import dataclasses
from enum import auto, Enum
from typing import List, Any, Dict, Union, Tuple
import re
import base64
from io import BytesIO
from PIL import Image
from transformers import AutoTokenizer


class SeparatorStyle(Enum):
    """Different separator style."""

    SINGLE = auto()
    TWO = auto()
    MPT = auto()
    PLAIN = auto()
    CHATML = auto()
    LLAMA_2 = auto()
    LLAMA_3 = auto()
    QWEN = auto()
    GEMMA = auto()


@dataclasses.dataclass
class Conversation:
    """A class that keeps all conversation history."""

    system: str
    roles: List[str]
    messages: List[List[str]]
    offset: int
    sep_style: SeparatorStyle = SeparatorStyle.SINGLE
    sep: str = "###"
    sep2: str = None
    version: str = "Unknown"

    tokenizer_id: str = ""
    tokenizer: Any = None
    # Stop criteria (the default one is EOS token)
    stop_str: Union[str, List[str]] = None
    # Stops generation if meeting any token in this list
    stop_token_ids: List[int] = None

    skip_next: bool = False

    def get_prompt(self):
        messages = self.messages
        if len(messages) > 0 and type(messages[0][1]) is tuple:
            messages = self.messages.copy()
            init_role, init_msg = messages[0].copy()
            init_msg = init_msg[0]
            if "mmtag" in self.version:
                init_msg = init_msg.replace("<image>", "").strip()
                messages[0] = (init_role, init_msg)
                messages.insert(0, (self.roles[0], "<Image><image></Image>"))
                messages.insert(1, (self.roles[1], "Received."))
            elif not init_msg.startswith("<image>"):
                init_msg = init_msg.replace("<image>", "").strip()
                messages[0] = (init_role, "<image>\n" + init_msg)
            else:
                messages[0] = (init_role, init_msg)

        if self.sep_style == SeparatorStyle.SINGLE:
            ret = self.system + self.sep
            for role, message in messages:
                if message:
                    if type(message) is tuple:
                        message, _, _ = message
                    ret += role + ": " + message + self.sep
                else:
                    ret += role + ":"

        elif self.sep_style == SeparatorStyle.TWO:
            seps = [self.sep, self.sep2]
            ret = self.system + seps[0]
            for i, (role, message) in enumerate(messages):
                if message:
                    if type(message) is tuple:
                        message, _, _ = message
                    ret += role + ": " + message + seps[i % 2]
                else:
                    ret += role + ":"

        elif self.sep_style == SeparatorStyle.CHATML:
            ret = "" if self.system == "" else self.system + self.sep + "\n"
            for role, message in messages:
                if message:
                    if type(message) is tuple:
                        message, images, _ = message
                        message = "<image>" * len(images) + message
                    ret += role + "\n" + message + self.sep + "\n"
                else:
                    ret += role + "\n"
            return ret

        elif self.sep_style == SeparatorStyle.LLAMA_3:
            if self.tokenizer is None:
                raise ValueError("Llama 3 tokenizer is not available. Make sure you have the necessary permissions.")
            chat_template_messages = [{"role": "system", "content": self.system}]
            for role, message in messages:
                if message:
                    if type(message) is tuple:
                        message, images = message
                        message = "<image>" * len(images) + message
                    chat_template_messages.append({"role": role, "content": message})

