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import gradio as gr | |
from textblob import TextBlob | |
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 | |
""" | |
if not text.strip(): | |
return { | |
"polarity": 0.0, | |
"subjectivity": 0.0, | |
"assessment": "neutral" | |
} | |
blob = TextBlob(text) | |
sentiment = blob.sentiment | |
return { | |
"polarity": round(sentiment.polarity, 2), # -1 (negative) to 1 (positive) | |
"subjectivity": round(sentiment.subjectivity, 2), # 0 (objective) to 1 (subjective) | |
"assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral" | |
} | |
# Create the Gradio interface | |
demo = gr.Interface( | |
fn=sentiment_analysis, | |
inputs=gr.Textbox(placeholder="Enter text to analyze...", label="Text Input"), | |
outputs=gr.JSON(label="Sentiment Analysis Results"), | |
title="Text Sentiment Analysis", | |
description="Analyze the sentiment of text using TextBlob. Returns polarity (-1 to 1), subjectivity (0 to 1), and overall assessment.", | |
examples=[ | |
["I love this product! It's amazing!"], | |
["This is terrible and I hate it."], | |
["The weather is okay today."], | |
["Python is a programming language."] | |
] | |
) | |
# Launch the interface | |
if __name__ == "__main__": | |
demo.launch(mcp_server=True) # Make sure this is True |