Update app.py

app.py

@@ -1,37 +1,55 @@
 import json
-import gradio as gr
 from textblob import TextBlob
+from fastapi import FastAPI, HTTPException
+import uvicorn
 
-def sentiment_analysis(text: str) -> str:
-    """
-    Analyze the sentiment of the given text.
-
-    Args:
-        text (str): The text to analyze
+app = FastAPI()
 
-    Returns:
-        str: A JSON string containing polarity, subjectivity, and assessment
-    """
+def analyze_sentiment(text: str) -> dict:
+    """Core sentiment analysis logic"""
     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 {
+        "polarity": round(sentiment.polarity, 2),
+        "subjectivity": round(sentiment.subjectivity, 2),
+        "assessment": "positive" if sentiment.polarity > 0 
+                     else "negative" if sentiment.polarity < 0 
+                     else "neutral"
     }
 
-    return json.dumps(result)
+@app.post("/mcp/sentiment")
+async def handle_mcp_request(data: dict):
+    """
+    MCP-compatible endpoint
+    Expected input: {"parameters": {"text": "your text here"}}
+    """
+    try:
+        text = data.get("parameters", {}).get("text", "")
+        if not text:
+            raise HTTPException(status_code=400, detail="Missing 'text' parameter")
+        
+        result = analyze_sentiment(text)
+        return {
+            "jsonrpc": "2.0",
+            "result": result,
+            "id": "sentiment-response"
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+from fastapi.staticfiles import StaticFiles
+import gradio as gr
+
+# Mount Gradio interface at /ui
+app.mount("/ui", gr.routes.App.create_app(demo))
 
-# Create the Gradio interface
+# Create Gradio interface (same as original)
 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"
+    fn=lambda text: analyze_sentiment(text),
+    inputs=gr.Textbox(),
+    outputs=gr.JSON(),
+    title="Sentiment Analysis UI"
 )
 
-# Launch the interface and MCP server
 if __name__ == "__main__":
-    demo.launch(mcp_server=True)
+    uvicorn.run(app, host="0.0.0.0", port=8000)