import os
import re
import spaces as spaces1, spaces as spaces2
import random
import string
import torch
import requests
import gradio as gr
import numpy as np
from lxml.html import fromstring
#from transformers import pipeline
from torch import multiprocessing as mp
from torch.multiprocessing import Pool as Pool
#from pathos.multiprocessing import ProcessPool as Pool
#from pathos.threading import ThreadPool as Pool
#from diffusers.pipelines.flux import FluxPipeline
#from diffusers.utils import export_to_gif
#from huggingface_hub import hf_hub_download
#from safetensors.torch import load_file
from diffusers import DiffusionPipeline, StableDiffusionXLImg2ImgPipeline
from diffusers.utils import load_image
#import jax
#import jax.numpy as jnp

def port_inc():
    env = os.getenv("CUSTOM_PORT")
    if env == None:
        os.environ["CUSTOM_PORT"]="7860"
    else:
        os.environ["CUSTOM_PORT"]=str(int(env)+1)

def pipe_t2i():
    PIPE = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16, token=os.getenv("hf_token")).to("cuda")
    return PIPE
    
def pipe_i2i():
    PIPE = StableDiffusionXLImg2ImgPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True).to("cuda")
    PIPE.unet = torch.compile(PIPE.unet, mode="reduce-overhead", fullgraph=True)
    return PIPE

def translate(text,lang):
    if text == None or lang == None:
        return ""       
    text = re.sub(f'[{string.punctuation}]', '', re.sub('[\s+]', ' ', text)).lower().strip()
    lang = re.sub(f'[{string.punctuation}]', '', re.sub('[\s+]', ' ', lang)).lower().strip()    
    if text == "" or lang == "":
        return ""
    if len(text) > 38:
        raise Exception("Translation Error: Too long text!")
    user_agents = [
        'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36',
        'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36',
        'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36',
        'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.1 Safari/605.1.15',
        'Mozilla/5.0 (Macintosh; Intel Mac OS X 13_1) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.1 Safari/605.1.15'
    ]
    padded_chars = re.sub("[(^\-)(\-$)]","",text.replace("","-").replace("- -"," ")).strip()
    query_text = f'Please translate {padded_chars}, into {lang}'
    url = f'https://www.google.com/search?q={query_text}'
    resp = requests.get(
        url = url,
        headers = {
            'User-Agent': random.choice(user_agents)
        }
    )
    content = resp.content
    html = fromstring(content)
    translated = text
    try:
        src_lang = html.xpath('//*[@class="source-language"]')[0].text_content().lower().strip()
        trgt_lang = html.xpath('//*[@class="target-language"]')[0].text_content().lower().strip()
        src_text = html.xpath('//*[@id="tw-source-text"]/*')[0].text_content().lower().strip()
        trgt_text = html.xpath('//*[@id="tw-target-text"]/*')[0].text_content().lower().strip()
        if trgt_lang == lang:
            translated = trgt_text
    except:
        print(f'Translation Warning: Failed To Translate!')
    ret = re.sub(f'[{string.punctuation}]', '', re.sub('[\s+]', ' ', translated)).lower().strip()
    print(ret)
    return ret

def generate_random_string(length):
    characters = string.ascii_letters + string.digits
    return ''.join(random.choice(characters) for _ in range(length))

@spaces1.GPU(duration=40)
def Piper1(_do):
    print("starting piper1")
    retu = pp1(
        _do,
        height=512,
        width=512,
        num_inference_steps=4,
        max_sequence_length=256,
        guidance_scale=0
    )
    print("returning piper1")
    return retu

