jskim commited on
Commit
3448819
·
1 Parent(s): 300debd

added links to each paper results (replacing textbox with markdown)

Browse files
Files changed (1) hide show
  1. app.py +19 -14
app.py CHANGED
@@ -73,7 +73,7 @@ def get_similar_paper(
73
  input_sentences = sent_tokenize(abstract_text_input)
74
  num_sents = len(input_sentences)
75
 
76
- for aa, (tt, ab, ds) in enumerate(zip(titles, abstracts, doc_scores)):
77
  # Compute sent-level and phrase-level affinity scores for each papers
78
  sent_ids, sent_scores, info, top_pairs_info = get_highlight_info(
79
  sent_model,
@@ -96,7 +96,8 @@ def get_similar_paper(
96
  'doc_score': '%0.3f'%ds,
97
  'source_sentences': input_sentences,
98
  'highlight': word_scores,
99
- 'top_pairs': top_pairs_info
 
100
  }
101
 
102
  end = time.time()
@@ -116,8 +117,9 @@ def get_similar_paper(
116
  summary_out = []
117
  for i in range(top_papers_show):
118
  out_tmp = [
119
- gr.update(value=titles[i], visible=True),
120
- gr.update(value='%0.3f'%doc_scores[i], visible=True) # document affinity
 
121
  ]
122
  tp = results[display_title[i]]['top_pairs']
123
  for j in range(top_num_info_show):
@@ -173,7 +175,9 @@ def change_paper(selected_papers_radio, info={}):
173
  abstract = info[selected_papers_radio]['abstract']
174
  aff_score = info[selected_papers_radio]['doc_score']
175
  highlights = info[selected_papers_radio]['highlight']
176
- return title, abstract, aff_score, highlights['0']
 
 
177
 
178
  else:
179
  return
@@ -206,7 +210,7 @@ Below we describe how to use the tool. Also feel free to check out the [video]()
206
  - Below the list of papers, we highlight relevant parts from the selected paper to different sentences of the submission abstract.
207
  - On the left, you will see individual sentences from the submission abstract to select from.
208
  - On the right, you will see the abstract of the selected paper, with **highlights** incidating relevant parts to the selected sentence.
209
- - **<span style="color:black;background-color:#DB7262;">Red highlights</span>**: sentences with high semantic similarity to the selected sentence.
210
  - **<span style="color:black;background-color:#65B5E3;">Blue highlights</span>**: phrases included in the selected sentence.
211
  - To see relevant parts in a different paper from the reviewer, select the new paper.
212
  -------
@@ -234,12 +238,11 @@ Below we describe how to use the tool. Also feel free to check out the [video]()
234
  # Paper title, score, and top-ranking sentence pairs -- two sentence pairs per paper, three papers
235
  ## ONE BLOCK OF INFO FOR A SINGLE PAPER
236
  ## PAPER1
237
- # TODO add link to each paper
238
  with gr.Row():
239
  with gr.Column(scale=3):
240
- paper_title1 = gr.Textbox(label="From the reviewer's paper:", interactive=False, visible=False)
241
  with gr.Column(scale=1):
242
- affinity1 = gr.Textbox(label='Affinity', interactive=False, value='', visible=False)
243
  with gr.Row() as rel1_1:
244
  with gr.Column(scale=1):
245
  sent_pair_score1_1 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
@@ -267,9 +270,10 @@ Below we describe how to use the tool. Also feel free to check out the [video]()
267
  ## PAPER 2
268
  with gr.Row():
269
  with gr.Column(scale=3):
270
- paper_title2 = gr.Textbox(label="From the reviewer's paper:", interactive=False, visible=False)
271
  with gr.Column(scale=1):
272
- affinity2 = gr.Textbox(label='Affinity', interactive=False, value='', visible=False)
 
273
  with gr.Row() as rel2_1:
274
  with gr.Column(scale=1):
275
  sent_pair_score2_1 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
@@ -297,9 +301,10 @@ Below we describe how to use the tool. Also feel free to check out the [video]()
297
  ## PAPER 3
298
  with gr.Row():
299
  with gr.Column(scale=3):
300
- paper_title3 = gr.Textbox(label="From the reviewer's paper:", interactive=False, visible=False)
301
  with gr.Column(scale=1):
302
- affinity3 = gr.Textbox(label='Affinity', interactive=False, value='', visible=False)
 
