updated app

app.py

@@ -1,26 +1,25 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
-from huggingface_hub import login
 import os
 from dotenv import load_dotenv
 import logging
 import sys  # Ensure sys is imported
+from huggingface_hub import login
 
 # Load environment variables
 load_dotenv()
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s', stream=sys.stdout)
 
-# Login to Hugging Face using the token
-hf_token = os.getenv('HUGGING_FACE_TOKEN')
-if hf_token:
-    #login(token=hf_token)
-    os.environ["HUGGINGFACEHUB_API_TOKEN"] = hf_token
-else:
-    raise ValueError("HUGGING_FACE_TOKEN environment variable not set.")
+# Authenticate with Hugging Face
+hf_token = os.environ.get("HUGGINGFACE_TOKEN")
+if not hf_token:
+    raise ValueError("HUGGINGFACE_TOKEN not found in environment variables")
+login(token=hf_token)
 
 # Load the Llama-3.1-8B model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B")
-model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B")
+model_name = "meta-llama/Llama-3.1-8B"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
 # Function to generate a formatted email
 def generate_email(recipient_name, recipient_email, industry, recipient_role, details):