# Agently SDK
[](https://badge.fury.io/py/agently-sdk)
[](https://opensource.org/licenses/MIT)
The official SDK for developing extensions for the [Agently](https://github.com/onwardplatforms/agently) framework. Currently focused on plugin development, with more capabilities planned for future releases.
## Installation
```bash
pip install agently-sdk
```
## Quick Start
Create a simple plugin:
```python
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.
```python
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
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"description": "# Agently SDK\n\n[](https://badge.fury.io/py/agently-sdk)\n[](https://opensource.org/licenses/MIT)\n\nThe official SDK for developing extensions for the [Agently](https://github.com/onwardplatforms/agently) framework. Currently focused on plugin development, with more capabilities planned for future releases.\n\n## Installation\n\n```bash\npip install agently-sdk\n```\n\n## Quick Start\n\nCreate a simple plugin:\n\n```python\nfrom agently_sdk.plugins import Plugin, PluginVariable, kernel_function\n\nclass HelloPlugin(Plugin):\n name = \"hello\"\n description = \"A simple hello world plugin\"\n \n default_name = PluginVariable(\n name=\"default_name\",\n description=\"Default name to use in greetings\",\n default=\"World\"\n )\n \n @kernel_function\n def greet(self, name=None) -> str:\n \"\"\"Greet the user.\"\"\"\n return f\"Hello, {name or self.default_name}!\"\n```\n\n## Plugin Development\n\n### Plugin Class\n\nThe `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.\n\n| Attribute | Type | Required | Description |\n| ------------- | ----- | -------- | ----------------------------------------------- |\n| `name` | `str` | Yes | The name of the plugin, used for identification |\n| `description` | `str` | Yes | A brief description of what the plugin does |\n\n#### Methods\n\n| Method | Description |\n| ------------------------ | --------------------------------------------------------------------------- |\n| `get_kernel_functions()` | Returns a dictionary of all methods decorated with `@kernel_function` |\n| `get_plugin_variables()` | Returns a dictionary of all `PluginVariable` instances defined in the class |\n\n### PluginVariable\n\nThe `PluginVariable` class represents a configurable variable for a plugin. It allows plugins to be configured with different values when they are loaded by Agently.\n\n| Parameter | Type | Required | Default | Description |\n| ------------- | ----------------------- | -------- | ------- | ---------------------------------------------- |\n| `name` | `str` | Yes | - | The name of the variable |\n| `description` | `str` | Yes | - | A description of what the variable is used for |\n| `default` | `Any` | No | `None` | The default value if none is provided |\n| `required` | `bool` | No | `False` | Whether this variable must be provided |\n| `validator` | `Callable[[Any], bool]` | No | `None` | Optional function that validates the value |\n| `choices` | `List[Any]` | No | `None` | Optional list of valid choices for the value |\n| `type` | `Type` | No | `None` | Optional type constraint for the value |\n\n#### Methods\n\n| Method | Description |\n| ----------------- | ----------------------------------------------------- |\n| `validate(value)` | Validates a value against this variable's constraints |\n| `to_dict()` | Converts this variable to a dictionary representation |\n\n### Kernel Function Decorator\n\nAgently SDK provides two decorators for marking methods as callable by agents:\n\n1. `@agently_function` - The recommended decorator for Agently plugins\n2. `@kernel_function` - An alias for `@agently_function` provided for backward compatibility\n\nBoth 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.\n\n```python\nfrom agently_sdk.plugins import Plugin, PluginVariable, agently_function\n\nclass MyPlugin(Plugin):\n name = \"my_plugin\"\n description = \"A sample plugin\"\n \n @agently_function\n def my_function(self, param1: str, param2: int = 0) -> str:\n \"\"\"\n Function docstring that describes what this function does.\n \n Args:\n param1: Description of param1\n param2: Description of param2\n \n Returns:\n Description of the return value\n \"\"\"\n # Implementation\n return result\n```\n\n## Best Practices\n\n### Plugin Design\n\n1. **Clear Purpose**: Each plugin should have a clear, focused purpose\n2. **Descriptive Names**: Use descriptive names for plugins, variables, and functions\n3. **Comprehensive Documentation**: Include detailed docstrings for all functions\n4. **Input Validation**: Validate all inputs to ensure robust behavior\n5. **Error Handling**: Handle errors gracefully and provide informative error messages\n\n### Variable Configuration\n\n1. **Default Values**: Provide sensible default values for variables when possible\n2. **Validation**: Use validators to ensure variables meet requirements\n3. **Type Constraints**: Specify value types to catch type errors early\n4. **Descriptive Names**: Use clear, descriptive names for variables\n\n## License\n\nMIT \n",
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