303
  with gr.Row() as rel3_1:
304
  with gr.Column(scale=1):
305
  sent_pair_score3_1 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
@@ -336,7 +341,7 @@ Below we describe how to use the tool. Also feel free to check out the [video]()
336
  # selected paper information
337
  with gr.Row(visible=False) as title_row:
338
  with gr.Column(scale=3):
339
- paper_title = gr.Textbox(label='Title', interactive=False)
340
  with gr.Column(scale=1):
341
  affinity= gr.Textbox(label='Affinity', interactive=False, value='')
342
  with gr.Row():
 
73
  input_sentences = sent_tokenize(abstract_text_input)
74
  num_sents = len(input_sentences)
75
 
76
+ for aa, (tt, ab, ds, url) in enumerate(zip(titles, abstracts, doc_scores, paper_urls)):
77
  # Compute sent-level and phrase-level affinity scores for each papers
78
  sent_ids, sent_scores, info, top_pairs_info = get_highlight_info(
79
  sent_model,
 
96
  'doc_score': '%0.3f'%ds,
97
  'source_sentences': input_sentences,
98
  'highlight': word_scores,
99
+ 'top_pairs': top_pairs_info,
100
+ 'url': url
101
  }
102
 
103
  end = time.time()
 
117
  summary_out = []
118
  for i in range(top_papers_show):
119
  out_tmp = [
120
+ #gr.update(value=titles[i], visible=True),
121
+ gr.update(value="#### [%s](%s)"%(titles[i], paper_urls[i]), visible=True),
122
+ gr.update(value='#### Affinity: %0.3f'%doc_scores[i], visible=True) # document affinity
123
  ]
124
  tp = results[display_title[i]]['top_pairs']
125
  for j in range(top_num_info_show):
 
175
  abstract = info[selected_papers_radio]['abstract']
176
  aff_score = info[selected_papers_radio]['doc_score']
177
  highlights = info[selected_papers_radio]['highlight']
178
+ url = info[selected_papers_radio]['url']
179
+ title_out = '#### [%s](%s)'%(title, url) # output in format of markdown
180
+ return title_out, abstract, aff_score, highlights['0']
181
 
182
  else:
183
  return
 
210
  - Below the list of papers, we highlight relevant parts from the selected paper to different sentences of the submission abstract.
211
  - On the left, you will see individual sentences from the submission abstract to select from.
212
  - On the right, you will see the abstract of the selected paper, with **highlights** incidating relevant parts to the selected sentence.
213
+ - **<span style="color:black;background-color:#DB7262;">Red highlights</span>**: sentences with high semantic similarity to the selected sentence. The darker the color, the higher the similarity.
214
  - **<span style="color:black;background-color:#65B5E3;">Blue highlights</span>**: phrases included in the selected sentence.
215
  - To see relevant parts in a different paper from the reviewer, select the new paper.
216
  -------
 
238
  # Paper title, score, and top-ranking sentence pairs -- two sentence pairs per paper, three papers
239
  ## ONE BLOCK OF INFO FOR A SINGLE PAPER
240
  ## PAPER1
 
241
  with gr.Row():
242
  with gr.Column(scale=3):
243
+ paper_title1 = gr.Markdown(value='', visible=False)
244
  with gr.Column(scale=1):
245
+ affinity1 = gr.Markdown(value='', visible=False)
246
  with gr.Row() as rel1_1:
247
  with gr.Column(scale=1):
248
  sent_pair_score1_1 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
 
270
  ## PAPER 2
271
  with gr.Row():
272
  with gr.Column(scale=3):
273
+ paper_title2 = gr.Markdown(value='', visible=False)
274
  with gr.Column(scale=1):
275
+ #affinity2 = gr.Textbox(label='Affinity', interactive=False, value='', visible=False)
276
+ affinity2 = gr.Markdown(value='', visible=False)
277
  with gr.Row() as rel2_1:
278
  with gr.Column(scale=1):
279
  sent_pair_score2_1 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
 
301
  ## PAPER 3
302
  with gr.Row():
303
  with gr.Column(scale=3):
304
+ paper_title3 = gr.Markdown(value='', visible=False)
305
  with gr.Column(scale=1):
306
+ # affinity3 = gr.Textbox(label='Affinity', interactive=False, value='', visible=False)
307
+ affinity3 = gr.Markdown(value='', visible=False)
308
  with gr.Row() as rel3_1:
309
  with gr.Column(scale=1):
310
  sent_pair_score3_1 = gr.Textbox(label='Sentence Relevance', interactive=False, value='', visible=False)
 
341
  # selected paper information
342
  with gr.Row(visible=False) as title_row:
343
  with gr.Column(scale=3):
344
+ paper_title = gr.Markdown(value='')
345
  with gr.Column(scale=1):
346
  affinity= gr.Textbox(label='Affinity', interactive=False, value='')
347
  with gr.Row():