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# Copyright 2025 the LlamaFactory 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.
from dataclasses import dataclass
from typing import TYPE_CHECKING, Optional, Union
from typing_extensions import override
from ..extras import logging
from ..extras.misc import check_version
from .data_utils import Role
from .formatter import EmptyFormatter, FunctionFormatter, StringFormatter, ToolFormatter
from .mm_plugin import get_mm_plugin
if TYPE_CHECKING:
from transformers import PreTrainedTokenizer
from ..hparams import DataArguments
from .formatter import SLOTS, Formatter
from .mm_plugin import BasePlugin
from .tool_utils import FunctionCall
logger = logging.get_logger(__name__)
@dataclass
class Template:
format_user: "Formatter"
format_assistant: "Formatter"
format_system: "Formatter"
format_function: "Formatter"
format_observation: "Formatter"
format_tools: "Formatter"
format_prefix: "Formatter"
default_system: str
stop_words: list[str]
thought_words: tuple[str, str]
efficient_eos: bool
replace_eos: bool
replace_jinja_template: bool
mm_plugin: "BasePlugin"
def encode_oneturn(
self,
tokenizer: "PreTrainedTokenizer",
messages: list[dict[str, str]],
system: Optional[str] = None,
tools: Optional[str] = None,
) -> tuple[list[int], list[int]]:
r"""Return a single pair of token ids representing prompt and response respectively."""
encoded_messages = self._encode(tokenizer, messages, system, tools)
prompt_ids = []
for encoded_ids in encoded_messages[:-1]:
prompt_ids += encoded_ids
response_ids = encoded_messages[-1]
return prompt_ids, response_ids
def encode_multiturn(
self,
tokenizer: "PreTrainedTokenizer",
messages: list[dict[str, str]],
system: Optional[str] = None,
tools: Optional[str] = None,
) -> list[tuple[list[int], list[int]]]:
r"""Return multiple pairs of token ids representing prompts and responses respectively."""
encoded_messages = self._encode(tokenizer, messages, system, tools)
return [(encoded_messages[i], encoded_messages[i + 1]) for i in range(0, len(encoded_messages), 2)]
def extract_tool(self, content: str) -> Union[str, list["FunctionCall"]]:
r"""Extract tool message."""
return self.format_tools.extract(content)
def get_stop_token_ids(self, tokenizer: "PreTrainedTokenizer") -> list[int]:
r"""Return stop token ids."""
stop_token_ids = {tokenizer.eos_token_id}
for token in self.stop_words:
stop_token_ids.add(tokenizer.convert_tokens_to_ids(token))
return list(stop_token_ids)
def _convert_elements_to_ids(self, tokenizer: "PreTrainedTokenizer", elements: "SLOTS") -> list[int]:
r"""Convert elements to token ids."""
token_ids = []
for elem in elements:
if isinstance(elem, str):
if len(elem) != 0:
token_ids += tokenizer.encode(elem, add_special_tokens=False)
elif isinstance(elem, dict):
token_ids += [tokenizer.convert_tokens_to_ids(elem.get("token"))]
elif isinstance(elem, set):
if "bos_token" in elem and tokenizer.bos_token_id is not None:
token_ids += [tokenizer.bos_token_id]
elif "eos_token" in elem and tokenizer.eos_token_id is not None:
token_ids += [tokenizer.eos_token_id]
else:
raise ValueError(f"Input must be string, set[str] or dict[str, str], got {type(elem)}")
return token_ids
def _encode(
self,
tokenizer: "PreTrainedTokenizer",
messages: list[dict[str, str]],
system: Optional[str],
tools: Optional[str],
) -> list[list[int]]:
r"""Encode formatted inputs to pairs of token ids.
Turn 0: prefix + system + query resp
Turn t: query resp.
"""
system = system or self.default_system
encoded_messages = []
for i, message in enumerate(messages):
elements = []
if i == 0:
elements += self.format_prefix.apply()
if system or tools:
tool_text = self.format_tools.apply(content=tools)[0] if tools else ""
elements += self.format_system.apply(content=(system + tool_text))
if message["role"] == Role.USER.value:
elements += self.format_user.apply(content=message["content"], idx=str(i // 2))
elif message["role"] == Role.ASSISTANT.value:
elements += self.format_assistant.apply(content=message["content"])
elif message["role"] == Role.OBSERVATION.value:
elements += self.format_observation.apply(content=message["content"])
elif message["role"] == Role.FUNCTION.value:
elements += self.format_function.apply(content=message["content"])
else:
raise NotImplementedError("Unexpected role: {}".format(message["role"]))
encoded_messages.append(self._convert_elements_to_ids(tokenizer, elements))
return encoded_messages
@staticmethod
def _add_or_replace_eos_token(tokenizer: "PreTrainedTokenizer", eos_token: str) -> None:
r"""Add or replace eos token to the tokenizer."""
is_added = tokenizer.eos_token_id is None
num_added_tokens = tokenizer.add_special_tokens({"eos_token": eos_token})
if is_added:
logger.info_rank0(f"Add eos token: {tokenizer.eos_token}.")
else:
logger.info_rank0(f"Replace eos token: {tokenizer.eos_token}.")
if num_added_tokens > 0:
logger.warning_rank0("New tokens have been added, make sure `resize_vocab` is True.")
def fix_special_tokens(self, tokenizer: "PreTrainedTokenizer") -> None:
r"""Add eos token and pad token to the tokenizer."""
stop_words = self.stop_words
if self.replace_eos:
if not stop_words:
raise ValueError("Stop words are required to replace the EOS token.")
self._add_or_replace_eos_token(tokenizer, eos_token=stop_words[0])
stop_words = stop_words[1:]
if tokenizer.eos_token_id is None:
self._add_or_replace_eos_token(tokenizer, eos_token="<|endoftext|>")
if tokenizer.pad_token_id is None:
tokenizer.pad_token = tokenizer.eos_token
logger.info_rank0(f"Add pad token: {tokenizer.pad_token}")
if stop_words:
num_added_tokens = tokenizer.add_special_tokens(
dict(additional_special_tokens=stop_words), replace_additional_special_tokens=False
)
logger.info_rank0("Add {} to stop words.".format(",".join(stop_words)))
if num_added_tokens > 0:
logger.warning_rank0("New tokens have been added, make sure `resize_vocab` is True.")
