Update mapp.py

mapp.py

@@ -1,37 +1,22 @@
-import json
-import gradio as gr
-from textblob import TextBlob
-
-def sentiment_analysis(text: str) -> str:
-    """
-    Analyze the sentiment of the given text.
-
-    Args:
-        text (str): The text to analyze
-
-    Returns:
-        str: A JSON string containing polarity, subjectivity, and assessment
-    """
-    blob = TextBlob(text)
-    sentiment = blob.sentiment
-    
-    result = {
-        "polarity": round(sentiment.polarity, 2),  # -1 (negative) to 1 (positive)
-        "subjectivity": round(sentiment.subjectivity, 2),  # 0 (objective) to 1 (subjective)
-        "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
-    }
-
-    return json.dumps(result)
-
-# Create the Gradio interface
-demo = gr.Interface(
-    fn=sentiment_analysis,
-    inputs=gr.Textbox(placeholder="Enter text to analyze..."),
-    outputs=gr.Textbox(),  # Changed from gr.JSON() to gr.Textbox()
-    title="Text Sentiment Analysis",
-    description="Analyze the sentiment of text using TextBlob"
-)
-
-# Launch the interface and MCP server
-if __name__ == "__main__":
-    demo.launch(mcp_server=True)
+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
+)
+
+# Attach Playwright MCP (local stdio server)
+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)