Update app.py

app.py

@@ -9,13 +9,13 @@ description = f"""This is a demo of the QASem Parsing pipeline. It wraps models
 title="QASem Parsing Demo"
 
 all_layers = ["qasrl", "qanom", "qadiscourse"]
-examples = [["Both were shot in the confrontation with police and have been recovering in hospital since the attack .", all_layers, 0.75],
-            ["the construction of the officer 's building was delayed by the lockdown and is expected to continue for at least 10 more months.", all_layers, 0.75],
-            ["While President Obama expressed condolences regarding the death of Margaret Thatcher upon her death earlier this year , he did not issue an executive order that flags be lowered in her honor .", all_layers, 0.75],
-            ["We made a very clear commitment : if there is any proposal in the next parliament for a transfer of powers to Brussels ( the EU ) we will have an in/out referendum .", all_layers, 0.75],
-            ["The doctor asked about the progress in Luke 's treatment .", all_layers, 0.75],
-            ["The Veterinary student was interested in Luke 's treatment of sea animals .", all_layers, 0.7],
-            ["Some reviewers agreed that the criticism raised by the AC is mostly justified .", all_layers, 0.6]]
+examples = [["Both were shot in the confrontation with police and have been recovering in hospital since the attack .", all_layers, False, 0.75],
+            ["the construction of the officer 's building was delayed by the lockdown and is expected to continue for at least 10 more months.", all_layers, False, 0.75],
+            ["While President Obama expressed condolences regarding the death of Margaret Thatcher upon her death earlier this year , he did not issue an executive order that flags be lowered in her honor .", all_layers, False, 0.75],
+            ["We made a very clear commitment : if there is any proposal in the next parliament for a transfer of powers to Brussels ( the EU ) we will have an in/out referendum .", all_layers, False, 0.75],
+            ["The doctor asked about the progress in Luke 's treatment .", all_layers, False, 0.75],
+            ["The Veterinary student was interested in Luke 's treatment of sea animals .", all_layers, False, 0.7],
+            ["Some reviewers agreed that the criticism raised by the AC is mostly justified .", all_layers, False, 0.6]]
             
 
 input_sent_box_label = "Insert sentence here, or select from the examples below"
@@ -24,9 +24,12 @@ links = """<p style='text-align: center'>
 </p>"""
 
 
-def call(sentence, layers, detection_threshold):
-
-    outputs = pipeline([sentence], nominalization_detection_threshold=detection_threshold)[0]
+def call(sentence, layers, show_openie: bool, detection_threshold: float):
+    outputs = pipeline([sentence], nominalization_detection_threshold=detection_threshold, output_openie=show_openie)
+    if show_openie:
+        openie_outputs = outputs["openie"][0] # list of OpenIE tuples
+        outputs = outputs["qasem"]
+    outputs = outputs[0] # only one sentence in input batch
     def pretty_qadisc_qas(qa_infos) -> List[str]:
         if not qa_infos: return []
         return ["- " + f"{qa['question']} --- {qa['answer']}".lstrip()
@@ -61,15 +64,24 @@ def call(sentence, layers, detection_threshold):
     def word_span(word, idx):
         return f'<span style="background-color: {color(idx)}">{word}</span>'
     html = '<span>' + ' '.join(word_span(word, idx) for idx, word in enumerate(sentence.split(" "))) + '</span>'
-    return html, pretty_qa_output , outputs
+    # show openie_outputs
+    if show_openie:
+        repr_oie = lambda tup: f"({','.join(e for e in tup)})"
+        openie_html = '<span><b>Open Information Extraction:</b><br>' + '<br>'.join([repr_oie(tup) for tup in openie_outputs]) + '</span>' 
+    else:
+        openie_html = ''
+        
+    return html, pretty_qa_output, openie_html, outputs
 
 iface = gr.Interface(fn=call, 
-                     inputs=[gr.inputs.Textbox(placeholder=input_sent_box_label, label="Sentence", lines=4), 
-                             gr.inputs.CheckboxGroup(all_layers, default=all_layers, label="Annotation Layers"),
-                             gr.inputs.Slider(minimum=0., maximum=1., step=0.01, default=0.75, label="Nominalization Detection Threshold")], 
-                     outputs=[gr.outputs.HTML(label="Detected Predicates"),
-                              gr.outputs.Textbox(label="Generated QAs"), 
-                              gr.outputs.JSON(label="Raw QASemEndToEndPipeline Output")],
+                     inputs=[gr.components.Textbox(placeholder=input_sent_box_label, label="Sentence", lines=4), 
+                             gr.components.CheckboxGroup(all_layers, value=all_layers, label="Annotation Layers"),
+                             gr.components.Checkbox(value=False, label="Show OpenIE format (converted from verbal QASRL only)"),
+                             gr.components.Slider(minimum=0., maximum=1., step=0.01, value=0.75, label="Nominalization Detection Threshold")], 
+                     outputs=[gr.components.HTML(label="Detected Predicates"),
+                              gr.components.Textbox(label="Generated QAs"), 
+                              gr.components.HTML(label="OpenIE Output"),
+                              gr.components.JSON(label="Raw QASemEndToEndPipeline Output")],
                      title=title,
                      description=description,
                      article=links,