wip

app.py

@@ -1,6 +1,11 @@
-import gradio as gr
 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
+
 def sentiment_analysis(text: str) -> dict:
     """
     Analyze the sentiment of the given text.
@@ -20,14 +25,26 @@ def sentiment_analysis(text: str) -> dict:
         "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
     }
 
-# 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"
+
+
+mcp_client = MCPClient(
+    {"url": "https://slimanemakh-mcp-course.hf.space/gradio_api/mcp/sse"}
 )
+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__":