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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 |