update inference APP

app.py

@@ -14,7 +14,15 @@ label_dict_relations={ i : l for i, l in enumerate(label_list) }
 PATH = "./saved-models/my_model"
 model_metaphor_detection = AutoModelForTokenClassification.from_pretrained(PATH, id2label=label_dict_relations)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-pipeline_metaphors=pipeline("ner", model=model_metaphor_detection, tokenizer=tokenizer, aggregation_strategy="simple")
+
+pipeline_metaphors=pipeline(
+    "ner", 
+    model=model_metaphor_detection, 
+    tokenizer=tokenizer, 
+    aggregation_strategy="none",
+    # aggregation_strategy="simple",
+    )
+
 
 examples = [
     "It would change the trajectory of your legal career.",
@@ -22,16 +30,115 @@ examples = [
     "Those statements are deeply concerning.", 
 ]
 
+# Demo usage
+import pprint
+detection_results = pipeline_metaphors("It would change the trajectory of your legal career.")
+pp = pprint.PrettyPrinter(indent=4)
+pp.pprint(detection_results)
+
+"""Example Output; aggregation_strategy="none"
+[   {   'end': 2,
+        'entity': 'literal',
+        'index': 1,
+        'score': 0.99981445,
+        'start': 0,
+        'word': '▁It'},
+    {   'end': 8,
+        'entity': 'literal',
+        'index': 2,
+        'score': 0.9999882,
+        'start': 3,
+        'word': '▁would'},
+    {   'end': 15,
+        'entity': 'literal',
+        'index': 3,
+        'score': 0.6243065,
+        'start': 9,
+        'word': '▁change'},
+    {   'end': 19,
+        'entity': 'literal',
+        'index': 4,
+        'score': 0.9999826,
+        'start': 16,
+        'word': '▁the'},
+    {   'end': 27,
+        'entity': 'metaphoric',
+        'index': 5,
+        'score': 0.99631363,
+        'start': 20,
+        'word': '▁traject'},
+    {   'end': 30,
+        'entity': 'metaphoric',
+        'index': 6,
+        'score': 0.9979997,
+        'start': 27,
+        'word': 'ory'},
+    {   'end': 33,
+        'entity': 'literal',
+        'index': 7,
+        'score': 0.9996278,
+        'start': 31,
+        'word': '▁of'},
+    {   'end': 38,
+        'entity': 'literal',
+        'index': 8,
+        'score': 0.99985147,
+        'start': 34,
+        'word': '▁your'},
+    {   'end': 44,
+        'entity': 'literal',
+        'index': 9,
+        'score': 0.99984956,
+        'start': 39,
+        'word': '▁legal'},
+    {   'end': 51,
+        'entity': 'literal',
+        'index': 10,
+        'score': 0.998919,
+        'start': 45,
+        'word': '▁career'},
+    {   'end': 52,
+        'entity': 'literal',
+        'index': 11,
+        'score': 0.99775606,
+        'start': 51,
+        'word': '.'}]
+"""
+
+
+"""Example Output; aggregation_strategy="simple"
+[   {   'end': 19,
+    'entity_group': 'literal',
+    'score': 0.9060229,
+    'start': 0,
+    'word': 'It would change the'},
+{   'end': 30,
+    'entity_group': 'metaphoric',
+    'score': 0.9971567,
+    'start': 20,
+    'word': 'trajectory'},
+{   'end': 52,
+    'entity_group': 'literal',
+    'score': 0.9992008,
+    'start': 31,
+    'word': 'of your legal career.'}]
+
+"""
+# exit(0)
+
 def ner(text):
     output = pipeline_metaphors(text)
-    # change name 
+    # # change name 
     for x in output:
-        x['entity'] = x['entity_group']
+        if 'entity_group' in x:
+            x['entity'] = x['entity_group']
     return {"text": text, "entities": output}    
 
+
+
 demo = gr.Interface(ner,
              gr.Textbox(placeholder="Enter sentence here..."), 
              gr.HighlightedText(),
              examples=examples)
 
-demo.launch(share=True)
+demo.launch()