import dataclasses
from enum import auto, Enum
from typing import List, Tuple, Any
class SeparatorStyle(Enum):
"""Different separator style."""
ADD_COLON_SINGLE = auto()
ADD_COLON_TWO = auto()
NO_COLON_SINGLE = auto()
BAIZE = auto()
PHOENIX = auto()
@dataclasses.dataclass
class Conversation:
"""A class that keeps all conversation history."""
# System prompts
system: str
# Two roles
roles: List[str]
# All messages
messages: List[List[str]]
# Offset of few shot examples
offset: int
# Separator
sep_style: SeparatorStyle
sep: str
sep2: str = None
# Stop criteria (the default one is EOS token)
stop_str: str = None
# Stops generation if meeting any token in this list
stop_token_ids: List[int] = None
# Used for the state in the gradio servers.
# TODO(lmzheng): refactor this
conv_id: Any = None
skip_next: bool = False
model_name: str = None
def get_prompt(self):
if self.sep_style == SeparatorStyle.ADD_COLON_SINGLE:
ret = self.system + self.sep
for role, message in self.messages:
if message:
ret += role + ": " + message + self.sep
else:
ret += role + ": "
return ret
elif self.sep_style == SeparatorStyle.ADD_COLON_TWO:
seps = [self.sep, self.sep2]
ret = self.system + seps[0]
for i, (role, message) in enumerate(self.messages):
if message:
ret += role + ": " + message + seps[i % 2]
else:
ret += role + ": "
return ret
elif self.sep_style == SeparatorStyle.NO_COLON_SINGLE:
ret = self.system
for role, message in self.messages:
if message:
ret += role + message + self.sep
else:
ret += role
return ret
elif self.sep_style == SeparatorStyle.BAIZE:
ret = self.system + "\n"
for role, message in self.messages:
if message:
ret += role + message + "\n"
else:
ret += role
return ret
elif self.sep_style == SeparatorStyle.PHOENIX:
ret = self.system
for role, message in self.messages:
if message:
ret += role + ": " + "" + message + ""
else:
ret += role + ": " + ""
return ret
else:
raise ValueError(f"Invalid style: {self.sep_style}")
def append_message(self, role, message):
self.messages.append([role, message])
def to_gradio_chatbot(self):
ret = []
for i, (role, msg) in enumerate(self.messages[self.offset:]):
if i % 2 == 0:
ret.append([msg, None])
else:
ret[-1][-1] = msg
return ret
def to_openai_api_messages(self):
ret = [{"role": "system", "content": self.system}]
for i, (_, msg) in enumerate(self.messages[self.offset:]):
if i % 2 == 0:
ret.append({"role": "user", "content": msg})
else:
if msg is not None:
ret.append({"role": "assistant", "content": msg})
return ret
def copy(self):
return Conversation(
system=self.system,
roles=self.roles,
messages=[[x, y] for x, y in self.messages],
offset=self.offset,
sep_style=self.sep_style,
sep=self.sep,
sep2=self.sep2,
stop_str=self.stop_str,
stop_token_ids=self.stop_token_ids,
conv_id=self.conv_id,
model_name=self.model_name,
)
def dict(self):
return {
"system": self.system,
"roles": self.roles,
"messages": self.messages,
"offset": self.offset,
"conv_id": self.conv_id,
"model_name": self.model_name,
}
conv_vicuna = Conversation(
system="A chat between a curious user and an artificial intelligence assistant. "
"The assistant gives helpful, detailed, and polite answers to the user's questions.",
roles=("USER", "ASSISTANT"),
messages=(),
offset=0,
sep_style=SeparatorStyle.ADD_COLON_TWO,
sep=" ",
sep2="",
)
conv_baize = Conversation(
system="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.BAIZE,
sep="\n",
stop_str="[|Human|]",
)
conv_phoenix = Conversation(
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.\n\n",
roles=("Human", "Assistant"),
messages=(),
offset=0,
sep_style=SeparatorStyle.PHOENIX,
sep="",
)
conv_chatgpt = Conversation(
system="You are a helpful assistant.",
roles=("user", "assistant"),
messages=(),
offset=0,
sep_style=None,
sep=None,
)
conv_templates = {
"vicuna": conv_vicuna,
"baize": conv_baize,
"phoenix": conv_phoenix,
"chatgpt": conv_chatgpt,
}
def get_default_conv_template(model_name):
model_name = model_name.lower()
try:
ret = conv_templates[model_name]
return ret.copy()
except:
raise NotImplementedError(f"No support for model {model_name}.")
if __name__ == "__main__":
conv = conv_templates["chatgpt"].copy()
conv.append_message(conv.roles[0], "Hello World.")
conv.append_message(conv.roles[1], None)
print([conv.get_prompt()])