add 'layers' to interface

app.py

@@ -7,13 +7,15 @@ pipeline = QASemEndToEndPipeline()
 
 description = f"""This is a demo of the QASem Parsing pipeline. It wraps models of three QA-based semantic tasks, composing a comprehensive semi-structured representation of sentence meaning - covering verbal and nominal semantic role labeling together with discourse relations.""" 
 title="QASem Parsing Demo"
-examples = [["Both were shot in the confrontation with police and have been recovering in hospital since the attack .", 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.", 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 .", 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 .", 0.75],
-            ["The doctor asked about the progress in Luke 's treatment .", 0.75],
-            ["The Veterinary student was interested in Luke 's treatment of sea animals .", 0.7],
-            ["Some reviewers agreed that the criticism raised by the AC is mostly justified .", 0.6]]
+
+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]]
             
 
 input_sent_box_label = "Insert sentence here, or select from the examples below"
@@ -22,7 +24,7 @@ links = """<p style='text-align: center'>
 </p>"""
 
 
-def call(sentence, detection_threshold):
+def call(sentence, layers, detection_threshold):
 
     outputs = pipeline([sentence], nominalization_detection_threshold=detection_threshold)[0]
     def pretty_qadisc_qas(qa_infos) -> List[str]:
@@ -33,6 +35,10 @@ def call(sentence, detection_threshold):
         if not pred_info or not pred_info['QAs']: return []
         return ["- " + f"{qa['question']} --- {';'.join(qa['answers'])}".lstrip()
                 for qa in pred_info['QAs'] if qa is not None]
+    # filter outputs by requested `layers`
+    outputs = {layer: qas if layer in layers else [] 
+               for layer, qas in outputs.items()} 
+    # Prettify outputs
     qasrl_qas = [qa for pred_info in outputs['qasrl'] for qa in pretty_qasrl_qas(pred_info)]
     qanom_qas = [qa for pred_info in outputs['qanom'] for qa in pretty_qasrl_qas(pred_info)]
     qadisc_qas= pretty_qadisc_qas(outputs['qadiscourse'])
@@ -55,6 +61,7 @@ def call(sentence, detection_threshold):
 
 iface = gr.Interface(fn=call, 
                      inputs=[gr.inputs.Textbox(placeholder=input_sent_box_label, label="Sentence", lines=4), 
+                             gr.inputs.CheckboxGroup(all_layers, value=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"),