43 lines
1.7 KiB
JavaScript
43 lines
1.7 KiB
JavaScript
import { defineTool, DirectReturnError } from 'libllmorbiter';
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import { TOOL_DESCRIPTIONS, TOOL_PARAMETER_DESCRIPTIONS } from './prompts.js';
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/**
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* ask_user tool:
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* Allows the LLM to ask the user for clarification or a decision (e.g. which SKU or ID
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* they meant, or what parameter to use).
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*
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* When invoked, it raises a DirectReturnError with recordResult: false so the LLMOrbiter
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* halts the inference loop immediately without generating a synthetic tool response.
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* The conversation transitions into `idle` state, allowing the client/user to submit
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* a tool response via the API.
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*/
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export function createAskUserTool() {
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return defineTool({
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name: 'ask_user',
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description: TOOL_DESCRIPTIONS.ask_user,
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strict: false,
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parameters: {
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type: 'object',
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additionalProperties: false,
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required: ['question'],
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properties: {
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question: {
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type: 'string',
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description: TOOL_PARAMETER_DESCRIPTIONS.ask_user.question,
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},
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options: {
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type: ['array', 'null'],
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description: TOOL_PARAMETER_DESCRIPTIONS.ask_user.options,
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items: { type: 'string' },
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maxItems: 3,
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},
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},
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},
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invoke: async ({ question, options = [] }) => {
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const capped = Array.isArray(options) ? options.slice(0, 3) : [];
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// Stop LLM loop immediately so the conversation stays idle awaiting user tool response
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throw new DirectReturnError({ question, options: capped }, { recordResult: false });
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},
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});
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}
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