Function make

packages/ai/ai/src/EmbeddingModel.ts:199–263

(options: {
  /**
   * A method which processes a batch of text inputs and returns embedding
   * results.
   */
  readonly embedMany: (input: ReadonlyArray<string>) => Effect.Effect<Array<Result>, AiError.AiError>
  /**
   * Optional maximum number of text inputs to process in one batch.
   */
  readonly maxBatchSize?: number
  /**
   * Optional configuration to control how batch request results are cached.
   */
  readonly cache?: {
    /**
     * The capacity of the cache.
     */
    readonly capacity: number
    /**
     * The time-to-live for items in the cache.
     */
    readonly timeToLive: Duration.DurationInput
  }
})

 * @category Constructors
 */
export const make = (options: {
  /**
   * A method which processes a batch of text inputs and returns embedding
   * results.
   */
  readonly embedMany: (input: ReadonlyArray<string>) => Effect.Effect<Array<Result>, AiError.AiError>
  /**
   * Optional maximum number of text inputs to process in one batch.
   */
  readonly maxBatchSize?: number
  /**
   * Optional configuration to control how batch request results are cached.
   */
  readonly cache?: {
    /**
     * The capacity of the cache.
     */
    readonly capacity: number
    /**
     * The time-to-live for items in the cache.
     */
    readonly timeToLive: Duration.DurationInput
  }
}) =>
  Effect.gen(function*() {
    const cache = yield* Option.fromNullable(options.cache).pipe(
      Effect.flatMap((config) => Request.makeCache(config)),
      Effect.optionFromOptional
    )

    const resolver = makeBatchedResolver(options.embedMany).pipe(
      options.maxBatchSize ? RequestResolver.batchN(options.maxBatchSize) : identity
    )

    const embed = (input: string) => {
      const request = Effect.request(new EmbeddingRequest({ input }), resolver)
      return Option.match(cache, {
        onNone: () => request,
        onSome: (cache) =>
          request.pipe(
            Effect.withRequestCaching(true),
            Effect.withRequestCache(cache)
          )
      })
    }

    const embedMany = (inputs: ReadonlyArray<string>, options?: {
      readonly concurrency?: Types.Concurrency | undefined
    }) =>
      Effect.forEach(inputs, embed, {
        batching: true,
        concurrency: options?.concurrency
      })

    return EmbeddingModel.of({
      embed: (input) =>
        embed(input).pipe(
          Effect.withSpan("EmbeddingModel.embed", { captureStackTrace: false })