Initial commit: Sentiment Analysis App with clean history

.gitignore

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+# Python virtual environment
+venv/
+
+# Python bytecode
+__pycache__/
+*.py[cod]
+*$py.class
+
+# Distribution / packaging
+dist/
+build/
+*.egg-info/
+
+# IDE specific files
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# Environment variables
+.env
+
+# Distribution / packaging
+.DS_Store 

README.md

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+# Text Sentiment Analysis
+
+This is a simple sentiment analysis application built with Gradio and TextBlob. It analyzes the sentiment of input text and provides:
+- Polarity score (-1 to 1, where -1 is negative and 1 is positive)
+- Subjectivity score (0 to 1, where 0 is objective and 1 is subjective)
+- Overall assessment (positive, negative, or neutral)
+
+## Usage
+Simply enter any text in the input box and the application will analyze its sentiment.
+
+## Technologies Used
+- Gradio for the web interface
+- TextBlob for sentiment analysis 

app.py

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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
+    """
+    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..."),
+    outputs=gr.JSON(),
+    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) 

requirements.txt

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+gradio[mcp]
+textblob