feat: enhance predict function with detailed docstring and add queue to demo interface

app.py

@@ -532,6 +532,22 @@ detection_model_eval_playground = gr.Interface(
 
 
 def predict(img):
+    """
+    Predicts whether an image is AI-generated or real using the SOTA Community Forensics model.
+
+    Args:
+        img (str): Path to the input image file to analyze.
+
+    Returns:
+        dict: A dictionary containing:
+            - 'Fake Probability' (float): Probability score between 0 and 1 indicating likelihood of being AI-generated
+            - 'Result Description' (str): Human-readable description of the prediction result
+
+    Example:
+        >>> result = predict("path/to/image.jpg")
+        >>> print(result)
+        {'Fake Probability': 0.002, 'Result Description': 'The image is likely real.'}
+    """
     client = Client("aiwithoutborders-xyz/OpenSight-Community-Forensics-Preview")
     client.view_api()
     result = client.predict(
@@ -697,6 +713,7 @@ demo = gr.TabbedInterface(
 
 # Add live update for the logs textbox
 # demo.load(get_captured_logs, None, demo.outputs[8], every=1)
+demo.queue(max_size=4)
 
 if __name__ == "__main__":
     demo.launch(mcp_server=True)