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packages/@n8n/nodes-langchain/nodes/embeddings/EmbeddingsHuggingFaceInference/EmbeddingsHuggingFaceInference.node.ts

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+import type { InferenceProviderOrPolicy } from '@huggingface/inference';
+import { PROVIDERS_OR_POLICIES } from '@huggingface/inference';
+import { HuggingFaceInferenceEmbeddings } from '@langchain/community/embeddings/hf';
+import {
+	NodeConnectionTypes,
+	NodeOperationError,
+	type INodeType,
+	type INodeTypeDescription,
+	type ISupplyDataFunctions,
+	type SupplyData,
+} from 'n8n-workflow';
+
+import { logWrapper, getConnectionHintNoticeField } from '@n8n/ai-utilities';
+
+export class EmbeddingsHuggingFaceInference implements INodeType {
+	description: INodeTypeDescription = {
+		displayName: 'Embeddings Hugging Face Inference',
+		name: 'embeddingsHuggingFaceInference',
+		icon: 'file:huggingface.svg',
+		group: ['transform'],
+		version: 1,
+		description: 'Use HuggingFace Inference Embeddings',
+		defaults: {
+			name: 'Embeddings HuggingFace Inference',
+		},
+		credentials: [
+			{
+				name: 'huggingFaceApi',
+				required: true,
+			},
+		],
+		codex: {
+			categories: ['AI'],
+			subcategories: {
+				AI: ['Embeddings'],
+			},
+			resources: {
+				primaryDocumentation: [
+					{
+						url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.embeddingshuggingfaceinference/',
+					},
+				],
+			},
+		},
+
+		inputs: [],
+
+		outputs: [NodeConnectionTypes.AiEmbedding],
+		outputNames: ['Embeddings'],
+		properties: [
+			getConnectionHintNoticeField([NodeConnectionTypes.AiVectorStore]),
+			{
+				displayName:
+					'Each model is using different dimensional density for embeddings. Please make sure to use the same dimensionality for your vector store. The default model is using 768-dimensional embeddings.',
+				name: 'notice',
+				type: 'notice',
+				default: '',
+			},
+			{
+				displayName: 'Model Name',
+				name: 'modelName',
+				type: 'string',
+				default: 'sentence-transformers/distilbert-base-nli-mean-tokens',
+				description: 'The model name to use from HuggingFace library',
+			},
+			{
+				displayName: 'Options',
+				name: 'options',
+				placeholder: 'Add Option',
+				description: 'Additional options to add',
+				type: 'collection',
+				default: {},
+				options: [
+					{
+						displayName: 'Custom Inference Endpoint',
+						name: 'endpointUrl',
+						default: '',
+						description: 'Custom endpoint URL',
+						type: 'string',
+					},
+					{
+						displayName: 'Provider',
+						name: 'provider',
+						type: 'options',
+						options: PROVIDERS_OR_POLICIES.map((value) => ({ value, name: value })),
+						default: 'auto',
+					},
+				],
+			},
+		],
+	};
+
+	async supplyData(this: ISupplyDataFunctions, itemIndex: number): Promise<SupplyData> {
+		this.logger.debug('Supply data for embeddings HF Inference');
+		const model = this.getNodeParameter(
+			'modelName',
+			itemIndex,
+			'sentence-transformers/distilbert-base-nli-mean-tokens',
+		) as string;
+		const credentials = await this.getCredentials('huggingFaceApi');
+		const options = this.getNodeParameter('options', itemIndex, {}) as object;
+
+		if ('provider' in options && !isValidHFProviderOrPolicy(options.provider)) {
+			throw new NodeOperationError(this.getNode(), 'Unsupported provider');
+		}
+
+		const embeddings = new HuggingFaceInferenceEmbeddings({
+			apiKey: credentials.apiKey as string,
+			model,
+			...options,
+		});
+
+		return {
+			response: logWrapper(embeddings, this),
+		};
+	}
+}
+
+function isValidHFProviderOrPolicy(provider: unknown): provider is InferenceProviderOrPolicy {
+	return (
+		typeof provider === 'string' && (PROVIDERS_OR_POLICIES as readonly string[]).includes(provider)
+	);
+}