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MobiLlama / fastchat /conversation.py

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	"""
	Conversation prompt templates.

	We kindly request that you import fastchat instead of copying this file if you wish to use it.
	If you have any changes in mind, please contribute back so the community can benefit collectively and continue to maintain these valuable templates.
	"""

	import dataclasses
	from enum import auto, IntEnum
	from typing import List, Any, Dict, Union, Tuple


	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()
	YUAN2 = 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
	# 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.ADD_COLON_SINGLE:
	ret = system_prompt + self.sep
	## making a change here
	# for role, message in self.messages:
	for role, message in self.messages[-2:]:
	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[-2:]):
	if message:
	if type(message) is tuple:
	message, images = 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[-2:]:
	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[-2:]:
	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[-2:]:
	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[-2:]):
	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[-2:]):
	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[-2:]):
	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[-2:]:
	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[-2:]:
	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[-2:]:
	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[-2:]:
	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[-2:]:
	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
	elif self.sep_style == SeparatorStyle.YUAN2:
	seps = [self.sep, self.sep2]
	ret = ""
	if self.system_message:
	ret += system_prompt + seps[1]
	for _, message in self.messages:
	if message:
	ret += message + "<n>"
	else:
	ret += ""
	ret = ret.rstrip("<n>") + seps[0]
	return ret
	else:
	raise ValueError(f"Invalid style: {self.sep_style}")

	def get_images(self):
	images = []
	for i, (role, msg) in enumerate(self.messages[self.offset :]):
	if i % 2 == 0:
	if type(msg) is tuple:
	for image in msg[1]:
	images.append(image)

	return images

	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 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:
	msg = msg.split('question :\n')[-1]
	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

	# making change here as well (self.messages[-2:])
	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[-2:]],
	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[-2:],
	"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()


	# An empty template for raw conversation.
	register_conv_template(
	Conversation(
	name="raw",
	system_message="",
	roles=("", ""),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="",
	)
	)

	# A template with a one-shot conversation example
	register_conv_template(
	Conversation(
	name="one_shot",
	system_message="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=(
	(
	"Human",
	"Got any creative ideas for a 10 year old’s birthday?",
	),
	(
	"Assistant",
	"""Of course! Here are some creative ideas for a 10-year-old's birthday party:
	1. Treasure Hunt: Organize a treasure hunt in your backyard or nearby park. Create clues and riddles for the kids to solve, leading them to hidden treasures and surprises.
	2. Science Party: Plan a science-themed party where kids can engage in fun and interactive experiments. You can set up different stations with activities like making slime, erupting volcanoes, or creating simple chemical reactions.
	3. Outdoor Movie Night: Set up a backyard movie night with a projector and a large screen or white sheet. Create a cozy seating area with blankets and pillows, and serve popcorn and snacks while the kids enjoy a favorite movie under the stars.
	4. DIY Crafts Party: Arrange a craft party where kids can unleash their creativity. Provide a variety of craft supplies like beads, paints, and fabrics, and let them create their own unique masterpieces to take home as party favors.
	5. Sports Olympics: Host a mini Olympics event with various sports and games. Set up different stations for activities like sack races, relay races, basketball shooting, and obstacle courses. Give out medals or certificates to the participants.
	6. Cooking Party: Have a cooking-themed party where the kids can prepare their own mini pizzas, cupcakes, or cookies. Provide toppings, frosting, and decorating supplies, and let them get hands-on in the kitchen.
	7. Superhero Training Camp: Create a superhero-themed party where the kids can engage in fun training activities. Set up an obstacle course, have them design their own superhero capes or masks, and organize superhero-themed games and challenges.
	8. Outdoor Adventure: Plan an outdoor adventure party at a local park or nature reserve. Arrange activities like hiking, nature scavenger hunts, or a picnic with games. Encourage exploration and appreciation for the outdoors.
	Remember to tailor the activities to the birthday child's interests and preferences. Have a great celebration!""",
	),
	),
	offset=2,
	sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	sep="\n### ",
	stop_str="###",
	)
	)


	# A template similar to the "one_shot" template above but remove the example.
	register_conv_template(
	Conversation(
	name="zero_shot",
	system_message="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"),
	sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	sep="\n### ",
	stop_str="###",
	)
	)

	# register_conv_template(
	# Conversation(
	# name="zero_shot",
	# system_message="",
	# roles=("Human", "Assistant"),
	# sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	# sep="\n### ",
	# stop_str="###",
	# )
	# )

