add get json

app.py

@@ -5,7 +5,7 @@ import gradio as gr
 # Your model’s raw NER output (we trust these start/end indices)
 ner = [
     {
-        'start': 12,
+        'start': 11,
         'end': 30,
         'text': 'Home Visits Survey',
         'label': 'named dataset',
@@ -50,22 +50,29 @@ def highlight_text(text):
                 })
     return {"text": text, "entities": entities}
 
+def get_model_predictions():
+    return json.dumps({"ner": ner, "relations": relations}, indent=2)
+
 with gr.Blocks() as demo:
-    gr.Markdown("## Data Use Detector\n"
-                "Paste or edit the sample text, then click **Highlight** to run inference.")
+    gr.Markdown("## GLiNER NER + RE Highlight & Predictions\n"
+                "Edit the sample text, then click **Highlight** to annotate entities, or **Get Model Predictions** to see the raw JSON.")
 
     txt_in      = gr.Textbox(label="Input Text", lines=4, value=SAMPLE_TEXT)
-    btn         = gr.Button("Highlight")
+    highlight_btn = gr.Button("Highlight")
     txt_out     = gr.HighlightedText(label="Annotated Entities")
-    ner_rel_box = gr.Textbox(
+
+    get_pred_btn = gr.Button("Get Model Predictions")
+    ner_rel_box  = gr.Textbox(
         label="Model Predictions (JSON)",
-        value=json.dumps({"ner": ner, "relations": relations}, indent=2),
         lines=15,
-        interactive=True
+        value="",
+        interactive=False
     )
 
-    # Only trigger on button click
-    btn.click(fn=highlight_text, inputs=txt_in, outputs=txt_out)
+    # Only trigger highlighting on click
+    highlight_btn.click(fn=highlight_text, inputs=txt_in, outputs=txt_out)
+    # Only show preds on click
+    get_pred_btn.click(fn=get_model_predictions, inputs=None, outputs=ner_rel_box)
 
 if __name__ == "__main__":
     demo.launch()