import gradio as gr
import os

from smolagents import InferenceClientModel, CodeAgent, MCPClient
# Load .env file for local development (ignored in production)
from dotenv import load_dotenv
load_dotenv()  # This will be ignored if .env doesn't exist (like in HF Spaces)

try:
    mcp_client = MCPClient(
        {
            "url": "https://snowcoader-mcp-sentiment.hf.space/gradio_api/mcp/sse",
            "transport": "sse"
        }
    )
    tools = mcp_client.get_tools()

    # Get token from environment - try both possible env var names
    token = os.getenv("HUGGINGFACE_API_TOKEN") or os.getenv("HF_TOKEN")
    if not token:
        print("Warning: No Hugging Face API token found. Some models may not work.")
        model = InferenceClientModel()  # Will use default/free tier
    else:
        model = InferenceClientModel(token=token)
    agent = CodeAgent(tools=[*tools], model=model, additional_authorized_imports=["json", "ast", "urllib", "base64"])

    demo = gr.ChatInterface(
        fn=lambda message, history: str(agent.run(message)),
        type="messages",
        examples=["Analyze the sentiment of the following text 'This is awesome'"],
        title="Agent with MCP Tools",
        description="This is a simple agent that uses MCP tools to answer questions.",
    )

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