Update app.py

app.py

@@ -2,7 +2,42 @@ import gradio as gr
 import torch
 import numpy as np
 import plotly.graph_objects as go
-from cognitive_net import DynamicCognitiveNet
+from huggingface_hub import hf_hub_download
+from pathlib import Path
+import sys
+import os
+
+# Download model files from hub
+def download_model_files():
+    files = ['memory.py', 'node.py', 'network.py', '__init__.py']
+    repo_id = "VLabTech/cognitive_net"
+    
+    model_dir = Path('cognitive_net')
+    model_dir.mkdir(exist_ok=True)
+    
+    for file in files:
+        try:
+            hf_hub_download(
+                repo_id=repo_id,
+                filename=file,
+                local_dir=model_dir
+            )
+        except Exception as e:
+            print(f"Error downloading {file}: {str(e)}")
+
+    # Add model directory to Python path
+    if str(model_dir.absolute()) not in sys.path:
+        sys.path.append(str(model_dir.absolute()))
+
+# Download files and setup path
+download_model_files()
+
+# Now import the model
+try:
+    from cognitive_net import DynamicCognitiveNet
+except ImportError as e:
+    print(f"Error importing model: {str(e)}")
+    raise
 
 class ModelDemo:
     def __init__(self):
@@ -87,6 +122,8 @@ with gr.Blocks(title="Cognitive Network Demo") as iface:
     - Adaptive structure
     
     Enter a sequence of numbers (comma-separated) to train the model to predict the next number.
+    
+    Model: [VLabTech/cognitive_net](https://huggingface.co/VLabTech/cognitive_net)
     """)
     
     with gr.Row():