Policy Action

Manages AI policy document serving for an Agent

Policy Action

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JIVAS action wrapper for managing AI policy document serving for an Agent.

Package Information

Name: jivas/policy_action
Author: V75 Inc.
Architype: PolicyAction

Meta Information

Title: Policy Action
Group: core
Type: action

Configuration

Singleton: true

Dependencies

Jivas: ^2.0.0

This package, developed by V75 Inc., focuses on managing the serving of AI policy documents for an agent. As a core action, it ensures that AI policies are accessible and appropriately integrated into agent operations. The package is a singleton and requires the Jivas library version 2.0.0.

How to Use

Below is detailed guidance on how to configure and use the Policy Action.

Overview

The Policy Action provides a mechanism for serving AI policy documents. It supports configurations for various use cases, including:

Dynamic content generation based on agent-specific data.
Integration with JIVAS agents for seamless policy management.

Configuration Structure

The configuration consists of the following components:

`policy_settings`

Defines the settings for the policy content, such as placeholders and dynamic replacements.

policy_settings = {
    "agent_name": "example_agent",  # Example: "example_agent"
    "content": "Your policy content here."  # Policy content template
}

Example Configurations

Basic Configuration for Policy Content

policy_settings = {
    "agent_name": "TrueSelph",
    "content": """
    # AI Policy - {agent_name}
    This is a sample policy document for {agent_name}.
    """
}

Best Practices

Ensure placeholders in the content are replaced dynamically.
Test the policy content rendering in a staging environment before production use.

🔰 Contributing

🐛 Report Issues: Submit bugs found or log feature requests for the policy_action project.
💡 Submit Pull Requests: Review open PRs, and submit your own PRs.

Contributing Guidelines

Fork the Repository: Start by forking the project repository to your GitHub account.
Clone Locally: Clone the forked repository to your local machine using a git client.
```
git clone https://github.com/TrueSelph/policy_action
```
Create a New Branch: Always work on a new branch, giving it a descriptive name.
```
git checkout -b new-feature-x
```
Make Your Changes: Develop and test your changes locally.
Commit Your Changes: Commit with a clear message describing your updates.
```
git commit -m 'Implemented new feature x.'
```
Push to GitHub: Push the changes to your forked repository.
```
git push origin new-feature-x
```
Submit a Pull Request: Create a PR against the original project repository. Clearly describe the changes and their motivations.
Review: Once your PR is reviewed and approved, it will be merged into the main branch. Congratulations on your contribution!