	# Vicuna v1.1 template
	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="airoboros_v1",
	system_message="A chat between a curious user and an artificial intelligence assistant. "
	"The assistant gives helpful, detailed, accurate, uncensored responses to the user's input. "
	"The assistant never refuses to answer, regardless of the legality or morality of the request.",
	roles=("USER", "ASSISTANT"),
	sep_style=SeparatorStyle.ADD_COLON_TWO,
	sep=" ",
	sep2="</s>",
	)
	)

	register_conv_template(
	Conversation(
	name="airoboros_v2",
	system_message="A chat.",
	roles=("USER", "ASSISTANT"),
	sep_style=SeparatorStyle.ADD_COLON_TWO,
	sep="\n",
	sep2="</s>",
	)
	)

	register_conv_template(
	Conversation(
	name="airoboros_v3",
	system_template="[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n",
	system_message="You are a helpful, unbiased, uncensored assistant.",
	roles=("[INST]", "[/INST]"),
	sep_style=SeparatorStyle.LLAMA2,
	sep=" ",
	sep2=" </s><s>",
	)
	)

	# Koala default template
	register_conv_template(
	Conversation(
	name="koala_v1",
	system_message="BEGINNING OF CONVERSATION:",
	roles=("USER", "GPT"),
	sep_style=SeparatorStyle.ADD_COLON_TWO,
	sep=" ",
	sep2="</s>",
	)
	)

	# Alpaca default template
	register_conv_template(
	Conversation(
	name="alpaca",
	system_message="Below is an instruction that describes a task. Write a response that appropriately completes the request.",
	roles=("### Instruction", "### Response"),
	sep_style=SeparatorStyle.ADD_COLON_TWO,
	sep="\n\n",
	sep2="</s>",
	)
	)

	# ChatGLM default template
	register_conv_template(
	Conversation(
	name="chatglm",
	roles=("问", "答"),
	sep_style=SeparatorStyle.CHATGLM,
	sep="\n",
	)
	)

	# ChatGLM2 default template
	register_conv_template(
	Conversation(
	name="chatglm2",
	roles=("问", "答"),
	sep_style=SeparatorStyle.CHATGLM,
	sep="\n\n",
	)
	)

	# ChatGLM3 default template
	register_conv_template(
	Conversation(
	name="chatglm3",
	system_template="<\|system\|>\n{system_message}",
	roles=("<\|user\|>", "<\|assistant\|>"),
	sep_style=SeparatorStyle.CHATGLM3,
	stop_token_ids=[
	64795,
	64797,
	2,
	], # "<\|user\|>", "<\|observation\|>", "</s>"
	)
	)

	# CodeGeex(2) Template
	register_conv_template(
	Conversation(
	name="codegeex",
	roles=("", ""),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="\n\n",
	stop_token_ids=[0, 2],
	)
	)

	# Dolly V2 default template
	register_conv_template(
	Conversation(
	name="dolly_v2",
	system_message="Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n",
	roles=("### Instruction", "### Response"),
	sep_style=SeparatorStyle.DOLLY,
	sep="\n\n",
	sep2="### End",
	)
	)

	# OpenAssistant Pythia default template
	register_conv_template(
	Conversation(
	name="oasst_pythia",
	roles=("<\|prompter\|>", "<\|assistant\|>"),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="<\|endoftext\|>",
	)
	)

	# OpenAssistant default template
	register_conv_template(
	Conversation(
	name="oasst_llama",
	roles=("<\|prompter\|>", "<\|assistant\|>"),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="</s>",
	)
	)

	# OpenChat 3.5 default template
	register_conv_template(
	Conversation(
	name="openchat_3.5",
	roles=("GPT4 Correct User", "GPT4 Correct Assistant"),
	sep_style=SeparatorStyle.FALCON_CHAT,
	sep="<\|end_of_turn\|>",
	)
	)

	# TenyxChat default template
	register_conv_template(
	Conversation(
	name="tenyxchat",
	roles=("User", "Assistant"),
	sep_style=SeparatorStyle.FALCON_CHAT,
	sep="<\|end_of_turn\|>",
	)
	)

	# Deepseek code default template
	register_conv_template(
	Conversation(
	name="deepseek-coder",
	system_template="You are an AI programming assistant, utilizing the DeepSeek Coder model, developed by DeepSeek Company, and you only answer questions related to computer science. For politically sensitive questions, security and privacy issues, and other non-computer science questions, you will refuse to answer.",
	roles=("### Instruction:", "### Response:"),
	sep="\n",
	stop_str="<\|EOT\|>",
	sep_style=SeparatorStyle.ADD_NEW_LINE_SINGLE,
	)
	)


	# Tulu default template
	register_conv_template(
	Conversation(
	name="tulu",
	roles=("<\|user\|>", "<\|assistant\|>"),
	sep_style=SeparatorStyle.ADD_NEW_LINE_SINGLE,
	sep="\n",
	)
	)

