Agently SDK

The official SDK for developing extensions for the Agently framework. Currently focused on plugin development, with more capabilities planned for future releases.

Installation

pip install agently-sdk

For development versions or pre-releases:

pip install agently-sdk==0.5.2.dev0

See our Versioning Guide for information about our release process and version numbering.

Quick Start

Create a simple plugin:

from agently_sdk.plugins import Plugin, PluginVariable, kernel_function

class HelloPlugin(Plugin):
    name = "hello"
    description = "A simple hello world plugin"
    
    default_name = PluginVariable(
        name="default_name",
        description="Default name to use in greetings",
        default="World"
    )
    
    @kernel_function
    def greet(self, name=None) -> str:
        """Greet the user."""
        return f"Hello, {name or self.default_name}!"

Plugin Development

Plugin Class

The Plugin class is the base class for all Agently plugins. It provides the structure and interface for creating plugins that can be used by Agently agents.

Attribute	Type	Required	Description
name	str	Yes	The name of the plugin, used for identification
description	str	Yes	A brief description of what the plugin does

Methods

Method	Description
get_kernel_functions()	Returns a dictionary of all methods decorated with @kernel_function
get_plugin_variables()	Returns a dictionary of all PluginVariable instances defined in the class

PluginVariable

The PluginVariable class represents a configurable variable for a plugin. It allows plugins to be configured with different values when they are loaded by Agently.

Parameter	Type	Required	Default	Description
name	str	Yes	-	The name of the variable
description	str	Yes	-	A description of what the variable is used for
default	Any	No	None	The default value if none is provided
required	bool	No	False	Whether this variable must be provided
validator	Callable[[Any], bool]	No	None	Optional function that validates the value
choices	List[Any]	No	None	Optional list of valid choices for the value
type	Type	No	None	Optional type constraint for the value

Methods

Method	Description
validate(value)	Validates a value against this variable's constraints
to_dict()	Converts this variable to a dictionary representation

Kernel Function Decorator

Agently SDK provides two decorators for marking methods as callable by agents:

1. @agently_function - The recommended decorator for Agently plugins
2. @kernel_function - An alias for @agently_function provided for backward compatibility

Both decorators wrap the kernel_function decorator from semantic_kernel.functions while maintaining compatibility with our existing code. If the Semantic Kernel package is not available, they fall back to a compatible implementation.

from agently_sdk.plugins import Plugin, PluginVariable, agently_function

class MyPlugin(Plugin):
    name = "my_plugin"
    description = "A sample plugin"
    
    @agently_function
    def my_function(self, param1: str, param2: int = 0) -> str:
        """
        Function docstring that describes what this function does.
        
        Args:
            param1: Description of param1
            param2: Description of param2
            
        Returns:
            Description of the return value
        """
        # Implementation
        return result

Best Practices

Plugin Design

1. Clear Purpose: Each plugin should have a clear, focused purpose
2. Descriptive Names: Use descriptive names for plugins, variables, and functions
3. Comprehensive Documentation: Include detailed docstrings for all functions
4. Input Validation: Validate all inputs to ensure robust behavior
5. Error Handling: Handle errors gracefully and provide informative error messages

Variable Configuration

1. Default Values: Provide sensible default values for variables when possible
2. Validation: Use validators to ensure variables meet requirements
3. Type Constraints: Specify value types to catch type errors early
4. Descriptive Names: Use clear, descriptive names for variables

License

MIT