79 lines
3.0 KiB
TypeScript
79 lines
3.0 KiB
TypeScript
import { ChatWrapper } from "../ChatWrapper.js";
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import { ChatModelFunctions, ChatModelResponse, ChatWrapperGenerateContextStateOptions, ChatWrapperGeneratedContextState, ChatWrapperSettings } from "../types.js";
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import { LlamaText } from "../utils/LlamaText.js";
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export declare class HarmonyChatWrapper extends ChatWrapper {
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readonly wrapperName: string;
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readonly modelIdentity: string | null;
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readonly cuttingKnowledgeDate?: Date | (() => Date) | null;
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readonly todayDate: Date | (() => Date) | null;
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readonly reasoningEffort: "high" | "medium" | "low" | null;
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readonly requiredChannels: {
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analysis: boolean;
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commentary: boolean;
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final: boolean;
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};
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readonly keepOnlyLastThought: boolean;
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readonly settings: ChatWrapperSettings;
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constructor(options?: {
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/**
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* The model identity to use in the internal system message.
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*
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* Set to `null` to disable.
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*
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* Defaults to `"You are ChatGPT, a large language model trained by OpenAI."`
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*/
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modelIdentity?: string | null;
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/**
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* Set to `null` to disable
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*
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* Defaults to `new Date("2024-06-01T00:00:00Z")`
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*/
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cuttingKnowledgeDate?: Date | (() => Date) | number | string | null;
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/**
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* Set to `null` to disable
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*
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* Defaults to the current date
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*/
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todayDate?: Date | (() => Date) | number | string | null;
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/**
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* The amount of reasoning to instruct the model to use.
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*
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* Not enforced, it's up to the model to follow this instruction.
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*
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* Set to `null` to omit the instruction.
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*
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* Defaults to `"medium"`.
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*/
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reasoningEffort?: "high" | "medium" | "low" | null;
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requiredChannels?: {
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/**
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* Defaults to `true`
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*/
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analysis?: boolean;
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/**
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* Defaults to `true`
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*/
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commentary?: boolean;
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/**
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* Defaults to `true`
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*/
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final?: boolean;
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};
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/**
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* Whether to keep only the chain of thought from the last model response.
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*
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* Setting this to `false` will keep all the chain of thoughts from the model responses in the context state.
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*
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* Defaults to `true`.
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*/
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keepOnlyLastThought?: boolean;
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});
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generateContextState({ chatHistory, availableFunctions, documentFunctionParams }: ChatWrapperGenerateContextStateOptions): ChatWrapperGeneratedContextState;
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generateFunctionCall(name: string, params: any): LlamaText;
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generateFunctionCallResult(functionName: string, functionParams: any, result: any): LlamaText;
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generateModelResponseText(modelResponse: ChatModelResponse["response"], useRawValues?: boolean): LlamaText;
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generateAvailableFunctionsSystemText(availableFunctions: ChatModelFunctions, { documentParams }: {
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documentParams?: boolean;
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}): import("../utils/LlamaText.js")._LlamaText;
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}
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