Update app.py

app.py

@@ -3,20 +3,43 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 from datetime import datetime, timezone
 import os
 from huggingface_hub import login
+from huggingface_hub.utils import RepositoryNotFoundError, HfHubHTTPError
 
-# Login to Hugging Face Hub
-login(token=os.getenv("HUGGING_FACE_HUB_TOKEN"))
+def initialize_model():
+    try:
+        # Login to Hugging Face Hub
+        login(token=os.getenv("HUGGING_FACE_HUB_TOKEN"))
+        
+        # Initialize the model and tokenizer with auth
+        model_id = "CohereLabs/c4ai-command-a-03-2025"
+        tokenizer = AutoTokenizer.from_pretrained(
+            model_id,
+            use_auth_token=True
+        )
+        model = AutoModelForCausalLM.from_pretrained(
+            model_id,
+            use_auth_token=True
+        )
+        return True, model, tokenizer
+    except RepositoryNotFoundError:
+        return False, "Model repository not found. Please check the model ID.", None
+    except HfHubHTTPError as e:
+        if e.response.status_code == 401:
+            return False, "Authentication failed. Please check your token permissions.", None
+        elif e.response.status_code == 403:
+            return False, "Access denied. Please ensure you have access to this model.", None
+        else:
+            return False, f"An error occurred: {str(e)}", None
+    except Exception as e:
+        return False, f"Unexpected error: {str(e)}", None
 
-# Initialize the model and tokenizer with auth
-model_id = "CohereLabs/c4ai-command-a-03-2025"
-tokenizer = AutoTokenizer.from_pretrained(
-    model_id,
-    use_auth_token=True  # Add authentication
-)
-model = AutoModelForCausalLM.from_pretrained(
-    model_id,
-    use_auth_token=True  # Add authentication
-)
+# Initialize model and handle potential errors
+success, result, tokenizer = initialize_model()
+if not success:
+    print(f"Error initializing model: {result}")
+    # You might want to raise an exception here or handle the error differently
+else:
+    model = result
 
 def get_timestamp():
     """Get current UTC datetime in specified format"""
@@ -30,40 +53,37 @@ def format_system_info():
     )
 
 def chat(message, history):
+    if not success:
+        return [(message, f"Error: {result}")]
+    
     if history is None:
         history = []
     
-    # Add system information
-    system_info = format_system_info()
-    
-    # Format messages with the c4ai-command-a-03-2025 chat template
-    messages = [{"role": "user", "content": message}]
-    input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True)
-    
-    # Generate response
-    gen_tokens = model.generate(
-        input_ids,
-        max_new_tokens=100,
-        do_sample=True,
-        temperature=0.3,
-    )
-    
-    # Decode response
-    gen_text = tokenizer.decode(gen_tokens[0])
-    
-    # Format the full response with system info
-    formatted_response = f"{system_info}\n{gen_text}"
-    history.append((message, formatted_response))
-    return history
-
-# Create custom theme
-theme = gr.themes.Default().set(
-    body_background_fill="#f0f8ff",
-    block_background_fill="#ffffff",
-    block_border_width="1px",
-    block_border_color="#2c3e50",
-    block_radius="10px"
-)
+    try:
+        # Add system information
+        system_info = format_system_info()
+        
+        # Format messages with the c4ai-command-a-03-2025 chat template
+        messages = [{"role": "user", "content": message}]
+        input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True)
+        
+        # Generate response
+        gen_tokens = model.generate(
+            input_ids,
+            max_new_tokens=100,
+            do_sample=True,
+            temperature=0.3,
+        )
+        
+        # Decode response
+        gen_text = tokenizer.decode(gen_tokens[0])
+        
+        # Format the full response with system info
+        formatted_response = f"{system_info}\n{gen_text}"
+        history.append((message, formatted_response))
+        return history
+    except Exception as e:
+        return [(message, f"Error during chat: {str(e)}")]
 
 # Create the Gradio interface
 demo = gr.ChatInterface(
@@ -71,7 +91,6 @@ demo = gr.ChatInterface(
     title="Medical Decision Support AI",
     description="""A medical decision support system that provides healthcare-related information and guidance.
     Current UTC Time: """ + get_timestamp(),
-    theme=theme,
     examples=[
         "What are the symptoms of hypertension?",
         "What are common drug interactions with aspirin?",