feat: Azure Open AI chat model & embeddings (n8n-io#8522)

Signed-off-by: Oleg Ivaniv <me@olegivaniv.com>

cypress/composables/workflow.ts

@@ -106,14 +106,19 @@ export function addSupplementalNodeToParent(
 	nodeName: string,
 	endpointType: EndpointType,
 	parentNodeName: string,
+	exactMatch = false,
 ) {
 	getAddInputEndpointByType(parentNodeName, endpointType).click({ force: true });
-	getNodeCreatorItems().contains(nodeName).click();
+	if (exactMatch) {
+		getNodeCreatorItems().contains(new RegExp("^" + nodeName + "$", "g")).click();
+	} else {
+		getNodeCreatorItems().contains(nodeName).click();
+	}
 	getConnectionBySourceAndTarget(parentNodeName, nodeName).should('exist');
 }
 
-export function addLanguageModelNodeToParent(nodeName: string, parentNodeName: string) {
-	addSupplementalNodeToParent(nodeName, 'ai_languageModel', parentNodeName);
+export function addLanguageModelNodeToParent(nodeName: string, parentNodeName: string, exactMatch = false) {
+	addSupplementalNodeToParent(nodeName, 'ai_languageModel', parentNodeName, exactMatch);
 }
 
 export function addMemoryNodeToParent(nodeName: string, parentNodeName: string) {

cypress/e2e/30-langchain.cy.ts

@@ -83,6 +83,7 @@ describe('Langchain Integration', () => {
 		addLanguageModelNodeToParent(
 			AI_LANGUAGE_MODEL_OPENAI_CHAT_MODEL_NODE_NAME,
 			BASIC_LLM_CHAIN_NODE_NAME,
+			true
 		);
 
 		clickCreateNewCredential();
@@ -121,7 +122,7 @@ describe('Langchain Integration', () => {
 		addNodeToCanvas(MANUAL_CHAT_TRIGGER_NODE_NAME, true);
 		addNodeToCanvas(AGENT_NODE_NAME, true);
 
-		addLanguageModelNodeToParent(AI_LANGUAGE_MODEL_OPENAI_CHAT_MODEL_NODE_NAME, AGENT_NODE_NAME);
+		addLanguageModelNodeToParent(AI_LANGUAGE_MODEL_OPENAI_CHAT_MODEL_NODE_NAME, AGENT_NODE_NAME, true);
 
 		clickCreateNewCredential();
 		setCredentialValues({
@@ -159,7 +160,7 @@ describe('Langchain Integration', () => {
 		addNodeToCanvas(MANUAL_CHAT_TRIGGER_NODE_NAME, true);
 		addNodeToCanvas(AGENT_NODE_NAME, true);
 
-		addLanguageModelNodeToParent(AI_LANGUAGE_MODEL_OPENAI_CHAT_MODEL_NODE_NAME, AGENT_NODE_NAME);
+		addLanguageModelNodeToParent(AI_LANGUAGE_MODEL_OPENAI_CHAT_MODEL_NODE_NAME, AGENT_NODE_NAME, true);
 
 		clickCreateNewCredential();
 		setCredentialValues({

packages/@n8n/nodes-langchain/credentials/AzureOpenAiApi.credentials.ts

@@ -0,0 +1,43 @@
+import type { IAuthenticateGeneric, ICredentialType, INodeProperties } from 'n8n-workflow';
+
+export class AzureOpenAiApi implements ICredentialType {
+	name = 'azureOpenAiApi';
+
+	displayName = 'Azure Open AI';
+
+	documentationUrl = 'azureopenai';
+
+	properties: INodeProperties[] = [
+		{
+			displayName: 'API Key',
+			name: 'apiKey',
+			type: 'string',
+			typeOptions: { password: true },
+			required: true,
+			default: '',
+		},
+		{
+			displayName: 'Resource Name',
+			name: 'resourceName',
+			type: 'string',
+			required: true,
+			default: '',
+		},
+		{
+			displayName: 'API Version',
+			name: 'apiVersion',
+			type: 'string',
+			required: true,
+			default: '2023-05-15',
+		},
+	];
+
+	authenticate: IAuthenticateGeneric = {
+		type: 'generic',
+		properties: {
+			headers: {
+				'api-key': '={{$credentials.apiKey}}',
+			},
+		},
+	};
+}

