Update app.py

app.py

@@ -1,15 +1,26 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, Text2TextGenerationPipeline
 
-pipe = Text2TextGenerationPipeline(model = AutoModelForSeq2SeqLM.from_pretrained("jpelhaw/t5-word-sense-disambiguation"),tokenizer = AutoTokenizer.from_pretrained("jpelhaw/t5-word-sense-disambiguation"), )
+pipe = Text2TextGenerationPipeline(model = AutoModelForSeq2SeqLM.from_pretrained("jpelhaw/t5-word-sense-disambiguation"),
+tokenizer = AutoTokenizer.from_pretrained("jpelhaw/t5-word-sense-disambiguation"))
 
+def wsd_gen(word, context, d1, d2, d3):
+            question = 'question: question: which description describes the word' + ' " ' + word + ' " '
+            descriptions_context = 'best in the following context? \descriptions:[  " ' + d1 + '" , " ' + d2 + ' " , or " '+ d3 + ' " ] context: ' + context + "'"
+            raw_input = question + descriptions_context
+            output = pipe(raw_input)[0]['generated_text']
+            return output
 
-examples = ["""'question: which description describes the word " java " best in the following context? descriptions: [ " A drink consisting of an infusion of ground coffee beans " , " a platform-independent programming lanugage " , or " an island in Indonesia to the south of Borneo " ] context: I like to drink "java" in the morning ."""]
-print(pipe(examples[0]))
 
-gr.Interface.from_pipeline(pipe,
-            inputs = "textbox",
-            outputs="textbox",
+
+examples = [["java", 'I like to drink "java" in the morning.', " A drink consisting of an infusion of ground coffee beans. " ,  " a platform-independent programming language.", " an island in Indonesia to the south of Borneo. "]]
+gr.Interface(wsd_gen,
+            inputs = [gr.inputs.Textbox(lines=1, placeholder= "Enter Word to Mask", default="", label = "Based on the context, which description best matches this word: "),
+                        gr.inputs.Textbox(lines=1, placeholder="Enter context", default="", label = "context: "),
+                        gr.inputs.Textbox(lines=1, placeholder="Enter description", default="", label = "description 1: "),
+                        gr.inputs.Textbox(lines=1, placeholder="Enter description", default="", label = "description 2: "),
+                        gr.inputs.Textbox(lines=1, placeholder="Enter description", default="", label = "description 3: ")],
+            outputs= "textbox",
             examples = examples,
             title = "word sense disambiguation", 
             allow_flagging="never").launch(inbrowser=True)