Create app.py

app.py

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+import gradio as gr
+from gradio_client import Client
+
+# This client connects to a language model that can write text
+llm_client = Client("hysts/zephyr-7b")
+
+def create_compliment(text_description: str) -> str:
+    """
+    Takes a text description of a scene and turns it into a fun, friendly compliment.
+
+    Args:
+        text_description: A description of what is in a picture.
+    """
+    prompt = f"Please turn the following description into a short, fun, and friendly compliment: {text_description}"
+    
+    # We send the prompt to the language model to get our final result.
+    compliment = llm_client.predict(
+			prompt=prompt,
+			max_new_tokens=128,
+			api_name="/add_text"
+    )
+    
+    return compliment
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=create_compliment,
+    inputs=gr.Textbox(label="Describe a scene or person"),
+    outputs=gr.Textbox(label="Generated Compliment"),
+    title="The Complimenter Tool",
+    description="An MCP server that generates compliments from text descriptions. [1, 2]"
+)
+
+# Launch the app as an MCP server
+if __name__ == "__main__":
+    iface.launch(mcp_server=True)