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

@@ -0,0 +1,126 @@
+/* eslint-disable n8n-nodes-base/node-dirname-against-convention */
+import {
+	NodeConnectionType,
+	type IExecuteFunctions,
+	type INodeType,
+	type INodeTypeDescription,
+	type SupplyData,
+} from 'n8n-workflow';
+
+import { OpenAIEmbeddings } from 'langchain/embeddings/openai';
+import { logWrapper } from '../../../utils/logWrapper';
+import { getConnectionHintNoticeField } from '../../../utils/sharedFields';
+
+export class EmbeddingsAzureOpenAi implements INodeType {
+	description: INodeTypeDescription = {
+		displayName: 'Embeddings Azure OpenAI',
+		name: 'embeddingsAzureOpenAi',
+		icon: 'file:azure.svg',
+		credentials: [
+			{
+				name: 'azureOpenAiApi',
+				required: true,
+			},
+		],
+		group: ['transform'],
+		version: 1,
+		description: 'Use Embeddings Azure OpenAI',
+		defaults: {
+			name: 'Embeddings Azure OpenAI',
+		},
+
+		codex: {
+			categories: ['AI'],
+			subcategories: {
+				AI: ['Embeddings'],
+			},
+			resources: {
+				primaryDocumentation: [
+					{
+						url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.embeddingsazureopenai/',
+					},
+				],
+			},
+		},
+		// 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: [NodeConnectionType.AiEmbedding],
+		outputNames: ['Embeddings'],
+		properties: [
+			getConnectionHintNoticeField([NodeConnectionType.AiVectorStore]),
+			{
+				displayName: 'Model (Deployment) Name',
+				name: 'model',
+				type: 'string',
+				description: 'The name of the model(deployment) to use',
+				default: '',
+			},
+			{
+				displayName: 'Options',
+				name: 'options',
+				placeholder: 'Add Option',
+				description: 'Additional options to add',
+				type: 'collection',
+				default: {},
+				options: [
+					{
+						displayName: 'Batch Size',
+						name: 'batchSize',
+						default: 512,
+						typeOptions: { maxValue: 2048 },
+						description: 'Maximum number of documents to send in each request',
+						type: 'number',
+					},
+					{
+						displayName: 'Strip New Lines',
+						name: 'stripNewLines',
+						default: true,
+						description: 'Whether to strip new lines from the input text',
+						type: 'boolean',
+					},
+					{
+						displayName: 'Timeout',
+						name: 'timeout',
+						default: -1,
+						description:
+							'Maximum amount of time a request is allowed to take in seconds. Set to -1 for no timeout.',
+						type: 'number',
+					},
+				],
+			},
+		],
+	};
+
+	async supplyData(this: IExecuteFunctions, itemIndex: number): Promise<SupplyData> {
+		this.logger.verbose('Supply data for embeddings');
+		const credentials = (await this.getCredentials('azureOpenAiApi')) as {
+			apiKey: string;
+			resourceName: string;
+			apiVersion: string;
+		};
+		const modelName = this.getNodeParameter('model', itemIndex) as string;
+
+		const options = this.getNodeParameter('options', itemIndex, {}) as {
+			batchSize?: number;
+			stripNewLines?: boolean;
+			timeout?: number;
+		};
+
+		if (options.timeout === -1) {
+			options.timeout = undefined;
+		}
+
+		const embeddings = new OpenAIEmbeddings({
+			azureOpenAIApiDeploymentName: modelName,
+			azureOpenAIApiInstanceName: credentials.resourceName,
+			azureOpenAIApiKey: credentials.apiKey,
+			azureOpenAIApiVersion: credentials.apiVersion,
+			...options,
+		});
+
+		return {
+			response: logWrapper(embeddings, this),
+		};
+	}
+}

packages/@n8n/nodes-langchain/nodes/llms/LmChatAzureOpenAi/LmChatAzureOpenAi.node.ts

