relevance scores in markdown

app.py

@@ -129,7 +129,8 @@ def get_similar_paper(
         tp = results[display_title[i]]['top_pairs']
         for j in range(top_num_info_show):
             out_tmp += [
-                gr.update(value='%0.3f'%tp[j]['score'], visible=True), # sentence relevance
+                #gr.update(value='%0.3f'%tp[j]['score'], visible=True), # sentence relevance
+                gr.update(value='Sentence Relevance:\n%0.3f'%tp[j]['score'], visible=True), # sentence relevance
                 tp[j]['query']['original'],
                 tp[j]['query'],
                 tp[j]['candidate']['original'],
@@ -202,6 +203,7 @@ with gr.Blocks() as demo:
     # Text description about the app and disclaimer
     ### TEXT Description
     # TODO add instruction video link
+    # TODO shorten the instruction and make it clearer
     gr.Markdown(
         """
 # Paper Matching Helper
@@ -251,6 +253,7 @@ Below we describe how to use the tool. Also feel free to check out [this video](
     # Paper title, score, and top-ranking sentence pairs -- two sentence pairs per paper, three papers
     ## ONE BLOCK OF INFO FOR A SINGLE PAPER
     ## PAPER1 
+    # TODO hovering instructions
     with gr.Row():
         with gr.Column(scale=3):
             paper_title1 = gr.Markdown(value='', visible=False)
@@ -258,7 +261,7 @@ Below we describe how to use the tool. Also feel free to check out [this video](
             affinity1 = gr.Markdown(value='', visible=False)
     with gr.Row() as rel1_1:
         with gr.Column(scale=1):
-            sent_pair_score1_1 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
+            sent_pair_score1_1 = gr.Markdown(interactive=False, value='', visible=False)
         with gr.Column(scale=4):
             sent_pair_source1_1 = gr.Textbox(label='Sentence from Submission', visible=False)
             sent_pair_source1_1_hl = gr.components.Interpretation(sent_pair_source1_1)
@@ -267,7 +270,7 @@ Below we describe how to use the tool. Also feel free to check out [this video](
             sent_pair_candidate1_1_hl = gr.components.Interpretation(sent_pair_candidate1_1)
     with gr.Row() as rel1_2:
         with gr.Column(scale=1):
-            sent_pair_score1_2 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
+            sent_pair_score1_2 = gr.Markdown(interactive=False, value='', visible=False)
         with gr.Column(scale=4):
             sent_pair_source1_2 = gr.Textbox(label='Sentence from Submission', visible=False)
             sent_pair_source1_2_hl = gr.components.Interpretation(sent_pair_source1_2)
@@ -289,7 +292,7 @@ Below we describe how to use the tool. Also feel free to check out [this video](
             affinity2 = gr.Markdown(value='', visible=False)
     with gr.Row() as rel2_1:
         with gr.Column(scale=1):
-            sent_pair_score2_1 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
+            sent_pair_score2_1 = gr.Markdown(interactive=False, value='', visible=False)
         with gr.Column(scale=4):
             sent_pair_source2_1 = gr.Textbox(label='Sentence from Submission', visible=False)
             sent_pair_source2_1_hl = gr.components.Interpretation(sent_pair_source2_1)
@@ -298,7 +301,7 @@ Below we describe how to use the tool. Also feel free to check out [this video](
             sent_pair_candidate2_1_hl = gr.components.Interpretation(sent_pair_candidate2_1)
     with gr.Row() as rel2_2:
         with gr.Column(scale=1):
-            sent_pair_score2_2 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
+            sent_pair_score2_2 = gr.Markdown(interactive=False, value='', visible=False)
         with gr.Column(scale=4):
             sent_pair_source2_2 = gr.Textbox(label='Sentence from Submission', visible=False)
             sent_pair_source2_2_hl = gr.components.Interpretation(sent_pair_source2_2)
@@ -320,7 +323,7 @@ Below we describe how to use the tool. Also feel free to check out [this video](
             affinity3 = gr.Markdown(value='', visible=False)
     with gr.Row() as rel3_1:
         with gr.Column(scale=1):
-            sent_pair_score3_1 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
+            sent_pair_score3_1 = gr.Markdown(interactive=False, value='', visible=False)
         with gr.Column(scale=4):
             sent_pair_source3_1 = gr.Textbox(label='Sentence from Submission', visible=False)
             sent_pair_source3_1_hl = gr.components.Interpretation(sent_pair_source3_1)
@@ -329,7 +332,7 @@ Below we describe how to use the tool. Also feel free to check out [this video](
             sent_pair_candidate3_1_hl = gr.components.Interpretation(sent_pair_candidate3_1)
     with gr.Row() as rel3_2:
         with gr.Column(scale=1):
-            sent_pair_score3_2 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
+            sent_pair_score3_2 = gr.Markdown(interactive=False, value='', visible=False)
         with gr.Column(scale=4):
             sent_pair_source3_2 = gr.Textbox(label='Sentence from Submission', visible=False)
             sent_pair_source3_2_hl = gr.components.Interpretation(sent_pair_source3_2)
@@ -484,4 +487,6 @@ Below we describe how to use the tool. Also feel free to check out [this video](
     )
     
 if __name__ == "__main__":
+    #demo.queue().launch(share=True) 
     demo.queue().launch() 
+    # TODO how to disable dark mode?