analysis, | |
inputs=gr.Textbox(placeholder="Enter text to analyze..."), | |
outputs=gr.JSON(), | |
title="Text Sentiment Analysis", | |
description="Analyze the sentiment of the input text using TextBlob.", | |
examples=[ | |
["I love programming!"], | |
["This is the worst day ever."], | |
["It's okay, nothing special."] | |
] | |
) | |
if __name__ == "__main__": | |
demo.launch(mcp_server=True) | |