from htbuilder import HtmlElement, div, ul, li, br, hr, a, p, img, styles, classes, fonts
from htbuilder.units import percent, px
from htbuilder.funcs import rgba, rgb
import streamlit as st
import os
import sys
import argparse
import clip
import numpy as np
from PIL import Image
from dalle.models import Dalle
from dalle.utils.utils import set_seed, clip_score

def link(link, text, **style):
    return a(_href=link, _target="_blank", style=styles(**style))(text)

def layout(*args):

    style = """
    <style>
      # MainMenu {visibility: hidden;}
      footer {visibility: hidden;}
     .stApp { bottom: 105px; }
    </style>
    """

    style_div = styles(
        position="fixed",
        left=0,
        bottom=0,
        margin=px(0, 0, 0, 0),
        width=percent(100),
        color="black",
        text_align="center",
        height="auto",
        opacity=1
    )

    style_hr = styles(
        display="block",
        margin=px(8, 8, "auto", "auto"),
        border_style="inset",
        border_width=px(2)
    )

    body = p()
    foot = div(
        style=style_div
    )(
        hr(
            style=style_hr
        ),
        body
    )

    st.markdown(style, unsafe_allow_html=True)

    for arg in args:
        if isinstance(arg, str):
            body(arg)

        elif isinstance(arg, HtmlElement):
            body(arg)

    st.markdown(str(foot), unsafe_allow_html=True)

def footer():
    myargs = [
        "Created by ",
        link("https://jonathanmalott.com", "Jonathan Malott"),
        br(),
        link("https://bridgingbarriers.utexas.edu/good-systems", "Good Systems Grand Challenge"),
        ", The University of Texas at Austin.",
        " Advised by Dr. Junfeng Jiao.",
        br(),
        br(),
    ]
    layout(*myargs)


model = False
def generate(prompt,crazy,k):
    global model

    device = 'cpu'
    if(model == False):
        model = Dalle.from_pretrained('minDALL-E/1.3B')  # This will automatically download the pretrained model.
        model.to(device=device)
    
    num_candidates = 1

    images = []
    
    set_seed(np.random.randint(0,10000))



    # Sampling
    images = model.sampling(prompt=prompt,
                            top_k=2048,
                            top_p=None,
                            softmax_temperature=crazy,
                            num_candidates=num_candidates,
                            device=device).cpu().numpy()
    images = np.transpose(images, (0, 2, 3, 1))

    # CLIP Re-ranking
    model_clip, preprocess_clip = clip.load("ViT-B/32", device=device)
    model_clip.to(device=device)
    rank = clip_score(prompt=prompt,
                      images=images,
                      model_clip=model_clip,
                      preprocess_clip=preprocess_clip,
                      device=device)

    result = images[rank]

    item = {}
    item['prompt'] = prompt
    item['crazy'] = crazy
    item['k'] = k
    item['image'] = Image.fromarray((result*255).astype(np.uint8))
    st.session_state.results.append(item)



def drawGrid():
    master = {}
    order = 0

    #print(st.session_state.results)
    
    for r in st.session_state.results[::-1]:
        _txt = r['prompt']+" "+str(r['crazy'])+" "+str(r['k'])

        if(_txt not in master):
            master[_txt] = [r]
            order += 1
        else:
            master[_txt].append(r)

    
    for m in master:
        #with placeholder.container():
            
        txt = master[m][0]['prompt']+" (temperature:"+ str(master[m][0]['crazy']) + ", top k:" + str(master[m][0]['k']) + ")"
        st.subheader(txt)
        col1, col2, col3 = st.columns(3)   

        for ix, item in enumerate(master[m]):
            if ix % 3 == 0:
                with col1:
                    st.image(item["image"])
            if ix % 3 == 1:
                with col2:
                    st.image(item["image"])
            if ix % 3 == 2:
                with col3:
                    st.image(item["image"])