Update app.py

app.py

@@ -1,7 +1,8 @@
 import os
 import base64
 import time
-import json
+from PIL import Image
+import io
 import gradio as gr
 from gradio_client import Client
 from dotenv import load_dotenv
@@ -52,11 +53,9 @@ def pretty_print_response(resp: dict):
 def process_webcam_stream(image):
     """Send webcam image to HF MCP Server and get result"""
     if image is None:
-        return None, None, None, None
+        return "", "", "", ""
 
     # Convert to base64
-    import io
-    from PIL import Image
     buffered = io.BytesIO()
     img = Image.fromarray(image)
     img.save(buffered, format="JPEG")
@@ -70,18 +69,20 @@ def process_webcam_stream(image):
         "hf_token": HF_TOKEN
     }
 
-    # Send to HF Space using streaming-friendly predict
+    # Send to HF Space
     client = Client(HF_SPACE)
     try:
         resp = client.predict(payload, api_name=API_NAME)
-        # Print table in console
         pretty_print_response(resp)
-
-        # Return selected fields for Gradio display
-        return resp.get("description", ""), resp.get("human", ""), ", ".join(resp.get("objects", [])), resp.get("environment", "")
+        return (
+            resp.get("description", ""),
+            resp.get("human", ""),
+            ", ".join(resp.get("objects", [])) if resp.get("objects") else "",
+            resp.get("environment", "")
+        )
     except Exception as e:
         console.print(f"[bold red]Error sending to HF:[/bold red] {e}")
-        return None, None, None, None
+        return "", "", "", ""
 
 
 with gr.Blocks() as demo:
@@ -94,7 +95,6 @@ with gr.Blocks() as demo:
         objects_out = gr.Textbox(label="Objects")
         environment_out = gr.Textbox(label="Environment")
 
-    # Connect streaming
     webcam_input.stream(
         process_webcam_stream,
         inputs=[webcam_input],