#!/usr/bin/env python
#patch 0.04
#Func() Dalle Collage Moved Midjourney Space 
#Pruned DalleCollage Space 
import os
import random
import uuid
import json

import torch
print(f"Is CUDA available: {torch.cuda.is_available()}")
# True
print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
# Tesla T4
import gradio as gr
import numpy as np
from PIL import Image
import spaces
import torch
from diffusers import DiffusionPipeline
from typing import Tuple

#BaseConditions--
bad_words = json.loads(os.getenv('BAD_WORDS', "[]"))
bad_words_negative = json.loads(os.getenv('BAD_WORDS_NEGATIVE', "[]"))
default_negative = os.getenv("default_negative","")

def check_text(prompt, negative=""):
    for i in bad_words:
        if i in prompt:
            return True
    for i in bad_words_negative:
        if i in negative:
            return True
    return False

style_list = [
    {
        "name": "3840 x 2160",
        "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
    },
    {
        "name": "2560 x 1440",
        "prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
    },

    {
        "name": "HD+",
        "prompt": "hyper-realistic 2K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
    },
    
    {
        "name": "Style Zero",
        "prompt": "{prompt}",
        "negative_prompt": "",
    },
]

collage_style_list = [
    {
        "name": "Hi-Res",
        "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
    },
    {
        "name": "B & W",
        "prompt": "black and white collage of {prompt}. monochromatic, timeless, classic, dramatic contrast",
        "negative_prompt": "colorful, vibrant, bright, flashy",
    },
    {
        "name": "Polaroid",
        "prompt": "collage of polaroid photos featuring {prompt}. vintage style, high contrast, nostalgic, instant film aesthetic",
        "negative_prompt": "digital, modern, low quality, blurry",
    },
    {
        "name": "Watercolor",
        "prompt": "watercolor collage of {prompt}. soft edges, translucent colors, painterly effects",
        "negative_prompt": "digital, sharp lines, solid colors",
    },
    {
        "name": "Cinematic",
        "prompt": "cinematic collage of {prompt}. film stills, movie posters, dramatic lighting",
        "negative_prompt": "static, lifeless, mundane",
    },
    {
        "name": "Nostalgic",
        "prompt": "nostalgic collage of {prompt}. retro imagery, vintage objects, sentimental journey",
        "negative_prompt": "contemporary, futuristic, forward-looking",
    },
    {
        "name": "Vintage",
        "prompt": "vintage collage of {prompt}. aged paper, sepia tones, retro imagery, antique vibes",
        "negative_prompt": "modern, contemporary, futuristic, high-tech",
    },
    {
        "name": "Scrapbook",
        "prompt": "scrapbook style collage of {prompt}. mixed media, hand-cut elements, textures, paper, stickers, doodles",
        "negative_prompt": "clean, digital, modern, low quality",
    },
    {
        "name": "NeoNGlow",
        "prompt": "neon glow collage of {prompt}. vibrant colors, glowing effects, futuristic vibes",
        "negative_prompt": "dull, muted colors, vintage, retro",
    },
    {
        "name": "Geometric",
        "prompt": "geometric collage of {prompt}. abstract shapes, colorful, sharp edges, modern design, high quality",
        "negative_prompt": "blurry, low quality, traditional, dull",
    },
    {
        "name": "Thematic",
        "prompt": "thematic collage of {prompt}. cohesive theme, well-organized, matching colors, creative layout",
        "negative_prompt": "random, messy, unorganized, clashing colors",
    },

    {
        "name": "No Style",
        "prompt": "{prompt}",
        "negative_prompt": "",
    },
]

filters = {
    "Vivid": {
        "prompt": "extra vivid {prompt}",
        "negative_prompt": "washed out, dull"
    },
    "Playa": {
        "prompt": "{prompt} set in a vast playa",
        "negative_prompt": "forest, mountains"
    },
    "Desert": {
        "prompt": "{prompt} set in a desert landscape",
        "negative_prompt": "ocean, city"
    },
    "West": {
        "prompt": "{prompt} with a western theme",
        "negative_prompt": "eastern, modern"
    },
    "Blush": {
        "prompt": "{prompt} with a soft blush color palette",
        "negative_prompt": "harsh colors, neon"
    },
    "Minimalist": {
        "prompt": "{prompt} with a minimalist design",
        "negative_prompt": "cluttered, ornate"
    },

    "Zero filter": {
        "prompt": "{prompt}",
        "negative_prompt": ""
    },
    
