# 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_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() 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 image_data: 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.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 += "" 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 + ": " + "" + message + "" else: ret += role + ": " + "" 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, ) 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=[], ) 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": conv.system_message = message.content 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 = "" for content in message.content: if content.type == "text": real_content += content.text elif content.type == "image_url": # NOTE: Only works for llava real_content += "\n" conv.append_image(content.image_url.url) conv.append_message(conv.roles[0], real_content) elif msg_role == "assistant": conv.append_message(conv.roles[1], message.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] <>\n{system_message}\n<>\n\n", roles=("[INST]", "[/INST]"), sep_style=SeparatorStyle.LLAMA2, sep=" ", sep2=" ", stop_str=["[INST]", "[/INST]", "<>", "<>"], ) ) 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="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="", ) )