Update app.py

app.py

@@ -77,10 +77,7 @@ def safe_parse_json_from_text(text: str):
 # ---------------------------------------------------
 #  TRUE MCP TOOL — THIS must be exposed to MCP client
 # ---------------------------------------------------
-@mcp.tool(
-    name="robot_watch",
-    description="Analyze a base64 image using Qwen VLM and return structured JSON.",
-)
+@mcp.api("/robot_watch", description="Analyze a base64 image using Qwen VLM and return structured JSON.")
 def robot_watch(payload: RobotWatchPayload): # <-- Type hint with Pydantic model
     # The payload is already validated and typed correctly by fastmcp/pydantic
     hf_token = payload.hf_token
@@ -139,17 +136,15 @@ Respond in STRICT JSON ONLY:
 
 
 # ---------------------------------------------------
-# Gradio UI — separate from MCP tool layer
+# Gradio UI — Use a simple placeholder function for the UI
 # ---------------------------------------------------
-# The process_json function will still work with the Pydantic model input
-def process_json(payload: Dict[str, Any]):
-    # When called via Gradio UI (not MCP), input will be Dict, so handle type conversion
-    pydantic_payload = RobotWatchPayload(**payload)
-    return robot_watch(pydantic_payload)
+def gradio_placeholder(payload):
+    # This is just for the interactive UI, the real API call goes to /robot_watch endpoint
+    return {"message": "Use the MCP Client to call the robot_watch tool."}
 
 
 app = gr.Interface(
-    fn=process_json,
+    fn=gradio_placeholder,
     inputs=gr.JSON(),
     outputs=gr.JSON(),
     title="Robot MCP Server",
@@ -157,5 +152,5 @@ app = gr.Interface(
 )
 
 if __name__ == "__main__":
-    # Gradio will use the 'mcp' instance defined globally to host the MCP server endpoints
+    # Launch Gradio, which automatically hooks up the 'mcp' instance's APIs
     app.launch(mcp_server=True)