            # print(chat_template_messages)
            return self.tokenizer.apply_chat_template(chat_template_messages, tokenize=False, add_generation_prompt=True)
            # ret = "" if self.system == "" else self.system + self.sep + "\n"
            # for role, message in messages:
            #     if message:
            #         if type(message) is tuple:
            #             message, images = message
            #             message = "<image>" * len(images) + message
            #         ret += role + "\n" + message + self.sep + "\n"
            #     else:
            #         ret += role + "\n"
            # return ret

        elif self.sep_style == SeparatorStyle.MPT:
            ret = self.system + self.sep
            for role, message in messages:
                if message:
                    if type(message) is tuple:
                        message, _, _ = message
                    ret += role + message + self.sep
                else:
                    ret += role

        elif self.sep_style == SeparatorStyle.GEMMA:
            ret = ""
            for i, (role, message) in enumerate(messages):
                assert role == self.roles[i % 2], "Conversation should alternate user/assistant/user/assistant/..."
                if message:
                    if type(message) is tuple:
                        message, _, _ = message
                    ret += role + message + self.sep
                else:
                    ret += role

        elif self.sep_style == SeparatorStyle.LLAMA_2:
            wrap_sys = lambda msg: f"<<SYS>>\n{msg}\n<</SYS>>\n\n" if len(msg) > 0 else msg
            wrap_inst = lambda msg: f"[INST] {msg} [/INST]"
            ret = ""

            for i, (role, message) in enumerate(messages):
                if i == 0:
                    assert message, "first message should not be none"
                    assert role == self.roles[0], "first message should come from user"
                if message:
                    if type(message) is tuple:
                        message, _, _ = message
                    if i == 0:
                        message = wrap_sys(self.system) + message
                    if i % 2 == 0:
                        message = wrap_inst(message)
                        ret += self.sep + message
                    else:
                        ret += " " + message + " " + self.sep2
                else:
                    ret += ""
            ret = ret.lstrip(self.sep)

        elif self.sep_style == SeparatorStyle.PLAIN:
            seps = [self.sep, self.sep2]
            ret = self.system
            for i, (role, message) in enumerate(messages):
                if message:
                    if type(message) is tuple:
                        message, _, _ = message
                    ret += message + seps[i % 2]
                else:
                    ret += ""
        else:
            raise ValueError(f"Invalid style: {self.sep_style}")

        return ret

    def append_message(self, role, message):
        self.messages.append([role, message])

    def process_image(self, image, image_process_mode, return_pil=False, image_format="PNG"):
        if image_process_mode == "Pad":

            def expand2square(pil_img, background_color=(122, 116, 104)):
                width, height = pil_img.size
                if width == height:
                    return pil_img
                elif width > height:
                    result = Image.new(pil_img.mode, (width, width), background_color)
                    result.paste(pil_img, (0, (width - height) // 2))
                    return result
                else:
                    result = Image.new(pil_img.mode, (height, height), background_color)
                    result.paste(pil_img, ((height - width) // 2, 0))
                    return result

            image = expand2square(image)
        elif image_process_mode in ["Default", "Crop"]:
            pass
        elif image_process_mode == "Resize":
            image = image.resize((336, 336))
        else:
            raise ValueError(f"Invalid image_process_mode: {image_process_mode}")

        if type(image) is not Image.Image:
            image = Image.open(image).convert("RGB")

        max_hw, min_hw = max(image.size), min(image.size)
        aspect_ratio = max_hw / min_hw
        max_len, min_len = 672, 448
        shortest_edge = int(min(max_len / aspect_ratio, min_len, min_hw))
        longest_edge = int(shortest_edge * aspect_ratio)
        W, H = image.size
        if H > W:
            H, W = longest_edge, shortest_edge
        else:
            H, W = shortest_edge, longest_edge
        image = image.resize((W, H))
        if return_pil:
            return image
        else:
            buffered = BytesIO()
            image.save(buffered, format=image_format)
            img_b64_str = base64.b64encode(buffered.getvalue()).decode()
            return img_b64_str

    def get_images(self, return_pil=False, return_path=False):
        images = []
        for i, (role, msg) in enumerate(self.messages[self.offset :]):
            if i % 2 == 0:
                if type(msg) is tuple:
                    msg, image, image_process_mode = msg
                    if type(image) != list:
                        image = [image]
                    for img in image:
                        if not return_path and self.is_image_file(img):
                            img = self.process_image(img, image_process_mode, return_pil=return_pil)
                        else:
                            images.append(img)
        return images