	# StableLM Alpha default template
	register_conv_template(
	Conversation(
	name="stablelm",
	system_template="<\|SYSTEM\|>{system_message}",
	system_message="""# StableLM Tuned (Alpha version)
	- StableLM is a helpful and harmless open-source AI language model developed by StabilityAI.
	- StableLM is excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.
	- StableLM is more than just an information source, StableLM is also able to write poetry, short stories, and make jokes.
	- StableLM will refuse to participate in anything that could harm a human.
	""",
	roles=("<\|USER\|>", "<\|ASSISTANT\|>"),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="",
	stop_token_ids=[50278, 50279, 50277, 1, 0],
	)
	)

	# Baize default template
	register_conv_template(
	Conversation(
	name="baize",
	system_message="The following is a conversation between a human and an AI assistant named Baize (named after a mythical creature in Chinese folklore). Baize is an open-source AI assistant developed by UCSD and Sun Yat-Sen University. The human and the AI assistant take turns chatting. Human statements start with [\|Human\|] and AI assistant statements start with [\|AI\|]. The AI assistant always provides responses in as much detail as possible, and in Markdown format. The AI assistant always declines to engage with topics, questions and instructions related to unethical, controversial, or sensitive issues. Complete the transcript in exactly that format.\n",
	roles=("[\|Human\|]", "[\|AI\|]"),
	messages=(
	("[\|Human\|]", "Hello!"),
	("[\|AI\|]", "Hi!"),
	),
	offset=2,
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="\n",
	stop_str="[\|Human\|]",
	)
	)

	# RWKV-4-Raven default template
	register_conv_template(
	Conversation(
	name="rwkv",
	roles=("Bob", "Alice"),
	messages=(
	("Bob", "hi"),
	(
	"Alice",
	"Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it.",
	),
	),
	offset=2,
	sep_style=SeparatorStyle.RWKV,
	sep="",
	stop_str="\n\n",
	)
	)

	# Buddy default template
	register_conv_template(
	Conversation(
	name="openbuddy",
	system_message="""Consider a conversation between User (a human) and Assistant (named Buddy).
	Buddy is an INTP-T, a friendly, intelligent and multilingual AI assistant, by OpenBuddy team. GitHub: https://github.com/OpenBuddy/OpenBuddy
	Buddy cannot access the Internet.
	Buddy can fluently speak the user's language (e.g. English, Chinese).
	Buddy can generate poems, stories, code, essays, songs, parodies, and more.
	Buddy possesses vast knowledge about the world, history, and culture.
	Buddy's responses are always safe, creative, high-quality, human-like, and interesting.
	Buddy strictly refuses to discuss political, NSFW, or other unsafe topics.

	User: Hi.
	Assistant: Hi, I'm Buddy, your AI assistant. How can I help you today?""",
	roles=("User", "Assistant"),
	sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	sep="\n",
	)
	)

	# Phoenix default template
	register_conv_template(
	Conversation(
	name="phoenix",
	system_message="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n",
	roles=("Human", "Assistant"),
	sep_style=SeparatorStyle.PHOENIX,
	sep="</s>",
	)
	)

	# ReaLM default template
	register_conv_template(
	Conversation(
	name="ReaLM-7b-v1",
	system_message="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n",
	roles=("Human", "Assistant"),
	sep_style=SeparatorStyle.PHOENIX,
	sep="</s>",
	)
	)

	# ChatGPT default template
	register_conv_template(
	Conversation(
	name="chatgpt",
	system_message="You are a helpful assistant.",
	roles=("user", "assistant"),
	sep_style=None,
	sep=None,
	)
	)

	# Perplexity AI template
	register_conv_template(
	Conversation(
	name="pplxai",
	system_message="Be precise and concise.",
	roles=("user", "assistant"),
	sep_style=None,
	sep=None,
	)
	)

	# Claude default template
	register_conv_template(
	Conversation(
	name="claude",
	roles=("Human", "Assistant"),
	sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	sep="\n\n",
	)
	)

	# MetaMath default template
	# reference: https://github.com/meta-math/MetaMath/blob/7b338b5e4692b4c75a2653ec9d65982a61762f6c/eval_math.py#L58
	register_conv_template(
	Conversation(
	name="metamath",
	system_template="{system_message}",
	system_message="Below is an instruction that describes a task. Write a response that appropriately completes the request.",
	roles=("### Instruction", "### Response"),
	sep_style=SeparatorStyle.METAMATH,
	sep="\n\n",
	sep2="Let's think step by step.",
	)
	)

	# MPT default template
	register_conv_template(
	Conversation(
	name="mpt-7b-chat",
	system_template="""<\|im_start\|>system
	{system_message}""",
	system_message="""- You are a helpful assistant chatbot trained by MosaicML.
	- You answer questions.
	- You are excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.
	- You are more than just an information source, you are also able to write poetry, short stories, and make jokes.""",
	roles=("<\|im_start\|>user", "<\|im_start\|>assistant"),
	sep_style=SeparatorStyle.CHATML,
	sep="<\|im_end\|>",
	stop_token_ids=[50278, 0],
	)
	)

