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import re | |
from pprint import pprint | |
from transformers import AutoTokenizer | |
from constants.models import AVAILABLE_MODELS, MODEL_MAP | |
from tclogger import logger | |
class MessageComposer: | |
def __init__(self, model: str = None): | |
if model in AVAILABLE_MODELS: | |
self.model = model | |
else: | |
self.model = "mixtral-8x7b" | |
self.model_fullname = MODEL_MAP[self.model] | |
self.system_roles = ["system"] | |
self.inst_roles = ["user", "system", "inst"] | |
self.answer_roles = ["assistant", "bot", "answer", "model"] | |
self.default_role = "user" | |
def concat_messages_by_role(self, messages): | |
def is_same_role(role1, role2): | |
if ( | |
(role1 == role2) | |
or (role1 in self.inst_roles and role2 in self.inst_roles) | |
or (role1 in self.answer_roles and role2 in self.answer_roles) | |
): | |
return True | |
else: | |
return False | |
concat_messages = [] | |
for message in messages: | |
role = message["role"] | |
content = message["content"] | |
if concat_messages and is_same_role(role, concat_messages[-1]["role"]): | |
concat_messages[-1]["content"] += "\n" + content | |
else: | |
if role in self.inst_roles: | |
message["role"] = "inst" | |
elif role in self.answer_roles: | |
message["role"] = "answer" | |
else: | |
message["role"] = "inst" | |
concat_messages.append(message) | |
return concat_messages | |
def merge(self, messages) -> str: | |
# Templates for Chat Models | |
# - https://huggingface.co/docs/transformers/main/en/chat_templating | |
# - https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1#instruction-format | |
# - https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO#prompt-format | |
# - https://huggingface.co/openchat/openchat-3.5-0106 | |
# - https://huggingface.co/google/gemma-1.1-7b-it#chat-template | |
# Mistral and Mixtral: | |
# <s> [INST] Instruction [/INST] Model answer </s> [INST] Follow-up instruction [/INST] | |
# Nous Mixtral: | |
# <|im_start|>system | |
# You are "Hermes 2".<|im_end|> | |
# <|im_start|>user | |
# Hello, who are you?<|im_end|> | |
# <|im_start|>assistant | |
# OpenChat: | |
# GPT4 Correct User: Hello<|end_of_turn|>GPT4 Correct Assistant: Hi<|end_of_turn|>GPT4 Correct User: How are you today?<|end_of_turn|>GPT4 Correct Assistant: | |
# Google Gemma-it | |
# <start_of_turn>user | |
# How does the brain work?<end_of_turn> | |
# <start_of_turn>model | |
self.messages = messages | |
self.merged_str = "" | |
# https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1#instruction-format | |
if self.model in ["mixtral-8x7b", "mistral-7b"]: | |
self.messages = self.concat_messages_by_role(messages) | |
self.cached_str = "" | |
for message in self.messages: | |
role = message["role"] | |
content = message["content"] | |
if role in self.inst_roles: | |
self.cached_str = f"[INST] {content} [/INST]" | |
elif role in self.answer_roles: | |
self.merged_str += f"<s> {self.cached_str} {content} </s>\n" | |
self.cached_str = "" | |
else: | |
self.cached_str = f"[INST] {content} [/INST]" | |
if self.cached_str: | |
self.merged_str += f"{self.cached_str}" | |
# https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO#prompt-format | |
elif self.model in ["nous-mixtral-8x7b"]: | |
self.merged_str_list = [] | |
for message in self.messages: | |
role = message["role"] | |
content = message["content"] | |
if role not in ["system", "user", "assistant"]: | |
role = self.default_role | |
message_line = f"<|im_start|>{role}\n{content}<|im_end|>" | |
self.merged_str_list.append(message_line) | |
self.merged_str_list.append("<|im_start|>assistant") | |
self.merged_str = "\n".join(self.merged_str_list) | |
# https://huggingface.co/openchat/openchat-3.5-0106 | |
elif self.model in ["openchat-3.5"]: | |
self.messages = self.concat_messages_by_role(messages) | |
self.merged_str_list = [] | |
self.end_of_turn = "<|end_of_turn|>" | |
for message in self.messages: | |
role = message["role"] | |
content = message["content"] | |
if role in self.inst_roles: | |
self.merged_str_list.append( | |
f"GPT4 Correct User:\n{content}{self.end_of_turn}" | |
) | |
elif role in self.answer_roles: | |
self.merged_str_list.append( | |
f"GPT4 Correct Assistant:\n{content}{self.end_of_turn}" | |
) | |
else: | |
self.merged_str_list.append( | |
f"GPT4 Correct User: {content}{self.end_of_turn}" | |
) | |
self.merged_str_list.append(f"GPT4 Correct Assistant:\n") | |
self.merged_str = "\n".join(self.merged_str_list) | |
# https://huggingface.co/google/gemma-1.1-7b-it#chat-template | |
elif self.model in ["gemma-1.1-7b"]: | |
self.messages = self.concat_messages_by_role(messages) | |
self.merged_str_list = [] | |
self.end_of_turn = "<end_of_turn>" | |
self.start_of_turn = "<start_of_turn>" | |
for message in self.messages: | |
role = message["role"] | |
content = message["content"] | |
if role in self.inst_roles: | |
self.merged_str_list.append( | |
f"{self.start_of_turn}user\n{content}{self.end_of_turn}" | |
) | |
elif role in self.answer_roles: | |
self.merged_str_list.append( | |
f"{self.start_of_turn}model\n{content}{self.end_of_turn}" | |
) | |
else: | |
self.merged_str_list.append( | |
f"{self.start_of_turn}user\n{content}{self.end_of_turn}" | |
) | |
self.merged_str_list.append(f"{self.start_of_turn}model\n") | |
self.merged_str = "\n".join(self.merged_str_list) | |
# https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO#prompt-format | |
# https://huggingface.co/openchat/openchat-3.5-0106 | |
# elif self.model in ["openchat-3.5", "nous-mixtral-8x7b"]: | |
else: | |
tokenizer = AutoTokenizer.from_pretrained("openchat/openchat-3.5-0106") | |
self.merged_str = tokenizer.apply_chat_template( | |
messages, tokenize=False, add_generation_prompt=True | |
) | |
return self.merged_str | |
if __name__ == "__main__": | |
# model = "mixtral-8x7b" | |
# model = "nous-mixtral-8x7b" | |
# model = "gemma-1.1-7b" | |
model = "openchat-3.5" | |
composer = MessageComposer(model) | |
messages = [ | |
{ | |
"role": "system", | |
"content": "You are a LLM developed by OpenAI.\nYour name is GPT-4.", | |
}, | |
{"role": "user", "content": "Hello, who are you?"}, | |
{"role": "assistant", "content": "I am a bot."}, | |
{"role": "user", "content": "What is your name?"}, | |
# {"role": "assistant", "content": "My name is Bing."}, | |
# {"role": "user", "content": "Tell me a joke."}, | |
# {"role": "assistant", "content": "What is a robot's favorite type of music?"}, | |
# { | |
# "role": "user", | |
# "content": "How many questions have I asked? Please list them.", | |
# }, | |
] | |
logger.note(f"model: {composer.model}") | |
merged_str = composer.merge(messages) | |
logger.note("merged_str:") | |
logger.mesg(merged_str) | |
# python -m messagers.message_composer | |