Update app.py

app.py

@@ -66,9 +66,13 @@ def keyphrase_generator(article_link, model_1, model_2, max_num_keywords):
   corpus_embeddings = model_1.encode(clean_sentences_new)
   sim_mat = np.zeros([len(clean_sentences_new), len(clean_sentences_new)])
   for i in range(len(clean_sentences_new)):
+    len_embeddings=(len(corpus_embeddings[i]))
     for j in range(len(clean_sentences_new)):
-      if i != j:
-        sim_mat[i][j] = cosine_similarity(corpus_embeddings[i].reshape(1,768), corpus_embeddings[j].reshape(1,768))[0,0]
+      if i != j:      
+        if(len_embeddings == 1024):
+          sim_mat[i][j] = cosine_similarity(corpus_embeddings[i].reshape(1,1024), corpus_embeddings[j].reshape(1,1024))[0,0]
+        elif(len_embeddings == 768):
+          sim_mat[i][j] = cosine_similarity(corpus_embeddings[i].reshape(1,768), corpus_embeddings[j].reshape(1,768))[0,0]
   nx_graph = nx.from_numpy_array(sim_mat)
   scores = nx.pagerank(nx_graph)
   sentences=((scores[i],s) for i,s in enumerate(corpus))
@@ -108,20 +112,21 @@ def keyphrase_generator(article_link, model_1, model_2, max_num_keywords):
 igen=gr.Interface(keyphrase_generator, 
                   inputs=[gr.inputs.Textbox(lines=1, placeholder="Provide an online health article web link here",default="", label="Article web link"),
                       gr.inputs.Dropdown(choices=['sentence-transformers/all-mpnet-base-v2',
-                                                 'sentence-transformers/all-mpnet-base-v1',                                             
-                                                 'sentence-transformers/all-distilroberta-v1',                                                 
+                                                 'sentence-transformers/all-mpnet-base-v1',                       
+                                                 'sentence-transformers/all-distilroberta-v1',
+                                                 'sentence-transformers/gtr-t5-large',
                                                  'pritamdeka/S-Bluebert-snli-multinli-stsb',
-                                                 'pritamdeka/S-Biomed-Roberta-snli-multinli-stsb',
+                                                 'pritamdeka/S-Biomed-Roberta-snli-multinli-stsb',                                                 
                                                  'sentence-transformers/stsb-mpnet-base-v2',
                                                  'sentence-transformers/stsb-roberta-base-v2',
                                                  'sentence-transformers/stsb-distilroberta-base-v2',
-                                                 'sentence-transformers/nli-roberta-base-v2',
-                                                 'sentence-transformers/nli-mpnet-base-v2',
-                                                 'sentence-transformers/nli-distilroberta-base-v2'], 
+                                                 'sentence-transformers/sentence-t5-large',
+                                                 'sentence-transformers/sentence-t5-base'], 
                                         type="value", 
                                         default='pritamdeka/S-Biomed-Roberta-snli-multinli-stsb', 
-                                        label="Select any model for TextRank from the list below"),
+                                        label="Select any SBERT model for TextRank from the list below"),
                      gr.inputs.Dropdown(choices=['sentence-transformers/paraphrase-mpnet-base-v2',
+                                                 'sentence-transformers/all-mpnet-base-v1',
                                                  'sentence-transformers/paraphrase-distilroberta-base-v1',
                                                  'sentence-transformers/paraphrase-xlm-r-multilingual-v1',
                                                  'sentence-transformers/paraphrase-multilingual-mpnet-base-v2',
@@ -135,8 +140,8 @@ igen=gr.Interface(keyphrase_generator,
                                                  'sentence-transformers/paraphrase-MiniLM-L3-v2',
                                                  'sentence-transformers/all-MiniLM-L6-v2'], 
                                         type="value", 
-                                        default='sentence-transformers/paraphrase-distilroberta-base-v1', 
-                                        label="Select any model for keyphrases from the list below"),                     
+                                        default='sentence-transformers/all-mpnet-base-v1', 
+                                        label="Select any SBERT model for keyphrases from the list below"),                     
                      gr.inputs.Slider(minimum=5, maximum=30, step=1, default=10, label="Max Keywords")],
              outputs=gr.outputs.Textbox(type="auto", label="Output"), theme="peach", 
              title="Health Article Keyphrase Generator",