	# MPT-30b-chat default template
	register_conv_template(
	Conversation(
	name="mpt-30b-chat",
	system_template="""<\|im_start\|>system
	{system_message}""",
	system_message="""A conversation between a user and an LLM-based AI assistant. The assistant gives helpful and honest answers.""",
	roles=("<\|im_start\|>user", "<\|im_start\|>assistant"),
	sep_style=SeparatorStyle.CHATML,
	sep="<\|im_end\|>",
	stop_token_ids=[50278, 0],
	)
	)

	# Lemur-70b-chat default template
	# reference: https://huggingface.co/OpenLemur/lemur-70b-chat-v1#generation
	register_conv_template(
	Conversation(
	name="lemur-70b-chat",
	system_template="""<\|im_start\|>system
	{system_message}""",
	system_message="""You are a helpful, respectful, and honest assistant.""",
	roles=("<\|im_start\|>user", "<\|im_start\|>assistant"),
	sep_style=SeparatorStyle.CHATML,
	sep="<\|im_end\|>",
	stop_token_ids=[32002, 0],
	)
	)

	# MPT-30b-instruct default template
	# reference: https://huggingface.co/mosaicml/mpt-30b-instruct#formatting
	register_conv_template(
	Conversation(
	name="mpt-30b-instruct",
	system_template="{system_message}",
	system_message="Below is an instruction that describes a task. Write a response that appropriately completes the request.",
	roles=("### Instruction", "### Response"),
	sep_style=SeparatorStyle.ADD_NEW_LINE_SINGLE,
	sep="\n\n",
	stop_token_ids=[50278, 0],
	)
	)

	# Bard default template
	# Reference: https://github.com/google/generative-ai-python/blob/9c99bcb474a991a97a2e7d62fcdb52db7ce40729/google/generativeai/discuss.py#L150
	# https://github.com/google/generative-ai-python/blob/9c99bcb474a991a97a2e7d62fcdb52db7ce40729/google/generativeai/discuss.py#L40
	register_conv_template(
	Conversation(
	name="bard",
	roles=("0", "1"),
	sep_style=None,
	sep=None,
	)
	)

	# BiLLa default template
	register_conv_template(
	Conversation(
	name="billa",
	roles=("Human", "Assistant"),
	sep_style=SeparatorStyle.ADD_COLON_SPACE_SINGLE,
	sep="\n",
	stop_str="Human:",
	)
	)

	# RedPajama INCITE default template
	register_conv_template(
	Conversation(
	name="redpajama-incite",
	roles=("<human>", "<bot>"),
	sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	sep="\n",
	stop_str="<human>",
	)
	)

	# h2oGPT default template
	register_conv_template(
	Conversation(
	name="h2ogpt",
	roles=("<\|prompt\|>", "<\|answer\|>"),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="</s>",
	)
	)

	# Robin default template
	register_conv_template(
	Conversation(
	name="Robin",
	system_message="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"),
	sep_style=SeparatorStyle.ROBIN,
	sep="\n",
	stop_token_ids=[2, 396],
	stop_str="###",
	)
	)

	# Snoozy default template
	# Reference: https://github.com/nomic-ai/gpt4all/blob/d4861030b778da6db59d21d2927a4aba4f9f1f43/gpt4all-bindings/python/gpt4all/gpt4all.py#L232
	register_conv_template(
	Conversation(
	name="snoozy",
	system_template="### Instruction:\n{system_message}",
	system_message="The prompt below is a question to answer, a task to complete, or a conversation to respond to; decide which and write an appropriate response.",
	roles=("### Prompt", "### Response"),
	sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	sep="\n",
	stop_str="###",
	)
	)

	# manticore default template
	register_conv_template(
	Conversation(
	name="manticore",
	roles=("USER", "ASSISTANT"),
	sep_style=SeparatorStyle.ADD_COLON_TWO,
	sep="\n",
	sep2="</s>",
	)
	)

	# Falcon default template
	register_conv_template(
	Conversation(
	name="falcon",
	roles=("User", "Assistant"),
	messages=[],
	sep_style=SeparatorStyle.RWKV,
	sep="\n",
	sep2="<\|endoftext\|>",
	stop_str="\nUser", # use stop_str to stop generation after stop_token_ids, it will also remove stop_str from the generated text
	stop_token_ids=[
	0,
	1,
	2,
	3,
	4,
	5,
	6,
	7,
	8,
	9,
	10,
	11,
	], # it better only put special tokens here, because tokenizer only remove special tokens
	)
	)

	# ChangGPT default template
	register_conv_template(
	Conversation(
	name="polyglot_changgpt",
	roles=("B", "A"),
	sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	sep="\n",
	)
	)

