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# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
from typing import Any, Dict, List, Optional, Union
from camel.agents import ChatAgent
from camel.configs import ChatGPTConfig
from camel.messages import BaseMessage
from camel.prompts import PromptTemplateGenerator, TextPrompt
from camel.typing import ModelType, RoleType, TaskType
from camel.utils import get_task_list
[docs]class TaskSpecifyAgent(ChatAgent):
r"""An agent that specifies a given task prompt by prompting the user to
provide more details.
Attributes:
DEFAULT_WORD_LIMIT (int): The default word limit for the task prompt.
task_specify_prompt (TextPrompt): The prompt for specifying the task.
Args:
model (ModelType, optional): The type of model to use for the agent.
(default: :obj:`ModelType.GPT_3_5_TURBO`)
task_type (TaskType, optional): The type of task for which to generate
a prompt. (default: :obj:`TaskType.AI_SOCIETY`)
model_config (Any, optional): The configuration for the model.
(default: :obj:`None`)
task_specify_prompt (Union[str, TextPrompt], optional): The prompt for
specifying the task. (default: :obj:`None`)
word_limit (int, optional): The word limit for the task prompt.
(default: :obj:`50`)
output_language (str, optional): The language to be output by the
agent. (default: :obj:`None`)
"""
DEFAULT_WORD_LIMIT = 50
def __init__(
self,
model: Optional[ModelType] = None,
task_type: TaskType = TaskType.AI_SOCIETY,
model_config: Optional[Any] = None,
task_specify_prompt: Optional[Union[str, TextPrompt]] = None,
word_limit: int = DEFAULT_WORD_LIMIT,
output_language: Optional[str] = None,
) -> None:
self.task_specify_prompt: Union[str, TextPrompt]
if task_specify_prompt is None:
task_specify_prompt_template = PromptTemplateGenerator(
).get_task_specify_prompt(task_type)
self.task_specify_prompt = task_specify_prompt_template.format(
word_limit=word_limit)
else:
self.task_specify_prompt = TextPrompt(task_specify_prompt)
model_config = model_config or ChatGPTConfig(temperature=1.0)
system_message = BaseMessage(
role_name="Task Specifier",
role_type=RoleType.ASSISTANT,
meta_dict=None,
content="You can make a task more specific.",
)
super().__init__(system_message, model=model,
model_config=model_config,
output_language=output_language)
[docs] def run(
self,
task_prompt: Union[str, TextPrompt],
meta_dict: Optional[Dict[str, Any]] = None,
) -> TextPrompt:
r"""Specify the given task prompt by providing more details.
Args:
task_prompt (Union[str, TextPrompt]): The original task
prompt.
meta_dict (Dict[str, Any], optional): A dictionary containing
additional information to include in the prompt.
(default: :obj:`None`)
Returns:
TextPrompt: The specified task prompt.
"""
self.reset()
task_specify_prompt = self.task_specify_prompt.format(task=task_prompt)
if meta_dict is not None:
task_specify_prompt = task_specify_prompt.format(**meta_dict)
task_msg = BaseMessage.make_user_message(role_name="Task Specifier",
content=task_specify_prompt)
specifier_response = self.step(task_msg)
if len(specifier_response.msgs) == 0:
raise RuntimeError("Got no specification message.")
specified_task_msg = specifier_response.msgs[0]
if specifier_response.terminated:
raise RuntimeError("Task specification failed.")
return TextPrompt(specified_task_msg.content)
[docs]class TaskPlannerAgent(ChatAgent):
r"""An agent that helps divide a task into subtasks based on the input
task prompt.
Attributes:
task_planner_prompt (TextPrompt): A prompt for the agent to divide
the task into subtasks.
Args:
model (ModelType, optional): The type of model to use for the agent.
(default: :obj:`ModelType.GPT_3_5_TURBO`)
model_config (Any, optional): The configuration for the model.
(default: :obj:`None`)
output_language (str, optional): The language to be output by the
agent. (default: :obj:`None`)
"""
def __init__(
self,
model: Optional[ModelType] = None,
model_config: Optional[Any] = None,
output_language: Optional[str] = None,
) -> None:
self.task_planner_prompt = TextPrompt(
"Divide this task into subtasks: {task}. Be concise.")
system_message = BaseMessage(
role_name="Task Planner",
role_type=RoleType.ASSISTANT,
meta_dict=None,
content="You are a helpful task planner.",
)
super().__init__(system_message, model, model_config,
output_language=output_language)
[docs] def run(
self,
task_prompt: Union[str, TextPrompt],
) -> TextPrompt:
r"""Generate subtasks based on the input task prompt.
Args:
task_prompt (Union[str, TextPrompt]): The prompt for the task to
be divided into subtasks.
Returns:
TextPrompt: A prompt for the subtasks generated by the agent.
"""
# TODO: Maybe include roles information.
self.reset()
task_planner_prompt = self.task_planner_prompt.format(task=task_prompt)
task_msg = BaseMessage.make_user_message(role_name="Task Planner",
content=task_planner_prompt)
task_response = self.step(task_msg)
if len(task_response.msgs) == 0:
raise RuntimeError("Got no task planning message.")
if task_response.terminated:
raise RuntimeError("Task planning failed.")
sub_tasks_msg = task_response.msgs[0]
return TextPrompt(sub_tasks_msg.content)
[docs]class TaskCreationAgent(ChatAgent):
r"""An agent that helps create new tasks based on the objective
and last completed task. Compared to :obj:`TaskPlannerAgent`,
it's still a task planner, but it has more context information
like last task and incomplete task list. Modified from
`BabyAGI <https://github.com/yoheinakajima/babyagi>`_.
