Update app.py

app.py

@@ -1,22 +1,36 @@
+# app.py
+import asyncio
 from huggingface_hub import MCPClient
 
-# Use Ollama via its 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 is accepted by Ollama
-)
+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
+    )
 
-# Attach Playwright MCP (local stdio server)
-client.add_mcp_server(
-    type="stdio",
-    command="npx",
-    args=["@playwright/mcp@latest"]
-)
+    # 1) Await the coroutine
+    await client.add_mcp_server(
+        type="stdio",
+        command="npx",
+        args=["@playwright/mcp@latest"]
+    )
 
-# Run a single tool-using turn
-for chunk in client.process_single_turn_with_tools(
-    messages=[{"role": "user", "content": "Open the browser and list the titles on https://news.ycombinator.com"}]
-):
-    print(chunk)
+    # 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"
+    }
+
+    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)
+
+    # optional: close network/process resources if the client exposes it
+    if hasattr(client, "aclose"):
+        await client.aclose()
+
+if __name__ == "__main__":
+    asyncio.run(main())