Universal AI | Documentation

The Universal AI component is an AI component that allows users to connect the AI models served on the different platforms with standardized input and output formats. It can carry out the following tasks:

Chat

#Release Stage

Alpha

#Configuration

The component definition and tasks are defined in the definition.yaml and tasks.yaml files respectively.

#Setup

In order to communicate with the external application, the following connection details need to be provided. You may specify them directly in a pipeline recipe as key-value pairs within the component's setup block, or you can create a Connection from the Integration Settings page and reference the whole setup as setup: ${connection.<my-connection-id>}.

Field	Field ID	Type	Note
Model Name (required)	`model`	string	The model to be used. Now, it only supports OpenAI model, and will support more models in the future. Enum values `o1-preview` `o1-mini` `gpt-4o-mini` `gpt-4o` `gpt-4o-2024-05-13` `gpt-4o-2024-08-06` `gpt-4-turbo` `gpt-4-turbo-2024-04-09` `gpt-4-0125-preview` `gpt-4-turbo-preview` `gpt-4-1106-preview` `gpt-4-vision-preview` `gpt-4` `gpt-4-0314` `gpt-4-0613` `gpt-4-32k` `gpt-4-32k-0314` `gpt-4-32k-0613` `gpt-3.5-turbo` `gpt-3.5-turbo-16k` `gpt-3.5-turbo-0301` `gpt-3.5-turbo-0613` `gpt-3.5-turbo-1106` `gpt-3.5-turbo-0125` `gpt-3.5-turbo-16k-0613`
API Key	`api-key`	string	Fill in your API key from the vendor's platform.
Organization ID	`organization`	string	Specify which organization is used for the requests. Usage will count against the specified organization's subscription quota.

#Supported Tasks

#Chat

Generate response base on conversation input

Input	Field ID	Type	Description
Task ID (required)	`task`	string	`TASK_CHAT`
Chat Data (required)	`data`	object	Input data.
Input Parameter	`parameter`	object	Input parameter.

Input Objects in Chat

Chat Data

Input data.

Field	Field ID	Type	Note
Chat Messages	`messages`	array	List of chat messages.

Chat Messages

List of chat messages.

Field	Field ID	Type	Note
Content	`content`	array	The message content.
Name	`name`	string	An optional name for the participant. Provides the model information to differentiate between participants of the same role.
Role	`role`	string	The message role, i.e. 'system', 'user' or 'assistant'. Enum values `system` `user` `assistant`

Input Parameter

Input parameter.

Field	Field ID	Type	Note
Max New Tokens	`max-tokens`	integer	The maximum number of tokens for model to generate.
Number of Choices	`n`	integer	How many chat completion choices to generate for each input message.
Seed	`seed`	integer	The seed, default is 0.
Stream	`stream`	boolean	If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events as they become available.
Temperature	`temperature`	number	The temperature for sampling.
Top P	`top-p`	number	An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.

Output	Field ID	Type	Description
Output Data	`data`	object	Output data.
Output Metadata (optional)	`metadata`	object	Output metadata.

Output Objects in Chat

Output Data

Field	Field ID	Type	Note
Choices	`choices`	array	List of chat completion choices.

Choices

Field	Field ID	Type	Note
Created	`created`	integer	The Unix timestamp (in seconds) of when the chat completion was created.
Finish Reason	`finish-reason`	string	The reason the model stopped generating tokens.
Index	`index`	integer	The index of the choice in the list of choices.
Message	`message`	object	A chat message generated by the model.

Message

Field	Field ID	Type	Note
Content	`content`	string	The contents of the message.
Role	`role`	string	The role of the author of this message.

Output Metadata

Field	Field ID	Type	Note
Usage	`usage`	object	Usage statistics for the request.

Usage

Field	Field ID	Type	Note
Completion Tokens	`completion-tokens`	integer	Number of tokens in the generated response.
Prompt Tokens	`prompt-tokens`	integer	Number of tokens in the prompt.
Total Tokens	`total-tokens`	integer	Total number of tokens used in the request (prompt + completion).

#Example Recipes

Please refer to the part of type: universal-ai

version: v1beta
variable:
  prompt:
    title: Prompt
    description: "User input message to be sent to the AI model."
    type: string
output:
  ai-output:
    title: AI Output
    value: "${ai.output.data.choices[0]}"
component:
  ai:
    type: universal-ai
    input:
      parameter:
        n: 1
        stream: true
      data:
        messages:
          - content:
            - type: text
              text: ${variable.prompt}
            role: user
    setup:
      model: gpt-4
    task: TASK_CHAT