@@ -0,0 +1,169 @@
+/* eslint-disable n8n-nodes-base/node-dirname-against-convention */
+import {
+	NodeConnectionType,
+	type IExecuteFunctions,
+	type INodeType,
+	type INodeTypeDescription,
+	type SupplyData,
+} from 'n8n-workflow';
+
+import type { ClientOptions } from 'openai';
+import { ChatOpenAI } from 'langchain/chat_models/openai';
+import { logWrapper } from '../../../utils/logWrapper';
+import { getConnectionHintNoticeField } from '../../../utils/sharedFields';
+
+export class LmChatAzureOpenAi implements INodeType {
+	description: INodeTypeDescription = {
+		displayName: 'Azure OpenAI Chat Model',
+		// eslint-disable-next-line n8n-nodes-base/node-class-description-name-miscased
+		name: 'lmChatAzureOpenAi',
+		icon: 'file:azure.svg',
+		group: ['transform'],
+		version: 1,
+		description: 'For advanced usage with an AI chain',
+		defaults: {
+			name: 'Azure OpenAI Chat Model',
+		},
+		codex: {
+			categories: ['AI'],
+			subcategories: {
+				AI: ['Language Models'],
+			},
+			resources: {
+				primaryDocumentation: [
+					{
+						url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatazureopenai/',
+					},
+				],
+			},
+		},
+		// 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: [NodeConnectionType.AiLanguageModel],
+		outputNames: ['Model'],
+		credentials: [
+			{
+				name: 'azureOpenAiApi',
+				required: true,
+			},
+		],
+		properties: [
+			getConnectionHintNoticeField([NodeConnectionType.AiChain, NodeConnectionType.AiAgent]),
+			{
+				displayName: 'Model (Deployment) Name',
+				name: 'model',
+				type: 'string',
+				description: 'The name of the model(deployment) to use',
+				default: '',
+			},
+			{
+				displayName: 'Options',
+				name: 'options',
+				placeholder: 'Add Option',
+				description: 'Additional options to add',
+				type: 'collection',
+				default: {},
+				options: [
+					{
+						displayName: 'Frequency Penalty',
+						name: 'frequencyPenalty',
+						default: 0,
+						typeOptions: { maxValue: 2, minValue: -2, numberPrecision: 1 },
+						description:
+							"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",
+						type: 'number',
+					},
+					{
+						displayName: 'Maximum Number of Tokens',
+						name: 'maxTokens',
+						default: -1,
+						description:
+							'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).',
+						type: 'number',
+						typeOptions: {
+							maxValue: 32768,
+						},
+					},
+					{
+						displayName: 'Presence Penalty',
+						name: 'presencePenalty',
+						default: 0,
+						typeOptions: { maxValue: 2, minValue: -2, numberPrecision: 1 },
+						description:
+							"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",
+						type: 'number',
+					},
+					{
+						displayName: 'Sampling Temperature',
+						name: 'temperature',
+						default: 0.7,
+						typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
+						description:
+							'Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.',
+						type: 'number',
+					},
+					{
+						displayName: 'Timeout',
+						name: 'timeout',
+						default: 60000,
+						description: 'Maximum amount of time a request is allowed to take in milliseconds',
+						type: 'number',
+					},
+					{
+						displayName: 'Max Retries',
+						name: 'maxRetries',
+						default: 2,
+						description: 'Maximum number of retries to attempt',
+						type: 'number',
+					},
+					{
+						displayName: 'Top P',
+						name: 'topP',
+						default: 1,
+						typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
+						description:
+							'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.',
+						type: 'number',
+					},
+				],
+			},
+		],
+	};
+
+	async supplyData(this: IExecuteFunctions, itemIndex: number): Promise<SupplyData> {
+		const credentials = (await this.getCredentials('azureOpenAiApi')) as {
+			apiKey: string;
+			resourceName: string;
+			apiVersion: string;
+		};
+
+		const modelName = this.getNodeParameter('model', itemIndex) as string;
+		const options = this.getNodeParameter('options', itemIndex, {}) as {
+			frequencyPenalty?: number;
+			maxTokens?: number;
+			maxRetries: number;
+			timeout: number;
+			presencePenalty?: number;
+			temperature?: number;
+			topP?: number;
+		};
+
+		const configuration: ClientOptions = {};
+
+		const model = new ChatOpenAI({
+			azureOpenAIApiDeploymentName: modelName,
+			azureOpenAIApiInstanceName: credentials.resourceName,
+			azureOpenAIApiKey: credentials.apiKey,
+			azureOpenAIApiVersion: credentials.apiVersion,
+			...options,
+			timeout: options.timeout ?? 60000,
+			maxRetries: options.maxRetries ?? 2,
+			configuration,
+		});
+
+		return {
+			response: logWrapper(model, this),
+		};
+	}
+}