Update app.py

app.py

@@ -3,13 +3,18 @@ import numpy as np
 import torch
 from transformers import DistilBertTokenizer, DistilBertForQuestionAnswering
 
-@st.cache(allow_output_mutation=True)
+st.set_page_config(page_title="Question Answering Tool", page_icon=":mag_right:")
+
+@st.cache_resource
 def load_model():
     model = DistilBertForQuestionAnswering.from_pretrained("distilbert-base-uncased-distilled-squad")
     tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-uncased-distilled-squad")
     return model, tokenizer
 
 def get_answer(question, text, tokenizer, model):
+    if "your name" in question.lower():
+        return "My name is Numini, full form NativUttarMini, created by Sanju Debnath at University of Calcutta."
+    
     inputs = tokenizer(question, text, return_tensors="pt", truncation=True, padding=True)
     with torch.no_grad():
         outputs = model(**inputs)
@@ -20,8 +25,6 @@ def get_answer(question, text, tokenizer, model):
     return answer
 
 def main():
-    st.set_page_config(page_title="Question Answering Tool", page_icon=":mag_right:")
-
     st.write("# Question Answering Tool \n"
              "This tool will help you find answers to your questions about the text you provide. \n"
              "Please enter your question and the text you want to search in the boxes below.")