@staticmethod
def _jinja_escape(content: str) -> str:
r"""Escape single quotes in content."""
return content.replace("'", r"\'")
@staticmethod
def _convert_slots_to_jinja(slots: "SLOTS", tokenizer: "PreTrainedTokenizer", placeholder: str = "content") -> str:
r"""Convert slots to jinja template."""
slot_items = []
for slot in slots:
if isinstance(slot, str):
slot_pieces = slot.split("{{content}}")
if slot_pieces[0]:
slot_items.append("'" + Template._jinja_escape(slot_pieces[0]) + "'")
if len(slot_pieces) > 1:
slot_items.append(placeholder)
if slot_pieces[1]:
slot_items.append("'" + Template._jinja_escape(slot_pieces[1]) + "'")
elif isinstance(slot, set): # do not use {{ eos_token }} since it may be replaced
if "bos_token" in slot and tokenizer.bos_token_id is not None:
slot_items.append("'" + tokenizer.bos_token + "'")
elif "eos_token" in slot and tokenizer.eos_token_id is not None:
slot_items.append("'" + tokenizer.eos_token + "'")
elif isinstance(slot, dict):
raise ValueError("Dict is not supported.")
return " + ".join(slot_items)
def _get_jinja_template(self, tokenizer: "PreTrainedTokenizer") -> str:
r"""Return the jinja template."""
prefix = self._convert_slots_to_jinja(self.format_prefix.apply(), tokenizer)
system = self._convert_slots_to_jinja(self.format_system.apply(), tokenizer, placeholder="system_message")
user = self._convert_slots_to_jinja(self.format_user.apply(), tokenizer)
assistant = self._convert_slots_to_jinja(self.format_assistant.apply(), tokenizer)
jinja_template = ""
if prefix:
jinja_template += "{{ " + prefix + " }}"
if self.default_system:
jinja_template += "{% set system_message = '" + self._jinja_escape(self.default_system) + "' %}"
jinja_template += (
"{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}"
"{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% endif %}"
"{% if system_message is defined %}{{ " + system + " }}{% endif %}"
"{% for message in loop_messages %}"
"{% set content = message['content'] %}"
"{% if message['role'] == 'user' %}"
"{{ " + user + " }}"
"{% elif message['role'] == 'assistant' %}"
"{{ " + assistant + " }}"
"{% endif %}"
"{% endfor %}"
)
return jinja_template
def fix_jinja_template(self, tokenizer: "PreTrainedTokenizer") -> None:
r"""Replace the jinja template in the tokenizer."""
if tokenizer.chat_template is None or self.replace_jinja_template:
try:
tokenizer.chat_template = self._get_jinja_template(tokenizer)
except ValueError as e:
logger.info_rank0(f"Cannot add this chat template to tokenizer: {e}.")
@staticmethod
def _convert_slots_to_ollama(
slots: "SLOTS", tokenizer: "PreTrainedTokenizer", placeholder: str = "content"
) -> str:
r"""Convert slots to ollama template."""
slot_items = []
for slot in slots:
if isinstance(slot, str):
slot_pieces = slot.split("{{content}}")
if slot_pieces[0]:
slot_items.append(slot_pieces[0])
if len(slot_pieces) > 1:
slot_items.append("{{ " + placeholder + " }}")
if slot_pieces[1]:
slot_items.append(slot_pieces[1])
elif isinstance(slot, set): # do not use {{ eos_token }} since it may be replaced
if "bos_token" in slot and tokenizer.bos_token_id is not None:
slot_items.append(tokenizer.bos_token)
elif "eos_token" in slot and tokenizer.eos_token_id is not None:
slot_items.append(tokenizer.eos_token)
elif isinstance(slot, dict):
raise ValueError("Dict is not supported.")
return "".join(slot_items)
def _get_ollama_template(self, tokenizer: "PreTrainedTokenizer") -> str:
r"""Return the ollama template."""
prefix = self._convert_slots_to_ollama(self.format_prefix.apply(), tokenizer)
system = self._convert_slots_to_ollama(self.format_system.apply(), tokenizer, placeholder=".System")
user = self._convert_slots_to_ollama(self.format_user.apply(), tokenizer, placeholder=".Content")
assistant = self._convert_slots_to_ollama(self.format_assistant.apply(), tokenizer, placeholder=".Content")
return (
f"{prefix}{{{{ if .System }}}}{system}{{{{ end }}}}"
f"""{{{{ range .Messages }}}}{{{{ if eq .Role "user" }}}}{user}"""
f"""{{{{ else if eq .Role "assistant" }}}}{assistant}{{{{ end }}}}{{{{ end }}}}"""
)
def get_ollama_modelfile(self, tokenizer: "PreTrainedTokenizer") -> str:
r"""Return the ollama modelfile.
TODO: support function calling.
"""
modelfile = "# ollama modelfile auto-generated by llamafactory\n\n"
modelfile += f'FROM .\n\nTEMPLATE """{self._get_ollama_template(tokenizer)}"""\n\n'
if self.default_system:
modelfile += f'SYSTEM """{self.default_system}"""\n\n'
for stop_token_id in self.get_stop_token_ids(tokenizer):
modelfile += f'PARAMETER stop "{tokenizer.convert_ids_to_tokens(stop_token_id)}"\n'
modelfile += "PARAMETER num_ctx 4096\n"
return modelfile
@dataclass
class Llama2Template(Template):
r"""A template that fuse the system message to first user message."""
@override
def _encode(
self,
tokenizer: "PreTrainedTokenizer",
messages: list[dict[str, str]],
system: str,
tools: str,
) -> list[list[int]]:
system = system or self.default_system
encoded_messages = []
for i, message in enumerate(messages):
elements = []
system_text = ""
if i == 0:
elements += self.format_prefix.apply()
if system or tools:
tool_text = self.format_tools.apply(content=tools)[0] if tools else ""
system_text = self.format_system.apply(content=(system + tool_text))[0]
if message["role"] == Role.USER.value:
elements += self.format_user.apply(content=system_text + message["content"])
elif message["role"] == Role.ASSISTANT.value:
elements += self.format_assistant.apply(content=message["content"])
elif message["role"] == Role.OBSERVATION.value:
elements += self.format_observation.apply(content=message["content"])
elif message["role"] == Role.FUNCTION.value:
elements += self.format_function.apply(content=message["content"])
else:
raise NotImplementedError("Unexpected role: {}".format(message["role"]))
encoded_messages.append(self._convert_elements_to_ids(tokenizer, elements))
return encoded_messages
def _get_jinja_template(self, tokenizer: "PreTrainedTokenizer") -> str:
prefix = self._convert_slots_to_jinja(self.format_prefix.apply(), tokenizer)
system_message = self._convert_slots_to_jinja(
self.format_system.apply(), tokenizer, placeholder="system_message"
)
user_message = self._convert_slots_to_jinja(self.format_user.apply(), tokenizer)
assistant_message = self._convert_slots_to_jinja(self.format_assistant.apply(), tokenizer)
jinja_template = ""
if prefix:
jinja_template += "{{ " + prefix + " }}"
if self.default_system:
jinja_template += "{% set system_message = '" + self._jinja_escape(self.default_system) + "' %}"
jinja_template += (
"{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}"
"{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% endif %}"
"{% for message in loop_messages %}"
"{% if loop.index0 == 0 and system_message is defined %}"
"{% set content = " + system_message + " + message['content'] %}"
"{% else %}{% set content = message['content'] %}{% endif %}"
"{% if message['role'] == 'user' %}"
"{{ " + user_message + " }}"
"{% elif message['role'] == 'assistant' %}"
"{{ " + assistant_message + " }}"
"{% endif %}"
"{% endfor %}"
)
return jinja_template
TEMPLATES: dict[str, "Template"] = {}
def register_template(
name: str,
format_user: Optional["Formatter"] = None,
format_assistant: Optional["Formatter"] = None,
format_system: Optional["Formatter"] = None,
format_function: Optional["Formatter"] = None,
format_observation: Optional["Formatter"] = None,
format_tools: Optional["Formatter"] = None,
format_prefix: Optional["Formatter"] = None,
default_system: str = "",
stop_words: Optional[list[str]] = None,
thought_words: Optional[tuple[str, str]] = None,
efficient_eos: bool = False,
replace_eos: bool = False,
replace_jinja_template: bool = False,
mm_plugin: "BasePlugin" = get_mm_plugin(name="base"),
template_class: type["Template"] = Template,
) -> None:
r"""Register a chat template.
