Update app.py

app.py

@@ -1,39 +1,19 @@
 import gradio as gr
 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
+from mcp import StdioServerParameters
+from smolagents import InferenceClientModel, CodeAgent, ToolCollection, MCPClient
 
-# Retrieve API keys securely
-hf_api_key = os.getenv('mcp2')  # 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"},
+        {"url": "https://wlchee-mcp-sentiment.hf.space/gradio_api/mcp/sse"} # This is the MCP Server we created in the previous section
     )
-    
-    # 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")
+
+    model = InferenceClientModel(token=os.getenv("mcp2"))
     agent = CodeAgent(tools=[*tools], model=model)
 
-    # Define the Gradio interface
     demo = gr.ChatInterface(
         fn=lambda message, history: str(agent.run(message)),
         type="messages",
@@ -42,10 +22,6 @@ try:
         description="This is a simple agent that uses MCP tools to answer questions.",
     )
 
-    # Launch the interface
-    demo.launch(share=True)
-
+    demo.launch()
 finally:
-    # Ensure MCPClient disconnects on script termination
-    if mcp_client:
-        mcp_client.disconnect()
+    mcp_client.disconnect()