Update app.py

app.py

@@ -1,27 +1,82 @@
 import gradio as gr
 import os
+from smolagents import InferenceClientModel, CodeAgent, MCPClient
 
-from mcp import StdioServerParameters
-from smolagents import InferenceClientModel, CodeAgent, ToolCollection, MCPClient
+# Configuration
+MCP_SERVER_URL = "https://ashokdll-mcp-sentiment.hf.space/gradio_api/mcp/sse"  # Replace with your actual URL
+mcp_client = None
+agent = None
 
+def initialize_agent():
+    """Initialize the MCP client and agent"""
+    global mcp_client, agent
+    
+    try:
+        # Connect to your MCP Server
+        mcp_client = MCPClient({"url": MCP_SERVER_URL})
+        tools = mcp_client.get_tools()
+        
+        # Debug: Print available tools
+        print("Available tools:")
+        for tool in tools:
+            print(f"- {tool.name}: {tool.description}")
+        
+        # Create the model with HF token
+        model = InferenceClientModel(token=os.getenv("HF_TOKEN"))
+        
+        # Create the agent with tools
+        agent = CodeAgent(tools=[*tools], model=model)
+        
+        return True, "Agent initialized successfully"
+    
+    except Exception as e:
+        print(f"Error initializing agent: {e}")
+        return False, str(e)
 
-try:
-    mcp_client = MCPClient(
-        {"url": "http://localhost:7860/gradio_api/mcp/sse"} # This is the MCP Server we created in the previous section
-    )
-    tools = mcp_client.get_tools()
+def chat_function(message, history):
+    """Handle chat messages"""
+    global agent
+    
+    # Initialize agent if not already done
+    if agent is None:
+        success, error_msg = initialize_agent()
+        if not success:
+            return f"❌ Error connecting to MCP server: {error_msg}\n\nPlease check:\n1. Your MCP server URL is correct\n2. Your sentiment analysis space is running\n3. MCP server is enabled in your sentiment analysis app"
+    
+    try:
+        # Run the agent with the user's message
+        response = agent.run(message)
+        return str(response)
+    
+    except Exception as e:
+        return f"❌ Error running agent: {str(e)}"
 
-    model = InferenceClientModel(token=os.getenv("HUGGINGFACE_API_TOKEN"))
-    agent = CodeAgent(tools=[*tools], model=model)
+def cleanup():
+    """Cleanup function to disconnect MCP client"""
+    global mcp_client
+    if mcp_client:
+        try:
+            mcp_client.disconnect()
+        except:
+            pass
 
-    demo = gr.ChatInterface(
-        fn=lambda message, history: str(agent.run(message)),
-        type="messages",
-        examples=["Prime factorization of 68"],
-        title="Agent with MCP Tools",
-        description="This is a simple agent that uses MCP tools to answer questions.",
-    )
+# Create the Gradio interface
+demo = gr.ChatInterface(
+    fn=chat_function,
+    type="messages",
+    examples=[
+        "Analyze the sentiment of: 'I absolutely love this new product!'",
+        "What's the sentiment of: 'This is terrible and I hate it'",
+        "Check sentiment: 'The weather is okay today'",
+        "Perform sentiment analysis on: 'Python programming is amazing!'"
+    ],
+    title="🤖 Sentiment Analysis Agent with MCP",
+    description="This agent connects to your sentiment analysis MCP server and can analyze text sentiment using natural language commands.",
+)
 
-    demo.launch()
-finally:
-    mcp_client.disconnect()
+# Launch the interface
+if __name__ == "__main__":
+    try:
+        demo.launch()
+    finally:
+        cleanup()