import base64
import io
import re
from pathlib import Path

import gradio as gr
import requests
import torch
from PIL import Image

from modules import chat, shared

torch._C._jit_set_profiling_mode(False)

# parameters which can be customized in settings.json of webui
params = {
    'enable_SD_api': False,
    'address': 'http://127.0.0.1:7860',
    'save_img': False,
    'SD_model': 'NeverEndingDream',  # not really used right now
    'prompt_prefix': '(Masterpiece:1.1), (solo:1.3), detailed, intricate, colorful',
    'negative_prompt': '(worst quality, low quality:1.3)',
    'side_length': 512,
    'restore_faces': False
}

SD_models = ['NeverEndingDream']  # TODO: get with http://{address}}/sdapi/v1/sd-models and allow user to select

streaming_state = shared.args.no_stream  # remember if chat streaming was enabled
picture_response = False  # specifies if the next model response should appear as a picture
pic_id = 0


def remove_surrounded_chars(string):
    # this expression matches to 'as few symbols as possible (0 upwards) between any asterisks' OR
    # 'as few symbols as possible (0 upwards) between an asterisk and the end of the string'
    return re.sub('\*[^\*]*?(\*|$)', '', string)

# I don't even need input_hijack for this as visible text will be commited to history as the unmodified string


def input_modifier(string):
    """
    This function is applied to your text inputs before
    they are fed into the model.
    """
    global params, picture_response
    if not params['enable_SD_api']:
        return string

    commands = ['send', 'mail', 'me']
    mediums = ['image', 'pic', 'picture', 'photo']
    subjects = ['yourself', 'own']
    lowstr = string.lower()

    # TODO: refactor out to separate handler and also replace detection with a regexp
    if any(command in lowstr for command in commands) and any(case in lowstr for case in mediums):  # trigger the generation if a command signature and a medium signature is found
        picture_response = True
        shared.args.no_stream = True                                                               # Disable streaming cause otherwise the SD-generated picture would return as a dud
        shared.processing_message = "*Is sending a picture...*"
        string = "Please provide a detailed description of your surroundings, how you look and the situation you're in and what you are doing right now"
        if any(target in lowstr for target in subjects):                                           # the focus of the image should be on the sending character
            string = "Please provide a detailed and vivid description of how you look and what you are wearing"

    return string

# Get and save the Stable Diffusion-generated picture


def get_SD_pictures(description):

    global params, pic_id

    payload = {
        "prompt": params['prompt_prefix'] + description,
        "seed": -1,
        "sampler_name": "DPM++ 2M Karras",
        "steps": 32,
        "cfg_scale": 7,
        "width": params['side_length'],
        "height": params['side_length'],
        "restore_faces": params['restore_faces'],
        "negative_prompt": params['negative_prompt']
    }

    response = requests.post(url=f'{params["address"]}/sdapi/v1/txt2img', json=payload)
    r = response.json()

    visible_result = ""
    for img_str in r['images']:
        image = Image.open(io.BytesIO(base64.b64decode(img_str.split(",", 1)[0])))
        if params['save_img']:
            output_file = Path(f'extensions/sd_api_pictures/outputs/{pic_id:06d}.png')
            image.save(output_file.as_posix())
            pic_id += 1
        # lower the resolution of received images for the chat, otherwise the log size gets out of control quickly with all the base64 values in visible history
        image.thumbnail((300, 300))
        buffered = io.BytesIO()
        image.save(buffered, format="JPEG")
        buffered.seek(0)
        image_bytes = buffered.getvalue()
        img_str = "data:image/jpeg;base64," + base64.b64encode(image_bytes).decode()
        visible_result = visible_result + f'<img src="{img_str}" alt="{description}">\n'

    return visible_result

# TODO: how do I make the UI history ignore the resulting pictures (I don't want HTML to appear in history)
# and replace it with 'text' for the purposes of logging?


def output_modifier(string):
    """
    This function is applied to the model outputs.
    """
    global pic_id, picture_response, streaming_state

    if not picture_response:
        return string

    string = remove_surrounded_chars(string)
    string = string.replace('"', '')
    string = string.replace('“', '')
    string = string.replace('\n', ' ')
    string = string.strip()

    if string == '':
        string = 'no viable description in reply, try regenerating'

    # I can't for the love of all that's holy get the name from shared.gradio['name1'], so for now it will be like this
    text = f'*Description: "{string}"*'

    image = get_SD_pictures(string)

    picture_response = False

    shared.processing_message = "*Is typing...*"
    shared.args.no_stream = streaming_state
    return image + "\n" + text


def bot_prefix_modifier(string):
    """
    This function is only applied in chat mode. It modifies
    the prefix text for the Bot and can be used to bias its
    behavior.
    """

    return string


def force_pic():
    global picture_response
    picture_response = True


def ui():

    # Gradio elements
    with gr.Accordion("Stable Diffusion api integration", open=True):
        with gr.Row():
            with gr.Column():
                enable = gr.Checkbox(value=params['enable_SD_api'], label='Activate SD Api integration')
                save_img = gr.Checkbox(value=params['save_img'], label='Keep original received images in the outputs subdir')
            with gr.Column():
                address = gr.Textbox(placeholder=params['address'], value=params['address'], label='Stable Diffusion host address')

        with gr.Row():
            force_btn = gr.Button("Force the next response to be a picture")
            generate_now_btn = gr.Button("Generate an image response to the input")

        with gr.Accordion("Generation parameters", open=False):
            prompt_prefix = gr.Textbox(placeholder=params['prompt_prefix'], value=params['prompt_prefix'], label='Prompt Prefix (best used to describe the look of the character)')
            with gr.Row():
                negative_prompt = gr.Textbox(placeholder=params['negative_prompt'], value=params['negative_prompt'], label='Negative Prompt')
                dimensions = gr.Slider(256, 702, value=params['side_length'], step=64, label='Image dimensions')
                # model = gr.Dropdown(value=SD_models[0], choices=SD_models, label='Model')

    # Event functions to update the parameters in the backend
    enable.change(lambda x: params.update({"enable_SD_api": x}), enable, None)
    save_img.change(lambda x: params.update({"save_img": x}), save_img, None)
    address.change(lambda x: params.update({"address": x}), address, None)
    prompt_prefix.change(lambda x: params.update({"prompt_prefix": x}), prompt_prefix, None)
    negative_prompt.change(lambda x: params.update({"negative_prompt": x}), negative_prompt, None)
    dimensions.change(lambda x: params.update({"side_length": x}), dimensions, None)
    # model.change(lambda x: params.update({"SD_model": x}), model, None)

    force_btn.click(force_pic)
    generate_now_btn.click(force_pic)
    generate_now_btn.click(chat.cai_chatbot_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream)