Enhance logging in load_model function

app.py

@@ -24,16 +24,22 @@ def load_model():
     peft_model_path = "yitzashapiro/FDA-guidance-zephyr-7b-beta-PEFT"
     
     try:
+        HF_API_TOKEN = os.getenv("HF_API_TOKEN")
+        st.write("Loading tokenizer...")
         tokenizer = AutoTokenizer.from_pretrained(
             model_path,
-            trust_remote_code=True  # Added parameter
+            trust_remote_code=True,
+            use_auth_token=HF_API_TOKEN  # Use token for private models
         )
+        st.write("Loading model...")
         model = AutoModelForCausalLM.from_pretrained(
             model_path,
             device_map="auto",
-            torch_dtype=torch.float16,  # Adjust if necessary
-            trust_remote_code=True  # Added parameter
+            torch_dtype=torch.float16,
+            trust_remote_code=True,
+            use_auth_token=HF_API_TOKEN  # Use token for private models
         ).eval()
+        st.write("Loading PEFT adapter...")
         model.load_adapter(peft_model_path)
         st.success("Model loaded successfully.")
     except Exception as e:
@@ -83,12 +89,12 @@ def generate_response(tokenizer, model, user_input):
 def main():
     apply_custom_css()
     
-    st.title("FDA Submissions Wizard")
-    st.write("I've Been Trained On Submissions To and Responses From FDA.")
+    st.title("FDA NDA Submission Assistant")
+    st.write("Ask the model about submitting an NDA to the FDA.")
     
     tokenizer, model = load_model()
     
-    user_input = st.text_input("Enter your question:", "How Do I Learn More About The FDA?")
+    user_input = st.text_input("Enter your question:", "What's the best way to submit an NDA to the FDA?")
     
     if st.button("Generate Response"):
         if user_input.strip() == "":
@@ -103,4 +109,4 @@ def main():
                 st.error(f"An error occurred: {e}")
 
 if __name__ == "__main__":
-    main()
+    main()