Update app.py

app.py

@@ -9,7 +9,10 @@ from pathlib import Path
 from transformers import AutoModelForCausalLM, AutoTokenizer
 from peft import PeftModel
 
-#login(token=os.environ.get("HF_TOKEN_LLAMA"))
+
+HF_TOKEN_LLAMA = os.environ.get("HF_TOKEN_LLAMA")
+login(token=HF_TOKEN_LLAMA)
+
 HF_TOKEN = os.environ.get("HF_TOKEN") #get HF_TOKEN 
 login(token=HF_TOKEN)
 
@@ -62,23 +65,35 @@ repo_dir = snapshot_download(
     repo_id=REPO_ID,
     repo_type=REPO_TYPE,
     token=HF_TOKEN,
-    cache_dir="private_space_cache"
+    cache_dir="private_space_cache",
+    force_download=True  # Forces redownload
 )
 
 # The fine-tuned model is located in "fine_tuned_llama3" inside the Space
 fine_tuned_model_path = os.path.join(repo_dir, "fine_tuned_llama3")
 
+
+adapter_config_path = os.path.join(fine_tuned_model_path, "adapter_config.json")
+
+if not os.path.exists(adapter_config_path):
+    raise FileNotFoundError(f"adapter_config.json not found in {fine_tuned_model_path}. Check if the model was downloaded correctly.")
+
 # Verify the model path
 if not os.path.exists(fine_tuned_model_path):
     raise FileNotFoundError(f"Fine-tuned model not found at {fine_tuned_model_path}")
 
+
+print("Downloaded Model Path:", fine_tuned_model_path)
+print("Files in Model Directory:", os.listdir(fine_tuned_model_path))
+
+
 # Add repo directory to sys.path
 sys.path.append(repo_dir)
 
 # Load the base model
 base_model = AutoModelForCausalLM.from_pretrained(
     "meta-llama/Meta-Llama-3-8B",
-    token=HF_TOKEN
+    token=HF_TOKEN_LLAMA
 )
 
 # Load fine-tuned adapter (PEFT)