n8n-nodes-sap-ai-core
Version:
n8n nodes for SAP AI Core LLM and embeddings integration
335 lines • 16 kB
JavaScript
;
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exports.SapAiCoreEmbeddings = void 0;
const n8n_workflow_1 = require("n8n-workflow");
class SapAiCoreEmbeddings {
constructor() {
this.description = {
displayName: 'SAP AI Core Embeddings',
name: 'sapAiCoreEmbeddings',
icon: 'file:sapaicore.svg',
group: ['transform'],
version: 1,
description: 'Use SAP AI Core for text embeddings with vector stores',
defaults: {
name: 'SAP AI Core Embeddings',
},
codex: {
categories: ['AI'],
subcategories: {
AI: ['Embeddings'],
},
resources: {
primaryDocumentation: [
{
url: 'https://help.sap.com/docs/sap-ai-core',
},
],
},
},
inputs: [],
outputs: ["ai_embedding" /* NodeConnectionType.AiEmbedding */],
outputNames: ['Embeddings'],
credentials: [
{
name: 'sapAiCoreApi',
required: true,
},
],
properties: [
{
displayName: 'Use this node to connect SAP AI Core embeddings to vector stores and other AI components.',
name: 'notice',
type: 'notice',
default: '',
},
{
displayName: 'Model',
name: 'model',
type: 'options',
default: 'text-embedding-ada-002',
description: 'The embedding model to use',
required: true,
options: [
{
name: 'Text Embedding Ada 002',
value: 'text-embedding-ada-002',
description: 'OpenAI ada-002 embedding model (1536 dimensions)',
},
{
name: 'Text Embedding 3 Small',
value: 'text-embedding-3-small',
description: 'OpenAI text-embedding-3-small (configurable dimensions)',
},
{
name: 'Text Embedding 3 Large',
value: 'text-embedding-3-large',
description: 'OpenAI text-embedding-3-large (configurable dimensions)',
},
],
},
{
displayName: 'Deployment ID',
name: 'deploymentId',
type: 'string',
default: '',
description: 'SAP AI Core deployment ID for the embedding model',
required: true,
placeholder: 'e.g., dabcd1234567890',
},
{
displayName: 'Resource Group',
name: 'resourceGroup',
type: 'string',
default: 'default',
description: 'SAP AI Core resource group (optional, uses default if not specified)',
required: false,
},
{
displayName: 'Options',
name: 'options',
placeholder: 'Add Option',
description: 'Additional options to add',
type: 'collection',
default: {},
options: [
{
displayName: 'Batch Size',
name: 'batchSize',
type: 'number',
default: 512,
typeOptions: {
maxValue: 2048,
minValue: 1,
},
description: 'Maximum number of documents to send in each request',
},
{
displayName: 'Dimensions',
name: 'dimensions',
type: 'options',
default: undefined,
description: 'Number of dimensions for the embeddings (only supported in text-embedding-3 models)',
options: [
{
name: '256',
value: 256,
},
{
name: '512',
value: 512,
},
{
name: '1024',
value: 1024,
},
{
name: '1536',
value: 1536,
},
{
name: '3072',
value: 3072,
},
],
displayOptions: {
show: {
'/model': ['text-embedding-3-small', 'text-embedding-3-large'],
},
},
},
{
displayName: 'Strip New Lines',
name: 'stripNewLines',
type: 'boolean',
default: true,
description: 'Whether to strip new lines from the input text',
},
{
displayName: 'Timeout',
name: 'timeout',
type: 'number',
default: 60000,
description: 'Request timeout in milliseconds',
},
{
displayName: 'Max Retries',
name: 'maxRetries',
type: 'number',
default: 2,
description: 'Maximum number of retries for failed requests',
},
],
},
],
};
}
async supplyData(itemIndex) {
try {
// Import SAP AI SDK and n8n utilities
const { AzureOpenAiEmbeddingClient } = await Promise.resolve().then(() => __importStar(require('@sap-ai-sdk/langchain')));
// Get parameters
const credentials = await this.getCredentials('sapAiCoreApi');
const model = this.getNodeParameter('model', itemIndex);
const deploymentId = this.getNodeParameter('deploymentId', itemIndex);
const resourceGroup = this.getNodeParameter('resourceGroup', itemIndex, 'default');
const options = this.getNodeParameter('options', itemIndex, {});
// Set up environment for SAP AI SDK authentication
process.env.AICORE_SERVICE_KEY = JSON.stringify({
clientid: credentials.clientId,
clientsecret: credentials.clientSecret,
url: credentials.oauthUrl,
serviceurls: {
AI_API_URL: credentials.baseUrl
},
ai_api_url: credentials.baseUrl
});
// Validate required credentials
if (!credentials.clientId || !credentials.clientSecret || !credentials.oauthUrl || !credentials.baseUrl) {
throw new n8n_workflow_1.NodeOperationError(this.getNode(), 'Incomplete SAP AI Core credentials. Please ensure all fields are filled:\n' +
'- Client ID\n- Client Secret\n- OAuth URL\n- Base URL', { itemIndex });
