""" Fork from fastchat: https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py Conversation prompt templates. This code file will be deprecated in the future. We have integrated fastchat. For details, see: dbgpt/model/model_adapter.py """ import dataclasses from enum import IntEnum, auto from typing import Callable, 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() @dataclasses.dataclass class Conversation: """A class that manages prompt templates and keeps all conversation history.""" # The name of this template name: str # The system prompt system: str # Two roles roles: List[str] # All messages. Each item is (role, message). messages: List[List[str]] # The number of few shot examples offset: int # Separators sep_style: SeparatorStyle sep: str 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 # format system message system_formatter: Callable = None def get_prompt(self) -> str: """Get the prompt for generation.""" if self.sep_style == SeparatorStyle.ADD_COLON_SINGLE: ret = self.system + 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 = self.system + 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 = self.system + 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 self.system == "" else self.system + 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 = self.system 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 = self.system 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 = self.system 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] ret = "" for i, (role, message) in enumerate(self.messages): if message: if i == 0: ret += self.system + message else: ret += role + " " + message + seps[i % 2] else: ret += role 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 self.system: ret = self.system + 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 self.system == "" else self.system + 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.CHATINTERN: # source: https://huggingface.co/internlm/internlm-chat-7b-8k/blob/bd546fa984b4b0b86958f56bf37f94aa75ab8831/modeling_internlm.py#L771 seps = [self.sep, self.sep2] ret = self.system 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 = self.system 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 = self.system for role, message in self.messages: if message: ret += role + ": " + "" + message + "" else: ret += role + ": " + "" return ret elif self.sep_style == SeparatorStyle.ROBIN: ret = self.system + self.sep for role, message in self.messages: if message: ret += role + ":\n" + message + self.sep else: ret += role + ":\n" return ret else: raise ValueError(f"Invalid style: {self.sep_style}") def append_message(self, role: str, message: str): """Append a new message.""" self.messages.append([role, message]) 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 update_system_message(self, system_message: str): """Update system message""" if self.system_formatter: self.system = self.system_formatter(system_message) else: self.system = system_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.""" ret = [{"role": "system", "content": self.system}] 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=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, stop_str=self.stop_str, stop_token_ids=self.stop_token_ids, system_formatter=self.system_formatter, ) def dict(self): return { "template_name": self.name, "system": self.system, "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() # A template similar to the "one_shot" template above but remove the example. register_conv_template( Conversation( name="zero_shot", system="A chat between a curious human and an artificial intelligence assistant. " "The assistant gives helpful, detailed, and polite answers to the human's questions.", roles=("Human", "Assistant"), messages=(), offset=0, sep_style=SeparatorStyle.ADD_COLON_SINGLE, sep="\n### ", stop_str="###", ) ) # Vicuna v1.1 template register_conv_template( Conversation( name="vicuna_v1.1", system="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"), messages=(), offset=0, sep_style=SeparatorStyle.ADD_COLON_TWO, sep=" ", sep2="", ) ) # llama2 template # reference: https://github.com/facebookresearch/llama/blob/cfc3fc8c1968d390eb830e65c63865e980873a06/llama/generation.py#L212 register_conv_template( Conversation( name="llama-2", system="[INST] <>\nYou are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. " "Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. " "Please ensure that your responses are socially unbiased and positive in nature.\n\n" "If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. " "If you don't know the answer to a question, please don't share false information.\n<>\n\n", roles=("[INST]", "[/INST]"), messages=(), offset=0, sep_style=SeparatorStyle.LLAMA2, sep=" ", sep2=" ", stop_token_ids=[2], system_formatter=lambda msg: f"[INST] <>\n{msg}\n<>\n\n", ) ) # codellama template # reference: https://github.com/facebookresearch/llama/blob/cfc3fc8c1968d390eb830e65c63865e980873a06/llama/generation.py#L212 # reference2 : https://github.com/eosphoros-ai/DB-GPT-Hub/blob/main/README.zh.md register_conv_template( Conversation( name="codellama", system="[INST] <>\nI want you to act as a SQL terminal in front of an example database, you need only to return the sql command to me.Below is an instruction that describes a task, Write a response that appropriately completes the request." "If you don't know the answer to the request, please don't share false information.\n<>\n\n", roles=("[INST]", "[/INST]"), messages=(), offset=0, sep_style=SeparatorStyle.LLAMA2, sep=" ", sep2=" ", stop_token_ids=[2], system_formatter=lambda msg: f"[INST] <>\n{msg}\n<>\n\n", ) ) # Alpaca default template register_conv_template( Conversation( name="alpaca", system="Below is an instruction that describes a task. Write a response that appropriately completes the request.", roles=("### Instruction", "### Response"), messages=(), offset=0, sep_style=SeparatorStyle.ADD_COLON_TWO, sep="\n\n", sep2="", ) ) # Baichuan-13B-Chat template register_conv_template( # source: https://huggingface.co/baichuan-inc/Baichuan-13B-Chat/blob/f5f47be2adbbdceb784f334d6fa1ca2c73e65097/modeling_baichuan.py#L507 # https://huggingface.co/baichuan-inc/Baichuan-13B-Chat/blob/main/generation_config.json Conversation( name="baichuan-chat", system="", roles=(" ", " "), messages=(), offset=0, sep_style=SeparatorStyle.NO_COLON_TWO, sep="", sep2="", stop_token_ids=[2, 195], ) ) # Internlm-chat template register_conv_template( Conversation( name="internlm-chat", system="A chat between a curious <|User|> and an <|Bot|>. The <|Bot|> gives helpful, detailed, and polite answers to the <|User|>'s questions.\n\n", roles=("<|User|>", "<|Bot|>"), messages=(), offset=0, sep_style=SeparatorStyle.CHATINTERN, sep="", sep2="", stop_token_ids=[1, 103028], stop_str="", ) ) # TODO Support other model conversation template