Update app.py

app.py

@@ -1,22 +1,57 @@
-from transformers import pipeline
-import gradio as gr
-
-ner_model = pipeline(
-    "ner",
-    model="dslim/bert-base-NER",
-    aggregation_strategy="simple"
-)
-
-def ner_inference(text):
-    return ner_model(text)
-
-interface = gr.Interface(
-    fn=ner_inference,
-    inputs=gr.Textbox(lines=5, placeholder="Enter text"),
-    outputs=gr.JSON(),
-    title="NER using Hugging Face",
-    description="Deployed with Gradio on HF Spaces"
-)
-
-if __name__ == "__main__":
-    interface.launch()
+from transformers import pipeline
+import gradio as gr
+import pandas as pd
+
+# Load NER model
+ner_model = pipeline(
+    "ner",
+    model="dslim/bert-base-NER",
+    aggregation_strategy="simple"
+)
+
+def create_df():
+    return pd.DataFrame(
+        columns=["Entity", "Confidence (%)"]
+    )
+
+def ner_inference(text):
+    entities = ner_model(text)
+
+    per_rows, org_rows, loc_rows = [], [], []
+
+    for ent in entities:
+        row = [ent["word"], round(ent["score"] * 100, 2)]
+
+        if ent["entity_group"] == "PER":
+            per_rows.append(row)
+        elif ent["entity_group"] == "ORG":
+            org_rows.append(row)
+        elif ent["entity_group"] == "LOC":
+            loc_rows.append(row)
+
+    df_per = pd.DataFrame(per_rows, columns=["Person", "Confidence (%)"]) if per_rows else create_df()
+    df_org = pd.DataFrame(org_rows, columns=["Organization", "Confidence (%)"]) if org_rows else create_df()
+    df_loc = pd.DataFrame(loc_rows, columns=["Location", "Confidence (%)"]) if loc_rows else create_df()
+
+    return df_per, df_org, df_loc
+
+# Gradio UI
+interface = gr.Interface(
+    fn=ner_inference,
+    inputs=gr.Textbox(
+        lines=5,
+        placeholder="Enter text here...",
+        label="Input Text"
+    ),
+    outputs=[
+        gr.Dataframe(label="👤 Persons", interactive=False),
+        gr.Dataframe(label="🏢 Organizations", interactive=False),
+        gr.Dataframe(label="📍 Locations", interactive=False),
+    ],
+    title="Named Entity Recognition (NER)",
+    description="NER results grouped by entity type for better readability and usability.",
+    theme="dark"
+)
+
+if __name__ == "__main__":
+    interface.launch()