update app

app.py

@@ -16,15 +16,6 @@ ner_pipeline = pipeline(
 )
 
 
-# Helper function to print entities nicely
-def print_nicely(entities):
-    entity_details = []
-    for entity in entities:
-        entity_info = f"Entity: {entity['entity']} | Confidence: {entity['score']:.2f}% | Text: {entity['word'].strip()} | Start: {entity['start']} | End: {entity['end']}"
-        entity_details.append(entity_info)
-    return "\n".join(entity_details)
-
-
 # Helper function to flatten entities and prepare them for HighlightedText
 def prepare_entities_for_highlight(text, results):
     entities = []
@@ -45,14 +36,8 @@ def prepare_entities_for_highlight(text, results):
 # Function to process the sentence and extract entities
 def extract_entities(sentence):
     results = ner_pipeline(sentence)
-    entity_results = []
-
-    # Extract and format the entities
-    for key in results.keys():
-        entity_results.append(print_nicely(results[key]))
 
-    print(results)
-    print(entity_results)
+    # Format the results for HighlightedText
     return prepare_entities_for_highlight(sentence, results)
 
 
@@ -70,6 +55,11 @@ def ner_app_interface():
         outputs=output_entities,
         title="Named Entity Recognition",
         description="Enter a sentence to extract named entities using the NER model from the Impresso project.",
+        examples=[
+            [
+                "In the year 1789, King Louis XVI, ruler of France, convened the Estates-General at the Palace of Versailles."
+            ]
+        ],
     )
 
     interface.launch()