Update app.py

app.py

@@ -1,26 +1,35 @@
+import json
 import gradio as gr
-import os
+from textblob import TextBlob
 
-from smolagents import InferenceClientModel, CodeAgent, MCPClient
+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"
+    }
 
-try:
-    mcp_client = MCPClient(
-        {"url": "https://abidlabs-mcp-tool-http.hf.space/gradio_api/mcp/sse"}
-    )
-    tools = mcp_client.get_tools()
+    return json.dumps(result)
 
-    model = InferenceClientModel(token=os.getenv("HUGGINGFACE_API_TOKEN"))
-    agent = CodeAgent(tools=[*tools], model=model, additional_authorized_imports=["json", "ast", "urllib", "base64"])
+# 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"
+)
 
-    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()
+# Launch the interface and MCP server
+if __name__ == "__main__":
+    demo.launch(mcp_server=True)