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import gradio as gr | |
from textblob import TextBlob | |
def sentiment_analysis(text: str) -> dict: | |
""" | |
Analyzes the sentiment of the given text using TextBlob | |
Args: | |
text (str): The text to analyze | |
Returns: | |
dict: A dictionary containing text polarity (from -1.0 = negative to 1.0 = positive), text subjectivity (from 0 = very objective to 1 = very subjective), and overall assessment | |
""" | |
blob = TextBlob(text) | |
sentiment = blob.sentiment | |
return { | |
"polarity": round(sentiment.polarity, 2), | |
"subjectivity": round(sentiment.subjectivity, 2), | |
"assessment": ( | |
"positive" | |
if sentiment.polarity > 0.1 | |
else "negative" if sentiment.polarity < -0.1 else "neutral" | |
), | |
} | |
demo = gr.Interface( | |
fn=sentiment_analysis, | |
inputs=gr.Textbox(placeholder="Enter text to analyze..."), | |
outputs=gr.JSON(), | |
title="MCP Text Sentiment Analysis Demo", | |
description="Analyze the sentiment of a text using TextBlob, on an MCP server", | |
) | |
if __name__ == "__main__": | |
demo.launch(mcp_server=True) | |