conversation.py

"""
Copyright 2023-2024 SGLang Team
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""

"""Conversation chat templates."""

# Adapted from
# https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py
import dataclasses
from enum import IntEnum, auto
from typing import Dict, List, Optional, Tuple, Union

from sglang.srt.openai_api.protocol import ChatCompletionRequest


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()
    LLAMA3 = auto()
    CHATGLM = auto()
    CHATML = auto()
    CHATINTERN = auto()
    DOLLY = auto()
    RWKV = auto()
    PHOENIX = auto()
    ROBIN = auto()
    FALCON_CHAT = auto()
    CHATGLM3 = auto()
    DEEPSEEK_CHAT = auto()
    METAMATH = 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: Tuple[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: Union[str, List[str]] = None
    # The string that represents an image token in the prompt
    image_token: str = "<image>"

    image_data: Optional[List[str]] = None
    modalities: Optional[List[str]] = 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.ADD_COLON_SINGLE:
            ret = system_prompt + self.sep
            for role, message in self.messages:
                if message:
                    ret += role + ": " + message + self.sep
                else:
                    ret += role + ":"
            return ret
        elif self.sep_style == SeparatorStyle.ADD_COLON_TWO:
            seps = [self.sep, self.sep2]
            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.ADD_COLON_SPACE_SINGLE:
            ret = system_prompt + self.sep
            for role, message in self.messages:
                if message:
                    ret += role + ": " + message + self.sep
                else:
                    ret += role + ": "  # must be end with a space
            return ret
        elif self.sep_style == SeparatorStyle.ADD_NEW_LINE_SINGLE:
            ret = "" if system_prompt == "" else system_prompt + self.sep
            for role, message in self.messages:
                if message:
                    ret += role + "\n" + message + self.sep
                else:
                    ret += role + "\n"
            return ret
        elif self.sep_style == SeparatorStyle.NO_COLON_SINGLE:
            ret = system_prompt
            for role, message in self.messages:
                if message:
                    ret += role + message + self.sep
                else:
                    ret += role
            return ret
        elif self.sep_style == SeparatorStyle.NO_COLON_TWO:
            seps = [self.sep, self.sep2]
            ret = system_prompt
            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.RWKV:
            ret = system_prompt
            for i, (role, message) in enumerate(self.messages):
                if message:
                    ret += (
                        role
                        + ": "
                        + message.replace("\r\n", "\n").replace("\n\n", "\n")
                    )
                    ret += "\n\n"
                else:
                    ret += role + ":"
            return ret
        elif self.sep_style == SeparatorStyle.LLAMA3:
            ret = "<|begin_of_text|>"
            if self.system_message:
                ret += system_prompt
            else:
                ret += ""
            for i, (role, message) in enumerate(self.messages):
                if message:
                    ret += f"<|start_header_id|>{role}<|end_header_id|>\n\n"
                    ret += f"{message.strip()}<|eot_id|>"
                else:
                    ret += f"<|start_header_id|>{role}<|end_header_id|>\n\n"
            # print(ret)
            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 i == 0:
                        ret += message + " "
                    else:
                        ret += tag + " " + message + seps[i % 2]
                else:
                    ret += tag
            return ret
        elif self.sep_style == SeparatorStyle.CHATGLM:
            # source: https://huggingface.co/THUDM/chatglm-6b/blob/1d240ba371910e9282298d4592532d7f0f3e9f3e/modeling_chatglm.py#L1302-L1308
            # source2: https://huggingface.co/THUDM/chatglm2-6b/blob/e186c891cf64310ac66ef10a87e6635fa6c2a579/modeling_chatglm.py#L926
            round_add_n = 1 if self.name == "chatglm2" else 0
            if system_prompt:
                ret = system_prompt + self.sep
            else:
                ret = ""

            for i, (role, message) in enumerate(self.messages):
                if i % 2 == 0:
                    ret += f"[Round {i//2 + round_add_n}]{self.sep}"