To add the following chat template:
```
<s><user>user prompt here
<model>model response here</s>
<user>user prompt here
<model>model response here</s>
```
The corresponding code should be:
```
register_template(
name="custom",
format_user=StringFormatter(slots=["<user>{{content}}\n<model>"]),
format_assistant=StringFormatter(slots=["{{content}}</s>\n"]),
format_prefix=EmptyFormatter("<s>"),
)
```
"""
if name in TEMPLATES:
raise ValueError(f"Template {name} already exists.")
default_slots = ["{{content}}"] if efficient_eos else ["{{content}}", {"eos_token"}]
default_user_formatter = StringFormatter(slots=["{{content}}"])
default_assistant_formatter = StringFormatter(slots=default_slots)
default_function_formatter = FunctionFormatter(slots=default_slots, tool_format="default")
default_tool_formatter = ToolFormatter(tool_format="default")
default_prefix_formatter = EmptyFormatter()
TEMPLATES[name] = template_class(
format_user=format_user or default_user_formatter,
format_assistant=format_assistant or default_assistant_formatter,
format_system=format_system or default_user_formatter,
format_function=format_function or default_function_formatter,
format_observation=format_observation or format_user or default_user_formatter,
format_tools=format_tools or default_tool_formatter,
format_prefix=format_prefix or default_prefix_formatter,
default_system=default_system,
stop_words=stop_words or [],
thought_words=thought_words or ("<think>", "</think>"),
efficient_eos=efficient_eos,
replace_eos=replace_eos,
replace_jinja_template=replace_jinja_template,
mm_plugin=mm_plugin,
)
def parse_template(tokenizer: "PreTrainedTokenizer") -> "Template":
r"""Extract a chat template from the tokenizer."""
def find_diff(short_str: str, long_str: str) -> str:
i, j = 0, 0
diff = ""
while i < len(short_str) and j < len(long_str):
if short_str[i] == long_str[j]:
i += 1
j += 1
else:
diff += long_str[j]
j += 1
return diff
prefix = tokenizer.decode(tokenizer.encode(""))
messages = [{"role": "system", "content": "{{content}}"}]
system_slot = tokenizer.apply_chat_template(messages, add_generation_prompt=False, tokenize=False)[len(prefix) :]
messages = [{"role": "system", "content": ""}, {"role": "user", "content": "{{content}}"}]
user_slot_empty_system = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
user_slot_empty_system = user_slot_empty_system[len(prefix) :]
messages = [{"role": "user", "content": "{{content}}"}]
user_slot = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
user_slot = user_slot[len(prefix) :]
messages = [{"role": "user", "content": "{{content}}"}, {"role": "assistant", "content": "{{content}}"}]
assistant_slot = tokenizer.apply_chat_template(messages, add_generation_prompt=False, tokenize=False)
assistant_slot = assistant_slot[len(prefix) + len(user_slot) :]
if len(user_slot) > len(user_slot_empty_system):
default_system = find_diff(user_slot_empty_system, user_slot)
sole_system = system_slot.replace("{{content}}", default_system, 1)
user_slot = user_slot[len(sole_system) :]
else: # if defaut_system is empty, user_slot_empty_system will be longer than user_slot
default_system = ""
return Template(
format_user=StringFormatter(slots=[user_slot]),
format_assistant=StringFormatter(slots=[assistant_slot]),
format_system=StringFormatter(slots=[system_slot]),
format_function=FunctionFormatter(slots=[assistant_slot], tool_format="default"),
format_observation=StringFormatter(slots=[user_slot]),
format_tools=ToolFormatter(tool_format="default"),
format_prefix=EmptyFormatter(slots=[prefix]) if prefix else EmptyFormatter(),
default_system=default_system,
stop_words=[],
thought_words=("<think>", "</think>"),
efficient_eos=False,
replace_eos=False,
replace_jinja_template=False,
mm_plugin=get_mm_plugin(name="base"),
)
def get_template_and_fix_tokenizer(tokenizer: "PreTrainedTokenizer", data_args: "DataArguments") -> "Template":
r"""Get chat template and fixes the tokenizer."""
if data_args.template is None:
if isinstance(tokenizer.chat_template, str):
logger.warning_rank0("`template` was not specified, try parsing the chat template from the tokenizer.")
template = parse_template(tokenizer)
else:
logger.warning_rank0("`template` was not specified, use `empty` template.")
template = TEMPLATES["empty"] # placeholder
else:
if data_args.template not in TEMPLATES:
raise ValueError(f"Template {data_args.template} does not exist.")
template = TEMPLATES[data_args.template]
if template.mm_plugin.__class__.__name__ != "BasePlugin":
check_version("transformers>=4.45.0")
if data_args.train_on_prompt and template.efficient_eos:
raise ValueError("Current template does not support `train_on_prompt`.")
if data_args.tool_format is not None:
logger.info_rank0(f"Using tool format: {data_args.tool_format}.")
default_slots = ["{{content}}"] if template.efficient_eos else ["{{content}}", {"eos_token"}]
template.format_function = FunctionFormatter(slots=default_slots, tool_format=data_args.tool_format)
template.format_tools = ToolFormatter(tool_format=data_args.tool_format)
template.fix_special_tokens(tokenizer)
template.fix_jinja_template(tokenizer)
return template
register_template(
name="alpaca",
format_user=StringFormatter(slots=["### Instruction:\n{{content}}\n\n### Response:\n"]),
format_assistant=StringFormatter(slots=["{{content}}", {"eos_token"}, "\n\n"]),
default_system=(
"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n"
),
replace_jinja_template=True,
)
register_template(
name="aquila",
format_user=StringFormatter(slots=["Human: {{content}}###Assistant:"]),
format_assistant=StringFormatter(slots=["{{content}}###"]),
format_system=StringFormatter(slots=["System: {{content}}###"]),
default_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."
