feat: Add support for google vertex embeddings (#14359)

Co-authored-by: Oleg Ivaniv <[email protected]>

Author: schrothbn

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

@@ -0,0 +1,160 @@
+/* eslint-disable n8n-nodes-base/node-dirname-against-convention */
+import { ProjectsClient } from '@google-cloud/resource-manager';
+import { VertexAIEmbeddings } from '@langchain/google-vertexai';
+import { formatPrivateKey } from 'n8n-nodes-base/dist/utils/utilities';
+import { NodeConnectionTypes } from 'n8n-workflow';
+import type {
+	ILoadOptionsFunctions,
+	INodeType,
+	INodeTypeDescription,
+	ISupplyDataFunctions,
+	SupplyData,
+} from 'n8n-workflow';
+
+import { logWrapper } from '@utils/logWrapper';
+import { getConnectionHintNoticeField } from '@utils/sharedFields';
+
+export class EmbeddingsGoogleVertex implements INodeType {
+	methods = {
+		listSearch: {
+			async gcpProjectsList(this: ILoadOptionsFunctions) {
+				const results: Array<{ name: string; value: string }> = [];
+
+				const credentials = await this.getCredentials('googleApi');
+				const privateKey = formatPrivateKey(credentials.privateKey as string);
+				const email = (credentials.email as string).trim();
+
+				const client = new ProjectsClient({
+					credentials: {
+						client_email: email,
+						private_key: privateKey,
+					},
+				});
+
+				const [projects] = await client.searchProjects();
+
+				for (const project of projects) {
+					if (project.projectId) {
+						results.push({
+							name: project.displayName ?? project.projectId,
+							value: project.projectId,
+						});
+					}
+				}
+
+				return { results };
+			},
+		},
+	};
+
+	description: INodeTypeDescription = {
+		displayName: 'Embeddings Google Vertex',
+		name: 'embeddingsGoogleVertex',
+		icon: 'file:google.svg',
+		group: ['transform'],
+		version: 1,
+		description: 'Use Google Vertex Embeddings',
+		defaults: {
+			name: 'Embeddings Google Vertex',
+		},
+		requestDefaults: {
+			ignoreHttpStatusErrors: true,
+			baseURL: '={{ $credentials.host }}',
+		},
+		credentials: [
+			{
+				name: 'googleApi',
+				required: true,
+			},
+		],
+		codex: {
+			categories: ['AI'],
+			subcategories: {
+				AI: ['Embeddings'],
+			},
+			resources: {
+				primaryDocumentation: [
+					{
+						url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.embeddingsgooglevertex/',
+					},
+				],
+			},
+		},
+		// eslint-disable-next-line n8n-nodes-base/node-class-description-inputs-wrong-regular-node
+		inputs: [],
+		// eslint-disable-next-line n8n-nodes-base/node-class-description-outputs-wrong
+		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. You can find available models <a href="https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/text-embeddings-api">here</a>.',
+				name: 'notice',
+				type: 'notice',
+				default: '',
+			},
+			{
+				displayName: 'Project ID',
+				name: 'projectId',
+				type: 'resourceLocator',
+				default: { mode: 'list', value: '' },
+				required: true,
+				description: 'Select or enter your Google Cloud project ID',
+				modes: [
+					{
+						displayName: 'From List',
+						name: 'list',
+						type: 'list',
+						typeOptions: {
+							searchListMethod: 'gcpProjectsList',
+						},
+					},
+					{
+						displayName: 'ID',
+						name: 'id',
+						type: 'string',
+					},
+				],
+			},
+			{
+				displayName: 'Model Name',
+				name: 'modelName',
+				type: 'string',
+				description:
+					'The model which will generate the embeddings. <a href="https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/text-embeddings-api">Learn more</a>.',
+				default: 'text-embedding-005',
+			},
+		],
+	};
+
+	async supplyData(this: ISupplyDataFunctions, itemIndex: number): Promise<SupplyData> {
+		const credentials = await this.getCredentials('googleApi');
+		const privateKey = formatPrivateKey(credentials.privateKey as string);
+		const email = (credentials.email as string).trim();
+		const region = credentials.region as string;
+
+		const modelName = this.getNodeParameter('modelName', itemIndex) as string;
+
+		const projectId = this.getNodeParameter('projectId', itemIndex, '', {
+			extractValue: true,
+		}) as string;
+
+		const embeddings = new VertexAIEmbeddings({
+			authOptions: {
+				projectId,
+				credentials: {
+					client_email: email,
+					private_key: privateKey,
+				},
+			},
+			location: region,
+			model: modelName,
+		});
+
+		return {
+			response: logWrapper(embeddings, this),
+		};
+	}
+}

packages/@n8n/nodes-langchain/nodes/embeddings/EmbeddingsGoogleVertex/google.svg

@@ -61,6 +61,7 @@
       "dist/nodes/embeddings/EmbeddingsAwsBedrock/EmbeddingsAwsBedrock.node.js",
       "dist/nodes/embeddings/EmbeddingsAzureOpenAi/EmbeddingsAzureOpenAi.node.js",
       "dist/nodes/embeddings/EmbeddingsGoogleGemini/EmbeddingsGoogleGemini.node.js",
+      "dist/nodes/embeddings/EmbeddingsGoogleVertex/EmbeddingsGoogleVertex.node.js",
       "dist/nodes/embeddings/EmbeddingsHuggingFaceInference/EmbeddingsHuggingFaceInference.node.js",
       "dist/nodes/embeddings/EmbeddingsMistralCloud/EmbeddingsMistralCloud.node.js",
       "dist/nodes/embeddings/EmbeddingsOpenAI/EmbeddingsOpenAi.node.js",