add txtbox

app.py

@@ -1,7 +1,8 @@
 import re
+import json
 import gradio as gr
 
-# Your actual model outputs:
+# Your model’s raw NER output (we trust these start/end indices)
 ner = [
     {
         'start': 12,
@@ -12,6 +13,7 @@ ner = [
     }
 ]
 
+# Your model’s raw RE output
 relations = {
     'Home Visits Survey': [
         {'source': 'Home Visits Survey', 'relation': 'data geography',   'target': 'Jordan',                                        'score': 0.6180844902992249},
@@ -25,12 +27,8 @@ relations = {
     ]
 }
 
-SAMPLE_TEXT = (
-    "The Jordan Home Visits Survey, Round II (HV), was carried out by UNHCR and the World Food "
-    "Programme between November 2013 and September 2014. Through in-home visits to Syrian refugee "
-    "households in Jordan, it gathered detailed socio-economic, health, and protection data—each "
-    "household tagged with a unique ID to allow longitudinal tracking."
-)
+# Exact sample text
+SAMPLE_TEXT = """The Jordan Home Visits Survey, Round II (HV), was carried out by UNHCR and the World Food Programme between November 2013 and September 2014. Through in-home visits to Syrian refugee households in Jordan, it gathered detailed socio-economic, health, and protection data—each household tagged with a unique ID to allow longitudinal tracking."""
 
 def highlight_text(text):
     entities = []
@@ -42,13 +40,11 @@ def highlight_text(text):
             "end":    ent["end"],
         })
     # 2) RE spans
-    for src, rels in relations.items():
-        for r in rels:
-            label = r["relation"]
-            target = r["target"]
-            for m in re.finditer(re.escape(target), text):
+    for rel_list in relations.values():
+        for r in rel_list:
+            for m in re.finditer(re.escape(r["target"]), text):
                 entities.append({
-                    "entity": label,
+                    "entity": r["relation"],
                     "start":  m.start(),
                     "end":    m.end(),
                 })
@@ -56,26 +52,20 @@ def highlight_text(text):
 
 with gr.Blocks() as demo:
     gr.Markdown("## Data Use Detector\n"
-                "Click **Highlight** to run inference on the sample sentence.")
+                "Paste or edit the sample text, then click **Highlight** to run inference.")
 
-    txt_in  = gr.Textbox(label="Input Text", lines=4, value=SAMPLE_TEXT)
-    btn     = gr.Button("Highlight")
-    txt_out = gr.HighlightedText(label="Annotated Entities")
+    txt_in      = gr.Textbox(label="Input Text", lines=4, value=SAMPLE_TEXT)
+    btn         = gr.Button("Highlight")
+    txt_out     = gr.HighlightedText(label="Annotated Entities")
+    ner_rel_box = gr.Textbox(
+        label="Model Predictions (JSON)",
+        value=json.dumps({"ner": ner, "relations": relations}, indent=2),
+        lines=15,
+        interactive=True
+    )
 
-    # **Only** trigger on button click
+    # Only trigger on button click
     btn.click(fn=highlight_text, inputs=txt_in, outputs=txt_out)
 
-    gr.Markdown("""
-**Legend**  
-- **named dataset** → Home Visits Survey  
-- **data geography** → Jordan  
-- **version** → Round II  
-- **acronym** → HV  
-- **author** → UNHCR, World Food Programme  
-- **reference year** → 2013  
-- **publication year** → 2014  
-- **data description** → detailed socio-economic, health, and protection data
-""")
-
 if __name__ == "__main__":
     demo.launch()