deepseek_vl/utils/conversation.py

# Copyright (c) 2023-2024 DeepSeek.
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"""
From https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py
"""

import dataclasses
from enum import IntEnum, auto
from typing import Dict, List


class SeparatorStyle(IntEnum):
    """Separator styles."""

    ADD_COLON_SINGLE = auto()
    ADD_COLON_TWO = auto()
    ADD_COLON_SPACE_SINGLE = auto()
    NO_COLON_SINGLE = auto()
    NO_COLON_TWO = auto()
    ADD_NEW_LINE_SINGLE = auto()
    LLAMA2 = auto()
    CHATGLM = auto()
    CHATML = auto()
    CHATINTERN = auto()
    DOLLY = auto()
    RWKV = auto()
    PHOENIX = auto()
    ROBIN = auto()
    DeepSeek = auto()
    PLAIN = auto()
    ALIGNMENT = auto()


@dataclasses.dataclass
class Conversation:
    """A class that manages prompt templates and keeps all conversation history."""

    # The name of this template
    name: str
    # The template of the system prompt
    system_template: str = "{system_message}"
    # The system message
    system_message: str = ""
    # The names of two roles
    roles: List[str] = (("USER", "ASSISTANT"),)
    # All messages. Each item is (role, message).
    messages: List[List[str]] = ()
    # The number of few shot examples
    offset: int = 0
    # The separator style and configurations
    sep_style: SeparatorStyle = SeparatorStyle.ADD_COLON_SINGLE
    sep: str = "\n"
    sep2: str = None
    # Stop criteria (the default one is EOS token)
    stop_str: str = None
    # Stops generation if meeting any token in this list
    stop_token_ids: List[int] = None

    def get_prompt(self) -> str:
        """Get the prompt for generation."""
        system_prompt = self.system_template.format(system_message=self.system_message)

        if self.sep_style == SeparatorStyle.DeepSeek:
            seps = [self.sep, self.sep2]
            if system_prompt == "" or system_prompt is None:
                ret = ""
            else:
                ret = system_prompt + seps[0]
            for i, (role, message) in enumerate(self.messages):
                if message:
                    ret += role + ": " + message + seps[i % 2]
                else:
                    ret += role + ":"
            return ret
        elif self.sep_style == SeparatorStyle.LLAMA2:
            seps = [self.sep, self.sep2]
            if self.system_message:
                ret = system_prompt
            else:
                ret = "[INST] "
            for i, (role, message) in enumerate(self.messages):
                tag = self.roles[i % 2]
                if message:
                    if type(message) is tuple:  # multimodal message
                        message, _ = message
                    if i == 0:
                        ret += message + " "
                    else:
                        ret += tag + " " + message + seps[i % 2]
                else:
                    ret += tag
            return ret
        elif self.sep_style == SeparatorStyle.PLAIN:
            seps = [self.sep, self.sep2]
            ret = ""
            for i, (role, message) in enumerate(self.messages):
                if message:
                    if type(message) is tuple:
                        message, _, _ = message
                    if i % 2 == 0:
                        ret += message + seps[i % 2]
                    else:
                        ret += message + seps[i % 2]
                else:
                    ret += ""
            return ret
        elif self.sep_style == SeparatorStyle.ALIGNMENT:
            seps = [self.sep, self.sep2]
            ret = ""
            for i, (role, message) in enumerate(self.messages):
                if message:
                    if type(message) is tuple:
                        message, _, _ = message
                    if i % 2 == 0:
                        ret += "<image>\n" + seps[i % 2]
                    else:
                        ret += message + seps[i % 2]
                else:
                    ret += ""
            return ret
        else:
            raise ValueError(f"Invalid style: {self.sep_style}")

    def get_prompt_for_current_round(self, content=None):
        """Get current round formatted question prompt during sft training"""
        if self.sep_style == SeparatorStyle.PLAIN:
            formatted_question = "<image>\n"
        elif self.sep_style == SeparatorStyle.DeepSeek:
            formatted_question = (
                f"{self.roles[0]}: " + content.strip() + self.sep + f"{self.roles[1]}:"
            )
        else:
            raise ValueError(f"Unsupported sep_style: {self.sep_style}")
        return formatted_question

    def set_system_message(self, system_message: str):
        """Set the system message."""
        self.system_message = system_message

    def append_message(self, role: str, message: str):
        """Append a new message."""
        self.messages.append([role, message])

    def reset_message(self):
        """Reset a new message."""
        self.messages = []

    def update_last_message(self, message: str):
        """Update the last output.

