Update app.py

app.py

@@ -1,12 +1,53 @@
 import gradio as gr
-with gr.Blocks() as demo:
-    gr.ChatInterface(
-        fn=lambda x: x,
-        title="MCP Client",
-        chatbot=gr.Chatbot(),
-        textbox=gr.Textbox(),
+import os
+
+from mcp.client.stdio import StdioServerParameters
+from smolagents import InferenceClientModel, CodeAgent, ToolCollection
+from smolagents.mcp_client import MCPClient
+from huggingface_hub import login
+
+# Retrieve API keys securely
+hf_api_key = os.getenv('HUGGINGFACE_API_KEY')  # Hugging Face API key from secret
+
+# Check if the Hugging Face API key is available
+if not hf_api_key:
+    raise ValueError("Hugging Face API key is not set. Please check your secrets.")
+
+# Log in to Hugging Face using the API key
+login(hf_api_key)
+
+mcp_client = None
+
+# Initialize MCPClient with URL
+try:
+    mcp_client = MCPClient(
+        {"url": "https://wlchee-mcp-sentiment.hf.space/gradio_api/mcp/sse"},
     )
-    demo.launch(
-        share=True,
-        mcp_server="https://wlchee-mcp-sentiment.hf.space/gradio_api/mcp/sse"  # Replace with your MCP server URL
-    )
+    
+    # Retrieve tools from the MCP client
+    tools = mcp_client.get_tools()
+    if not tools:
+        raise Exception("No tools retrieved from the MCP client.")
+    
+    # Create the model and agent
+    model = InferenceClientModel(model_id="Qwen/Qwen2.5-Omni-7B")
+    agent = CodeAgent(tools=[*tools], model=model)
+
+    # Define the Gradio interface
+    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.",
+    )
+
+    # Launch the interface
+    demo.launch(share=True,mcp_server="https://wlchee-mcp-sentiment.hf.space/gradio_api/mcp/sse")
+
+finally:
+    # Ensure MCPClient disconnects on script termination
+    if mcp_client:
+        mcp_client.disconnect()
+
+====