Update app.py

app.py

@@ -1,17 +1,27 @@
-from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+# from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+# import gradio as grad
+# import ast
+# # mdl_name = "deepset/roberta-base-squad2"
+# mdl_name = "distilbert-base-cased-distilled-squad"
+# my_pipeline = pipeline('question-answering', model=mdl_name, tokenizer=mdl_name)
+
+# def answer_question(question,context):
+#     text= "{"+"'question': '"+question+"','context': '"+context+"'}"
+    
+#     di=ast.literal_eval(text)
+#     response = my_pipeline(di)
+#     return response
+# grad.Interface(answer_question, inputs=["text","text"], outputs="text").launch()
+
+from transformers import pipeline
 import gradio as grad
-import ast
-# mdl_name = "deepset/roberta-base-squad2"
-mdl_name = "distilbert-base-cased-distilled-squad"
-my_pipeline = pipeline('question-answering', model=mdl_name, tokenizer=mdl_name)
+mdl_name = "Helsinki-NLP/opus-mt-en-de"
+opus_translator = pipeline("translation", model=mdl_name)
 
-def answer_question(question,context):
-    text= "{"+"'question': '"+question+"','context': '"+context+"'}"
+def translate(text):
     
-    di=ast.literal_eval(text)
-    response = my_pipeline(di)
+    response = opus_translator(text)
     return response
-grad.Interface(answer_question, inputs=["text","text"], outputs="text").launch()
-
+grad.Interface(translate, inputs=["text",], outputs="text").launch()