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SuggestionsEventSource

The SuggestionsEventSource is a class that wraps around EventTarget. It's specifically designed to handle a stream of suggestions retrieved from an AI model. When instantiated, it initializes a connection to an EventSource and listens for incoming data chunks. These chunks are concatenated into a full message which is processed and emitted through events.

Dependencies

  • EventSourceMessage, fetchEventSource from @microsoft/fetch-event-source
  • debugFactory from debug

Events

  • 'suggestion': Emitted when the full suggestion has been received so far
  • 'message': Emitted when a message has been received
  • 'chunk': Emitted for each chunk of data received
  • 'done': Emitted when the stream has been closed and no more data will be received

Error events

  • 'error': Emitted when an error has occurred
  • 'error_network': Emitted when the EventSource connection to the server returned some error
  • 'error_service_unavailable': Emitted when the server returned a 503 error
  • 'error_quota_exceeded': Emitted when the server returned a 429 error
  • 'error_moderation': Emitted when the server returned a 422 error
  • 'error_unclear_prompt': Emitted when the server returned a message starting with JETPACK_AI_ERROR

Class Properties

  • fullMessage: String that accumulates the incoming chunks of data into a complete message
  • isPromptClear: Boolean that represents whether the prompt is clear or not
  • controller: AbortController instance used to close the fetchEventSource connection

Constructor

The constructor takes an object with the following properties:

  • url (optional): URL of the EventSource. If not provided, the default will be used.
  • question: The prompt/question to the AI model. It can be a string or an array of PromptItemProps objects.
  • token: The token to authenticate the request.
  • options (optional): An object that may include the following properties:
    • postId (optional): The post ID.
    • feature (optional): A string that specifies the AI model to use (default or 'ai-assistant-experimental').
    • fromCache (optional): A boolean to indicate whether to fetch the response from cache.
    • model (optional): Allows to use a specific AI model.

Usage

To use this class, you would instantiate it with the necessary data, and then you can listen to its events to get and handle the suggestions.

Here is a basic usage example:

const eventSource = new SuggestionsEventSource( {
  question: "Who won the world cup in 2022?",
  token: "your_token_here",
} );

eventSource.addEventListener( 'suggestion', event => {
  console.log( event.detail ); // Logs the suggestion
} );

It's possible to simulate a "conversation" when requesting a suggestion by providing an array of PromptItemProps. Each PromptItemProps is an object with a role (either 'system', 'user', or 'assistant') and content:

const eventSource = new SuggestionsEventSource( {
  question: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'Who won the world cup in 2022?' },
  ],
  token: "your_token_here",
} );

eventSource.addEventListener( 'suggestion', event => {
  console.log( event.detail ); // Logs the suggestion
} );

In this example, we've passed an array of prompts to the question parameter. The 'system' role typically represents the context or environment in which the 'user' and 'assistant' are interacting. The 'user' and 'assistant' roles denote the roles of user and assistant in a conversation, respectively. The prompts are processed in the order they appear in the array, simulating a conversation that culminates with the final question: "Who won the world cup in 2022?".