fix loading ui

app.py

@@ -2,6 +2,9 @@ import gradio as gr
 from llama_cpp import Llama
 from huggingface_hub import hf_hub_download
 
+# Global variable to track model loading status
+model = None
+
 def load_model():
     repo_id = "forestav/gguf_lora_model"
     model_file = "unsloth.F16.gguf"  
@@ -22,7 +25,9 @@ def load_model():
     return model
 
 def generate_career_response(message, history):
-    # Enhance the prompt with career guidance context
+    if model is None:
+        return "Model is still loading. Please wait..."
+        
     enhanced_prompt = f"""As a career development advisor, help the user with their professional growth. 
     Consider:
     1. Skill development opportunities
@@ -46,12 +51,7 @@ def generate_career_response(message, history):
     
     return response['choices'][0]['message']['content']
 
-# Load model globally
-print("Starting model loading...")
-model = load_model()
-print("Model loaded successfully!")
-
-# Create Gradio interface with career-focused examples
+# Create the interface first
 demo = gr.ChatInterface(
     fn=generate_career_response,
     title="Career Growth Navigator 🚀",
@@ -72,9 +72,32 @@ demo = gr.ChatInterface(
     ]
 )
 
-# Add proper Gradio launch configuration for Spaces
-demo.launch(
-    server_name="0.0.0.0",
-    server_port=7860,
-    share=False
-)
+# Create loading interface
+with gr.Blocks() as loading_demo:
+    gr.Markdown("# Loading Career Growth Navigator 🚀")
+    with gr.Row():
+        loading_msg = gr.Markdown("⏳ The model is currently loading. Please wait...")
+
+if __name__ == "__main__":
+    # Start with loading interface
+    loading_demo.queue()
+    loading_demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,
+        prevent_thread_lock=True
+    )
+    
+    # Load the model
+    print("Starting model loading...")
+    model = load_model()
+    print("Model loaded successfully!")
+    
+    # Close loading interface and launch main interface
+    loading_demo.close()
+    demo.queue()
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False
+    )