Generate Persona-Driven Content Summaries
Persona Hub Prompts from CAMEL-AI provides system prompts that define assistant behavior and role characteristics for conversational AI applications.
Why it matters
Leverage AI personas to generate insightful summaries of information, tailored to specific audience needs and research objectives.
Outcomes
What it gets done
Define and utilize AI personas for targeted information processing.
Summarize web content and other data sources.
Adapt summaries based on persona characteristics and research goals.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/camel-prompt-personahub | bash Use cases
What you can do with it
Condenses long documents or threads into key takeaways.
Searches the web and retrieves relevant sources.
Chunks, embeds, and indexes documents for semantic retrieval.
Overview
Persona Hub Prompts
What it does
Persona Hub Prompts is a collection of system and role prompts from the CAMEL-AI framework that define how AI assistants behave in conversations. These prompts establish personality, expertise, communication style, and behavioral boundaries for conversational agents, enabling developers to create consistent role-specific interactions.
How it connects
Use these prompts when building conversational AI applications that require specific assistant roles or personalities, such as technical support agents, domain experts, or specialized assistants. They're particularly valuable for multi-agent systems where different agents need distinct, reproducible personas.
Source code
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,
}
)
Discussion
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