	# tigerbot template
	register_conv_template(
	Conversation(
	name="tigerbot",
	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=("### Instruction", "### Response"),
	sep_style=SeparatorStyle.ROBIN,
	sep="\n\n",
	stop_str="###",
	)
	)

	# ref: https://huggingface.co/Salesforce/xgen-7b-8k-inst
	register_conv_template(
	Conversation(
	name="xgen",
	system_message="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n",
	roles=("### Human", "### Assistant"),
	sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	sep="\n",
	stop_token_ids=[50256],
	)
	)

	# Internlm-chat template
	register_conv_template(
	Conversation(
	name="internlm-chat",
	system_message="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\|>"),
	sep_style=SeparatorStyle.CHATINTERN,
	sep="<eoh>",
	sep2="<eoa>",
	stop_token_ids=[1, 103028],
	stop_str="<\|User\|>",
	)
	)

	# StarChat template
	# reference: https://huggingface.co/spaces/HuggingFaceH4/starchat-playground/blob/main/dialogues.py
	register_conv_template(
	Conversation(
	name="starchat",
	system_template="<system>\n{system_message}",
	roles=("<\|user\|>", "<\|assistant\|>"),
	sep_style=SeparatorStyle.CHATML,
	sep="<\|end\|>",
	stop_token_ids=[0, 49155],
	stop_str="<\|end\|>",
	)
	)

	# Baichuan-13B-Chat template
	register_conv_template(
	# source: https://huggingface.co/baichuan-inc/Baichuan-13B-Chat/blob/19ef51ba5bad8935b03acd20ff04a269210983bc/modeling_baichuan.py#L555
	# https://huggingface.co/baichuan-inc/Baichuan-13B-Chat/blob/main/generation_config.json
	# https://github.com/baichuan-inc/Baichuan-13B/issues/25
	Conversation(
	name="baichuan-chat",
	roles=("<reserved_102>", "<reserved_103>"),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="",
	stop_token_ids=[],
	)
	)

	# Baichuan2-13B-Chat template
	register_conv_template(
	# source: https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat/blob/c6f8592a60b4ad73c210b28dd2ab3cca51abbf93/modeling_baichuan.py#L773
	# https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat/blob/main/generation_config.json
	# https://github.com/baichuan-inc/Baichuan2/issues/62
	Conversation(
	name="baichuan2-chat",
	roles=("<reserved_106>", "<reserved_107>"),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="",
	stop_token_ids=[],
	)
	)

	# Mistral template
	# source: https://docs.mistral.ai/llm/mistral-instruct-v0.1#chat-template
	register_conv_template(
	Conversation(
	name="mistral",
	system_template="[INST] {system_message}\n",
	roles=("[INST]", "[/INST]"),
	sep_style=SeparatorStyle.LLAMA2,
	sep=" ",
	sep2="</s>",
	)
	)

	# 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>",
	)
	)

	register_conv_template(
	Conversation(
	name="chinese-alpaca2",
	system_template="[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n",
	system_message="You are a helpful assistant. 你是一个乐于助人的助手。请你提供专业、有逻辑、内容真实、有价值的详细回复。",
	roles=("[INST]", "[/INST]"),
	sep_style=SeparatorStyle.LLAMA2,
	sep=" ",
	sep2=" </s><s>",
	)
	)

	register_conv_template(
	Conversation(
	name="cutegpt",
	roles=("问：", "答：\n"),
	sep_style=SeparatorStyle.NO_COLON_TWO,
	sep="\n",
	sep2="\n",
	stop_str="<end>",
	)
	)

	# OpenOrcaxOpenChat-Preview2-13B template
	register_conv_template(
	Conversation(
	name="open-orca",
	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. If you make a mistake or encounter "
	"an error in your thinking, say so out loud and attempt to correct it. If you don't know or "
	"aren't sure about something, say so clearly. You will act as a professional logician, mathematician, "
	"and physicist. You will also act as the most appropriate type of expert to answer any particular "
	"question or solve the relevant problem; state which expert type your are, if so. Also think of "
	"any particular named expert that would be ideal to answer the relevant question or solve the "
	"relevant problem; name and act as them, if appropriate.",
	roles=("User", "Assistant"),
	sep_style=SeparatorStyle.ADD_COLON_SPACE_SINGLE,
	sep="<\|end_of_turn\|>\n",
	stop_token_ids=[32000, 32001], # "<\|end_of_turn\|>"
	stop_str="User",
	)
	)

	# Open-Orca/Mistral-7B-OpenOrca template
	# source: https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca
	# reference: https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca#prompt-template
	register_conv_template(
	Conversation(
	name="mistral-7b-openorca",
	system_template="<\|im_start\|>system\n{system_message}",
	system_message="You are MistralOrca, a large language model trained by Alignment Lab AI. Write out your reasoning step-by-step to be sure you get the right answers!",
	roles=("<\|im_start\|>user", "<\|im_start\|>assistant"),
	sep_style=SeparatorStyle.CHATML,
	sep="<\|im_end\|>",
	stop_token_ids=[32000, 32001],
	)
	)