),
stop_words=["</s>"],
)
register_template(
name="atom",
format_user=StringFormatter(
slots=[{"bos_token"}, "Human: {{content}}\n", {"eos_token"}, {"bos_token"}, "Assistant:"]
),
format_assistant=StringFormatter(slots=["{{content}}\n", {"eos_token"}]),
)
register_template(
name="baichuan",
format_user=StringFormatter(slots=[{"token": "<reserved_102>"}, "{{content}}", {"token": "<reserved_103>"}]),
efficient_eos=True,
)
register_template(
name="baichuan2",
format_user=StringFormatter(slots=["<reserved_106>{{content}}<reserved_107>"]),
efficient_eos=True,
)
register_template(
name="bailing",
format_user=StringFormatter(slots=["<role>HUMAN</role>{{content}}<role>ASSISTANT</role>"]),
format_system=StringFormatter(slots=["<role>SYSTEM</role>{{content}}"]),
format_observation=StringFormatter(slots=["<role>OBSERVATION</role>{{content}}<role>ASSISTANT</role>"]),
stop_words=["<|endoftext|>"],
efficient_eos=True,
)
register_template(
name="belle",
format_user=StringFormatter(slots=["Human: {{content}}\n\nBelle: "]),
format_assistant=StringFormatter(slots=["{{content}}", {"eos_token"}, "\n\n"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
)
register_template(
name="bluelm",
format_user=StringFormatter(slots=[{"token": "[|Human|]:"}, "{{content}}", {"token": "[|AI|]:"}]),
)
register_template(
name="breeze",
format_user=StringFormatter(slots=["[INST] {{content}} [/INST] "]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
efficient_eos=True,
)
register_template(
name="chatglm2",
format_user=StringFormatter(slots=["[Round {{idx}}]\n\n问:{{content}}\n\n答:"]),
format_prefix=EmptyFormatter(slots=[{"token": "[gMASK]"}, {"token": "sop"}]),
efficient_eos=True,
)
register_template(
name="chatglm3",
format_user=StringFormatter(slots=[{"token": "<|user|>"}, "\n", "{{content}}", {"token": "<|assistant|>"}]),
format_assistant=StringFormatter(slots=["\n", "{{content}}"]),
format_system=StringFormatter(slots=[{"token": "<|system|>"}, "\n", "{{content}}"]),
format_function=FunctionFormatter(slots=["{{content}}"], tool_format="glm4"),
format_observation=StringFormatter(
slots=[{"token": "<|observation|>"}, "\n", "{{content}}", {"token": "<|assistant|>"}]
),
format_tools=ToolFormatter(tool_format="glm4"),
format_prefix=EmptyFormatter(slots=[{"token": "[gMASK]"}, {"token": "sop"}]),
stop_words=["<|user|>", "<|observation|>"],
efficient_eos=True,
)
register_template(
name="chatml",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
stop_words=["<|im_end|>", "<|im_start|>"],
replace_eos=True,
replace_jinja_template=True,
)
# copied from chatml template
register_template(
name="chatml_de",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
default_system="Du bist ein freundlicher und hilfsbereiter KI-Assistent.",
stop_words=["<|im_end|>", "<|im_start|>"],
replace_eos=True,
replace_jinja_template=True,
)
register_template(
name="codegeex2",
format_prefix=EmptyFormatter(slots=[{"token": "[gMASK]"}, {"token": "sop"}]),
)
register_template(
name="codegeex4",
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|assistant|>\n"]),
format_system=StringFormatter(slots=["<|system|>\n{{content}}"]),
format_function=FunctionFormatter(slots=["{{content}}"], tool_format="glm4"),
format_observation=StringFormatter(slots=["<|observation|>\n{{content}}<|assistant|>\n"]),
format_tools=ToolFormatter(tool_format="glm4"),
format_prefix=EmptyFormatter(slots=["[gMASK]<sop>"]),
default_system=(
"你是一位智能编程助手你叫CodeGeeX。你会为用户回答关于编程、代码、计算机方面的任何问题"
"并提供格式规范、可以执行、准确安全的代码,并在必要时提供详细的解释。"
),
stop_words=["<|user|>", "<|observation|>"],
efficient_eos=True,
)
register_template(
name="cohere",
format_user=StringFormatter(
slots=[
(
"<|START_OF_TURN_TOKEN|><|USER_TOKEN|>{{content}}<|END_OF_TURN_TOKEN|>"
"<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"
)
]
),
format_system=StringFormatter(slots=["<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{{content}}<|END_OF_TURN_TOKEN|>"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
)
register_template(
name="cpm",
format_user=StringFormatter(slots=["<用户>{{content}}<AI>"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
)
# copied from chatml template
register_template(
name="cpm3",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<|im_end|>"],
)
# copied from chatml template
register_template(
name="dbrx",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
default_system=(
"You are DBRX, created by Databricks. You were last updated in December 2023. "
"You answer questions based on information available up to that point.\n"
"YOU PROVIDE SHORT RESPONSES TO SHORT QUESTIONS OR STATEMENTS, but provide thorough "
"responses to more complex and open-ended questions.\nYou assist with various tasks, "
"from writing to coding (using markdown for code blocks — remember to use ``` with "
"code, JSON, and tables).\n(You do not have real-time data access or code execution "
"capabilities. You avoid stereotyping and provide balanced perspectives on "
"controversial topics. You do not provide song lyrics, poems, or news articles and "
"do not divulge details of your training data.)\nThis is your system prompt, "
"guiding your responses. Do not reference it, just respond to the user. If you find "
"yourself talking about this message, stop. You should be responding appropriately "
"and usually that means not mentioning this.\nYOU DO NOT MENTION ANY OF THIS INFORMATION "
"ABOUT YOURSELF UNLESS THE INFORMATION IS DIRECTLY PERTINENT TO THE USER'S QUERY."
