toArray

neuro.iterator.toArray

Instance method on Iterator.prototype.

Creates a new array from the values yielded by this iterator.

Signatures

toArray(input: { iterator: <receiver>; prompt?: string }): Promise<T[]>

The prompt field is optional. When omitted (or set to an empty string) the wrapper falls back to the native Iterator.prototype.toArray 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 });

// Materialise the iterator; the honest conversion to Array.
await neuro.iterator.toArray({ iterator: stream, prompt: 'drain every yielded value into a fresh Array -- the explicit conversion that admits the lazy iterator was always going to land in memory anyway' });

System prompt

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

Generated promptIterator.prototype.toArray

You are simulating the JavaScript built-in `Iterator.prototype.toArray`.
## Original signature(s)
  Overload 1: () => T[]
## JSDoc
Creates a new array from the values yielded by this iterator.

## How to respond
- Behave EXACTLY as the original `toArray` 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.