initial commit

app.py

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+import gradio as gr
+import os
+import atexit
+
+from smolagents import InferenceClientModel, CodeAgent, MCPClient
+
+
+def create_agent_with_fallback():
+    """Create agent with MCP tools if available, otherwise use basic tools"""
+    token = os.getenv("HUGGINGFACE_API_TOKEN")  # use a generic env var name
+    if not token:
+        raise RuntimeError("HF_API_TOKEN environment variable not set.")
+
+    model = InferenceClientModel(token=token)
+
+    try:
+        # Try to connect to MCP server
+        mcp_url = os.getenv("MCP_SERVER_URL", "https://trainhubai-mcp-sentiment.hf.space/gradio_api/mcp/sse")
+        mcp_client = MCPClient({"url": mcp_url})
+        tools = mcp_client.get_tools()
+        agent = CodeAgent(tools=tools, model=model)
+        return agent, mcp_client
+
+    except Exception as e:
+        print(f"Failed to connect to MCP server: {e}")
+        print("Creating agent with basic tools...")
+        agent = CodeAgent(tools=[], model=model)
+        return agent, None
+
+
+# Initialize agent globally
+agent, mcp_client = create_agent_with_fallback()
+
+# Chat function
+def chat_function(message, history):
+    try:
+        return str(agent.run(message))
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Gradio ChatInterface defined at the top level (needed for Spaces)
+demo = gr.ChatInterface(
+    fn=chat_function,
+    type="messages",
+    examples=["What's the sentiment of this?"],
+    title="Agent with MCP Tools",
+    description="This is a simple agent that uses MCP tools to analyze the sentiment of text.",
+)
+
+# Cleanup on exit
+def cleanup():
+    if mcp_client:
+        try:
+            mcp_client.disconnect()
+        except:
+            pass
+
+atexit.register(cleanup)

requirements.txt

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+gradio[mcp]
+smolagents[mcp]