Update app.py

app.py

@@ -63,9 +63,11 @@ def qa_ranker(query, docs_, top_k_ranker):
 
 def cstr(s, color='black'):
     return "<text style=color:{}>{}</text>".format(color, s)
+def cstr_bold(s, color='black'):
+    return "<text style=color:{}><b>{}</b></text>".format(color, s)
 
 def print_colored(text, start_idx, end_idx):
-    a = cstr(' '.join([text[:start_idx], cstr(text[start_idx:end_idx], color='red'), text[end_idx:]]), color='black')
+    a = cstr(' '.join([text[:start_idx], cstr_bold(text[start_idx:end_idx], color='red'), text[end_idx:]]), color='black')
     #a = colored(text[:start_idx]) + colored(text[start_idx:end_idx], 'red', 'on_yellow') + colored(text[end_idx:])
     return a
        
@@ -83,13 +85,13 @@ def final_qa_pipeline(file, query):
     if len(lvl1) > 0:
         fnl_rank = qa_ranker(query, [l["docs"] for l in lvl1], top_k_ranker)
         #return (fnl_rank[0]["answer"], str(np.round(100*fnl_rank[0]["score"],2))+"%" , fnl_rank[0]['doc'])
-        return (fnl_rank[0]["answer"], str(np.round(100*fnl_rank[0]["score"],2))+"%" , print_colored(fnl_rank[0]['doc'], fnl_rank[0]['start'], fnl_rank[0]['end']))
+        return (print_colored(fnl_rank[0]['doc'], fnl_rank[0]['start'], fnl_rank[0]['end']), str(np.round(100*fnl_rank[0]["score"],2))+"%" )
         #for fnl_ in fnl_rank:
         #    print("\n")
         #    print_colored(fnl_['doc'], fnl_['start'], fnl_['end'])
         #    print(colored("Confidence score of ") + colored(str(fnl_['score'])[:4], attrs=['bold']))
     else:
-        return ("No match", 0)
+        return ("No match", "0")
         
 examples = [
     [os.path.abspath("dbs-annual-report-2020.pdf"), "how much dividend was paid to shareholders ?"],
@@ -103,7 +105,7 @@ examples = [
 iface = gr.Interface(
    fn = final_qa_pipeline,
    inputs = [gr.inputs.File(label="input pdf file"), gr.inputs.Textbox(label="Question:")],
-   outputs = [gr.outputs.Textbox(label="Answer"), gr.outputs.Textbox(label="Confidence"), gr.outputs.HTML(label="Reference text")],
+   outputs = [gr.outputs.HTML(label="Predicted answer"), gr.outputs.Textbox(label="Confidence") ],
    examples=examples,
    title = "Question Answering on company annual reports",
    description = "Simply upload any annual report pdf you are interested in and ask model a question OR load an example from below."