# =========== 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.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an “AS IS” BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
import re
from typing import Dict, Optional, Union
from camel.agents.chat_agent import ChatAgent
from camel.messages import BaseMessage
from camel.models import BaseModelBackend
from camel.prompts import TextPrompt
from camel.types import RoleType
# AgentOps decorator setting
try:
import os
if os.getenv("AGENTOPS_API_KEY") is not None:
from agentops import track_agent
else:
raise ImportError
except (ImportError, AttributeError):
from camel.utils import track_agent
[docs]
@track_agent(name="RoleAssignmentAgent")
class RoleAssignmentAgent(ChatAgent):
r"""An agent that generates role names based on the task prompt.
Args:
model (BaseModelBackend, optional): The model backend to use for
generating responses. (default: :obj:`OpenAIModel` with
`GPT_4O_MINI`)
Attributes:
role_assignment_prompt (TextPrompt): A prompt for the agent to generate
role names.
"""
def __init__(
self,
model: Optional[BaseModelBackend] = None,
) -> None:
system_message = BaseMessage(
role_name="Role Assigner",
role_type=RoleType.ASSISTANT,
meta_dict=None,
content="You assign roles based on tasks.",
)
super().__init__(system_message, model=model)
[docs]
def run(
self,
task_prompt: Union[str, TextPrompt],
num_roles: int = 2,
) -> Dict[str, str]:
r"""Generate role names based on the input task prompt.
Args:
task_prompt (Union[str, TextPrompt]): The prompt
for the task based on which the roles are to be generated.
num_roles (int, optional): The number of roles to generate.
(default: :obj:`2`)
Returns:
Dict[str, str]: A dictionary mapping role names to their
descriptions.
"""
self.reset()
expert_prompt = "===== ANSWER PROMPT =====\n" + "\n".join(
f"Domain expert {i + 1}: <BLANK>\n"
f"Associated competencies, characteristics, duties "
f"and workflows: <BLANK>. End."
for i in range(num_roles or 0)
)
role_assignment_generation_prompt = TextPrompt(
"You are a role assignment agent, and you're in charge of "
+ "recruiting {num_roles} experts for the following task."
+ "\n==== TASK =====\n {task}\n\n"
+ "Identify the domain experts you'd recruit and detail their "
+ "associated competencies, characteristics, duties and workflows "
+ "to complete the task.\n "
+ "Your answer MUST adhere to the format of ANSWER PROMPT, and "
+ "ONLY answer the BLANKs.\n"
+ expert_prompt
)
role_assignment_generation = role_assignment_generation_prompt.format(
num_roles=num_roles, task=task_prompt
)
role_assignment_generation_msg = BaseMessage.make_user_message(
role_name="Role Assigner", content=role_assignment_generation
)
response = self.step(input_message=role_assignment_generation_msg)
msg = response.msg # type: BaseMessage
terminated = response.terminated
# Distribute the output completions into role names and descriptions
role_names = [
desc.replace("<|", "").replace("|>", "")
for desc in re.findall(
r"Domain expert \d: (.+?)\nAssociated competencies,",
msg.content,
re.DOTALL,
)
]
role_descriptions = [
desc.replace("<|", "").replace("|>", "")
for desc in re.findall(
r"Associated competencies, characteristics, "
r"duties and workflows: (.+?) End.",
msg.content,
re.DOTALL,
)
]
if len(role_names) != num_roles or len(role_descriptions) != num_roles:
raise RuntimeError(
"Got None or insufficient information of roles."
)
if terminated:
raise RuntimeError("Role assignment failed.")
role_descriptions_dict = {
role_name: description
for role_name, description in zip(role_names, role_descriptions)
}
return role_descriptions_dict
