Update app.py

app.py

@@ -3,6 +3,9 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 from huggingface_hub import Repository
 import os
 
+# Retrieve the Hugging Face token from Streamlit secrets
+token = st.secrets["HUGGINGFACE_TOKEN"]  # Ensure your secret key is "HUGGINGFACE_TOKEN"
+
 # Define model directory and Hugging Face repo name
 model_dir = "./tuned_model"  # Directory where the fine-tuned model is saved
 repo_name = "krisha06/Python_tutor"  # Replace with your Hugging Face repo name
@@ -20,7 +23,7 @@ if upload_model_button:
     if os.path.exists(model_dir):
         # Initialize the Hugging Face Repository and push model to the Hub
         repo = Repository(local_dir=model_dir, clone_from=repo_name)
-        repo.push_to_hub()
+        repo.push_to_hub(token=token)  # Use the token from Streamlit secrets
         st.success("Model uploaded to Hugging Face Hub successfully!")
     else:
         st.error("Model directory does not exist. Please make sure the model is fine-tuned first.")
@@ -30,7 +33,6 @@ st.header("Ask Me Any Coding Question!")
 
 # Load model and tokenizer (either from local directory or Hugging Face Hub)
 model_name = repo_name  # Use the repo name if the model is on Hugging Face Hub, else use local dir
-token = "<HUGGINGFACE_TOKEN>"  # Replace with your Hugging Face token if the model is private
 
 if os.path.exists(model_dir):
     # Load the model and tokenizer from the local directory