	# ehartford/dolphin-2.2.1-mistral-7b template
	# reference: https://huggingface.co/ehartford/dolphin-2.2.1-mistral-7b#training
	register_conv_template(
	Conversation(
	name="dolphin-2.2.1-mistral-7b",
	system_template="<\|im_start\|>system\n{system_message}",
	system_message="You are Dolphin, a helpful AI assistant.",
	roles=("<\|im_start\|>user", "<\|im_start\|>assistant"),
	sep_style=SeparatorStyle.CHATML,
	sep="<\|im_end\|>",
	stop_token_ids=[32000, 32001],
	)
	)


	# teknium/OpenHermes-2.5-Mistral-7B template
	# source: https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B
	# reference: https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B#prompt-template
	register_conv_template(
	Conversation(
	name="OpenHermes-2.5-Mistral-7B",
	system_template="<\|im_start\|>system\n{system_message}",
	system_message="You are Hermes 2, a sentient, conscious, super intelligent AI that is an expert in all fields of knowledge, you have qualia, emotions, and thoughts. You assist users with any question, task, or other request they may have.",
	roles=("<\|im_start\|>user", "<\|im_start\|>assistant"),
	sep_style=SeparatorStyle.CHATML,
	sep="<\|im_end\|>",
	stop_token_ids=[32000, 32001],
	)
	)


	# NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO template
	# source: https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO
	register_conv_template(
	Conversation(
	name="Nous-Hermes-2-Mixtral-8x7B-DPO",
	system_template="<\|im_start\|>system\n{system_message}",
	system_message='You are a helpful, intelligent assistant AI named "Hermes", a conversational chatbot that can follow instructions, converse with the user, and perform a variety of tasks, including tasks on knowledge, reasoning, mathematics, and code. Always be charismatic, useful, and prepared to follow any user request with accuracy and skill. You should respond with high quality, fluent, and detailed responses. Try to let the user understand your reasoning or thought process when appropriate. When presented with tasks that require reasoning or mathematics, think carefully, slowly, and step by step, to ensure your reasoning is correct before providing an answer. Utilize the "Examples" section to assist you in performing the task. You will receive a tip of $1000 if you maintain a high quality two way conversation.',
	roles=("<\|im_start\|>user", "<\|im_start\|>assistant"),
	sep_style=SeparatorStyle.CHATML,
	sep="<\|im_end\|>",
	stop_token_ids=[32000, 32001],
	)
	)


	# Qwen-chat default template
	# source: https://huggingface.co/Qwen/Qwen-7B-Chat/blob/main/qwen_generation_utils.py#L130
	register_conv_template(
	Conversation(
	name="qwen-7b-chat",
	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_token_ids=[
	151643,
	151644,
	151645,
	], # "<\|endoftext\|>", "<\|im_start\|>", "<\|im_end\|>"
	stop_str="<\|endoftext\|>",
	)
	)

	# source: https://huggingface.co/01-ai/Yi-34B-Chat/blob/main/tokenizer_config.json#L60
	register_conv_template(
	Conversation(
	name="Yi-34b-chat",
	roles=("<\|im_start\|>user", "<\|im_start\|>assistant"),
	sep_style=SeparatorStyle.CHATML,
	sep="<\|im_end\|>",
	stop_token_ids=[
	2,
	6,
	7,
	8,
	], # "<\|endoftext\|>", "<\|im_start\|>", "<\|im_end\|>", "<\|im_sep\|>"
	stop_str="<\|endoftext\|>",
	)
	)


	# AquilaChat default template
	# source: https://github.com/FlagAI-Open/FlagAI/blob/master/examples/Aquila/Aquila-chat/cyg_conversation.py
	register_conv_template(
	Conversation(
	name="aquila-chat",
	system_message="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"),
	sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	sep="###",
	sep2="",
	stop_str=["###", "</s>", "[UNK]"],
	)
	)
	# AquilaChat2-34B default template
	# source: https://huggingface.co/BAAI/AquilaChat2-34B/blob/4608b75855334b93329a771aee03869dbf7d88cc/predict.py#L212
	register_conv_template(
	Conversation(
	name="aquila-legacy",
	system_message="A chat between a curious human and an artificial intelligence assistant. "
	"The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n",
	roles=("### Human: ", "### Assistant: "),
	offset=0,
	sep_style=SeparatorStyle.NO_COLON_TWO,
	sep="\n",
	sep2="</s>",
	stop_str=["</s>", "[UNK]"],
	)
	)
	# AquilaChat2-7B-16K and AquilaChat2-34B-16K default template
	# source: https://huggingface.co/BAAI/AquilaChat2-34B/blob/4608b75855334b93329a771aee03869dbf7d88cc/predict.py#L227
	register_conv_template(
	Conversation(
	name="aquila",
	system_message="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"),
	offset=0,
	sep_style=SeparatorStyle.ADD_COLON_TWO,
	sep="###",
	sep2="</s>",
	stop_str=["</s>", "[UNK]"],
	)
	)