                if message:
                    ret += f"{role}：{message}{self.sep}"
                else:
                    ret += f"{role}："
            return ret
        elif self.sep_style == SeparatorStyle.CHATML:
            ret = "" if system_prompt == "" else system_prompt + self.sep + "\n"
            for role, message in self.messages:
                if message:
                    ret += role + "\n" + message + self.sep + "\n"
                else:
                    ret += role + "\n"
            return ret
        elif self.sep_style == SeparatorStyle.CHATGLM3:
            ret = ""
            if self.system_message:
                ret += system_prompt
            for role, message in self.messages:
                if message:
                    ret += role + "\n" + message
                else:
                    ret += role
            return ret
        elif self.sep_style == SeparatorStyle.CHATINTERN:
            # source: https://huggingface.co/internlm/internlm-chat-7b-8k/blob/bd546fa984b4b0b86958f56bf37f94aa75ab8831/modeling_internlm.py#L771
            seps = [self.sep, self.sep2]
            ret = system_prompt
            for i, (role, message) in enumerate(self.messages):
                if i % 2 == 0:
                    ret += "<s>"
                if message:
                    ret += role + ":" + message + seps[i % 2] + "\n"
                else:
                    ret += role + ":"
            return ret
        elif self.sep_style == SeparatorStyle.DOLLY:
            seps = [self.sep, self.sep2]
            ret = system_prompt
            for i, (role, message) in enumerate(self.messages):
                if message:
                    ret += role + ":\n" + message + seps[i % 2]
                    if i % 2 == 1:
                        ret += "\n\n"
                else:
                    ret += role + ":\n"
            return ret
        elif self.sep_style == SeparatorStyle.PHOENIX:
            ret = system_prompt
            for role, message in self.messages:
                if message:
                    ret += role + ": " + "<s>" + message + "</s>"
                else:
                    ret += role + ": " + "<s>"
            return ret
        elif self.sep_style == SeparatorStyle.ROBIN:
            ret = system_prompt + self.sep
            for role, message in self.messages:
                if message:
                    ret += role + ":\n" + message + self.sep
                else:
                    ret += role + ":\n"
            return ret
        elif self.sep_style == SeparatorStyle.FALCON_CHAT:
            ret = ""
            if self.system_message:
                ret += system_prompt + self.sep
            for role, message in self.messages:
                if message:
                    ret += role + ": " + message + self.sep
                else:
                    ret += role + ":"
            return ret
        elif self.sep_style == SeparatorStyle.METAMATH:
            ret = "" if system_prompt == "" else system_prompt + self.sep
            for i, (role, message) in enumerate(self.messages):
                # For MetaMath, sep2 is used to prefix the message.
                starting_sep = ":\n" if i % 2 == 0 else ": " + self.sep2
                ending_sep = self.sep if i % 2 == 0 else ""
                if message:
                    ret += role + starting_sep + message + ending_sep
                else:
                    ret += role + starting_sep
            return ret
        elif self.sep_style == SeparatorStyle.DEEPSEEK_CHAT:
            seps = [self.sep, self.sep2]
            ret = system_prompt
            for i, (role, message) in enumerate(self.messages):
                if message:
                    ret += role + ": " + message + seps[i % 2]
                else:
                    ret += role + ":"
            return ret
        else:
            raise ValueError(f"Invalid style: {self.sep_style}")

    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 append_image(self, image: str):
        """Append a new message."""
        self.image_data.append(image)

    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."""
        if self.system_message == "":
            ret = []
        else:
            ret = [{"role": "system", "content": self.system_message}]

        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,
            image_token=self.image_token,
        )

    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
chat_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 chat_templates
        ), f"{template.name} has been registered."

    chat_templates[template.name] = template


def chat_template_exists(template_name: str) -> bool:
    return template_name in chat_templates


def generate_chat_conv(
    request: ChatCompletionRequest, template_name: str
) -> Conversation:
    conv = chat_templates[template_name].copy()
    conv = Conversation(
        name=conv.name,
        system_template=conv.system_template,
        system_message=conv.system_message,
        roles=conv.roles,
        messages=list(conv.messages),  # prevent in-place modification
        offset=conv.offset,
        sep_style=SeparatorStyle(conv.sep_style),
        sep=conv.sep,
        sep2=conv.sep2,
        stop_str=conv.stop_str,
        image_data=[],
        modalities=[],
        image_token=conv.image_token,
    )