        The last message is typically set to be None when constructing the prompt,
        so we need to update it in-place after getting the response from a model.
        """
        self.messages[-1][1] = message

    def to_gradio_chatbot(self):
        """Convert the conversation to gradio chatbot format."""
        ret = []
        for i, (role, msg) in enumerate(self.messages[self.offset :]):
            if i % 2 == 0:
                ret.append([msg, None])
            else:
                ret[-1][-1] = msg
        return ret

    def to_openai_api_messages(self):
        """Convert the conversation to OpenAI chat completion format."""
        system_prompt = self.system_template.format(system_message=self.system_message)
        ret = [{"role": "system", "content": system_prompt}]

        for i, (_, msg) in enumerate(self.messages[self.offset :]):
            if i % 2 == 0:
                ret.append({"role": "user", "content": msg})
            else:
                if msg is not None:
                    ret.append({"role": "assistant", "content": msg})
        return ret

    def copy(self):
        return Conversation(
            name=self.name,
            system_template=self.system_template,
            system_message=self.system_message,
            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,
            stop_str=self.stop_str,
            stop_token_ids=self.stop_token_ids,
        )

    def dict(self):
        return {
            "template_name": self.name,
            "system_message": self.system_message,
            "roles": self.roles,
            "messages": self.messages,
            "offset": self.offset,
        }


# A global registry for all conversation templates
conv_templates: Dict[str, Conversation] = {}


def register_conv_template(template: Conversation, override: bool = False):
    """Register a new conversation template."""
    if not override:
        assert (
            template.name not in conv_templates
        ), f"{template.name} has been registered."

    conv_templates[template.name] = template


def get_conv_template(name: str) -> Conversation:
    """Get a conversation template."""
    return conv_templates[name].copy()


# llava_llama2 template
register_conv_template(
    Conversation(
        name="llava_llama2",
        system_message="You are a helpful language and vision assistant. "
        "You are able to understand the visual content that the user provides, "
        "and assist the user with a variety of tasks using natural language.",
        system_template="[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n",
        roles=("[INST]", "[/INST]"),
        messages=(),
        offset=0,
        sep_style=SeparatorStyle.LLAMA2,
        sep=" ",
        sep2=" </s><s>",
        stop_token_ids=[2],
    )
)

# llama2 template
# reference: https://github.com/facebookresearch/llama/blob/cfc3fc8c1968d390eb830e65c63865e980873a06/llama/generation.py#L212
register_conv_template(
    Conversation(
        name="llama-2",
        system_template="[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n",
        roles=("[INST]", "[/INST]"),
        messages=(),
        offset=0,
        sep_style=SeparatorStyle.LLAMA2,
        sep=" ",
        sep2=" </s><s>",
        stop_token_ids=[2],
    )
)


# deepseek template
register_conv_template(
    Conversation(
        name="deepseek",
        system_template="{system_message}",
        # system_message="You are a helpful assistant. Please answer truthfully and write out your "
        # "thinking step by step to be sure you get the right answer.",
        system_message="",
        roles=("User", "Assistant"),
        messages=(),
        offset=0,
        sep_style=SeparatorStyle.DeepSeek,
        sep="\n\n",
        sep2="<｜end▁of▁sentence｜>",
        stop_token_ids=[100001],
        stop_str=["User:", "<｜end▁of▁sentence｜>"],
    )
)

register_conv_template(
    Conversation(
        name="plain",
        system_template="",
        system_message="",
        roles=("", ""),
        messages=(),
        offset=0,
        sep_style=SeparatorStyle.PLAIN,
        sep="",
        sep2="",
        stop_token_ids=[2],
        stop_str=["</s>"],
    )
)


register_conv_template(
    Conversation(
        name="alignment",
        system_template="",
        system_message="",
        roles=("", ""),
        messages=(),
        offset=0,
        sep_style=SeparatorStyle.ALIGNMENT,
        sep="",
        sep2="",
        stop_token_ids=[2],
        stop_str=["</s>"],
    )
)


if __name__ == "__main__":
    # print("Llama-2 template:")
    # conv = get_conv_template("llama-2")
    # conv.set_system_message("You are a helpful, respectful and honest assistant.")
    # conv.append_message(conv.roles[0], "Hello!")
    # conv.append_message(conv.roles[1], "Hi!")
    # conv.append_message(conv.roles[0], "How are you?")
    # conv.append_message(conv.roles[1], None)
    # print(conv.get_prompt())

    # print("\n")

    print("deepseek template:")
    conv = get_conv_template("deepseek")
    conv.append_message(conv.roles[0], "Hello!")
    conv.append_message(conv.roles[1], "Hi! This is Tony.")
    conv.append_message(conv.roles[0], "Who are you?")
    conv.append_message(conv.roles[1], "I am a helpful assistant.")
    conv.append_message(conv.roles[0], "How are you?")
    conv.append_message(conv.roles[1], None)
    print(conv.get_prompt())