Update app.py

app.py

@@ -14,16 +14,20 @@ import sentencepiece
 import huggingface_hub
 from transformers import TrainingArguments, Trainer
 
+# Debug: Print all environment variables to verify 'LLama' is present
+print("Environment variables:", dict(os.environ))
+
 # Retrieve the token from Hugging Face Space secrets
-llama = os.getenv("llama:levi put token here")  # Token expected as env variable 'llama'
-if not llama:
-    raise ValueError("llama token not found in environment variables. Please set it in Hugging Face Space secrets under 'Settings' > 'Secrets' as 'llama'.")
+# Token placement: LLama:levi put token here
+LLama = os.getenv("LLama")  # Retrieves the value of the 'LLama' environment variable
+if not LLama:
+    raise ValueError("LLama token not found in environment variables. Please set it in Hugging Face Space secrets under 'Settings' > 'Secrets' as 'LLama'.")
 
 # Debug: Print the token to verify it's being read (remove this in production)
-print(f"Retrieved llama token: {llama[:5]}... (first 5 chars for security)")
+print(f"Retrieved LLama token: {LLama[:5]}... (first 5 chars for security)")
 
 # Authenticate with Hugging Face
-huggingface_hub.login(token=llama)
+huggingface_hub.login(token=LLama)
 
 # Model setup
 MODEL_ID = "meta-llama/Llama-2-7b-hf"
@@ -146,7 +150,7 @@ def train_ui(files):
         return "Training completed! Model saved to ./fine_tuned_llama_healthcare"
 
     except Exception as e:
-        return f"Error: {str(e)}. Please check file format, dependencies, or the llama token."
+        return f"Error: {str(e)}. Please check file format, dependencies, or the LLama token."
 
 # Gradio UI
 with gr.Blocks(title="Healthcare Fraud Detection Fine-Tuning") as demo: