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| """ | |
| Conversation prompt template. | |
| Now we support | |
| - Vicuna | |
| - Koala | |
| - OpenAssistant/oasst-sft-1-pythia-12b | |
| - StabilityAI/stablelm-tuned-alpha-7b | |
| - databricks/dolly-v2-12b | |
| - THUDM/chatglm-6b | |
| - Alpaca/LLaMa | |
| """ | |
| import dataclasses | |
| from enum import auto, Enum | |
| from typing import List, Tuple, Any | |
| class SeparatorStyle(Enum): | |
| """Different separator style.""" | |
| SINGLE = auto() | |
| TWO = auto() | |
| DOLLY = auto() | |
| OASST_PYTHIA = auto() | |
| class Conversation: | |
| """A class that keeps all conversation history.""" | |
| system: str | |
| roles: List[str] | |
| messages: List[List[str]] | |
| offset: int | |
| sep_style: SeparatorStyle = SeparatorStyle.SINGLE | |
| sep: str = "###" | |
| sep2: str = None | |
| # Used for gradio server | |
| skip_next: bool = False | |
| conv_id: Any = None | |
| def get_prompt(self): | |
| if self.sep_style == SeparatorStyle.SINGLE: | |
| ret = self.system | |
| for role, message in self.messages: | |
| if message: | |
| ret += self.sep + " " + role + ": " + message | |
| else: | |
| ret += self.sep + " " + role + ":" | |
| return ret | |
| elif self.sep_style == SeparatorStyle.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.DOLLY: | |
| seps = [self.sep, self.sep2] | |
| ret = self.system | |
| for i, (role, message) in enumerate(self.messages): | |
| if message: | |
| ret += role + ":\n" + message + seps[i % 2] | |
| if i % 2 == 1: | |
| ret += "\n\n" | |
| else: | |
| ret += role + ":\n" | |
| return ret | |
| elif self.sep_style == SeparatorStyle.OASST_PYTHIA: | |
| ret = self.system | |
| for role, message in self.messages: | |
| if message: | |
| ret += role + message + self.sep | |
| 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 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, | |
| conv_id=self.conv_id, | |
| ) | |
| def dict(self): | |
| return { | |
| "system": self.system, | |
| "roles": self.roles, | |
| "messages": self.messages, | |
| "offset": self.offset, | |
| "sep": self.sep, | |
| "sep2": self.sep2, | |
| "conv_id": self.conv_id, | |
| } | |
| conv_one_shot = 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.", | |
| roles=("Human", "Assistant"), | |
| messages=( | |
| ( | |
| "Human", | |
| "What are the key differences between renewable and non-renewable energy sources?", | |
| ), | |
| ( | |
| "Assistant", | |
| "Renewable energy sources are those that can be replenished naturally in a relatively " | |
| "short amount of time, such as solar, wind, hydro, geothermal, and biomass. " | |
| "Non-renewable energy sources, on the other hand, are finite and will eventually be " | |
| "depleted, such as coal, oil, and natural gas. Here are some key differences between " | |
| "renewable and non-renewable energy sources:\n" | |
| "1. Availability: Renewable energy sources are virtually inexhaustible, while non-renewable " | |
| "energy sources are finite and will eventually run out.\n" | |
| "2. Environmental impact: Renewable energy sources have a much lower environmental impact " | |
| "than non-renewable sources, which can lead to air and water pollution, greenhouse gas emissions, " | |
| "and other negative effects.\n" | |
| "3. Cost: Renewable energy sources can be more expensive to initially set up, but they typically " | |
| "have lower operational costs than non-renewable sources.\n" | |
| "4. Reliability: Renewable energy sources are often more reliable and can be used in more remote " | |
| "locations than non-renewable sources.\n" | |