    
}

styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
collage_styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in collage_style_list}
filter_styles = {k: (v["prompt"], v["negative_prompt"]) for k, v in filters.items()}
STYLE_NAMES = list(styles.keys())
COLLAGE_STYLE_NAMES = list(collage_styles.keys())
FILTER_NAMES = list(filters.keys())
DEFAULT_STYLE_NAME = "3840 x 2160"
DEFAULT_COLLAGE_STYLE_NAME = "Hi-Res"
DEFAULT_FILTER_NAME = "Vivid"

def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]:
    if style_name in styles:
        p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
    elif style_name in collage_styles:
        p, n = collage_styles.get(style_name, collage_styles[DEFAULT_COLLAGE_STYLE_NAME])
    elif style_name in filter_styles:
        p, n = filter_styles.get(style_name, filter_styles[DEFAULT_FILTER_NAME])
    else:
        p, n = styles[DEFAULT_STYLE_NAME]
    
    if not negative:
        negative = ""
    return p.replace("{prompt}", positive), n + negative

    

DESCRIPTION = """## MidJourney

Drop your best results in the community: [rb.gy/klkbs7](http://rb.gy/klkbs7), Have you tried the stable hamster space? [rb.gy/hfrm2f](http://rb.gy/hfrm2f)
"""


if not torch.cuda.is_available():
    DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"

MAX_SEED = np.iinfo(np.int32).max
CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1"
MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048"))
USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")

if torch.cuda.is_available():
    pipe = DiffusionPipeline.from_pretrained(
        "----you model goes here-----",
        torch_dtype=torch.float16,
        use_safetensors=True,
        add_watermarker=False,
        variant="fp16"
    ).to(device)

    if ENABLE_CPU_OFFLOAD:
        pipe.enable_model_cpu_offload()
    else:
        pipe.to(device)
        print("Loaded on Device!")

    if USE_TORCH_COMPILE:
        pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
        print("Model Compiled!")

def save_image(img, path):
    img.save(path)

def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
    if randomize_seed:
        seed = random.randint(0, MAX_SEED)
    return seed

@spaces.GPU(enable_queue=True)
def generate(
    prompt: str,
    negative_prompt: str = "",
    use_negative_prompt: bool = False,
    style: str = DEFAULT_STYLE_NAME,
    collage_style: str = DEFAULT_COLLAGE_STYLE_NAME,
    filter_name: str = DEFAULT_FILTER_NAME,
    grid_size: str = "2x2",
    seed: int = 0,
    width: int = 1024,
    height: int = 1024,
    guidance_scale: float = 3,
    randomize_seed: bool = False,
    use_resolution_binning: bool = True,
    progress=gr.Progress(track_tqdm=True),
):
    if check_text(prompt, negative_prompt):
        raise ValueError("Prompt contains restricted words.")
    
    if collage_style != "No Style":
        prompt, negative_prompt = apply_style(collage_style, prompt, negative_prompt)
    elif filter_name != "No Filter":
        prompt, negative_prompt = apply_style(filter_name, prompt, negative_prompt)
    else:
        prompt, negative_prompt = apply_style(style, prompt, negative_prompt)
    
    seed = int(randomize_seed_fn(seed, randomize_seed))
    generator = torch.Generator().manual_seed(seed)

    if not use_negative_prompt:
        negative_prompt = ""  # type: ignore
    negative_prompt += default_negative    

    grid_sizes = {
        "2x1": (2, 1),
        "1x2": (1, 2),
        "2x2": (2, 2),
        "2x3": (2, 3),
        "3x2": (3, 2),
        "1x1": (1, 1)
    }
    
    grid_size_x, grid_size_y = grid_sizes.get(grid_size, (2, 2))
    num_images = grid_size_x * grid_size_y

    options = {
        "prompt": prompt,
        "negative_prompt": negative_prompt,
        "width": width,
        "height": height,
        "guidance_scale": guidance_scale,
        "num_inference_steps": 20,
        "generator": generator,
        "num_images_per_prompt": num_images,
        "use_resolution_binning": use_resolution_binning,
        "output_type": "pil",
    }
    
    torch.cuda.empty_cache()  # Clear GPU memory
    images = pipe(**options).images

    grid_img = Image.new('RGB', (width * grid_size_x, height * grid_size_y))

    for i, img in enumerate(images[:num_images]):
        grid_img.paste(img, (i % grid_size_x * width, i // grid_size_x * height))

    unique_name = str(uuid.uuid4()) + ".png"
    save_image(grid_img, unique_name)
    return [unique_name], seed