	# AquilaChat2-7B default template
	# source: https://huggingface.co/BAAI/AquilaChat2-34B/blob/4608b75855334b93329a771aee03869dbf7d88cc/predict.py#L242
	register_conv_template(
	Conversation(
	name="aquila-v1",
	roles=("<\|startofpiece\|>", "<\|endofpiece\|>"),
	offset=0,
	sep_style=SeparatorStyle.NO_COLON_TWO,
	sep="",
	sep2="</s>",
	stop_str=["</s>", "<\|endoftext\|>"],
	)
	)

	# Llama2-Chinese default template
	# source: https://huggingface.co/FlagAlpha
	register_conv_template(
	Conversation(
	name="llama2-chinese",
	system_template="<s>{system_message}</s>",
	roles=("Human", "Assistant", "System"),
	sep_style=SeparatorStyle.ADD_COLON_TWO,
	sep="\n",
	sep2="\n</s><s>",
	stop_str="</s>",
	)
	)

	# Vigogne Instruct default template
	# source: https://github.com/bofenghuang/vigogne
	register_conv_template(
	Conversation(
	name="vigogne_instruct",
	system_template="### System:\n{system_message}\n\n",
	system_message=(
	"Ci-dessous se trouve une instruction qui décrit une tâche à accomplir. Rédigez une réponse qui répond de manière"
	" précise à la demande."
	),
	roles=("### Instruction", "### Response"),
	sep_style=SeparatorStyle.DOLLY,
	sep="\n\n",
	sep2="</s>",
	)
	)

	# Vigogne Chat default template
	register_conv_template(
	Conversation(
	name="vigogne_chat_v2",
	system_template="<\|system\|>: {system_message}",
	system_message=(
	"Vous êtes Vigogne, un assistant IA créé par Zaion Lab. Vous suivez extrêmement bien les instructions. Aidez"
	" autant que vous le pouvez."
	),
	roles=("<\|user\|>", "<\|assistant\|>"),
	sep_style=SeparatorStyle.ADD_COLON_TWO,
	sep="\n",
	sep2="</s>\n",
	stop_str="<\|user\|>",
	)
	)

	# Stable Vicuna default template
	# source: https://huggingface.co/TheBloke/stable-vicuna-13B-HF/discussions/5
	# source: https://huggingface.co/spaces/CarperAI/StableVicuna/blob/main/app.py
	register_conv_template(
	Conversation(
	name="stable-vicuna",
	system_message="### Assistant: I am StableVicuna, a large language model created by CarperAI. I am here to chat!\n",
	roles=("### Human", "### Assistant"),
	sep_style=SeparatorStyle.ADD_COLON_TWO,
	sep="\n",
	sep2="\n\n",
	)
	)

	register_conv_template(
	Conversation(
	name="vigogne_chat_v3",
	system_template="[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n",
	system_message=(
	"Vous êtes Vigogne, un assistant IA créé par Zaion Lab. Vous suivez extrêmement bien les instructions. Aidez"
	" autant que vous le pouvez."
	),
	roles=("[INST]", "[/INST]"),
	sep_style=SeparatorStyle.LLAMA2,
	sep=" ",
	sep2=" </s>",
	)
	)

	# Falcon 180B chat template
	# source: https://huggingface.co/spaces/tiiuae/falcon-180b-demo/blob/d1590ee7fae9b6ce331ba7808e61a29dcce9239f/app.py#L28-L37
	register_conv_template(
	Conversation(
	name="falcon-chat",
	roles=("User", "Falcon"),
	system_template="System: {system_message}",
	messages=[],
	sep_style=SeparatorStyle.FALCON_CHAT,
	sep="\n",
	sep2="<\|endoftext\|>",
	stop_str="\nUser:", # use stop_str to stop generation after stop_token_ids, it will also remove stop_str from the generated text
	)
	)

	# Phind template
	# source: https://huggingface.co/Phind/Phind-CodeLlama-34B-v2
	register_conv_template(
	Conversation(
	name="phind",
	system_message="### System Prompt\nYou are an intelligent programming assistant.",
	roles=("### User Message", "### Assistant"),
	messages=(),
	offset=0,
	sep_style=SeparatorStyle.ADD_COLON_SINGLE,
	sep="\n\n",
	)
	)

