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Download app.py from cormak/mcp-sentiment: direct link, hf CLI and curl.
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https://huggingface.co/spaces/cormak/mcp-sentiment/resolve/main/app.py
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hf download hf://spaces/cormak/mcp-sentiment/app.py
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curl -L -o app.py https://huggingface.co/spaces/cormak/mcp-sentiment/resolve/main/app.py
1.12 kB
| import json | |
| import gradio as gr | |
| from textblob import TextBlob | |
| def sentiment_analysis(text: str) -> str: | |
| """ | |
| Analyze the sentiment of the given text. | |
| Args: | |
| text (str): The text to analyze | |
| Returns: | |
| str: A JSON string containing polarity, subjectivity, and assessment | |
| """ | |
| blob = TextBlob(text) | |
| sentiment = blob.sentiment | |
| result = { | |
| "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" | |
| } | |
| return json.dumps(result) | |
| # Create the Gradio interface | |
| demo = gr.Interface( | |
| fn=sentiment_analysis, | |
| inputs=gr.Textbox(placeholder="Enter text to analyze..."), | |
| outputs=gr.Textbox(), # Changed from gr.JSON() to gr.Textbox() | |
| title="Text Sentiment Analysis", | |
| description="Analyze the sentiment of text using TextBlob" | |
| ) | |
| # Launch the interface and MCP server | |
| if __name__ == "__main__": | |
| demo.launch(mcp_server=True) |