Update app.py

app.py

@@ -4,39 +4,22 @@ from PIL import Image
 import io
 import json
 
-# Add a docstring for your function; this is used to generate the MCP tool description
-def process(json_input: dict) -> dict:
-    """
-    Processes incoming JSON data containing a base64 encoded image and robot ID.
+def process(json_input):
+    data = json_input
+    img_bytes = base64.b64decode(data["image_b64"])
+    img = Image.open(io.BytesIO(img_bytes))
 
-    Args:
-        json_input (dict): A dictionary with keys "image_b64" and "robot_id".
-
-    Returns:
-        dict: A response dictionary indicating success, robot ID, and image size, or an error.
-    """
-    try:
-        data = json_input  # Already a dict from Gradio API
-
-        img_bytes = base64.b64decode(data["image_b64"])
-        img = Image.open(io.BytesIO(img_bytes))
-
-        response = {
-            "received": True,
-            "robot_id": data.get("robot_id", "unknown"),
-            "image_size": img.size
-        }
-        return response
-
-    except Exception as e:
-        return {"error": str(e)}
+    return {
+        "received": True,
+        "robot_id": data.get("robot_id", "unknown"),
+        "image_size": img.size
+    }
 
 demo = gr.Interface(
     fn=process,
     inputs=gr.JSON(label="Input JSON from Jetson"),
     outputs=gr.JSON(label="Reply to Jetson"),
+    api_name="predict"    # very important
 )
 
-# Launch with mcp_server enabled
-if __name__ == "__main__":
-    demo.launch(mcp_server=True)
+demo.launch()