app.py

import gradio as gr
import numpy as np
import random
import torch
from diffusers import DiffusionPipeline

# Load the model
dtype = torch.bfloat16 if torch.cuda.is_available() else torch.float32
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=dtype).to(device)

# Constants
MAX_SEED = np.iinfo(np.int32).max
MAX_IMAGE_SIZE = 2048

# Style list for prompt customization
style_list = [
    {"name": "D&D Art", "prompt": "dungeons & dragons style artwork {prompt}. d&d style, key visual, vibrant, studio anime, highly detailed", "negative_prompt": "photo, deformed, black and white, realism, disfigured, low contrast"},
    {"name": "Dark Fantasy", "prompt": "dark and moody dungeons & dragons artwork of {prompt}. gothic ruins, shadowy figures, haunting atmospheres, grim villains, muted colors, intricate textures, sinister undertones", "negative_prompt": "bright, cheerful, cartoonish, lighthearted, futuristic, deformed"},
    {"name": "Epic Battle", "prompt": "dynamic dungeons & dragons artwork of {prompt}. epic battle scene, legendary heroes, fierce monsters, intense action, dramatic lighting, high-detail environment, magical effects, vibrant colors", "negative_prompt": "peaceful, mundane, low energy, modern, sci-fi, simplistic, cartoonish, low contrast"},
    {"name": "(No style)", "prompt": "{prompt}", "negative_prompt": ""},
]

styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
STYLE_NAMES = list(styles.keys())
DEFAULT_STYLE_NAME = "D&D Art"

# Function to apply selected style
def apply_style(style_name: str, positive: str, negative: str = ""):
    p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
    return p.replace("{prompt}", positive), n + (negative or "")

# Inference function
def infer(
    prompt,
    style,
    seed=42,
    randomize_seed=False,
    width=1024,
    height=1024,
    num_inference_steps=4,
    batch_size=1,
    positive_override=None,
    negative_override=None,
    progress=gr.Progress(track_tqdm=True),
):
    if randomize_seed:
        seed = random.randint(0, MAX_SEED)

    images = []
    for _ in range(batch_size):
        # Apply custom styles if specified
        if positive_override and negative_override:
            styled_prompt = positive_override.replace("{prompt}", prompt)
            negative_prompt = negative_override
        else:
            styled_prompt, negative_prompt = apply_style(style, prompt)

        generator = torch.manual_seed(seed)
        image = pipe(
            prompt=styled_prompt,
            width=width,
            height=height,
            num_inference_steps=num_inference_steps,
            generator=generator,
            guidance_scale=0.0,
            negative_prompt=negative_prompt,
        ).images[0]
        images.append(image)
    return images, seed

# Example prompts
examples = [
    ["A heroic adventurer wielding a flaming sword standing on a cliff", "D&D Art"],
    ["A mystical library with ancient scrolls and glowing runes", "Dark Fantasy"],
    ["A ferocious dragon breathing fire in a dark cavern", "Epic Battle"],
]

# Predefined previews for styles
style_previews = {
    "D&D Art": "https://example.com/dnd_preview.png",
    "Dark Fantasy": "https://example.com/dark_fantasy_preview.png",
    "Epic Battle": "https://example.com/epic_battle_preview.png",
    "(No style)": "https://example.com/no_style_preview.png",
}

# Custom CSS for a Dungeons & Dragons theme
css = """
body {
    background-color: #1b1b1b;
    font-family: 'Cinzel', serif;
    color: #f5f5f5;
    background-image: url('https://www.transparenttextures.com/patterns/dark-matter.png');
}
#col-container {
    margin: 0 auto;
    max-width: 550px;
    padding: 15px;
    border: 4px solid #8b4513;
    background: linear-gradient(145deg, #2e2b2a, #3a3433);
    border-radius: 15px;
    box-shadow: 0 0 20px rgba(0, 0, 0, 0.8);
}
"""

# Interface
with gr.Blocks(css=css) as demo:
    with gr.Column(elem_id="col-container"):
        # Title and Description
        gr.Markdown(
            """
            # 🛡️ ChatDnD.net 🛡️
            # ⚔️ Dungeons & Dragons Image Generator ⚔️
            **Unleash Your Imagination!** Create heroes, maps, quests, and epic scenes to bring your campaigns to life. 
            Tailored for adventurers seeking inspiration or Dungeon Masters constructing their next grand story. <br>
            [Visit Our Website](https://chatdnd.net) | [Support Us](https://buymeacoffee.com/watchoutformike)
            """
        )

        # Style previews
        with gr.Row():
            for name, url in style_previews.items():
                gr.Image(value=url, label=name)

        # Prompt input and style selector
        with gr.Row():
            prompt = gr.Textbox(
                label="🎲 Describe Your Vision:",
                lines=3,
                placeholder="Describe your hero, monster, or legendary landscape..."
            )
            style = gr.Dropdown(
                label="🎨 Select a Style",
                choices=STYLE_NAMES,
                value=DEFAULT_STYLE_NAME,
            )
        
        # Custom style builder
        with gr.Accordion("🛠️ Custom Style Builder", open=False):
            positive_override = gr.Textbox(
                label="Custom Positive Prompt",
                placeholder="Enter custom positive prompt. Use '{prompt}' as a placeholder for the main description."
            )
            negative_override = gr.Textbox(
                label="Custom Negative Prompt",
                placeholder="Enter custom negative prompt for exclusion criteria."
            )

        # Run button and result display
        with gr.Row():
            run_button = gr.Button("Generate Image")
        results = gr.Gallery(label="🖼️ Generated Images")
        
        # Advanced settings
        with gr.Accordion("⚙️ Advanced Settings", open=False):
            seed = gr.Slider(
                label="Seed",
                minimum=0,
                maximum=MAX_SEED,
                step=1,
                value=0,
            )
            randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
            
            with gr.Row():
                width = gr.Slider(
                    label="Width",
                    minimum=256,
                    maximum=MAX_IMAGE_SIZE,
                    step=32,
                    value=1024,
                )
                height = gr.Slider(
                    label="Height",
                    minimum=256,
                    maximum=MAX_IMAGE_SIZE,
                    step=32,
                    value=1024,
                )
            
            num_inference_steps = gr.Slider(
                label="Inference Steps",
                minimum=1,
                maximum=50,
                step=1,
                value=4,
            )
            batch_size = gr.Slider(
                label="Batch Size",
                minimum=1,
                maximum=10,
                step=1,
                value=1,
            )

        # Examples with styles
        gr.Examples(
            examples=examples,
            inputs=[prompt, style],
            outputs=[results],
            fn=infer,
            cache_examples="lazy",
        )

    # Interactivity
    run_button.click(
        fn=infer,
        inputs=[prompt, style, seed, randomize_seed, width, height, num_inference_steps, batch_size, positive_override, negative_override],
        outputs=[results, seed],
    )

# Launch the demo
demo.launch()