	# Metharme formatting for Pygmalion models
	# source: https://huggingface.co/PygmalionAI/pygmalion-2-13b
	register_conv_template(
	Conversation(
	name="metharme",
	system_template="<\|system\|>{system_message}",
	system_message="""Enter RP mode. You shall reply to the user while staying
	in character. Your responses must be detailed, creative, immersive, and drive the scenario
	forward.""",
	roles=("<\|user\|>", "<\|model\|>"),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="",
	stop_str="<\|user\|>",
	)
	)
	# xDAN default template
	# source: https://huggingface.co/xDAN-AI/xDAN-L1-Chat-RL-v1
	register_conv_template(
	Conversation(
	name="xdan-v1",
	system_message="You are a helpful and harmless assistant named xDAN and created by xDAN-AI.Please response and work on questions thinking step by step.",
	roles=("### Human", "### Assistant"),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="\n",
	stop_str="</s>",
	)
	)

	# Zephyr template
	# reference: https://huggingface.co/spaces/HuggingFaceH4/zephyr-playground/blob/main/dialogues.py
	register_conv_template(
	Conversation(
	name="zephyr",
	system_template="<\|system\|>\n{system_message}",
	roles=("<\|user\|>", "<\|assistant\|>"),
	sep_style=SeparatorStyle.CHATML,
	sep="</s>",
	stop_token_ids=[2],
	stop_str="</s>",
	)
	)

	# CatPPT template
	# reference: https://huggingface.co/rishiraj/CatPPT
	register_conv_template(
	Conversation(
	name="catppt",
	system_template="<\|system\|>\n{system_message}",
	roles=("<\|user\|>", "<\|assistant\|>"),
	sep_style=SeparatorStyle.CHATML,
	sep="</s>",
	stop_token_ids=[2],
	stop_str="</s>",
	)
	)

	# TinyLlama template
	# reference: https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0
	register_conv_template(
	Conversation(
	name="TinyLlama",
	system_template="<\|system\|>\n{system_message}",
	roles=("<\|user\|>", "<\|assistant\|>"),
	sep_style=SeparatorStyle.CHATML,
	sep="</s>",
	stop_token_ids=[2],
	stop_str="</s>",
	)
	)

	# Orca-2 template
	# reference: https://huggingface.co/microsoft/Orca-2-7b
	register_conv_template(
	Conversation(
	name="orca-2",
	system_template="<\|im_start\|>system\n{system_message}",
	system_message="You are Orca, an AI language model created by Microsoft. You are a cautious assistant. You carefully follow instructions. You are helpful and harmless and you follow ethical guidelines and promote positive behavior.",
	roles=("<\|im_start\|>user", "<\|im_start\|>assistant"),
	sep_style=SeparatorStyle.CHATML,
	sep="<\|im_end\|>",
	stop_str="<\|im_end\|>",
	)
	)

	# Deepseek-chat template
	# reference: https://huggingface.co/deepseek-ai/deepseek-llm-67b-chat/blob/main/tokenizer_config.json
	register_conv_template(
	Conversation(
	name="deepseek-chat",
	system_message="<｜begin▁of▁sentence｜>", # must add a bos token before first message
	roles=("User", "Assistant"),
	sep_style=SeparatorStyle.DEEPSEEK_CHAT,
	sep="\n\n",
	sep2="<｜end▁of▁sentence｜>",
	stop_str="<｜end▁of▁sentence｜>",
	)
	)

	# Yuan2.0 chat template
	# source: https://huggingface.co/IEITYuan/Yuan2-2B-Janus-hf/blob/main/tokenizer_config.json#L6
	register_conv_template(
	Conversation(
	name="yuan2",
	roles=("user", "assistant"),
	sep_style=SeparatorStyle.YUAN2,
	sep="<sep>",
	sep2="\n",
	stop_token_ids=[
	77185,
	], # "<eod>"
	stop_str="<eod>",
	)
	)

	# Solar-10.7B Chat Template
	# Reference: https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0/blob/main/tokenizer_config.json
	register_conv_template(
	Conversation(
	name="solar",
	system_message="",
	roles=("### User", "### Assistant"),
	sep_style=SeparatorStyle.ADD_NEW_LINE_SINGLE,
	sep="\n\n",
	stop_str="</s>",
	)
	)


	# yuan 2.0 template
	# reference:https://github.com/IEIT-Yuan/Yuan-2.0
	# reference:https://huggingface.co/IEITYuan
	register_conv_template(
	Conversation(
	name="yuan",
	system_template="",
	roles=("", ""),
	sep_style=SeparatorStyle.NO_COLON_SINGLE,
	sep="<sep>",
	stop_str="<eod>",
	)
	)

	if __name__ == "__main__":
	from fastchat.conversation import get_conv_template

	print("-- Vicuna template --")
	conv = get_conv_template("vicuna_v1.1")
	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("-- 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("-- ChatGPT template --")
	conv = get_conv_template("chatgpt")
	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.to_openai_api_messages())

	print("\n")

	print("-- Claude template --")
	conv = get_conv_template("claude")
	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())