Update app.py

app.py

@@ -1,20 +1,29 @@
 import gradio as gr
 from transformers import pipeline
 
-ner = pipeline("ner", model="Keyurjotaniya007/xlm-roberta-base-xtreme-multilingual-ner-2.0", aggregation_strategy="simple")
+ner = pipeline(
+    "ner",
+    model="Keyurjotaniya007/xlm-roberta-base-xtreme-multilingual-ner-2.0",
+    aggregation_strategy="simple"
+)
 
 def extract_entities(text):
     results = ner(text)
-    return [(ent['word'], ent['entity_group']) for ent in results]
+    entities = [{"word": r["word"], "label": r.get("entity_group"), "score": float(r.get("score", 0))} for r in results]
+
+    annotated = "  |  ".join([f"{e['word']} ({e['label']})" for e in entities]) if entities else "No entities found."
+
+    return entities, annotated
 
 with gr.Blocks() as demo:
     gr.Markdown(instructions)
     with gr.Row():
-        inp = gr.Textbox(label="Enter Text", placeholder="Type a sentence in any language...", lines=3)
-        out = gr.HighlightedText(label="Named Entities")
+        inp = gr.Textbox(label="Enter Text", placeholder="Type a sentence...", lines=3)
+        out_json = gr.JSON(label="Entities (JSON)")
+        out_text = gr.Textbox(label="Annotated Text")
     btn = gr.Button("Extract Entities")
 
-    btn.click(fn=extract_entities, inputs=inp, outputs=out)
+    btn.click(fn=extract_entities, inputs=inp, outputs=[out_json, out_text])
 
 if __name__ == "__main__":
     demo.launch()