@spaces2.GPU(duration=40)
def Piper2(img,posi,neg):
    retu = pp2(
        prompt=posi,
        negative_prompt=neg,
        image=img
    )
    return retu

def tok(pipe,txt):
    toks = pipe.tokenizer(txt)['input_ids']
    print(toks)
    return toks

css="""
input, input::placeholder {
    text-align: center !important;
}
*, *::placeholder {
    direction: ltr !important;
    font-family: Suez One !important;
}
h1,h2,h3,h4,h5,h6,span,p,pre {
    width: 100% !important;
    text-align: center !important;
    display: block !important;
}
footer {
    display: none !important;
}
#col-container {
    margin: 0 auto !important;
    max-width: 15cm !important;
 }
.image-container {
    aspect-ratio: 512 / 512 !important;
}
.dropdown-arrow {
    display: none !important;
}
*:has(.btn), .btn {
    width: 100% !important;
    margin: 0 auto !important;
}
"""

js="""
function custom(){
    document.querySelector("div#prompt input").setAttribute("maxlength","38")
    document.querySelector("div#prompt2 input").setAttribute("maxlength","38")
}
"""

def infer1(p):
        print("infer1: started")
        p1 = p["a"]
        print(f'prompt 1: {p1}')
        p2 = p["b"]
        print(f'prompt 2: {p2}')
        name = generate_random_string(12)+".png"
        print(f'name: {name}')
        _do = ['beautiful', 'playful', 'photographed', 'realistic', 'dynamic poze', 'deep field', 'reasonable coloring', 'rough texture', 'best quality', 'focused']
        if p1 != "":
            _do.append(f'{p1}')
        posi = " ".join(_do)
        print(posi)
        output = Piper1(posi)
        output.images[0].save(name)
        return name
def infer2(p):
        print("infer2: started")
        p1 = p["a"]
        p2 = p["b"]
        name = p["c"]
        if p2 != "":
            _dont = f'{p2} where in {p1}'
            neg = _dont
        else:
            return name
        img = load_image(name).convert("RGB")
        output2 = Piper2(img,p1,neg)
        output2.images[0].save("_"+name)
        return "_"+name

def run(p1,p2,*result):
        p1_en = translate(p1,"english")
        p2_en = translate(p2,"english")
        p = {"a":p1_en,"b":p2_en}
        ln = len(result)
        print("images: "+str(ln))
        rng = list(range(ln))
    
        arr1 = [p for _ in rng]
        pool1 = Pool(ln)
        out1 = list(pool1.imap(infer1,arr1))
        pool1.close()
        pool1.join()
        pool1.clear()
    
        arr2 = [{"a":p1_en,"b":p2_en,"c":out1[_]} for _ in rng]
        pool2 = Pool(ln)
        out2 = list(pool2.imap(infer2,arr2))
        pool2.close()
        pool2.join()
        pool2.clear()
    
        return out2

def main():

    global result
    global pp1
    global pp2

    result=[]
    pp1=pipe_t2i()
    pp2=pipe_i2i()

    mp.set_start_method("spawn", force=True)
    
    with gr.Blocks(theme=gr.themes.Soft(),css=css,js=js) as demo:
        with gr.Column(elem_id="col-container"):
            gr.Markdown(f"""
                # MULTI-LANGUAGE IMAGE GENERATOR
            """)
            with gr.Row():
                prompt = gr.Textbox(
                    elem_id="prompt",
                    placeholder="INCLUDE",
                    container=False,
                    max_lines=1
                )
            with gr.Row():
                prompt2 = gr.Textbox(
                    elem_id="prompt2",
                    placeholder="EXCLUDE",
                    container=False,
                    max_lines=1
                )
            with gr.Row():
                run_button = gr.Button("START",elem_classes="btn",scale=0)
            with gr.Row():
                result.append(gr.Image(interactive=False,elem_classes="image-container", label="Result", show_label=False, type='filepath', show_share_button=False))
                result.append(gr.Image(interactive=False,elem_classes="image-container", label="Result", show_label=False, type='filepath', show_share_button=False))

        run_button.click(fn=run,inputs=[prompt,prompt2,*result],outputs=result)
        demo.queue().launch()

if __name__ == "__main__":
    main()