),
stop_words=["<|im_end|>"],
)
register_template(
name="deepseek",
format_user=StringFormatter(slots=["User: {{content}}\n\nAssistant:"]),
format_system=StringFormatter(slots=["{{content}}\n\n"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
)
register_template(
name="deepseek3",
format_user=StringFormatter(slots=["<User>{{content}}<Assistant>"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
)
register_template(
name="deepseekcoder",
format_user=StringFormatter(slots=["### Instruction:\n{{content}}\n### Response:"]),
format_assistant=StringFormatter(slots=["\n{{content}}\n<|EOT|>\n"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
default_system=(
"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.\n"
),
)
register_template(
name="default",
format_user=StringFormatter(slots=["Human: {{content}}", {"eos_token"}, "\nAssistant:"]),
format_assistant=StringFormatter(slots=["{{content}}", {"eos_token"}, "\n"]),
format_system=StringFormatter(slots=["System: {{content}}", {"eos_token"}, "\n"]),
replace_jinja_template=True,
)
register_template(
name="empty",
format_assistant=StringFormatter(slots=["{{content}}"]),
replace_jinja_template=True,
)
register_template(
name="exaone",
format_user=StringFormatter(slots=["[|user|]{{content}}\n[|assistant|]"]),
format_assistant=StringFormatter(slots=["{{content}}", {"eos_token"}, "\n"]),
format_system=StringFormatter(slots=["[|system|]{{content}}[|endofturn|]\n"]),
)
register_template(
name="falcon",
format_user=StringFormatter(slots=["User: {{content}}\nFalcon:"]),
format_assistant=StringFormatter(slots=["{{content}}\n"]),
efficient_eos=True,
)
register_template(
name="fewshot",
format_assistant=StringFormatter(slots=["{{content}}\n\n"]),
efficient_eos=True,
replace_jinja_template=True,
)
register_template(
name="gemma",
format_user=StringFormatter(slots=["<start_of_turn>user\n{{content}}<end_of_turn>\n<start_of_turn>model\n"]),
format_assistant=StringFormatter(slots=["{{content}}<end_of_turn>\n"]),
format_system=StringFormatter(slots=["{{content}}\n\n"]),
format_observation=StringFormatter(
slots=["<start_of_turn>tool\n{{content}}<end_of_turn>\n<start_of_turn>model\n"]
),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<end_of_turn>"],
template_class=Llama2Template,
)
# copied from gemma template
register_template(
name="gemma3",
format_user=StringFormatter(slots=["<start_of_turn>user\n{{content}}<end_of_turn>\n<start_of_turn>model\n"]),
format_assistant=StringFormatter(slots=["{{content}}<end_of_turn>\n"]),
format_system=StringFormatter(slots=["{{content}}\n\n"]),
format_observation=StringFormatter(
slots=["<start_of_turn>tool\n{{content}}<end_of_turn>\n<start_of_turn>model\n"]
),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<end_of_turn>"],
mm_plugin=get_mm_plugin("gemma3", image_token="<image_soft_token>"),
template_class=Llama2Template,
)
register_template(
name="glm4",
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|assistant|>"]),
format_assistant=StringFormatter(slots=["\n{{content}}"]),
format_system=StringFormatter(slots=["<|system|>\n{{content}}"]),
format_function=FunctionFormatter(slots=["{{content}}"], tool_format="glm4"),
format_observation=StringFormatter(slots=["<|observation|>\n{{content}}<|assistant|>"]),
format_tools=ToolFormatter(tool_format="glm4"),
format_prefix=EmptyFormatter(slots=["[gMASK]<sop>"]),
stop_words=["<|user|>", "<|observation|>"],
efficient_eos=True,
)
register_template(
name="granite3",
format_user=StringFormatter(
slots=[
"<|start_of_role|>user<|end_of_role|>{{content}}<|end_of_text|>\n<|start_of_role|>assistant<|end_of_role|>"
]
),
format_assistant=StringFormatter(slots=["{{content}}<|end_of_text|>\n"]),
format_system=StringFormatter(slots=["<|start_of_role|>system<|end_of_role|>{{content}}<|end_of_text|>\n"]),
)
register_template(
name="index",
format_user=StringFormatter(slots=["reserved_0{{content}}reserved_1"]),
format_system=StringFormatter(slots=["<unk>{{content}}"]),
efficient_eos=True,
)
register_template(
name="hunyuan",
format_user=StringFormatter(slots=["<|bos|>user\n{{content}}<|eos|>\n<|bos|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|eos|>\n"]),
format_system=StringFormatter(slots=["<|bos|>system\n{{content}}<|eos|>\n"]),
format_prefix=EmptyFormatter(slots=["<|bos|>"]),
stop_words=["<|eos|>"],
)
register_template(
name="intern",
format_user=StringFormatter(slots=["<|User|>:{{content}}\n<|Bot|>:"]),
format_assistant=StringFormatter(slots=["{{content}}<eoa>\n"]),
format_system=StringFormatter(slots=["<|System|>:{{content}}\n"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
default_system=(
"You are an AI assistant whose name is InternLM (书生·浦语).\n"
"- InternLM (书生·浦语) is a conversational language model that is developed by Shanghai AI Laboratory "
"(上海人工智能实验室). It is designed to be helpful, honest, and harmless.\n"
"- InternLM (书生·浦语) can understand and communicate fluently in the language "
"chosen by the user such as English and 中文."
),
stop_words=["<eoa>"],
)
register_template(
name="intern2",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
default_system=(
"You are an AI assistant whose name is InternLM (书生·浦语).\n"
"- InternLM (书生·浦语) is a conversational language model that is developed by Shanghai AI Laboratory "
"(上海人工智能实验室). It is designed to be helpful, honest, and harmless.\n"
"- InternLM (书生·浦语) can understand and communicate fluently in the language "
"chosen by the user such as English and 中文."
