app.py

import gradio as gr
import os

from mcp import StdioServerParameters
from smolagents import InferenceClientModel, CodeAgent, ToolCollection, MCPClient
from smolagents import LiteLLMModel


try:
    mcp_client = MCPClient(
        {"url": "https://abdallalswaiti-mcp-sentiment.hf.space/gradio_api/mcp/sse"} # This is the MCP Server we created in the previous section
    )
    tools = mcp_client.get_tools()

    model = InferenceClientModel(token=os.getenv("HUGGINGFACE_API_TOKEN"))
    # model = LiteLLMModel(
    #     model_id="gemini/gemini-2.5-flash-preview-05-20",  # Gemini model name for LiteLLM
    #     temperature=0.2,
    #     api_key=os.environ["GOOGLE_API_KEY"]               # Must have access to Gemini via Vertex AI
    # )
    agent = CodeAgent(tools=[*tools], model=model)

    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.",
    )

    demo.launch()
finally:
    mcp_client.disconnect()