# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
# Licensed under the Apache License, Version 2.0 (the “License”);
# you may not use this file except in compliance with the License.
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#
# http://www.apache.org/licenses/LICENSE-2.0
#
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# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
from typing import Dict, Generator, List, Optional, Set, Tuple
from camel.messages import BaseMessage
from camel.prompts import PromptTemplateGenerator, TextPrompt
from camel.typing import RoleType, TaskType
[docs]class SystemMessageGenerator:
r"""System message generator for agents.
Args:
task_type (TaskType, optional): The task type.
(default: :obj:`TaskType.AI_SOCIETY`)
sys_prompts (Optional[Dict[RoleType, str]], optional): The prompts of
the system messages for each role type. (default: :obj:`None`)
sys_msg_meta_dict_keys (Optional[Set[str]], optional): The set of keys
of the meta dictionary used to fill the prompts.
(default: :obj:`None`)
"""
def __init__(
self,
task_type: TaskType = TaskType.AI_SOCIETY,
sys_prompts: Optional[Dict[RoleType, str]] = None,
sys_msg_meta_dict_keys: Optional[Set[str]] = None,
) -> None:
self.sys_prompts: Dict[RoleType, str]
if sys_prompts is not None:
self.sys_prompts = sys_prompts
self.sys_msg_meta_dict_keys = sys_msg_meta_dict_keys or set()
else:
assistant_prompt_template = PromptTemplateGenerator(
).get_system_prompt(
task_type,
RoleType.ASSISTANT,
)
user_prompt_template = PromptTemplateGenerator().get_system_prompt(
task_type,
RoleType.USER,
)
critic_prompt_template = PromptTemplateGenerator(
).get_system_prompt(
task_type,
RoleType.CRITIC,
)
embodiment_prompt_template = PromptTemplateGenerator(
).get_system_prompt(
task_type,
RoleType.EMBODIMENT,
)
self.sys_prompts = dict()
self.sys_prompts[RoleType.ASSISTANT] = assistant_prompt_template
self.sys_prompts[RoleType.USER] = user_prompt_template
self.sys_prompts[RoleType.CRITIC] = critic_prompt_template
self.sys_prompts[RoleType.EMBODIMENT] = embodiment_prompt_template
self.sys_msg_meta_dict_keys = (
assistant_prompt_template.key_words
| user_prompt_template.key_words
| critic_prompt_template.key_words
| embodiment_prompt_template.key_words)
if RoleType.DEFAULT not in self.sys_prompts:
self.sys_prompts[RoleType.DEFAULT] = "You are a helpful assistant."
[docs] def from_dict(
self,
meta_dict: Dict[str, str],
role_tuple: Tuple[str, RoleType] = ("", RoleType.DEFAULT),
) -> BaseMessage:
r"""Generates a system message from a dictionary.
Args:
meta_dict (Dict[str, str]): The dictionary containing the
information to generate the system message.
role_tuple (Tuple[str, RoleType], optional): The tuple containing
the role name and role type. (default: ("", RoleType.DEFAULT))
Returns:
BaseMessage: The generated system message.
"""
self.validate_meta_dict_keys(meta_dict)
role_name, role_type = role_tuple
sys_prompt = self.sys_prompts[role_type]
sys_prompt = sys_prompt.format(**meta_dict)
return BaseMessage(role_name=role_name, role_type=role_type,
meta_dict=meta_dict, content=sys_prompt)
[docs] def from_dicts(
self,
meta_dicts: List[Dict[str, str]],
role_tuples: List[Tuple[str, RoleType]],
) -> List[BaseMessage]:
r"""Generates a list of system messages from a list of dictionaries.
Args:
meta_dicts (List[Dict[str, str]]): A list of dictionaries
containing the information to generate the system messages.
role_tuples (List[Tuple[str, RoleType]]): A list of tuples
containing the role name and role type for each system message.
Returns:
List[BaseMessage]: A list of generated system messages.
Raises:
ValueError: If the number of meta_dicts and role_tuples are
different.
