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0f7ae3f50a
Signed-off-by: Oleg Ivaniv <me@olegivaniv.com> Co-authored-by: Michael Kret <michael.k@radency.com>
151 lines
4.6 KiB
TypeScript
151 lines
4.6 KiB
TypeScript
/* eslint-disable n8n-nodes-base/node-dirname-against-convention */
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import {
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NodeConnectionType,
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type IExecuteFunctions,
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type INodeType,
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type INodeTypeDescription,
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type SupplyData,
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} from 'n8n-workflow';
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import { HuggingFaceInference } from '@langchain/community/llms/hf';
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import { logWrapper } from '../../../utils/logWrapper';
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import { getConnectionHintNoticeField } from '../../../utils/sharedFields';
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export class LmOpenHuggingFaceInference implements INodeType {
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description: INodeTypeDescription = {
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displayName: 'Hugging Face Inference Model',
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// eslint-disable-next-line n8n-nodes-base/node-class-description-name-miscased
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name: 'lmOpenHuggingFaceInference',
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icon: 'file:huggingface.svg',
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group: ['transform'],
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version: 1,
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description: 'Language Model HuggingFaceInference',
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defaults: {
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name: 'Hugging Face Inference 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.lmopenhuggingfaceinference/',
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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: 'huggingFaceApi',
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required: true,
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},
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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: 'string',
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default: 'gpt2',
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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: 'Custom Inference Endpoint',
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name: 'endpointUrl',
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default: '',
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description: 'Custom endpoint URL',
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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: 128,
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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: 1,
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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: 'Top K',
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name: 'topK',
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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 the top tokens to consider within the sample operation to create new text',
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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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async supplyData(this: IExecuteFunctions, itemIndex: number): Promise<SupplyData> {
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const credentials = await this.getCredentials('huggingFaceApi');
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const modelName = this.getNodeParameter('model', itemIndex) as string;
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const options = this.getNodeParameter('options', itemIndex, {}) as object;
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const model = new HuggingFaceInference({
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model: modelName,
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apiKey: credentials.apiKey as string,
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...options,
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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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