Update app.py

app.py

@@ -1,13 +1,16 @@
 import streamlit as st
 import torch
-from transformers import RagTokenizer, RagRetriever, RagSequenceForGeneration
 import pandas as pd
 import pdfplumber
+from transformers import RagTokenizer, RagRetriever, RagSequenceForGeneration
 
-# Load the RAG model and tokenizer
-tokenizer = RagTokenizer.from_pretrained("facebook/rag-sequence-nq", use_auth_token=True)
-retriever = RagRetriever.from_pretrained("facebook/wiki_dpr", use_auth_token=True)
-model = RagSequenceForGeneration.from_pretrained("facebook/rag-sequence-nq", retriever=retriever, use_auth_token=True)
+# Ensure you are logged in with `huggingface-cli login`
+token = "YOUR_HUGGINGFACE_TOKEN"  # Optional if you have logged in via CLI
+
+# Load the tokenizer and model for RAG
+tokenizer = RagTokenizer.from_pretrained("facebook/rag-token-nq", use_auth_token=token)
+retriever = RagRetriever.from_pretrained("facebook/wikipedia-dpr", use_auth_token=token)
+model = RagSequenceForGeneration.from_pretrained("facebook/rag-sequence-nq", retriever=retriever, use_auth_token=token)
 
 # Function to extract text from a PDF file
 def extract_text_from_pdf(pdf_file):
@@ -60,3 +63,4 @@ if st.button("Get Response"):
         response = tokenizer.batch_decode(output, skip_special_tokens=True)[0]
         st.write("### Response:")
         st.write(response)
+