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# ========= Copyright 2023-2024 @ 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 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
from typing import Any
from camel.prompts.base import TextPrompt, TextPromptDict
class PersonaHubPrompt(TextPromptDict):
r"""A dictionary containing :obj:`TextPrompt` used for generating and
relating personas based on given text or existing personas.
This class inherits from TextPromptDict, allowing for easy access and
management of the prompts.
Attributes:
TEXT_TO_PERSONA (TextPrompt): A prompt for inferring a persona from a
given text. This prompt asks to identify who is likely to interact
with the provided text in various ways (read, write, like,
dislike). The response should follow a specific template format.
PERSONA_TO_PERSONA (TextPrompt): A prompt for deriving related personas
based on a given persona. This prompt asks to describe personas who
might have a close relationship with the provided persona. The
response should follow a specific template format, allowing for
multiple related personas.
"""
TEXT_TO_PERSONA = TextPrompt("""
Who is likely to {action} the following text? Provide a detailed and specific persona description.
Text: {text}
""") # noqa: E501
PERSONA_TO_PERSONA = TextPrompt("""
Given the following persona:
{persona_name}
{persona_description}
Who is likely to be in a close relationship with this persona? Describe the related personas and their relationships.
""") # noqa: E501
def __init__(self, *args: Any, **kwargs: Any) -> None:
super().__init__(*args, **kwargs)
self.update(
{
"text_to_persona": self.TEXT_TO_PERSONA,
"persona_to_persona": self.PERSONA_TO_PERSONA,
}
)
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