Create app.py

app.py

@@ -0,0 +1,97 @@
+import gradio as gr
+import torch
+from diffusers import DiffusionPipeline
+
+# Path for the LoRA model
+color_book_lora_path = "artificialguybr/ColoringBookRedmond-V2"
+color_book_trigger = ", ColoringBookAF, Coloring Book"
+
+# Predefined styles for users to choose from
+styles = {
+    "Neonpunk": {
+        "prompt": "neonpunk style, cyberpunk, vaporwave, neon, vibrant, stunningly beautiful, crisp, "
+                  "detailed, sleek, ultramodern, magenta highlights, dark purple shadows, high contrast, cinematic",
+        "negative_prompt": "painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured"
+    },
+    "Retro Cyberpunk": {
+        "prompt": "retro cyberpunk, 80's inspired, synthwave, neon, vibrant, detailed, retro futurism",
+        "negative_prompt": "modern, desaturated, black and white, realism, low contrast"
+    },
+    "Dark Fantasy": {
+        "prompt": "Dark Fantasy Art, dark, moody, dark fantasy style",
+        "negative_prompt": "ugly, deformed, noisy, blurry, low contrast, bright, sunny"
+    },
+    "Double Exposure": {
+        "prompt": "Double Exposure Style, double image ghost effect, image combination, double exposure style",
+        "negative_prompt": "ugly, deformed, noisy, blurry, low contrast"
+    },
+    "None": {
+        "prompt": "8K",
+        "negative_prompt": "painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured"
+    }
+}
+
+# Cache the pipeline to avoid reloading it multiple times
+@gr.memo
+def load_pipeline(use_lora: bool):
+    """Load the diffusion pipeline with or without LoRA weights."""
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+
+    # Load the base model
+    pipe = DiffusionPipeline.from_pretrained(
+        "stabilityai/stable-diffusion-xl-refiner-1.0",
+        torch_dtype=torch.float16 if device == "cuda" else torch.float32,
+        use_safetensors=True,
+        variant="fp16" if device == "cuda" else None
+    )
+
+    # Apply LoRA weights if selected
+    if use_lora:
+        pipe.load_lora_weights(color_book_lora_path)
+
+    return pipe
+
+def generate_image(prompt: str, style_name: str, use_lora: bool):
+    """Generates an AI-generated image based on user input and selected style."""
+    try:
+        # Load the pre-trained pipeline
+        pipeline = load_pipeline(use_lora)
+
+        # Retrieve style prompts
+        style_prompt = styles.get(style_name, {}).get("prompt", "")
+        negative_prompt = styles.get(style_name, {}).get("negative_prompt", "")
+
+        # Apply LoRA trigger phrase if selected
+        if use_lora:
+            prompt += color_book_trigger
+
+        # Generate the image
+        image = pipeline(
+            prompt=prompt + " " + style_prompt,
+            negative_prompt="blurred, ugly, watermark, low resolution, " + negative_prompt,
+            num_inference_steps=20,
+            guidance_scale=9.0
+        ).images[0]
+
+        return image
+
+    except Exception as e:
+        return f"Error generating image: {str(e)}"
+
+# Gradio UI
+interface = gr.Interface(
+    fn=generate_image,
+    inputs=[
+        gr.Textbox(label="Enter Your Prompt", placeholder="A cute lion"),
+        gr.Dropdown(label="Select a Style", choices=list(styles.keys()), value="None"),
+        gr.Checkbox(label="Use Coloring Book LoRA", value=False)
+    ],
+    outputs=gr.Image(label="Generated Image"),
+    title="🎨 AI Coloring Book & Style Generator",
+    description="Generate amazing AI-powered art using Stable Diffusion XL. "
+                "Choose a style or apply a Coloring Book LoRA for unique results."
+)
+
+# Run the Gradio interface
+if __name__ == "__main__":
+    interface.launch()