Update app.py

app.py

@@ -1,10 +1,22 @@
 import streamlit as st
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
+import os
+import subprocess
+from dotenv import load_dotenv
 
-# Function to load model and tokenizer only once
+# Function to load model, tokenizer, and dataset only once
 @st.cache_resource  # This decorator caches the loading process
 def load_resources():
+    load_dotenv()
+
+    huggingface_token = os.getenv("HUGGINGFACE_TOKEN")
+
+    # Set the environment variable using os
+    # huggingface_token = st.secrets["huggingface"]["token"]
+
+    # Run the huggingface-cli login command from the Python script using subprocess
+    subprocess.run(["huggingface-cli", "login", "--token", huggingface_token])
     # Load the pre-trained Llama3 model (or your fine-tuned model)
     tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-1B")
     model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B")