Update app.py

app.py

@@ -1,6 +1,10 @@
 import os
 import gradio as gr
-from huggingface_hub import HfApi
+import random
+import tempfile
+import importlib.util
+import sys
+from huggingface_hub import snapshot_download, HfApi
 from huggingface_hub.utils import RepositoryNotFoundError, HfHubHTTPError
 
 # Get the secret model ID
@@ -8,19 +12,33 @@ MODEL_ID = os.getenv("HF_MODEL_ID")
 if not MODEL_ID:
     raise RuntimeError("Secret HF_MODEL_ID not set in environment!")
 
-# Create API instance
-api = HfApi()
-
 # Function to generate random number using the model
 def generate_random_number():
     try:
-        # Import the model dynamically - this keeps the implementation hidden
-        from model import RandomNumberGenerator
-        
-        # Use the model to generate a random number
-        generator = RandomNumberGenerator()
-        number = generator.generate()
-        return f"Generated random number: {number}"
+        # Download the model files to a temporary directory
+        with tempfile.TemporaryDirectory() as temp_dir:
+            # Download the private repo (requires authentication)
+            model_path = snapshot_download(
+                repo_id=MODEL_ID,
+                token=os.getenv("HF_TOKEN"),  # You'll need to add this secret too
+                local_dir=temp_dir
+            )
+            
+            # Dynamically import the model module
+            sys.path.insert(0, model_path)
+            
+            # Now we can import from the downloaded model
+            from model import RandomNumberGenerator
+            
+            # Use the model to generate a random number
+            generator = RandomNumberGenerator()
+            number = generator.generate()
+            
+            # Clean up path
+            sys.path.remove(model_path)
+            
+            return f"Generated random number: {number}"
+            
     except (RepositoryNotFoundError, HfHubHTTPError) as e:
         return f"Error accessing model: {str(e)}"
     except Exception as e: