Update app.py

app.py

@@ -1,54 +1,34 @@
-import asyncio
-import sys
-import argparse
-from gradio_interface import create_gradio_interface
-from mcp_server import main as run_mcp_server
+import gradio as gr
+from textblob import TextBlob
 
-def main():
-    parser = argparse.ArgumentParser(description="Knowledge Graph Navigator")
-    parser.add_argument(
-        "--mode", 
-        choices=["gradio", "mcp", "both"],
-        default="gradio",
-        help="Run mode: gradio (web interface), mcp (server only), or both"
-    )
-    parser.add_argument(
-        "--port",
-        type=int,
-        default=7860,
-        help="Port for Gradio interface (default: 7860)"
-    )
-    parser.add_argument(
-        "--share",
-        action="store_true",
-        help="Create public Gradio link"
-    )
-    
-    args = parser.parse_args()
-    
-    if args.mode == "gradio":
-        print("🚀 Launching Gradio interface...")
-        interface = create_gradio_interface()
-        interface.launch(
-            server_port=args.port,
-            share=args.share,
-            debug=True
-        )
-    
-    elif args.mode == "mcp":
-        print("🔧 Starting MCP server...")
-        asyncio.run(run_mcp_server())
+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
     
-    elif args.mode == "both":
-        print("🚀 Starting both Gradio and MCP server...")
-        # In production, you'd want to run these in separate processes
-        # For now, just run Gradio (MCP would run in background)
-        interface = create_gradio_interface()
-        interface.launch(
-            server_port=args.port,
-            share=args.share,
-            debug=True
-        )
+    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__":
-    main()
+    demo.launch(mcp_server=True)