Custom plugins in TeamAI allow users to extend the functionality of their AI models by enabling them to interact with external APIs and services. By creating custom plugins, you can tailor your AI's capabilities to suit your specific needs and provide a more comprehensive and efficient user experience.
Key Fields in Custom Plugin Creation
When creating a custom plugin in TeamAI, there are several key fields to consider:
Name
The name of your custom plugin is crucial, as it is used by AI models to identify and interact with the plugin. Choose a clear and descriptive name that accurately represents the plugin's purpose.
Description
The description field is equally important, as it provides AI models with additional context about the plugin's functionality. Write a concise and informative description that helps AI models understand how to use the plugin effectively.
Icon
The icon you select for your custom plugin will be visible throughout the TeamAI platform. While the choice of icon is up to you, we recommend selecting an icon that is relevant to the plugin's purpose and easily recognizable.
Endpoint and Methods
When configuring your custom plugin, you'll need to specify the endpoint and the HTTP methods it supports.
Endpoint
The endpoint is the URL where your plugin will send requests. Enter the full URL, including any necessary path parameters.
Methods
TeamAI supports two HTTP methods for custom plugins: GET and POST. Select the appropriate method based on the requirements of the external API or service you're integrating with.
Parameters
Parameters are a powerful feature in custom plugins that allow you to create dynamic and flexible interactions between your AI models and external APIs.
Definition
Parameters are variables that can be used in the endpoint, headers, query parameters, and payloads of your custom plugin. They enable AI models to provide dynamic values based on the context of the user's query.
Usefulness
By using parameters, you can create custom plugins that are more adaptable and reusable across different scenarios. Parameters allow you to define a single plugin that can handle a variety of user queries and inputs.
Creating Parameters
To create a parameter in your custom plugin:
In the plugin configuration, click on the "Add property" button in the "Parameters" section.
Enter a name for the parameter that is meaningful and descriptive.
Provide a description for the parameter to help AI models understand its purpose and usage.
Select the appropriate type for the parameter (e.g., string, number, boolean).
Click "Save" to add the parameter.
Using Parameters
To use a parameter in your custom plugin, simply reference the parameter name wrapped in double curly braces, like this: {{parameterName}}. You can use parameters in the endpoint, headers, query parameters, and payloads of your plugin.
Headers, Query Parameters, and Payloads
Custom plugins in TeamAI support the configuration of headers, query parameters, and payloads to facilitate communication with external APIs.
Headers
Headers are key-value pairs that provide additional information about the request. To add a header, click on the "Add Header" button in the plugin configuration and enter the key and value for the header.
Query Parameters
Query parameters are key-value pairs that are appended to the endpoint URL. They are commonly used to filter or sort data returned by the API. To add a query parameter, click on the "Add Parameter" button in the plugin configuration and enter the key and value for the parameter.
Payloads
Payloads are the data sent in the body of a POST request. To configure the payload in your custom plugin, click on the "Add Property" button in the "Payload" section and enter the key and value for each property.
Hidden Option for Sensitive Information
TeamAI provides a hidden option for headers, query parameters, and payloads to protect sensitive information. If you have a value that should be kept secret, such as an API key or access token, you can check the "Hidden" checkbox next to the corresponding row in the plugin configuration. When the hidden option is enabled, the value will not be visible the next time you edit the plugin.
Conclusion
Creating custom plugins in TeamAI is a powerful way to extend the capabilities of your AI models and integrate them with external APIs and services. By configuring the key fields, endpoint, methods, parameters, headers, query parameters, and payloads, you can create versatile and adaptable plugins that enhance your AI's functionality.
Remember to choose meaningful names and descriptions for your plugins and parameters, as they are used by AI models to understand and interact with your plugins effectively. Don't forget to use the hidden option for sensitive information to ensure the security of your data.
With custom plugins, you can unlock new possibilities for your AI models and provide a more comprehensive and efficient user experience. Start creating your own custom plugins in TeamAI today and take your AI to the next level!