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demo.py

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+#!/usr/bin/env python3
+"""
+T5 Prompt Enhancer V0.3 Demo Script
+Quick test of all four instruction types
+"""
+
+import torch
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+
+def load_model():
+    """Load the T5 V0.3 model"""
+    print("🤖 Loading T5 Prompt Enhancer V0.3...")
+    
+    tokenizer = T5Tokenizer.from_pretrained(".")
+    model = T5ForConditionalGeneration.from_pretrained(".")
+    
+    if torch.cuda.is_available():
+        model = model.cuda()
+        print("✅ Model loaded on GPU")
+    else:
+        print("✅ Model loaded on CPU")
+    
+    return model, tokenizer
+
+def enhance_prompt(model, tokenizer, text, style="clean"):
+    """Generate enhanced prompt with style control"""
+    
+    style_prompts = {
+        "clean": f"Enhance this prompt (no lora): {text}",
+        "technical": f"Enhance this prompt (with lora): {text}",
+        "simplify": f"Simplify this prompt: {text}",
+        "standard": f"Enhance this prompt: {text}"
+    }
+    
+    prompt = style_prompts[style]
+    inputs = tokenizer(prompt, return_tensors="pt", max_length=256, truncation=True)
+    
+    if torch.cuda.is_available():
+        inputs = {k: v.cuda() for k, v in inputs.items()}
+    
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_length=80,
+            num_beams=2,
+            repetition_penalty=2.0,
+            no_repeat_ngram_size=3,
+            pad_token_id=tokenizer.pad_token_id
+        )
+    
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+def main():
+    """Demo all four instruction types"""
+    
+    # Load model
+    model, tokenizer = load_model()
+    
+    # Test prompts
+    test_prompts = [
+        "woman in red dress",
+        "cat on chair", 
+        "cyberpunk cityscape",
+        "masterpiece, best quality, ultra-detailed render of a fantasy dragon with golden scales"
+    ]
+    
+    styles = ["standard", "clean", "technical", "simplify"]
+    
+    print("\n🎨 T5 Prompt Enhancer V0.3 Demo")
+    print("="*60)
+    
+    for prompt in test_prompts:
+        print(f"\n📝 Input: '{prompt}'")
+        print("-" * 40)
+        
+        for style in styles:
+            try:
+                result = enhance_prompt(model, tokenizer, prompt, style)
+                print(f"{style:>10}: {result}")
+            except Exception as e:
+                print(f"{style:>10}: ERROR - {e}")
+        
+        print()
+
+if __name__ == "__main__":
+    main()