Update app.py

app.py

@@ -1,36 +1,26 @@
-# app.py
-import asyncio
-from huggingface_hub import MCPClient
+import gradio as gr
+import os
 
-async def main():
-    # Ollama's OpenAI-compatible endpoint
-    client = MCPClient(
-        provider="openai",
-        base_url="http://localhost:11434/v1",
-        model="devstral",   # or your custom Ollama model name
-        api_key="ollama"    # any non-empty string works for Ollama
-    )
+from smolagents import InferenceClientModel, CodeAgent, MCPClient
 
-    # 1) Await the coroutine
-    await client.add_mcp_server(
-        type="stdio",
-        command="npx",
-        args=["@playwright/mcp@latest"]
-    )
 
-    # 2) Iterate with 'async for' over the async generator
-    user_msg = {
-        "role": "user",
-        "content": "Open the browser and list the titles on https://news.ycombinator.com"
-    }
+try:
+    mcp_client = MCPClient(
+        {"url": "https://abidlabs-mcp-tool-http.hf.space/gradio_api/mcp/sse"}
+    )
+    tools = mcp_client.get_tools()
 
-    async for chunk in client.process_single_turn_with_tools(messages=[user_msg]):
-        # chunks are streamed tool/assistant updates; print or handle them
-        print(chunk)
+    model = InferenceClientModel(token=os.getenv("HUGGINGFACE_API_TOKEN"))
+    agent = CodeAgent(tools=[*tools], model=model, additional_authorized_imports=["json", "ast", "urllib", "base64"])
 
-    # optional: close network/process resources if the client exposes it
-    if hasattr(client, "aclose"):
-        await client.aclose()
+    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.",
+    )
 
-if __name__ == "__main__":
-    asyncio.run(main())
+    demo.launch()
+finally:
+    mcp_client.disconnect()