privateGPT/private_gpt/components/llm/prompt_helper.py
2024-01-16 22:51:14 +01:00

188 lines
6.7 KiB
Python

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
<s> [INST] <<SYS>> your system prompt here. <</SYS>>
user message here [/INST] assistant (model) response here </s>
```
"""
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 `<s>` and `</s>` 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 = "<s>"
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 += "</s>"
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}'")