import abc import logging from collections.abc import Sequence from typing import Any, Literal from llama_index.llms import ChatMessage, MessageRole from llama_index.llms.llama_utils import ( completion_to_prompt, messages_to_prompt, ) logger = logging.getLogger(__name__) class AbstractPromptStyle(abc.ABC): """Abstract class for prompt styles. This class is used to format a series of messages into a prompt that can be understood by the models. A series of messages represents the interaction(s) between a user and an assistant. This series of messages can be considered as a session between a user X and an assistant Y.This session holds, through the messages, the state of the conversation. This session, to be understood by the model, needs to be formatted into a prompt (i.e. a string that the models can understand). Prompts can be formatted in different ways, depending on the model. The implementations of this class represent the different ways to format a series of messages into a prompt. """ def __init__(self, *args: Any, **kwargs: Any) -> None: logger.debug("Initializing prompt_style=%s", self.__class__.__name__) @abc.abstractmethod def _messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str: pass @abc.abstractmethod def _completion_to_prompt(self, completion: str) -> str: pass def messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str: prompt = self._messages_to_prompt(messages) logger.debug("Got for messages='%s' the prompt='%s'", messages, prompt) return prompt def completion_to_prompt(self, completion: str) -> str: prompt = self._completion_to_prompt(completion) logger.debug("Got for completion='%s' the prompt='%s'", completion, prompt) return prompt class DefaultPromptStyle(AbstractPromptStyle): """Default prompt style that uses the defaults from llama_utils. It basically passes None to the LLM, indicating it should use the default functions. """ def __init__(self, *args: Any, **kwargs: Any) -> None: super().__init__(*args, **kwargs) # Hacky way to override the functions # Override the functions to be None, and pass None to the LLM. self.messages_to_prompt = None # type: ignore[method-assign, assignment] self.completion_to_prompt = None # type: ignore[method-assign, assignment] def _messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str: return "" def _completion_to_prompt(self, completion: str) -> str: return "" class Llama2PromptStyle(AbstractPromptStyle): """Simple prompt style that just uses the default llama_utils functions. It transforms the sequence of messages into a prompt that should look like: ```text [INST] <> your system prompt here. <> user message here [/INST] assistant (model) response here ``` """ def _messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str: return messages_to_prompt(messages) def _completion_to_prompt(self, completion: str) -> str: return completion_to_prompt(completion) class TagPromptStyle(AbstractPromptStyle): """Tag prompt style (used by Vigogne) that uses the prompt style `<|ROLE|>`. It transforms the sequence of messages into a prompt that should look like: ```text <|system|>: your system prompt here. <|user|>: user message here (possibly with context and question) <|assistant|>: assistant (model) response here. ``` FIXME: should we add surrounding `` and `` tags, like in llama2? """ def _messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str: """Format message to prompt with `<|ROLE|>: MSG` style.""" prompt = "" for message in messages: role = message.role content = message.content or "" message_from_user = f"<|{role.lower()}|>: {content.strip()}" message_from_user += "\n" prompt += message_from_user # we are missing the last <|assistant|> tag that will trigger a completion prompt += "<|assistant|>: " return prompt def _completion_to_prompt(self, completion: str) -> str: return self._messages_to_prompt( [ChatMessage(content=completion, role=MessageRole.USER)] ) class MistralPromptStyle(AbstractPromptStyle): def _messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str: prompt = "" for message in messages: role = message.role content = message.content or "" if role.lower() == "system": message_from_user = f"[INST] {content.strip()} [/INST]" prompt += message_from_user elif role.lower() == "user": prompt += "" message_from_user = f"[INST] {content.strip()} [/INST]" prompt += message_from_user return prompt def _completion_to_prompt(self, completion: str) -> str: return self._messages_to_prompt( [ChatMessage(content=completion, role=MessageRole.USER)] ) class ChatMLPromptStyle(AbstractPromptStyle): def _messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str: prompt = "<|im_start|>system\n" for message in messages: role = message.role content = message.content or "" if role.lower() == "system": message_from_user = f"{content.strip()}" prompt += message_from_user elif role.lower() == "user": prompt += "<|im_end|>\n<|im_start|>user\n" message_from_user = f"{content.strip()}<|im_end|>\n" prompt += message_from_user prompt += "<|im_start|>assistant\n" return prompt def _completion_to_prompt(self, completion: str) -> str: return self._messages_to_prompt( [ChatMessage(content=completion, role=MessageRole.USER)] ) def get_prompt_style( prompt_style: Literal["default", "llama2", "tag", "mistral", "chatml"] | None ) -> AbstractPromptStyle: """Get the prompt style to use from the given string. :param prompt_style: The prompt style to use. :return: The prompt style to use. """ if prompt_style is None or prompt_style == "default": return DefaultPromptStyle() elif prompt_style == "llama2": return Llama2PromptStyle() elif prompt_style == "tag": return TagPromptStyle() elif prompt_style == "mistral": return MistralPromptStyle() elif prompt_style == "chatml": return ChatMLPromptStyle() raise ValueError(f"Unknown prompt_style='{prompt_style}'")