Create app.py

Add app.py directly as remote push is failing

app.py

@@ -0,0 +1,64 @@
+import json
+import gradio as gr
+from textblob import TextBlob
+
+def call_model(text: str, model_type: str = "textblob"):
+    """
+    Return raw sentiment analysis output from selected model.
+    """
+    if model_type == "textblob":
+        blob = TextBlob(text)
+        return blob.sentiment  # returns namedtuple(polarity, subjectivity)
+
+    elif model_type == "transformer":
+        # Placeholder for future integration
+        return {"label": "POSITIVE", "score": 0.98}
+
+    else:
+        raise ValueError(f"Unsupported model type: {model_type}")
+    
+
+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
+    """
+    sentiment = call_model(text, model_type="textblob")
+    
+    # Handle TextBlob response (namedtuple)
+    if isinstance(sentiment, tuple):  # Simple check for TextBlob style
+        polarity = round(sentiment.polarity, 2)
+        subjectivity = round(sentiment.subjectivity, 2)
+        assessment = (
+            "positive" if polarity > 0 else
+            "negative" if polarity < 0 else
+            "neutral"
+        )
+        result = {
+            "polarity": polarity,
+            "subjectivity": subjectivity,
+            "assessment": assessment
+        }
+    else:
+        # Future: handle ML-based sentiment output
+        result = sentiment
+
+    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)