}
// Validate deployment ID
if (!deploymentId || deploymentId.trim() === '') {
throw new n8n_workflow_1.NodeOperationError(this.getNode(), 'Deployment ID is required. Please provide your SAP AI Core embedding deployment ID.', { itemIndex });
}
// Prepare embedding configuration (keeping original working config)
const embeddingConfig = {
modelName: model,
deploymentId: deploymentId,
resourceGroup: resourceGroup,
};
// Add dimensions if specified (for text-embedding-3 models)
if (options.dimensions && (model === 'text-embedding-3-small' || model === 'text-embedding-3-large')) {
embeddingConfig.dimensions = options.dimensions;
}
// Add other options
if (options.batchSize) {
embeddingConfig.batchSize = options.batchSize;
}
if (options.stripNewLines !== undefined) {
embeddingConfig.stripNewLines = options.stripNewLines;
}
// Create SAP AI SDK embeddings client
let sapEmbeddings;
try {
sapEmbeddings = new AzureOpenAiEmbeddingClient(embeddingConfig);
// Test the client initialization
if (!sapEmbeddings) {
throw new Error('Client creation returned null/undefined');
}
if (typeof sapEmbeddings.embedQuery !== 'function') {
throw new Error(`embedQuery method not available. Client type: ${typeof sapEmbeddings}, methods: ${Object.keys(sapEmbeddings || {}).join(', ')}`);
}
if (typeof sapEmbeddings.embedDocuments !== 'function') {
throw new Error(`embedDocuments method not available. Client methods: ${Object.keys(sapEmbeddings || {}).join(', ')}`);
}
}
catch (clientError) {
throw new n8n_workflow_1.NodeOperationError(this.getNode(), `Failed to create SAP AI Core embeddings client: ${clientError instanceof Error ? clientError.message : String(clientError)}. Please check your SAP AI Core credentials and configuration.`, { itemIndex });
}
// Create a wrapper that implements the full LangChain Embeddings interface
const { Embeddings } = await Promise.resolve().then(() => __importStar(require('@langchain/core/embeddings')));
class SapEmbeddingsWrapper extends Embeddings {
constructor(sapClient) {
super({});
this.sapClient = sapClient;
if (!this.sapClient) {
throw new Error('SAP client is null or undefined');
}
}
async embedDocuments(texts) {
if (!this.sapClient) {
throw new Error('SAP client is not initialized');
}
try {
const result = await this.sapClient.embedDocuments(texts);
return result;
}
catch (error) {
throw new Error(`SAP embedDocuments failed: ${error instanceof Error ? error.message : String(error)}`);
}
}
async embedQuery(text) {
if (!this.sapClient) {
throw new Error('SAP client is not initialized');
}
try {
const result = await this.sapClient.embedQuery(text);
return result;
}
catch (error) {
throw new Error(`SAP embedQuery failed: ${error instanceof Error ? error.message : String(error)}`);
}
}
}
const embeddings = new SapEmbeddingsWrapper(sapEmbeddings);
// Import logWrapper for execution tracking (using local copy)
try {
const { logWrapper } = await Promise.resolve().then(() => __importStar(require('../../utils/logWrapper')));
const wrappedEmbeddings = logWrapper(embeddings, this);
return {
response: wrappedEmbeddings,
};
}
catch (logWrapperError) {
// Fallback to unwrapped embeddings if logWrapper fails
return {
response: embeddings,
};
}
}
catch (error) {
const errorMessage = error instanceof Error ? error.message : 'Unknown error occurred';
if (errorMessage.includes('Cannot find module') && errorMessage.includes('@sap-ai-sdk/langchain')) {
throw new n8n_workflow_1.NodeOperationError(this.getNode(), 'SAP AI SDK LangChain package is required. Please install it with:\n' +
'npm install @sap-ai-sdk/langchain', { itemIndex });
}
// Enhanced error handling for SAP AI Core specific issues
if (errorMessage.includes('authentication') || errorMessage.includes('401')) {
throw new n8n_workflow_1.NodeOperationError(this.getNode(), 'SAP AI Core authentication failed. Please check your credentials:\n' +
'- Client ID\n- Client Secret\n- OAuth URL\n- Base URL', { itemIndex });
}
if (errorMessage.includes('deployment') || errorMessage.includes('404')) {
throw new n8n_workflow_1.NodeOperationError(this.getNode(), 'SAP AI Core deployment not found. Please check:\n' +
'- Deployment ID is correct\n- Model is deployed and active\n- Resource group has access', { itemIndex });
}
throw new n8n_workflow_1.NodeOperationError(this.getNode(), `Failed to initialize SAP AI Core Embeddings: ${errorMessage}`, { itemIndex });
}
}
}
exports.SapAiCoreEmbeddings = SapAiCoreEmbeddings;
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