better output

app.py

@@ -1,24 +1,35 @@
 import gradio as gr
 from transformers import pipeline
 
-print('starat')
 nlp_qa = pipeline(
     'question-answering',
     model='mrm8488/bert-italian-finedtuned-squadv1-it-alfa',
     tokenizer='mrm8488/bert-italian-finedtuned-squadv1-it-alfa'
 )
-print('end')
+
+def get_colored_text(response, context):
+    colored_string = context[:response['start']] + \
+        '<span style="color:blue">' + context[response['start']:response['end']] + '</span>' + \
+        context[response['end']:]
+    return colored_string
 
 def start(question, context):
     response = nlp_qa({
         'question': question,
         'context': context
     })
-    return response['answer'], response['score']
+    return  get_colored_text(response, context), response['answer'], {response['answer']: response['score']}
 
 face = gr.Interface(
     fn=start, 
-    inputs=[gr.inputs.Textbox(lines=1, placeholder="Question Here… "), gr.inputs.Textbox(lines=10, placeholder="Context Here… ")], 
-    outputs=["text", "number"]
+    inputs=[
+        gr.inputs.Textbox(lines=1, placeholder="Question Here… "), 
+        gr.inputs.Textbox(lines=10, placeholder="Context Here… ")
+    ], 
+    outputs=[
+        gr.outputs.HTML(label='Context'),
+        gr.outputs.Textbox(label="Answer"), 
+        gr.outputs.Label(num_top_classes=1, label='Score'), 
+    ]
 )
 face.launch(share=True)