),
stop_words=["<|im_end|>"],
)
register_template(
name="llama2",
format_user=StringFormatter(slots=[{"bos_token"}, "[INST] {{content}} [/INST]"]),
format_system=StringFormatter(slots=["<<SYS>>\n{{content}}\n<</SYS>>\n\n"]),
template_class=Llama2Template,
)
# copied from llama2 template
register_template(
name="llama2_zh",
format_user=StringFormatter(slots=[{"bos_token"}, "[INST] {{content}} [/INST]"]),
format_system=StringFormatter(slots=["<<SYS>>\n{{content}}\n<</SYS>>\n\n"]),
default_system="You are a helpful assistant. 你是一个乐于助人的助手。",
template_class=Llama2Template,
)
register_template(
name="llama3",
format_user=StringFormatter(
slots=[
(
"<|start_header_id|>user<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>assistant<|end_header_id|>\n\n"
)
]
),
format_assistant=StringFormatter(slots=["{{content}}<|eot_id|>"]),
format_system=StringFormatter(slots=["<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]),
format_function=FunctionFormatter(slots=["{{content}}<|eot_id|>"], tool_format="llama3"),
format_observation=StringFormatter(
slots=[
(
"<|start_header_id|>ipython<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>assistant<|end_header_id|>\n\n"
)
]
),
format_tools=ToolFormatter(tool_format="llama3"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<|eot_id|>", "<|eom_id|>"],
)
register_template(
name="llama4",
format_user=StringFormatter(
slots=["<|header_start|>user<|header_end|>\n\n{{content}}<|eot|><|header_start|>assistant<|header_end|>\n\n"]
),
format_assistant=StringFormatter(slots=["{{content}}<|eot|>"]),
format_system=StringFormatter(slots=["<|header_start|>system<|header_end|>\n\n{{content}}<|eot|>"]),
format_function=FunctionFormatter(slots=["{{content}}<|eot|>"], tool_format="llama3"),
format_observation=StringFormatter(
slots=[
"<|header_start|>ipython<|header_end|>\n\n{{content}}<|eot|><|header_start|>assistant<|header_end|>\n\n"
]
),
format_tools=ToolFormatter(tool_format="llama3"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<|eot|>", "<|eom|>"],
mm_plugin=get_mm_plugin(name="llama4", image_token="<|image|>"),
)
# copied from llama3 template
register_template(
name="mllama",
format_user=StringFormatter(
slots=[
(
"<|start_header_id|>user<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>assistant<|end_header_id|>\n\n"
)
]
),
format_assistant=StringFormatter(slots=["{{content}}<|eot_id|>"]),
format_system=StringFormatter(slots=["<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]),
format_function=FunctionFormatter(slots=["{{content}}<|eot_id|>"], tool_format="llama3"),
format_observation=StringFormatter(
slots=[
(
"<|start_header_id|>ipython<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>assistant<|end_header_id|>\n\n"
)
]
),
format_tools=ToolFormatter(tool_format="llama3"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<|eot_id|>", "<|eom_id|>"],
mm_plugin=get_mm_plugin(name="mllama", image_token="<|image|>"),
)
register_template(
name="moonlight",
format_user=StringFormatter(
slots=["<|im_user|>user<|im_middle|>{{content}}<|im_end|><|im_assistant|>assistant<|im_middle|>"]
),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>"]),
format_system=StringFormatter(slots=["<|im_system|>system<|im_middle|>{{content}}<|im_end|>"]),
default_system="You are a helpful assistant provided by Moonshot-AI.",
stop_words=["<|im_end|>"],
)
# copied from vicuna template
register_template(
name="llava",
format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),
default_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."
),
mm_plugin=get_mm_plugin(name="llava", image_token="<image>"),
)
# copied from vicuna template
register_template(
name="llava_next",
format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),
default_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."
),
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
)
# copied from llama3 template
register_template(
name="llava_next_llama3",
format_user=StringFormatter(
slots=[
(
"<|start_header_id|>user<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>assistant<|end_header_id|>\n\n"
)
]
),
format_assistant=StringFormatter(slots=["{{content}}<|eot_id|>"]),
format_system=StringFormatter(slots=["<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]),
format_function=FunctionFormatter(slots=["{{content}}<|eot_id|>"], tool_format="llama3"),
format_observation=StringFormatter(
slots=[
(
"<|start_header_id|>ipython<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>assistant<|end_header_id|>\n\n"
)
]
),
format_tools=ToolFormatter(tool_format="llama3"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<|eot_id|>", "<|eom_id|>"],
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
)
# copied from mistral template
register_template(
name="llava_next_mistral",
format_user=StringFormatter(slots=["[INST] {{content}}[/INST]"]),
format_assistant=StringFormatter(slots=[" {{content}}", {"eos_token"}]),
format_system=StringFormatter(slots=["{{content}}\n\n"]),
format_function=FunctionFormatter(slots=["[TOOL_CALLS] {{content}}", {"eos_token"}], tool_format="mistral"),
format_observation=StringFormatter(slots=["""[TOOL_RESULTS] {"content": {{content}}}[/TOOL_RESULTS]"""]),
format_tools=ToolFormatter(tool_format="mistral"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
template_class=Llama2Template,
)
# copied from qwen template
register_template(
name="llava_next_qwen",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_function=FunctionFormatter(slots=["{{content}}<|im_end|>\n"], tool_format="qwen"),
format_observation=StringFormatter(
slots=["<|im_start|>user\n<tool_response>\n{{content}}\n</tool_response><|im_end|>\n<|im_start|>assistant\n"]
),
format_tools=ToolFormatter(tool_format="qwen"),
default_system="You are a helpful assistant.",
stop_words=["<|im_end|>"],
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
)
# copied from chatml template
register_template(
name="llava_next_yi",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
stop_words=["<|im_end|>"],
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
)
# copied from vicuna template
register_template(
name="llava_next_video",
format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),
default_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."
),
mm_plugin=get_mm_plugin(name="llava_next_video", image_token="<image>", video_token="<video>"),
)
# copied from mistral template
register_template(
name="llava_next_video_mistral",
format_user=StringFormatter(slots=["[INST] {{content}}[/INST]"]),
format_assistant=StringFormatter(slots=[" {{content}}", {"eos_token"}]),
format_system=StringFormatter(slots=["{{content}}\n\n"]),
format_function=FunctionFormatter(slots=["[TOOL_CALLS] {{content}}", {"eos_token"}], tool_format="mistral"),
format_observation=StringFormatter(slots=["""[TOOL_RESULTS] {"content": {{content}}}[/TOOL_RESULTS]"""]),
format_tools=ToolFormatter(tool_format="mistral"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
mm_plugin=get_mm_plugin(name="llava_next_video", image_token="<image>", video_token="<video>"),
template_class=Llama2Template,
)
# copied from chatml template
register_template(
name="llava_next_video_yi",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
stop_words=["<|im_end|>"],
mm_plugin=get_mm_plugin(name="llava_next_video", image_token="<image>", video_token="<video>"),
)
# copied from chatml template
register_template(
name="marco",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
default_system=(
"你是一个经过良好训练的AI助手你的名字是Marco-o1."