    def is_image_file(self, filename):
        image_extensions = [".png", ".jpg", ".jpeg", ".gif", ".bmp", ".tiff", ".webp"]
        return any(filename.lower().endswith(ext) for ext in image_extensions)

    def is_video_file(self, filename):
        video_extensions = [".mp4", ".mov", ".avi", ".mkv", ".wmv", ".flv", ".mpeg", ".mpg"]
        return any(filename.lower().endswith(ext) for ext in video_extensions)

    def to_gradio_chatbot(self):
        ret = []
        for i, (role, msg) in enumerate(self.messages[self.offset :]):
            if i % 2 == 0:
                if type(msg) is tuple:
                    msg, image, image_process_mode = msg
                    if type(image) != list:
                        image = [image]
                    if len(image) == 1:
                        msg = "<image>\n" + msg.replace("<image>", "").strip()
                    else:
                        msg = re.sub(r"(<image>)\n(?=<image>)", r"\1 ", msg)

                    img_str_list = []                         
                    for img in image:
                        if self.is_image_file(img):
                            img_b64_str = self.process_image(img, "Default", return_pil=False, image_format="JPEG")
                            img_str = f'<img src="data:image/jpeg;base64,{img_b64_str}" style="max-width: 256px; max-height: 256px; width: auto; height: auto; object-fit: contain;"/>'
                            img_str_list.append(img_str)
                        elif self.is_video_file(img):
                            ret.append(((img,), None))

                    msg = msg.strip()
                    img_place_holder = ""
                    for img_str in img_str_list:
                        img_place_holder += f"{img_str}\n\n"

                    if len(img_str_list) > 0:
                        msg = f"{img_place_holder}\n\n{msg}"

                    if len(msg) > 0:
                        ret.append([msg, None])
                else:
                    ret.append([msg, None])
            else:
                ret[-1][-1] = msg
        return ret

    def copy(self):
        return Conversation(system=self.system, roles=self.roles, messages=[[x, y] for x, y in self.messages], offset=self.offset, sep_style=self.sep_style, sep=self.sep, sep2=self.sep2, version=self.version)

    def dict(self):
        if len(self.get_images()) > 0:
            return {
                "system": self.system,
                "roles": self.roles,
                "messages": [[x, y[0] if type(y) is tuple else y] for x, y in self.messages],
                "offset": self.offset,
                "sep": self.sep,
                "sep2": self.sep2,
            }
        return {
            "system": self.system,
            "roles": self.roles,
            "messages": self.messages,
            "offset": self.offset,
            "sep": self.sep,
            "sep2": self.sep2,
        }

def safe_load_tokenizer(tokenizer_id):
    try:
        return AutoTokenizer.from_pretrained(tokenizer_id)
    except Exception:
        return None


conv_qwen = Conversation(
    system="""<|im_start|>system
You are a helpful assistant.""",
    roles=("<|im_start|>user", "<|im_start|>assistant"),
    version="qwen",
    messages=[],
    offset=0,
    sep_style=SeparatorStyle.CHATML,
    sep="<|im_end|>",
)

conv_plain = Conversation(
    system="",
    roles=("", ""),
    messages=[],
    offset=0,
    sep_style=SeparatorStyle.PLAIN,
    sep="\n",
)


conv_chatml_direct = Conversation(
    system="""<|im_start|>system
Answer the questions.""",
    roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
    version="mpt",
    messages=[],
    offset=0,
    sep_style=SeparatorStyle.MPT,
    sep="<|im_end|>",
)

default_conversation = conv_plain
conv_templates = {
    "default": conv_qwen,
    "plain": conv_plain,
    "chatml_direct": conv_chatml_direct,
    "qwen_1_5": conv_qwen,
    "qwen_2": conv_qwen,
}


if __name__ == "__main__":
    print(default_conversation.get_prompt())