    if isinstance(request.messages, str):
        raise ValueError("The messages should be a list of dict.")
    for message in request.messages:
        msg_role = message.role
        if msg_role == "system":
            if isinstance(message.content, str):
                conv.system_message = message.content
            elif isinstance(message.content, list):
                if (
                    len(message.content) != 1
                    or getattr(message.content[0], "type", None) != "text"
                ):
                    raise ValueError("The system message should be a single text.")
                else:
                    conv.system_message = getattr(message.content[0], "text", "")
        elif msg_role == "user":
            # Handle the various types of Chat Request content types here.
            role = conv.roles[0]
            if isinstance(message.content, str):
                conv.append_message(conv.roles[0], message.content)
            else:
                real_content = ""
                # calculate number of image_url
                num_image_url = 0
                for content in message.content:
                    if content.type == "image_url":
                        num_image_url += 1
                        conv.modalities.append(content.modalities)
                if num_image_url > 1:
                    image_token = conv.image_token
                else:
                    image_token = (
                        conv.image_token + "\n"
                        if conv.name != "qwen2-vl"
                        else conv.image_token
                    )
                for content in message.content:
                    if content.type == "text":
                        if num_image_url > 16:
                            real_content += "\n"  # for video
                        real_content += content.text
                    elif content.type == "image_url":
                        # NOTE: Only works for llava
                        real_content += image_token
                        conv.append_image(content.image_url.url)
                conv.append_message(conv.roles[0], real_content)
        elif msg_role == "assistant":
            parsed_content = ""
            if isinstance(message.content, str):
                parsed_content = message.content
            elif isinstance(message.content, list):
                if (
                    len(message.content) != 1
                    or getattr(message.content[0], "type", None) != "text"
                ):
                    raise ValueError(
                        "The assistant's response should be a single text."
                    )
                else:
                    parsed_content = getattr(message.content[0], "text", "")
            conv.append_message(conv.roles[1], parsed_content)
        else:
            raise ValueError(f"Unknown role: {msg_role}")

    # Add a blank message for the assistant.
    conv.append_message(conv.roles[1], None)

    return conv


# llama2 template
# reference: https://huggingface.co/blog/codellama#conversational-instructions
# reference: https://github.com/facebookresearch/llama/blob/1a240688810f8036049e8da36b073f63d2ac552c/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]"),
        sep_style=SeparatorStyle.LLAMA2,
        sep=" ",
        sep2=" </s><s>",
        stop_str=["[INST]", "[/INST]", "<<SYS>>", "<</SYS>>"],
    )
)

register_conv_template(
    Conversation(
        name="chatml",
        system_template="<|im_start|>system\n{system_message}",
        system_message="You are a helpful assistant.",
        roles=("<|im_start|>user", "<|im_start|>assistant"),
        sep_style=SeparatorStyle.CHATML,
        sep="<|im_end|>",
        stop_str=["<|endoftext|>", "<|im_end|>"],
    )
)

register_conv_template(
    Conversation(
        name="chatml-llava",
        system_template="<|im_start|>system\n{system_message}",
        system_message="You are a helpful assistant.",
        roles=("<|im_start|>user", "<|im_start|>assistant"),
        sep_style=SeparatorStyle.CHATML,
        sep="<|im_end|>",
        stop_str=["<|endoftext|>", "<|im_end|>"],
    )
)

register_conv_template(
    Conversation(
        name="vicuna_v1.1",
        system_message="A chat between a curious user and an artificial intelligence assistant. "
        "The assistant gives helpful, detailed, and polite answers to the user's questions.",
        roles=("USER", "ASSISTANT"),
        sep_style=SeparatorStyle.ADD_COLON_TWO,
        sep=" ",
        sep2="</s>",
    )
)

register_conv_template(
    Conversation(
        name="llama_3_vision",
        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="<|start_header_id|>system<|end_header_id|>\n\n{system_message}<|eot_id|>",
        roles=("user", "assistant"),
        sep_style=SeparatorStyle.LLAMA3,
        sep="",
        stop_str=["<|end_of_text|>", "<|eot_id|>"],
        image_token="<|image|>",
    )
)

register_conv_template(
    Conversation(
        name="llava_llama_3",
        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="<|start_header_id|>system<|end_header_id|>\n\n{system_message}<|eot_id|>",
        roles=("user", "assistant"),
        sep_style=SeparatorStyle.LLAMA3,
        sep="",
        stop_str=["<|end_of_text|>", "<|eot_id|>"],
    )
)
# Reference: https://github.com/InternLM/lmdeploy/blob/387bf54b4f124e72aab30ae9755f562e435d3d01/lmdeploy/model.py#L425-L442
register_conv_template(
    Conversation(
        name="internlm2-chat",
        system_template="<|im_start|>system\n{system_message}",
        roles=("<|im_start|>user", "<|im_start|>assistant"),
        sep="\n",
        stop_str=["<|im_end|>", "<|action_end|>"],
    )
)

# Reference: https://huggingface.co/docs/transformers/main/model_doc/qwen2_vl#usage-example
register_conv_template(
    Conversation(
        name="qwen2-vl",
        system_message="You are a helpful assistant.",
        system_template="<|im_start|>system\n{system_message}",
        roles=("<|im_start|>user", "<|im_start|>assistant"),
        sep="<|im_end|>\n",
        sep_style=SeparatorStyle.ADD_NEW_LINE_SINGLE,
        stop_str=["<|im_end|>"],
        image_token="<|vision_start|><|image_pad|><|vision_end|>",
    )
)