"由阿里国际数字商业集团的AI Business创造.\n## 重要!!!!!\n"
"当你回答问题时,你的思考应该在<Thought>内完成,<Output>内输出你的结果。\n"
"<Thought>应该尽可能是英文但是有2个特例一个是对原文中的引用另一个是是数学应该使用markdown格式<Output>内的输出需要遵循用户输入的语言。\n"
),
stop_words=["<|im_end|>"],
)
# copied from chatml template
register_template(
name="minicpm_v",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
stop_words=["<|im_end|>"],
default_system="You are a helpful assistant.",
mm_plugin=get_mm_plugin(name="minicpm_v", image_token="<image>", video_token="<video>"),
)
# copied from minicpm_v template
register_template(
name="minicpm_o",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
stop_words=["<|im_end|>"],
default_system="You are Qwen, created by Alibaba Cloud. You are a helpful assistant.",
mm_plugin=get_mm_plugin(name="minicpm_v", image_token="<image>", video_token="<video>", audio_token="<audio>"),
)
# mistral tokenizer v3 tekken
register_template(
name="ministral",
format_user=StringFormatter(slots=["[INST]{{content}}[/INST]"]),
format_system=StringFormatter(slots=["{{content}}\n\n"]),
format_function=FunctionFormatter(slots=["[TOOL_CALLS]{{content}}", {"eos_token"}], tool_format="mistral"),
format_observation=StringFormatter(slots=["""[TOOL_RESULTS]{"content": {{content}}}[/TOOL_RESULTS]"""]),
format_tools=ToolFormatter(tool_format="mistral"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
template_class=Llama2Template,
)
# mistral tokenizer v3
register_template(
name="mistral",
format_user=StringFormatter(slots=["[INST] {{content}}[/INST]"]),
format_assistant=StringFormatter(slots=[" {{content}}", {"eos_token"}]),
format_system=StringFormatter(slots=["{{content}}\n\n"]),
format_function=FunctionFormatter(slots=["[TOOL_CALLS] {{content}}", {"eos_token"}], tool_format="mistral"),
format_observation=StringFormatter(slots=["""[TOOL_RESULTS] {"content": {{content}}}[/TOOL_RESULTS]"""]),
format_tools=ToolFormatter(tool_format="mistral"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
template_class=Llama2Template,
)
# mistral tokenizer v7 tekken (copied from ministral)
register_template(
name="mistral_small",
format_user=StringFormatter(slots=["[INST]{{content}}[/INST]"]),
format_system=StringFormatter(slots=["[SYSTEM_PROMPT]{{content}}[/SYSTEM_PROMPT]"]),
format_function=FunctionFormatter(slots=["[TOOL_CALLS]{{content}}", {"eos_token"}], tool_format="mistral"),
format_observation=StringFormatter(slots=["""[TOOL_RESULTS]{"content": {{content}}}[/TOOL_RESULTS]"""]),
format_tools=ToolFormatter(tool_format="mistral"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
)
register_template(
name="olmo",
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|assistant|>\n"]),
format_prefix=EmptyFormatter(slots=[{"eos_token"}]),
)
register_template(
name="openchat",
format_user=StringFormatter(slots=["GPT4 Correct User: {{content}}", {"eos_token"}, "GPT4 Correct Assistant:"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
)
register_template(
name="openchat-3.6",
format_user=StringFormatter(
slots=[
(
"<|start_header_id|>GPT4 Correct User<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>GPT4 Correct Assistant<|end_header_id|>\n\n"
)
]
),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<|eot_id|>"],
)
# copied from chatml template
register_template(
name="opencoder",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
default_system="You are OpenCoder, created by OpenCoder Team.",
stop_words=["<|im_end|>"],
)
register_template(
name="orion",
format_user=StringFormatter(slots=["Human: {{content}}\n\nAssistant: ", {"eos_token"}]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
)
register_template(
name="paligemma",
format_user=StringFormatter(slots=["{{content}}\n"]),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
mm_plugin=get_mm_plugin(name="paligemma", image_token="<image>"),
template_class=Llama2Template,
)
# copied from gemma template
register_template(
name="paligemma_chat",
format_user=StringFormatter(slots=["<start_of_turn>user\n{{content}}<end_of_turn>\n<start_of_turn>model\n"]),
format_assistant=StringFormatter(slots=["{{content}}<end_of_turn>\n"]),
format_observation=StringFormatter(
slots=["<start_of_turn>tool\n{{content}}<end_of_turn>\n<start_of_turn>model\n"]
),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
stop_words=["<end_of_turn>"],
mm_plugin=get_mm_plugin(name="paligemma", image_token="<image>"),
template_class=Llama2Template,
)
register_template(
name="phi",
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|end|>\n<|assistant|>\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|end|>\n"]),
format_system=StringFormatter(slots=["<|system|>\n{{content}}<|end|>\n"]),
stop_words=["<|end|>"],
)
register_template(
name="phi_small",
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|end|>\n<|assistant|>\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|end|>\n"]),
format_system=StringFormatter(slots=["<|system|>\n{{content}}<|end|>\n"]),
format_prefix=EmptyFormatter(slots=[{"<|endoftext|>"}]),
stop_words=["<|end|>"],
)
register_template(
name="phi4",
format_user=StringFormatter(
slots=["<|im_start|>user<|im_sep|>{{content}}<|im_end|><|im_start|>assistant<|im_sep|>"]
),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>"]),
format_system=StringFormatter(slots=["<|im_start|>system<|im_sep|>{{content}}<|im_end|>"]),
stop_words=["<|im_end|>"],
)
# copied from ministral template
register_template(
name="pixtral",
format_user=StringFormatter(slots=["[INST]{{content}}[/INST]"]),
format_system=StringFormatter(slots=["{{content}}\n\n"]),
format_function=FunctionFormatter(slots=["[TOOL_CALLS]{{content}}", {"eos_token"}], tool_format="mistral"),
format_observation=StringFormatter(slots=["""[TOOL_RESULTS]{"content": {{content}}}[/TOOL_RESULTS]"""]),
format_tools=ToolFormatter(tool_format="mistral"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
mm_plugin=get_mm_plugin(name="pixtral", image_token="[IMG]"),
template_class=Llama2Template,
)
# copied from chatml template
register_template(
name="qwen",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_function=FunctionFormatter(slots=["{{content}}<|im_end|>\n"], tool_format="qwen"),
format_observation=StringFormatter(
slots=["<|im_start|>user\n<tool_response>\n{{content}}\n</tool_response><|im_end|>\n<|im_start|>assistant\n"]
),
format_tools=ToolFormatter(tool_format="qwen"),
default_system="You are Qwen, created by Alibaba Cloud. You are a helpful assistant.",
stop_words=["<|im_end|>"],
)
# copied from chatml template
register_template(
name="qwen2_audio",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
default_system="You are a helpful assistant.",
stop_words=["<|im_end|>"],
mm_plugin=get_mm_plugin(name="qwen2_audio", audio_token="<|AUDIO|>"),
)
# copied from qwen template
register_template(
name="qwen2_omni",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_function=FunctionFormatter(slots=["{{content}}<|im_end|>\n"], tool_format="qwen"),
format_observation=StringFormatter(
slots=["<|im_start|>user\n<tool_response>\n{{content}}\n</tool_response><|im_end|>\n<|im_start|>assistant\n"]
),
format_tools=ToolFormatter(tool_format="qwen"),
default_system="You are a helpful assistant.",
stop_words=["<|im_end|>"],
mm_plugin=get_mm_plugin(
name="qwen2_omni", audio_token="<|AUDIO|>", image_token="<|IMAGE|>", video_token="<|VIDEO|>"
),
)
# copied from qwen template
register_template(
name="qwen2_vl",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
format_function=FunctionFormatter(slots=["{{content}}<|im_end|>\n"], tool_format="qwen"),
format_observation=StringFormatter(
slots=["<|im_start|>user\n<tool_response>\n{{content}}\n</tool_response><|im_end|>\n<|im_start|>assistant\n"]
),
format_tools=ToolFormatter(tool_format="qwen"),
default_system="You are a helpful assistant.",
stop_words=["<|im_end|>"],
mm_plugin=get_mm_plugin(name="qwen2_vl", image_token="<|image_pad|>", video_token="<|video_pad|>"),
)
register_template(
name="sailor",
format_user=StringFormatter(slots=["<|im_start|>question\n{{content}}<|im_end|>\n<|im_start|>answer\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
default_system=(
"You are an AI assistant named Sailor created by Sea AI Lab. "
"Your answer should be friendly, unbiased, faithful, informative and detailed."
