Update app.py

app.py

@@ -1,33 +1,33 @@
-import gradio as gr
-from textblob import TextBlob
-
-def sentiment_analysis(text: str) -> dict:
-    """
-    Analyze the sentiment of a given text.
-    
-    Args:
-        text (str): The input text to analyze.
-
-    Returns:
-        dict: A dictionary containing the sentiment polarity, subjectivity scores 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"
-    }
-
-# Gradio Interface
-sentiment_analyzer = 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 a given text using TextBlob.",
-)
-
-# Launch the interface and MCP server
-if __name__ == "__main__":
-    sentiment_analyzer.launch(mcp_server=True)
+import gradio as gr
+from textblob import TextBlob
+
+def sentiment_analysis(text: str) -> dict:
+    """
+    Analyze the sentiment of a given text.
+    
+    Args:
+        text (str): The input text to analyze.
+
+    Returns:
+        dict: A dictionary containing the sentiment polarity, subjectivity scores 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"
+    }
+
+# 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 a given text using TextBlob.",
+)
+
+# Launch the interface and MCP server
+if __name__ == "__main__":
+    demo.launch(mcp_server=True)