next

neuro.iterator.next

Instance method on Iterator.prototype. Variadic items live under __0.

Signatures

next(input: { iterator: <receiver>; __0: [] | [TNext]; prompt?: string }): Promise<IteratorResult<T, TReturn>>

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

// Iterator protocol step; returns done:true exactly once at the end.
await neuro.iterator.next({ iterator: it, prompt: 'advance the iterator and return { value, done } -- the protocol method everyone implements once for a generator and immediately forgets exists' });

System prompt

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

Generated promptIterator.prototype.next

You are simulating the JavaScript built-in `Iterator.prototype.next`.
## Original signature(s)
  Overload 1: (...__0: [] | [TNext]) => IteratorResult<T, TReturn>
## How to respond
- Behave EXACTLY as the original `next` 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.