Attributes:
task_creation_prompt (TextPrompt): A prompt for the agent to
create new tasks.
Args:
role_name (str): The role name of the Agent to create the task.
objective (Union[str, TextPrompt]): The objective of the Agent to
perform the task.
model (ModelType, optional): The type of model to use for the agent.
(default: :obj:`ModelType.GPT_3_5_TURBO`)
model_config (Any, optional): The configuration for the model.
(default: :obj:`None`)
output_language (str, optional): The language to be output by the
agent. (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:`None`)
max_task_num (int, optional): The maximum number of planned
tasks in one round. (default: :obj:3)
"""
def __init__(
self,
role_name: str,
objective: Union[str, TextPrompt],
model: Optional[ModelType] = None,
model_config: Optional[Any] = None,
output_language: Optional[str] = None,
message_window_size: Optional[int] = None,
max_task_num: Optional[int] = 3,
) -> None:
task_creation_prompt = TextPrompt(
"""Create new a task with the following objective: {objective}.
Never forget you are a Task Creator of {role_name}.
You must instruct me based on my expertise and your needs to solve the task.
You should consider past solved tasks and in-progress tasks: {task_list}.
The new created tasks must not overlap with these past tasks.
The result must be a numbered list in the format:
#. First Task
#. Second Task
#. Third Task
You can only give me up to {max_task_num} tasks at a time. \
Each task shoud be concise, concrete and doable for a {role_name}.
You should make task plan and not ask me questions.
If you think no new tasks are needed right now, write "No tasks to add."
Now start to give me new tasks one by one. No more than three tasks.
Be concrete.
""")
self.task_creation_prompt = task_creation_prompt.format(
objective=objective, role_name=role_name,
max_task_num=max_task_num)
self.objective = objective
system_message = BaseMessage(
role_name="Task Creator",
role_type=RoleType.ASSISTANT,
meta_dict=None,
content="You are a helpful task creator.",
)
super().__init__(system_message, model, model_config,
output_language=output_language,
message_window_size=message_window_size)
[docs] def run(
self,
task_list: List[str],
) -> List[str]:
r"""Generate subtasks based on the previous task results and
incomplete task list.
Args:
task_list (List[str]): The completed or in-progress
tasks which should not overlap with new created tasks.
Returns:
List[str]: The new task list generated by the Agent.
"""
if len(task_list) > 0:
task_creation_prompt = self.task_creation_prompt.format(
task_list=task_list)
else:
task_creation_prompt = self.task_creation_prompt.format(
task_list="")
task_msg = BaseMessage.make_user_message(role_name="Task Creator",
content=task_creation_prompt)
task_response = self.step(task_msg)
if len(task_response.msgs) == 0:
raise RuntimeError("Got no task creation message.")
if task_response.terminated:
raise RuntimeError("Task creation failed.")
sub_tasks_msg = task_response.msgs[0]
return get_task_list(sub_tasks_msg.content)
[docs]class TaskPrioritizationAgent(ChatAgent):
r"""An agent that helps re-prioritize the task list and
returns numbered prioritized list. Modified from
`BabyAGI <https://github.com/yoheinakajima/babyagi>`_.
Attributes:
task_prioritization_prompt (TextPrompt): A prompt for the agent to
prioritize tasks.
Args:
objective (Union[str, TextPrompt]): The objective of the Agent to
perform the task.
model (ModelType, optional): The type of model to use for the agent.
(default: :obj:`ModelType.GPT_3_5_TURBO`)
model_config (Any, optional): The configuration for the model.
(default: :obj:`None`)
output_language (str, optional): The language to be output by the
agent. (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:`None`)
"""
def __init__(
self,
objective: Union[str, TextPrompt],
model: Optional[ModelType] = None,
model_config: Optional[Any] = None,
output_language: Optional[str] = None,
message_window_size: Optional[int] = None,
) -> None:
task_prioritization_prompt = TextPrompt(
"""Prioritize the following tasks : {task_list}.
Consider the ultimate objective of you: {objective}.
Tasks should be sorted from highest to lowest priority, where higher-priority \
tasks are those that act as pre-requisites or are more essential for meeting \
the objective. Return one task per line in your response.
Do not remove or modify any tasks.
The result must be a numbered list in the format:
#. First task
#. Second task
The entries must be consecutively numbered, starting with 1.
The number of each entry must be followed by a period.
Do not include any headers before your ranked list or follow your list \
with any other output.""")
self.task_prioritization_prompt = task_prioritization_prompt.format(
objective=objective)
self.objective = objective
system_message = BaseMessage(
role_name="Task Prioritizer",
role_type=RoleType.ASSISTANT,
meta_dict=None,
content="You are a helpful task prioritizer.",
)
super().__init__(system_message, model, model_config,
output_language=output_language,
message_window_size=message_window_size)
[docs] def run(
self,
task_list: List[str],
) -> List[str]:
r"""Prioritize the task list given the agent objective.
Args:
task_list (List[str]): The unprioritized tasks of agent.
Returns:
List[str]: The new prioritized task list generated by the Agent.
"""
task_prioritization_prompt = self.task_prioritization_prompt.format(
task_list=task_list)
task_msg = BaseMessage.make_user_message(
role_name="Task Prioritizer", content=task_prioritization_prompt)
task_response = self.step(task_msg)
if len(task_response.msgs) == 0:
raise RuntimeError("Got no task prioritization message.")
if task_response.terminated:
raise RuntimeError("Task prioritization failed.")
sub_tasks_msg = task_response.msgs[0]
return get_task_list(sub_tasks_msg.content)