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# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
import random
import warnings
from typing import Any, Dict, Optional, Sequence
from colorama import Fore
from camel.agents import ChatAgent, ChatAgentResponse
from camel.messages import BaseMessage
from camel.typing import ModelType
from camel.utils import get_first_int, print_text_animated
[docs]class CriticAgent(ChatAgent):
r"""A class for the critic agent that assists in selecting an option.
Args:
system_message (BaseMessage): The system message for the critic
agent.
model (ModelType, optional): The LLM model to use for generating
responses. (default :obj:`ModelType.GPT_3_5_TURBO`)
model_config (Any, optional): Configuration options for the LLM model.
(default: :obj:`None`)
message_window_size (int, optional): The maximum number of previous
messages to include in the context window. If `None`, no windowing
is performed. (default: :obj:`6`)
retry_attempts (int, optional): The number of retry attempts if the
critic fails to return a valid option. (default: :obj:`2`)
verbose (bool, optional): Whether to print the critic's messages.
logger_color (Any): The color of the menu options displayed to the
user. (default: :obj:`Fore.MAGENTA`)
"""
def __init__(
self,
system_message: BaseMessage,
model: ModelType = ModelType.GPT_3_5_TURBO,
model_config: Optional[Any] = None,
message_window_size: int = 6,
retry_attempts: int = 2,
verbose: bool = False,
logger_color: Any = Fore.MAGENTA,
) -> None:
super().__init__(system_message, model=model,
model_config=model_config,
message_window_size=message_window_size)
self.options_dict: Dict[str, str] = dict()
self.retry_attempts = retry_attempts
self.verbose = verbose
self.logger_color = logger_color
[docs] def flatten_options(self, messages: Sequence[BaseMessage]) -> str:
r"""Flattens the options to the critic.
Args:
messages (Sequence[BaseMessage]): A list of `BaseMessage` objects.
Returns:
str: A string containing the flattened options to the critic.
"""
options = [message.content for message in messages]
flatten_options = (
f"> Proposals from "
f"{messages[0].role_name} ({messages[0].role_type}). "
"Please choose an option:\n")
for index, option in enumerate(options):
flatten_options += f"Option {index + 1}:\n{option}\n\n"
self.options_dict[str(index + 1)] = option
format = (
f"Please first enter your choice ([1-{len(self.options_dict)}]) "
"and then your explanation and comparison: ")
return flatten_options + format
[docs] def get_option(self, input_message: BaseMessage) -> str:
r"""Gets the option selected by the critic.
Args:
input_message (BaseMessage): A `BaseMessage` object representing
the input message.
Returns:
str: The option selected by the critic.
"""
# TODO: Add support for editing options by the critic.
msg_content = input_message.content
i = 0
while i < self.retry_attempts:
critic_response = self.step(input_message)
if critic_response.msgs is None or len(critic_response.msgs) == 0:
raise RuntimeError("Got None critic messages.")
if critic_response.terminated:
raise RuntimeError("Critic step failed.")
critic_msg = critic_response.msg
self.update_messages('assistant', critic_msg)
if self.verbose:
print_text_animated(self.logger_color + "\n> Critic response: "
f"\x1b[3m{critic_msg.content}\x1b[0m\n")
choice = self.parse_critic(critic_msg)
if choice in self.options_dict:
return self.options_dict[choice]
else:
input_message = BaseMessage(
role_name=input_message.role_name,
role_type=input_message.role_type,
meta_dict=input_message.meta_dict,
content="> Invalid choice. Please choose again.\n" +
msg_content,
)
i += 1
warnings.warn("Critic failed to get a valid option. "
f"After {self.retry_attempts} attempts. "
"Returning a random option.")
return random.choice(list(self.options_dict.values()))
[docs] def parse_critic(self, critic_msg: BaseMessage) -> Optional[str]:
r"""Parses the critic's message and extracts the choice.
Args:
critic_msg (BaseMessage): A `BaseMessage` object representing the
critic's response.
Returns:
Optional[str]: The critic's choice as a string, or None if the
message could not be parsed.
"""
choice = str(get_first_int(critic_msg.content))
return choice
[docs] def reduce_step(
self,
input_messages: Sequence[BaseMessage],
) -> ChatAgentResponse:
r"""Performs one step of the conversation by flattening options to the
critic, getting the option, and parsing the choice.
Args:
messages (Sequence[BaseMessage]): A list of BaseMessage objects.
Returns:
ChatAgentResponse: A `ChatAgentResponse` object includes the
critic's choice.
"""
meta_chat_message = BaseMessage(
role_name=input_messages[0].role_name,
role_type=input_messages[0].role_type,
meta_dict=input_messages[0].meta_dict,
content="",
)
flatten_options = self.flatten_options(input_messages)
if self.verbose:
print_text_animated(self.logger_color +
f"\x1b[3m{flatten_options}\x1b[0m\n")
input_msg = meta_chat_message.create_new_instance(flatten_options)
option = self.get_option(input_msg)
output_msg = meta_chat_message.create_new_instance(option)
# TODO: The return `info` can be improved.
return ChatAgentResponse([output_msg], terminated=False, info={})