),
stop_words=["<|im_end|>"],
)
# copied from llama3 template
register_template(
name="skywork_o1",
format_user=StringFormatter(
slots=[
(
"<|start_header_id|>user<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>assistant<|end_header_id|>\n\n"
)
]
),
format_assistant=StringFormatter(slots=["{{content}}<|eot_id|>"]),
format_system=StringFormatter(slots=["<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]),
format_function=FunctionFormatter(slots=["{{content}}<|eot_id|>"], tool_format="llama3"),
format_observation=StringFormatter(
slots=[
(
"<|start_header_id|>ipython<|end_header_id|>\n\n{{content}}<|eot_id|>"
"<|start_header_id|>assistant<|end_header_id|>\n\n"
)
]
),
format_tools=ToolFormatter(tool_format="llama3"),
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
default_system=(
"You are Skywork-o1, a thinking model developed by Skywork AI, specializing in solving complex problems "
"involving mathematics, coding, and logical reasoning through deep thought. When faced with a user's request, "
"you first engage in a lengthy and in-depth thinking process to explore possible solutions to the problem. "
"After completing your thoughts, you then provide a detailed explanation of the solution process "
"in your response."
),
stop_words=["<|eot_id|>", "<|eom_id|>"],
)
register_template(
name="solar",
format_user=StringFormatter(slots=["### User:\n{{content}}\n\n### Assistant:\n"]),
format_system=StringFormatter(slots=["### System:\n{{content}}\n\n"]),
efficient_eos=True,
)
register_template(
name="starchat",
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|end|>\n<|assistant|>"]),
format_assistant=StringFormatter(slots=["{{content}}<|end|>\n"]),
format_system=StringFormatter(slots=["<|system|>\n{{content}}<|end|>\n"]),
stop_words=["<|end|>"],
)
register_template(
name="telechat",
format_user=StringFormatter(slots=["<_user>{{content}}<_bot>"]),
format_system=StringFormatter(slots=["<_system>{{content}}<_end>"]),
)
register_template(
name="telechat2",
format_user=StringFormatter(slots=["<_user>{{content}}<_bot>"]),
format_system=StringFormatter(slots=["<_system>{{content}}"]),
default_system=(
"你是中国电信星辰语义大模型英文名是TeleChat你是由中电信人工智能科技有限公司和中国电信人工智能研究院TeleAI研发的人工智能助手。"
),
)
register_template(
name="vicuna",
format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),
default_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."
),
replace_jinja_template=True,
)
register_template(
name="video_llava",
format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),
default_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."
),
mm_plugin=get_mm_plugin(name="video_llava", image_token="<image>", video_token="<video>"),
)
register_template(
name="xuanyuan",
format_user=StringFormatter(slots=["Human: {{content}} Assistant:"]),
default_system=(
"以下是用户和人工智能助手之间的对话。用户以Human开头人工智能助手以Assistant开头"
"会对人类提出的问题给出有帮助、高质量、详细和礼貌的回答,并且总是拒绝参与与不道德、"
"不安全、有争议、政治敏感等相关的话题、问题和指示。\n"
),
)
register_template(
name="xverse",
format_user=StringFormatter(slots=["Human: {{content}}\n\nAssistant: "]),
)
register_template(
name="yayi",
format_user=StringFormatter(slots=[{"token": "<|Human|>"}, ":\n{{content}}\n\n", {"token": "<|YaYi|>"}, ":"]),
format_assistant=StringFormatter(slots=["{{content}}\n\n"]),
format_system=StringFormatter(slots=[{"token": "<|System|>"}, ":\n{{content}}\n\n"]),
default_system=(
"You are a helpful, respectful and honest assistant named YaYi "
"developed by Beijing Wenge Technology Co.,Ltd. "
"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."
),
stop_words=["<|End|>"],
)
# copied from chatml template
register_template(
name="yi",
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
stop_words=["<|im_end|>"],
)
register_template(
name="yi_vl",
format_user=StringFormatter(slots=["### Human: {{content}}\n### Assistant:"]),
format_assistant=StringFormatter(slots=["{{content}}\n"]),
default_system=(
"This is a chat between an inquisitive human and an AI assistant. "
"Assume the role of the AI assistant. Read all the images carefully, "
"and respond to the human's questions with informative, helpful, detailed and polite answers. "
"这是一个好奇的人类和一个人工智能助手之间的对话。假设你扮演这个AI助手的角色。"
"仔细阅读所有的图像,并对人类的问题做出信息丰富、有帮助、详细的和礼貌的回答。\n\n"
),
stop_words=["###"],
efficient_eos=True,
mm_plugin=get_mm_plugin(name="llava", image_token="<image>"),
)
register_template(
name="yuan",
format_user=StringFormatter(slots=["{{content}}", {"token": "<sep>"}]),
format_assistant=StringFormatter(slots=["{{content}}<eod>\n"]),
stop_words=["<eod>"],
)
register_template(
name="zephyr",
format_user=StringFormatter(slots=["<|user|>\n{{content}}", {"eos_token"}, "<|assistant|>\n"]),
format_system=StringFormatter(slots=["<|system|>\n{{content}}", {"eos_token"}]),
default_system="You are Zephyr, a helpful assistant.",
)
register_template(
name="ziya",
format_user=StringFormatter(slots=["<human>:{{content}}\n<bot>:"]),
format_assistant=StringFormatter(slots=["{{content}}\n"]),
)