Update app.py

app.py

@@ -6,6 +6,7 @@ import PyPDF2
 import pandas as pd
 import torch
 import time
+import os
 
 # Check if 'peft' is installed
 try:
@@ -23,8 +24,8 @@ st.set_page_config(
     layout="centered"
 )
 
-# Hardcoded Hugging Face token (replace with your actual token)
-HF_TOKEN = "your_hugging_face_token_here"
+# Load Hugging Face token from environment variable
+HF_TOKEN = os.getenv("HF_TOKEN")  # Set this in your environment, e.g., via export HF_TOKEN="your_token"
 
 # Model names
 BASE_MODEL_NAME = "google-bert/bert-base-uncased"
@@ -80,7 +81,7 @@ def process_file(uploaded_file):
 def load_model(hf_token, model_type, selected_model):
     try:
         if not hf_token:
-            st.error("🔐 Authentication required! Please provide a valid Hugging Face token.")
+            st.error("🔐 Authentication required! Please set the HF_TOKEN environment variable.")
             return None
         
         login(token=hf_token)
@@ -163,7 +164,7 @@ if prompt := st.chat_input("Ask your inspection question..."):
     if "model" not in st.session_state or st.session_state.get("model_type") != model_type:
         model_data = load_model(HF_TOKEN, model_type, selected_model)
         if model_data is None:
-            st.error("Failed to load model. Please check your token and try again.")
+            st.error("Failed to load model. Please ensure HF_TOKEN is set correctly.")
             st.stop()
             
         st.session_state.model, st.session_state.tokenizer = model_data
@@ -177,7 +178,7 @@ if prompt := st.chat_input("Ask your inspection question..."):
         st.markdown(prompt)
     st.session_state.messages.append({"role": "user", "content": prompt})
 
-    # Process file
+    # Process Rank
     file_context = process_file(uploaded_file)
     
     # Generate response with KV caching