Add application file

.gitignore

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+.env
+demo.ipynb

app.py

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+import gradio as gr
+from transformers import pipeline
+from spacy import displacy
+
+# load model pipeline globally 
+ner_pipe = pipeline("token-classification", model="cindyangelira/ner-roberta-large-bahasa-indonesia")
+
+# define colors for each tag
+def get_colors():
+    return {
+        "O": "#ffffff",            # White for 'O'
+        "PERSON": "#ffadad",      # Light red for 'PERSON'
+        "LOCATION": "#ffda83",    # Light yellow for 'LOCATION'
+        "DOB": "#ffadad",         # Light red for 'DOB'
+        "EMAIL": "#85e0e0",       # Light cyan for 'EMAIL'
+        "GENDER": "#c3c3e0",      # Light gray for 'GENDER'
+        "ACCOUNT": "#b0e0e6",     # Light blue for 'ACCOUNT'
+        "ID": "#800080",          # Purple for 'ID'
+        "PHONE": "#d1ff85" # Light green for 'PHONE NUMBER'
+    }
+
+
+def process_prediction(text, pred):
+    colors = get_colors()
+
+    for token in pred:
+        token['label'] = token['entity'].replace('B-', '').replace('I-', '')
+
+    ents = [{'start': token['start'], 'end': token['end'], 'label': token['label']} for token in pred]
+
+    doc = {
+        "text": text,
+        "ents": ents,
+        "title": None
+    }
+
+    options = {"ents": list(colors.keys()), "colors": colors}
+    html = displacy.render(doc, style="ent", manual=True, options=options)
+    return html
+
+
+def ner_visualization(text):
+    predictions = ner_pipe(text)  
+    return process_prediction(text, predictions)
+
+
+def build_interface():
+    iface = gr.Interface(
+        fn=ner_visualization,                 # Main function for NER visualization
+        inputs=gr.Textbox(label="Input Text"),# Input textbox
+        outputs="html",                       # Output is HTML with rendered NER
+        title="NER Bahasa Indonesia",            # Title of the app
+        description="Enter text to see named entity recognition results highlighted."
+    )
+    return iface
+
+
+if __name__ == "__main__":
+    app = build_interface()
+    app.launch()