Update app.py

app.py

@@ -113,13 +113,52 @@ def keyphrase_generator(article_link, model_1, model_2, max_num_keywords):
   return keywords
 
 igen=gr.Interface(keyphrase_generator, 
-             inputs=[gr.inputs.Textbox(lines=3, placeholder="Provide article link here", label="Article link"),gr.inputs.Textbox(lines=1, placeholder="SBERT model",default="all-mpnet-base-v2", label="Provide any SBERT model for TextRank (e.g. all-mpnet-base-v2)"),gr.inputs.Textbox(lines=1, placeholder="SBERT model",default="all-distilroberta-v1",label="Provide any SBERT model for Keyphrases (e.g. all-distilroberta-v1)"),gr.inputs.Slider(minimum=5, maximum=30, step=1, default=10, label="Max number of keyphrases to show")], 
+                  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/paraphrase-mpnet-base-v2',
+                                                 'sentence-transformers/all-distilroberta-v1',
+                                                 'sentence-transformers/paraphrase-distilroberta-base-v1',
+                                                 'sentence-transformers/paraphrase-xlm-r-multilingual-v1',
+                                                 'sentence-transformers/paraphrase-multilingual-mpnet-base-v2',
+                                                 'sentence-transformers/paraphrase-albert-small-v2',
+                                                 'sentence-transformers/paraphrase-albert-base-v2',
+                                                 'pritamdeka/S-Bluebert-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'], 
+                                        type="value", 
+                                        default='sentence-transformers/all-mpnet-base-v2', 
+                                        label="Select any model for TextRank from the list below"),
+                     gr.inputs.Dropdown(choices=['sentence-transformers/paraphrase-mpnet-base-v2',
+                                                 'sentence-transformers/paraphrase-distilroberta-base-v1',
+                                                 'sentence-transformers/paraphrase-xlm-r-multilingual-v1',
+                                                 'sentence-transformers/paraphrase-multilingual-mpnet-base-v2',
+                                                 'sentence-transformers/paraphrase-albert-small-v2',
+                                                 'sentence-transformers/paraphrase-albert-base-v2',                                                
+                                                 'sentence-transformers/paraphrase-MiniLM-L12-v2',
+                                                 'sentence-transformers/paraphrase-MiniLM-L6-v2',
+                                                 'sentence-transformers/all-MiniLM-L12-v2',
+                                                 'sentence-transformers/all-distilroberta-v1',
+                                                 'sentence-transformers/paraphrase-TinyBERT-L6-v2',
+                                                 'sentence-transformers/paraphrase-MiniLM-L3-v2',
+                                                 'sentence-transformers/all-MiniLM-L6-v2'], 
+                                        type="value", 
+                                        default='sentence-transformers/all-distilroberta-v1', 
+                                        label="Select any model for keyphrases from the list below"),                     
+                     gr.inputs.Slider(minimum=5, maximum=30, step=1, default=10, label="Max Keywords")],
              outputs="text", theme="huggingface", 
              title="Health Article Keyphrase Generator", 
              description="Generates the keyphrases from an online health article which best describes the article.",
-             article= "The work is based on a part of the paper <a href=https://dl.acm.org/doi/10.1145/3487664.3487701>Unsupervised Keyword Combination Query Generation from Online Health Related Content for Evidence-Based Fact Checking</a>." 
-             "\t It uses the TextRank algorithm with SBERT to first find the top sentences and then extracts the keyphrases from those sentences using scispaCy and SBERT."
+             article= "The work is based on a part of the paper provided <a href=https://dl.acm.org/doi/10.1145/3487664.3487701>here</a>." 
+             "\t It uses the TextRank algorithm with SBERT to first find the top sentences and then extracts the keyphrases from those sentences using scispaCy" 
+             "\t and SBERT."
              "\t The list of SBERT models required in the textboxes can be found in <a href=www.sbert.net/docs/pretrained_models.html>SBERT Pre-trained models hub</a>."
              "\t The default model names are provided which can be changed from the list of pretrained models. "
              "\t The value of output keyphrases can be changed. The default value is 10, minimum is 5 and a maximum value of 30.")
+             
 igen.launch(share=True)