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0f7ae3f50a
Signed-off-by: Oleg Ivaniv <me@olegivaniv.com> Co-authored-by: Michael Kret <michael.k@radency.com>
250 lines
6.8 KiB
TypeScript
250 lines
6.8 KiB
TypeScript
/* eslint-disable n8n-nodes-base/node-dirname-against-convention */
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import { NodeConnectionType } from 'n8n-workflow';
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import type {
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IExecuteFunctions,
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INodeType,
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INodeTypeDescription,
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SupplyData,
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ILoadOptionsFunctions,
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} from 'n8n-workflow';
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import { OpenAI, type ClientOptions } from '@langchain/openai';
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import { logWrapper } from '../../../utils/logWrapper';
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import { getConnectionHintNoticeField } from '../../../utils/sharedFields';
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type LmOpenAiOptions = {
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baseURL?: string;
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frequencyPenalty?: number;
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maxTokens?: number;
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presencePenalty?: number;
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temperature?: number;
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timeout?: number;
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maxRetries?: number;
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topP?: number;
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};
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export class LmOpenAi implements INodeType {
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description: INodeTypeDescription = {
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displayName: 'OpenAI Model',
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// eslint-disable-next-line n8n-nodes-base/node-class-description-name-miscased
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name: 'lmOpenAi',
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icon: 'file:openAi.svg',
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group: ['transform'],
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version: 1,
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description: 'For advanced usage with an AI chain',
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defaults: {
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name: 'OpenAI Model',
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},
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codex: {
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categories: ['AI'],
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subcategories: {
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AI: ['Language Models'],
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},
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resources: {
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primaryDocumentation: [
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{
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url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmopenai/',
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},
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],
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},
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},
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// eslint-disable-next-line n8n-nodes-base/node-class-description-inputs-wrong-regular-node
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inputs: [],
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// eslint-disable-next-line n8n-nodes-base/node-class-description-outputs-wrong
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outputs: [NodeConnectionType.AiLanguageModel],
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outputNames: ['Model'],
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credentials: [
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{
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name: 'openAiApi',
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required: true,
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},
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],
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requestDefaults: {
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ignoreHttpStatusErrors: true,
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baseURL:
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'={{ $parameter.options?.baseURL?.split("/").slice(0,-1).join("/") || "https://api.openai.com" }}',
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},
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properties: [
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getConnectionHintNoticeField([NodeConnectionType.AiChain, NodeConnectionType.AiAgent]),
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{
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displayName: 'Model',
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name: 'model',
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type: 'resourceLocator',
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default: { mode: 'list', value: 'gpt-3.5-turbo-instruct' },
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required: true,
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description:
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'The model which will generate the completion. <a href="https://beta.openai.com/docs/models/overview">Learn more</a>.',
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modes: [
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{
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displayName: 'From List',
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name: 'list',
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type: 'list',
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typeOptions: {
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searchListMethod: 'openAiModelSearch',
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},
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},
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{
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displayName: 'ID',
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name: 'id',
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type: 'string',
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},
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],
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routing: {
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send: {
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type: 'body',
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property: 'model',
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value: '={{$parameter.model.value}}',
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},
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},
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},
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{
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displayName: 'Options',
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name: 'options',
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placeholder: 'Add Option',
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description: 'Additional options to add',
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type: 'collection',
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default: {},
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options: [
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{
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displayName: 'Base URL',
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name: 'baseURL',
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default: 'https://api.openai.com/v1',
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description: 'Override the default base URL for the API',
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type: 'string',
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},
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{
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displayName: 'Frequency Penalty',
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name: 'frequencyPenalty',
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default: 0,
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typeOptions: { maxValue: 2, minValue: -2, numberPrecision: 1 },
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description:
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"Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim",
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type: 'number',
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},
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{
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displayName: 'Maximum Number of Tokens',
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name: 'maxTokens',
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default: -1,
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description:
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'The maximum number of tokens to generate in the completion. Most models have a context length of 2048 tokens (except for the newest models, which support 32,768).',
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type: 'number',
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typeOptions: {
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maxValue: 32768,
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},
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},
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{
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displayName: 'Presence Penalty',
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name: 'presencePenalty',
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default: 0,
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typeOptions: { maxValue: 2, minValue: -2, numberPrecision: 1 },
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description:
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"Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics",
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type: 'number',
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},
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{
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displayName: 'Sampling Temperature',
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name: 'temperature',
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default: 0.7,
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typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
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description:
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'Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.',
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type: 'number',
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},
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{
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displayName: 'Timeout',
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name: 'timeout',
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default: 60000,
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description: 'Maximum amount of time a request is allowed to take in milliseconds',
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type: 'number',
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},
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{
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displayName: 'Max Retries',
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name: 'maxRetries',
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default: 2,
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description: 'Maximum number of retries to attempt',
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type: 'number',
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},
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{
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displayName: 'Top P',
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name: 'topP',
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default: 1,
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typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
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description:
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'Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.',
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type: 'number',
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},
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],
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},
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],
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};
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methods = {
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listSearch: {
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async openAiModelSearch(this: ILoadOptionsFunctions) {
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const results = [];
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const options = this.getNodeParameter('options', {}) as LmOpenAiOptions;
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let uri = 'https://api.openai.com/v1/models';
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if (options.baseURL) {
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uri = `${options.baseURL}/models`;
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}
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const { data } = (await this.helpers.requestWithAuthentication.call(this, 'openAiApi', {
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method: 'GET',
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uri,
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json: true,
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})) as { data: Array<{ owned_by: string; id: string }> };
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for (const model of data) {
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if (!model.owned_by?.startsWith('system')) continue;
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results.push({
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name: model.id,
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value: model.id,
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});
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}
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return { results };
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},
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},
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};
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async supplyData(this: IExecuteFunctions, itemIndex: number): Promise<SupplyData> {
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const credentials = await this.getCredentials('openAiApi');
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const modelName = this.getNodeParameter('model', itemIndex, '', {
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extractValue: true,
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}) as string;
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const options = this.getNodeParameter('options', itemIndex, {}) as {
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baseURL?: string;
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frequencyPenalty?: number;
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maxTokens?: number;
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presencePenalty?: number;
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temperature?: number;
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timeout?: number;
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maxRetries?: number;
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topP?: number;
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};
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const configuration: ClientOptions = {};
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if (options.baseURL) {
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configuration.baseURL = options.baseURL;
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}
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const model = new OpenAI({
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openAIApiKey: credentials.apiKey as string,
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modelName,
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...options,
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configuration,
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timeout: options.timeout ?? 60000,
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maxRetries: options.maxRetries ?? 2,
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});
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return {
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response: logWrapper(model, this),
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};
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}
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}
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