wip

app.py

@@ -1,10 +1,5 @@
-from textblob import TextBlob
-
 import gradio as gr
-
-from mcp.client.stdio import StdioServerParameters
-from smolagents import InferenceClientModel, CodeAgent, ToolCollection
-from smolagents.mcp_client import MCPClient
+from textblob import TextBlob
 
 def sentiment_analysis(text: str) -> dict:
     """
@@ -25,26 +20,14 @@ def sentiment_analysis(text: str) -> dict:
         "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
     }
 
-
-
-mcp_client = MCPClient(
-    {"url": "https://slimanemakh-mcp-course.hf.space/gradio_api/mcp/sse"}
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=sentiment_analysis,
+    inputs=gr.Textbox(placeholder="Enter text to analyze..."),
+    outputs=gr.JSON(),
+    title="Text Sentiment Analysis",
+    description="Analyze the sentiment of text using TextBlob"
 )
-tools = mcp_client.get_tools()
-
-model = InferenceClientModel()
-agent = CodeAgent(tools=[*tools], model=model)
-
-
-demo = gr.ChatInterface(
-    fn=lambda message, history: str(agent.run(message)),
-    type="messages",
-    examples=["Prime factorization of 68"],
-    title="Agent with MCP Tools",
-    description="This is a simple agent that uses MCP tools to answer questions.",
-    messages=[],
-)
-
 
 # Launch the interface and MCP server
 if __name__ == "__main__":