| "5. Flexibility: Renewable energy sources are often more flexible and can be adapted to different " | |
| "situations and needs, while non-renewable sources are more rigid and inflexible.\n" | |
| "6. Sustainability: Renewable energy sources are more sustainable over the long term, while " | |
| "non-renewable sources are not, and their depletion can lead to economic and social instability.", | |
| ), | |
| ), | |
| offset=2, | |
| sep_style=SeparatorStyle.SINGLE, | |
| sep="###", | |
| ) | |
| conv_vicuna_v1_1 = 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. You are built by NTU Miulab by Yen-Ting Lin for research purpose.", | |
| # system="一位好奇的用戶和一個人工智能助理之間的聊天。你是一位助理。請對用戶的問題提供有用、詳細和有禮貌的答案。", | |
| roles=("USER", "ASSISTANT"), | |
| messages=(), | |
| offset=0, | |
| sep_style=SeparatorStyle.TWO, | |
| sep=" ", | |
| sep2="</s>", | |
| ) | |
| conv_story = 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.TWO, | |
| sep=" ", | |
| sep2="<|endoftext|>", | |
| ) | |
| conv_koala_v1 = Conversation( | |
| system="BEGINNING OF CONVERSATION:", | |
| roles=("USER", "GPT"), | |
| messages=(), | |
| offset=0, | |
| sep_style=SeparatorStyle.TWO, | |
| sep=" ", | |
| sep2="</s>", | |
| ) | |
| conv_dolly = Conversation( | |
| system="Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n", | |
| roles=("### Instruction", "### Response"), | |
| messages=(), | |
| offset=0, | |
| sep_style=SeparatorStyle.DOLLY, | |
| sep="\n\n", | |
| sep2="### End", | |
| ) | |
| conv_oasst = Conversation( | |
| system="", | |
| roles=("<|prompter|>", "<|assistant|>"), | |
| messages=(), | |
| offset=0, | |
| sep_style=SeparatorStyle.OASST_PYTHIA, | |
| sep="<|endoftext|>", | |
| ) | |
| conv_stablelm = Conversation( | |
| system="""<|SYSTEM|># 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|>"), | |
| messages=(), | |
| offset=0, | |
| sep_style=SeparatorStyle.OASST_PYTHIA, | |
| sep="", | |
| ) | |
| conv_templates = { | |
| "conv_one_shot": conv_one_shot, | |
| "vicuna_v1.1": conv_vicuna_v1_1, | |
| "koala_v1": conv_koala_v1, | |
| "dolly": conv_dolly, | |
| "oasst": conv_oasst, | |
| } | |
| def get_default_conv_template(model_name): | |
| model_name = model_name.lower() | |
| if "vicuna" in model_name or "output" in model_name: | |
| return conv_vicuna_v1_1 | |
| elif "koala" in model_name: | |
| return conv_koala_v1 | |
| elif "dolly-v2" in model_name: | |
| return conv_dolly | |
| elif "oasst" in model_name and "pythia" in model_name: | |
| return conv_oasst | |
| elif "stablelm" in model_name: | |
| return conv_stablelm | |
| return conv_one_shot | |
| def compute_skip_echo_len(model_name, conv, prompt): | |
| model_name = model_name.lower() | |
| if "chatglm" in model_name: | |
| skip_echo_len = len(conv.messages[-2][1]) + 1 | |
| elif "dolly-v2" in model_name: | |
| special_toks = ["### Instruction:", "### Response:", "### End"] | |
| skip_echo_len = len(prompt) | |
| for tok in special_toks: | |
| skip_echo_len -= prompt.count(tok) * len(tok) | |
| elif "oasst" in model_name and "pythia" in model_name: | |
| special_toks = ["<|prompter|>", "<|assistant|>", "<|endoftext|>"] | |
| skip_echo_len = len(prompt) | |
| for tok in special_toks: | |
| skip_echo_len -= prompt.count(tok) * len(tok) | |
| elif "stablelm" in model_name: | |
| special_toks = ["<|SYSTEM|>", "<|USER|>", "<|ASSISTANT|>"] | |
| skip_echo_len = len(prompt) | |
| for tok in special_toks: | |
| skip_echo_len -= prompt.count(tok) * len(tok) | |
| else: | |
| skip_echo_len = len(prompt) + 1 - prompt.count("</s>") * 3 | |
| return skip_echo_len | |
| if __name__ == "__main__": | |
| print(default_conversation.get_prompt()) | |