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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,120 @@ | ||
| # =========== 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 Any, Dict, Optional, Union | ||
|
|
||
| from tenacity import retry, stop_after_attempt, wait_exponential | ||
|
|
||
| from camel.agents import ChatAgent | ||
| from camel.messages import BaseMessage | ||
| from camel.prompts import TextPrompt | ||
| from camel.typing import ModelType, RoleType | ||
|
|
||
|
|
||
| class RoleAssignmentAgent(ChatAgent): | ||
| r"""An agent that generates role names based on the task prompt. | ||
| Attributes: | ||
| role_assignment_prompt (TextPrompt): A prompt for the agent to generate | ||
| role names. | ||
| 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`) | ||
| """ | ||
|
|
||
| def __init__( | ||
| self, | ||
| model: ModelType = ModelType.GPT_3_5_TURBO, | ||
| model_config: Optional[Any] = 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_config) | ||
|
|
||
| @retry(wait=wait_exponential(min=5, max=60), stop=stop_after_attempt(5)) | ||
| 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) | ||
|
|
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| response = self.step(input_message=role_assignment_generation_msg) | ||
|
|
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| 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 |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,53 @@ | ||
| # =========== 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. =========== | ||
| from typing import Any | ||
|
|
||
| from camel.prompts import AISocietyPromptTemplateDict, TextPrompt | ||
| from camel.typing import RoleType | ||
|
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||
|
|
||
| # flake8: noqa :E501 | ||
| class RoleDescriptionPromptTemplateDict(AISocietyPromptTemplateDict): | ||
| r"""A dictionary containing :obj:`TextPrompt` used in the `role description` | ||
| task. | ||
| Attributes: | ||
| ROLE_DESCRIPTION_PROMPT (TextPrompt): A default prompt to | ||
| describe the role descriptions. | ||
| ASSISTANT_PROMPT (TextPrompt): A system prompt for the AI assistant | ||
| that outlines the rules of the conversation and provides | ||
| instructions for completing tasks. | ||
| USER_PROMPT (TextPrompt): A system prompt for the AI user that | ||
| outlines the rules of the conversation and provides instructions | ||
| for giving instructions to the AI assistant. | ||
| """ | ||
| ROLE_DESCRIPTION_PROMPT = TextPrompt("""===== ROLES WITH DESCRIPTION ===== | ||
| {user_role} and {assistant_role} are collaborating to complete a task: {task}. | ||
| Competencies, characteristics, duties and workflows of {user_role} to complete the task: {user_description} | ||
| {assistant_role}'s competencies, characteristics, duties and workflows to complete the task: {assistant_description} | ||
| """) | ||
|
|
||
| ASSISTANT_PROMPT = TextPrompt(ROLE_DESCRIPTION_PROMPT + | ||
| AISocietyPromptTemplateDict.ASSISTANT_PROMPT) | ||
|
|
||
| USER_PROMPT = TextPrompt(ROLE_DESCRIPTION_PROMPT + | ||
| AISocietyPromptTemplateDict.USER_PROMPT) | ||
|
|
||
| def __init__(self, *args: Any, **kwargs: Any) -> None: | ||
| super().__init__(*args, **kwargs) | ||
| self.update({ | ||
| "role_description": self.ROLE_DESCRIPTION_PROMPT, | ||
| RoleType.ASSISTANT: self.ASSISTANT_PROMPT, | ||
| RoleType.USER: self.USER_PROMPT, | ||
| }) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,43 @@ | ||
| # =========== 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. =========== | ||
| from colorama import Fore | ||
|
|
||
| from camel.agents import RoleAssignmentAgent | ||
| from camel.configs import ChatGPTConfig | ||
|
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|
|
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| def main(model_type=None, num_roles=3) -> None: | ||
| task_prompt = "Develop a trading bot for the stock market." | ||
|
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| model_config_description = ChatGPTConfig() | ||
| role_description_agent = RoleAssignmentAgent( | ||
| model=model_type, model_config=model_config_description) | ||
|
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| role_description_dict = role_description_agent.run(task_prompt=task_prompt, | ||
| num_roles=num_roles) | ||
|
|
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| if (len(role_description_dict) != num_roles): | ||
| raise ValueError( | ||
| f"Length of role_names ({len(role_description_dict)}) " | ||
| f"does not equal to num_roles ({num_roles}).") | ||
|
|
||
| print(Fore.YELLOW + f"Original task prompt:\n{task_prompt}\n") | ||
| print(Fore.GREEN + f"List of {num_roles} roles with description:") | ||
| for role_name in role_description_dict.keys(): | ||
| print(Fore.BLUE + f"{role_name}:\n" | ||
| f"{role_description_dict[role_name]}\n") | ||
|
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||
|
|
||
| if __name__ == "__main__": | ||
| main() |
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