examples = [
    "Portrait of a beautiful woman in a hat, summer outfit, with freckles on her face, in a close up shot, with sunlight, outdoors, in soft light, with a beach background, looking at the camera, with high resolution photography, in the style of Hasselblad X2D50c --ar 85:128 --v 6.0 --style raw",
    "3d image, cute girl, in the style of Pixar --ar 1:2 --stylize 750, 4K resolution highlights, Sharp focus, octane render, ray tracing, Ultra-High-Definition, 8k, UHD, HDR, (Masterpiece:1.5), (best quality:1.5)",
    "Cold coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K, Photo-Realistic",
    "Closeup of blonde woman depth of field, bokeh, shallow focus, minimalism, fujifilm xh2s with Canon EF lens, cinematic --ar 85:128 --v 6.0 --style raw"
]

css = '''
.gradio-container{max-width: 670px !important}
h1{text-align:center}
'''
with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
    gr.Markdown(DESCRIPTION)
    gr.DuplicateButton(
        value="Duplicate Space for private use",
        elem_id="duplicate-button",
        visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
    )
    with gr.Group():
        with gr.Row():
            prompt = gr.Text(
                label="Prompt",
                show_label=False,
                max_lines=1,
                placeholder="Enter your prompt",
                container=False,
            )
            run_button = gr.Button("Run")
        result = gr.Gallery(label="Grid", columns=1, preview=True)


    with gr.Row(visible=True):
        filter_selection = gr.Radio(
            show_label=True,
            container=True,
            interactive=True,
            choices=FILTER_NAMES,
            value=DEFAULT_FILTER_NAME,
            label="Filter Type",
        )

    with gr.Row(visible=True):
        style_selection = gr.Radio(
            show_label=True,
            container=True,
            interactive=True,
            choices=STYLE_NAMES,
            value=DEFAULT_STYLE_NAME,
            label="Quality Style",
        )

    with gr.Row(visible=True):
        collage_style_selection = gr.Radio(
            show_label=True,
            container=True,
            interactive=True,
            choices=COLLAGE_STYLE_NAMES,
            value=DEFAULT_COLLAGE_STYLE_NAME,
            label="Collage Template",
        )
    with gr.Row(visible=True):
        grid_size_selection = gr.Dropdown(
            choices=["2x1", "1x2", "2x2", "2x3", "3x2", "1x1"],
            value="2x2",
            label="Grid Size"
        )

    with gr.Accordion("Advanced options", open=False):
        use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True)
        negative_prompt = gr.Text(
            label="Negative prompt",
            max_lines=1,
            placeholder="Enter a negative prompt",
            value="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
            visible=True,
        )
        with gr.Row():
            num_inference_steps = gr.Slider(
                label="Steps",
                minimum=10,
                maximum=30,
                step=1,
                value=15,
            )
        with gr.Row():
            num_images_per_prompt = gr.Slider(
                label="Images",
                minimum=1,
                maximum=5,
                step=1,
                value=2,
            )
        seed = gr.Slider(
            label="Seed",
            minimum=0,
            maximum=MAX_SEED,
            step=1,
            value=0,
            visible=True
        )
        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)

        with gr.Row(visible=True):
            width = gr.Slider(
                label="Width",
                minimum=512,
                maximum=2048,
                step=8,
                value=1024,
            )
            height = gr.Slider(
                label="Height",
                minimum=512,
                maximum=2048,
                step=8,
                value=1024,
            )

        with gr.Row():
            guidance_scale = gr.Slider(
                label="Guidance Scale",
                minimum=0.1,
                maximum=20.0,
                step=0.1,
                value=6,
            )

    gr.Examples(
        examples=examples,
        inputs=prompt,
        outputs=[result, seed],
        fn=generate,
        #cache_examples=True,
        cache_examples=CACHE_EXAMPLES,
    )

    use_negative_prompt.change(
        fn=lambda x: gr.update(visible=x),
        inputs=use_negative_prompt,
        outputs=negative_prompt,
        api_name=False,
    )

    gr.on(
        triggers=[
            prompt.submit,
            negative_prompt.submit,
            run_button.click,
        ],
        fn=generate,
        inputs=[
            prompt,
            negative_prompt,
            use_negative_prompt,
            style_selection,
            collage_style_selection,
            filter_selection,
            grid_size_selection,
            seed,
            width,
            height,
            guidance_scale,
            randomize_seed,
        ],
        outputs=[result, seed],
        api_name="run",
    )

if __name__ == "__main__":
    demo.queue(max_size=20).launch()