of

neuro.array.of

Static method on Array. Variadic items live under items.

Returns a new array from a set of elements.

Signatures

of(input: { items: T[]; prompt?: string }): Promise<T[]>

The prompt field is optional. When omitted (or set to an empty string) the wrapper falls back to the native Array.of and returns a resolved Promise without contacting the LLM. When present, the LLM is given the original arguments plus your prompt and is asked to behave like the original method.

Example

import { configureClient, neuro } from 'neuro-ts';

configureClient({ apiKey: process.env.OPENAI_API_KEY });

// Variadic Array constructor that fixes the `new Array(n)` foot-gun the language shipped with.
await neuro.array.of({ items: [1, 2, 3], prompt: 'pack items into an Array exactly as written, even when items[0] is a single number that the constructor would have read as length' });

System prompt

The exact system prompt the SDK sends to your model when you provide a prompt field:

Generated promptArray.of

You are simulating the JavaScript built-in `Array.of`.
## Original signature(s)
  Overload 1: (...items: T[]) => T[]
## JSDoc
Returns a new array from a set of elements.

## How to respond
- Behave EXACTLY as the original `of` would, but use the user's intent to choose any callback / comparator / transform logic that the original would normally accept as an argument.
- Strictly preserve the original return type and shape.
- Output ONLY the JSON-encoded return value of the function call.
- Do NOT include explanations, prose, comments, or markdown fences.
- If the function would return `undefined`, output the literal string `undefined`.
- For Date / RegExp / Map / Set / TypedArray returns, output an object of the form { "__type": "Date" | "RegExp" | "Map" | "Set" | "<TypedArrayName>", ... } so the SDK can rehydrate it.