Update app.py

app.py

@@ -26,7 +26,7 @@ def ner(text: str, labels: str, threshold: float, nested_ner: bool):
     entities = model.predict_entities(truncated_text, labels_list, flat_ner=not nested_ner, threshold=threshold)
     
     # Prepare entities for color-coded display using gr.HighlightedText
-    highlights = [(ent["start"], ent["end"], ent["label"]) for ent in entities]
+    highlights = [{"start": ent["start"], "end": ent["end"], "entity": ent["label"]} for ent in entities]
     
     # Return both the highlighted text and the raw entities in JSON format
     return {
@@ -44,7 +44,7 @@ with gr.Blocks(title="General NER with Color-Coded Output") as demo:
     
     # Display a random example
     input_text = gr.Textbox(
-        value="Click 'Get New Snippet' to load a random sample from the British Library Dataset",
+        value="The machine is fed by means of an endless apron, the wool entering at the smaller end...",
         label="Text input",
         placeholder="Enter your text here",
         lines=5
@@ -52,7 +52,7 @@ with gr.Blocks(title="General NER with Color-Coded Output") as demo:
 
     with gr.Row() as row:
         labels = gr.Textbox(
-            value="People, Places",  # Default example labels
+            value="Machine, Wool",  # Default example labels
             label="Labels",
             placeholder="Enter your labels here (comma separated)",
             scale=2,