Deploy Gradio app with multiple files

app.py

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+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import spaces
+
+# Model configuration
+MODEL_ID = "WeiboAI/VibeThinker-1.5B"
+SYSTEM_PROMPT = "You are a concise solver. Respond briefly."
+
+# Load model and tokenizer
+def load_model():
+    """Load the model and tokenizer"""
+    try:
+        print(f"Loading model: {MODEL_ID}")
+        tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+        model = AutoModelForCausalLM.from_pretrained(
+            MODEL_ID,
+            torch_dtype=torch.float16,
+            device_map="auto",
+        )
+        print("Model loaded successfully!")
+        return model, tokenizer
+    except Exception as e:
+        print(f"Error loading model: {e}")
+        raise
+
+# Initialize model and tokenizer
+try:
+    model, tokenizer = load_model()
+except Exception as e:
+    print(f"Failed to load model: {e}")
+    model = None
+    tokenizer = None
+
+@spaces.GPU
+def chat_response(message, history):
+    """
+    Generate response for the chat interface.
+    
+    Args:
+        message (str): Current user message
+        history (list): Chat history as list of tuples [(user_msg, assistant_msg), ...]
+    
+    Returns:
+        str: Generated response
+    """
+    if model is None or tokenizer is None:
+        return "Model not loaded. Please check the model configuration."
+    
+    try:
+        # Build conversation format
+        messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+        
+        # Add chat history
+        for user_msg, assistant_msg in history:
+            messages.append({
+"role": "user", "content": user_msg
+})
+            messages.append({
+"role": "assistant", "content": assistant_msg
+})
+        
+        # Add current message
+        messages.append({
+"role": "user", "content": message
+})
+        
+        # Apply chat template
+        formatted_input = tokenizer.apply_chat_template(
+            messages, 
+            tokenize=False, 
+            add_generation_prompt=True
+        )
+        
+        # Tokenize input
+        model_inputs = tokenizer([formatted_input], return_tensors="pt").to(model.device)
+        
+        # Generate response
+        with torch.no_grad():
+            generated_ids = model.generate(
+                **model_inputs,
+                max_new_tokens=512,
+                do_sample=True,
+                temperature=0.7,
+                top_p=0.9,
+                pad_token_id=tokenizer.eos_token_id
+            )
+        
+        # Decode response
+        generated_ids = [
+            output_ids[len(input_ids):] 
+            for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+        ]
+        
+        response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+        
+        return response.strip()
+        
+    except Exception as e:
+        print(f"Error generating response: {e}")
+        return f"Sorry, I encountered an error: {str(e)}"
+
+def create_demo():
+    """Create the Gradio chat interface"""
+    
+    # Create chat interface
+    demo = gr.ChatInterface(
+        fn=chat_response,
+        title="VibeThinker-1.5B Chat",
+        description=f"Chat with {MODEL_ID}. {SYSTEM_PROMPT}",
+        examples=[
+            "What is 2+2?",
+            "Explain quantum physics briefly",
+            "Write a short poem",
+            "How do I make good decisions?"
+        ],
+        theme=gr.themes.Soft(),
+        show_progress="minimal",
+        retry_btn="🔄 Retry",
+        undo_btn="↩️ Undo",
+        clear_btn="🗑️ Clear",
+    )
+    
+    return demo
+
+if __name__ == "__main__":
+    demo = create_demo()
+    demo.launch(share=False)

requirements.txt

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+gradio==4.7.1
+transformers==4.36.0
+accelerate==0.25.0
+torch>=2.0.0
+spaces==0.19.4
+title: VibeThinker-1.5B Chat
+emoji: 🤖
+colorFrom: blue
+colorTo: pink
+sdk: gradio
+sdk_version: 4.7.1
+app_port: 7860
+hardware: zero-gpu
+Simple chat interface for the VibeThinker-1.5B model.
+ZeroGPU hardware support
+Interactive chat interface
+Built with Gradio
+Model runs directly in the browser using ZeroGPU inference
+What is 2+2?
+Explain quantum physics briefly
+Write a short poem
+How do I make good decisions?