"""
if len(meta_dicts) != len(role_tuples):
raise ValueError(
"The number of meta_dicts and role_types should be the same.")
return [
self.from_dict(meta_dict, role_tuple)
for meta_dict, role_tuple in zip(meta_dicts, role_tuples)
]
[docs]class RoleNameGenerator:
def __init__(self, assistant_role_names_path:
str = "data/ai_society/assistant_roles.txt",
user_role_names_path: str = "data/ai_society/user_roles.txt",
assistant_role_names: Optional[List[str]] = None,
user_role_names: Optional[List[str]] = None) -> None:
if assistant_role_names is None:
with open(assistant_role_names_path, "r") as f:
assistant_role_names_: List[str] = f.read().splitlines()
self.assistant_role_names = [
" ".join(name.split(" ")[1:])
for name in assistant_role_names_
]
else:
self.assistant_role_names = assistant_role_names
if user_role_names is None:
with open(user_role_names_path, "r") as f:
user_role_names_: List[str] = f.read().splitlines()
self.user_role_names = [
" ".join(name.split(" ")[1:]) for name in user_role_names_
]
else:
self.user_role_names = user_role_names
[docs] def from_role_files(self) -> Generator[Tuple, None, None]:
for assistant_role_name in self.assistant_role_names:
for user_role_name in self.user_role_names:
yield (assistant_role_name, user_role_name)
[docs]class AISocietyTaskPromptGenerator:
def __init__(
self,
num_tasks: int = 10,
) -> None:
self.generate_tasks_prompt = PromptTemplateGenerator(
).get_generate_tasks_prompt(TaskType.AI_SOCIETY)
self.num_tasks = num_tasks
# TODO: Return role names for user and assistant with the generator.
[docs] def from_role_files(
self,
assistant_role_names_path: str = "data/ai_society/assistant_roles.txt",
user_role_names_path: str = "data/ai_society/user_roles.txt"
) -> Generator[Tuple[str, Tuple[str, str]], None, None]:
roles_generator = RoleNameGenerator(
assistant_role_names_path, user_role_names_path).from_role_files()
for role_1, role_2 in roles_generator:
generate_tasks_prompt = self.generate_tasks_prompt.format(
assistant_role=role_1, user_role=role_2,
num_tasks=self.num_tasks)
yield (generate_tasks_prompt, (role_1, role_2))
[docs] def from_role_generator(
self, role_generator: Generator[Tuple, None, None]
) -> Generator[Tuple[str, Tuple[str, str]], None, None]:
for role_1, role_2 in role_generator:
generate_tasks_prompt = self.generate_tasks_prompt.format(
assistant_role=role_1, user_role=role_2,
num_tasks=self.num_tasks)
yield (generate_tasks_prompt, (role_1, role_2))
[docs]class SingleTxtGenerator:
def __init__(
self,
text_file_path: str,
) -> None:
with open(text_file_path, "r") as f:
data_list: List[str] = f.read().splitlines()
self.data_list = [
" ".join(name.split(" ")[1:]) for name in data_list
]
[docs] def from_role_files(self) -> Generator[str, None, None]:
for data in self.data_list:
yield data
[docs]class CodeTaskPromptGenerator:
def __init__(
self,
num_tasks: int = 50,
) -> None:
self.generate_tasks_prompt = PromptTemplateGenerator(
).get_generate_tasks_prompt(TaskType.CODE)
self.num_tasks = num_tasks
[docs] def from_role_files(
self, languages_path: str = "data/code/languages.txt",
domains_path: str = "data/code/domains.txt"
) -> Generator[Tuple[TextPrompt, str, str], None, None]:
language_generator = SingleTxtGenerator(
languages_path).from_role_files()
for language in language_generator:
domains_generator = SingleTxtGenerator(
domains_path).from_role_files()
for domain in domains_generator:
generated_tasks_prompt = self.generate_tasks_prompt.format(
language=language, domain=domain, num_tasks=self.num_tasks)
yield generated_tasks_prompt, language, domain
[docs] def from_role_generator(
self, role_generator: Generator[Tuple, None, None]
) -> Generator[str, None, None]:
raise NotImplementedError