Update app.py

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 import os
 import faiss
 import numpy as np
-from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+from transformers import AutoTokenizer, AutoModelForCausalLM
 from sentence_transformers import SentenceTransformer
 from PyPDF2 import PdfReader
 from docx import Document
@@ -14,28 +14,29 @@ def load_models():
     # Text embedding model
     embed_model = SentenceTransformer('sentence-transformers/all-mpnet-base-v2')
     
-    TOKEN = "TOKEN"  
-
-    # IBM Granite models with proper token and trust_remote_code settings
+    # Replace with your actual token from Hugging Face
+    TOKEN = "TOKEN"
+    
+    # IBM Granite models with proper token usage
     summary_tokenizer = AutoTokenizer.from_pretrained(
         "ibm/granite-13b-instruct-v2",
-        token=TOKEN,
+        use_auth_token=TOKEN,
         trust_remote_code=True
     )
     summary_model = AutoModelForCausalLM.from_pretrained(
         "ibm/granite-13b-instruct-v2",
-        token=TOKEN,
+        use_auth_token=TOKEN,
         trust_remote_code=True
     )
     
     qa_tokenizer = AutoTokenizer.from_pretrained(
         "ibm/granite-13b-instruct-v2",
-        token=TOKEN,
+        use_auth_token=TOKEN,
         trust_remote_code=True
     )
     qa_model = AutoModelForCausalLM.from_pretrained(
         "ibm/granite-13b-instruct-v2",
-        token=TOKEN,
+        use_auth_token=TOKEN,
         trust_remote_code=True
     )