@n8n/n8n-nodes-langchain
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JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
exports.EmbeddingsOpenAi = void 0;
const openai_1 = require("@langchain/openai");
const config_1 = require("@n8n/config");
const di_1 = require("@n8n/di");
const n8n_workflow_1 = require("n8n-workflow");
const checkDomainRestrictions_1 = require("../../../utils/checkDomainRestrictions");
const helpers_1 = require("../../../utils/helpers");
const ai_utilities_1 = require("@n8n/ai-utilities");
const modelParameter = {
displayName: 'Model',
name: 'model',
type: 'options',
description: 'The model which will generate the embeddings. <a href="https://platform.openai.com/docs/models/overview">Learn more</a>.',
typeOptions: {
loadOptions: {
routing: {
request: {
method: 'GET',
url: '={{ $parameter.options?.baseURL?.split("/").slice(-1).pop() || $credentials?.url?.split("/").slice(-1).pop() || "v1" }}/models',
},
output: {
postReceive: [
{
type: 'rootProperty',
properties: {
property: 'data',
},
},
{
type: 'filter',
properties: {
pass: `={{
($parameter.options?.baseURL && !$parameter.options?.baseURL?.startsWith('https://api.openai.com/')) ||
($credentials?.url && !$credentials.url.startsWith('https://api.openai.com/')) ||
$responseItem.id.includes('embed')
}}`,
},
},
{
type: 'setKeyValue',
properties: {
name: '={{$responseItem.id}}',
value: '={{$responseItem.id}}',
},
},
{
type: 'sort',
properties: {
key: 'name',
},
},
],
},
},
},
},
routing: {
send: {
type: 'body',
property: 'model',
},
},
default: 'text-embedding-3-small',
};
class EmbeddingsOpenAi {
constructor() {
this.description = {
displayName: 'Embeddings OpenAI',
name: 'embeddingsOpenAi',
icon: { light: 'file:openAiLight.svg', dark: 'file:openAiLight.dark.svg' },
credentials: [
{
name: 'openAiApi',
required: true,
},
],
group: ['transform'],
version: [1, 1.1, 1.2],
description: 'Use Embeddings OpenAI',
defaults: {
name: 'Embeddings OpenAI',
},
codex: {
categories: ['AI'],
subcategories: {
AI: ['Embeddings'],
},
resources: {
primaryDocumentation: [
{
url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.embeddingsopenai/',
},
],
},
},
inputs: [],
outputs: [n8n_workflow_1.NodeConnectionTypes.AiEmbedding],
outputNames: ['Embeddings'],
requestDefaults: {
ignoreHttpStatusErrors: true,
baseURL: '={{ $parameter.options?.baseURL?.split("/").slice(0,-1).join("/") || $credentials.url?.split("/").slice(0,-1).join("/") || "https://api.openai.com" }}',
},
properties: [
(0, ai_utilities_1.getConnectionHintNoticeField)([n8n_workflow_1.NodeConnectionTypes.AiVectorStore]),
{
...modelParameter,
default: 'text-embedding-ada-002',
displayOptions: {
show: {
'@version': [1],
},
},
},
{
...modelParameter,
displayOptions: {
hide: {
'@version': [1],
},
},
},
{
displayName: 'Options',
name: 'options',
placeholder: 'Add Option',
description: 'Additional options to add',
type: 'collection',
default: {},
options: [
{
displayName: 'Dimensions',
name: 'dimensions',
default: 1536,
description: 'The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models.',
type: 'options',
options: [
{
name: '256',
value: 256,
},
{
name: '512',
value: 512,
},
{
name: '1024',
value: 1024,
},
{
name: '1536',
value: 1536,
},
{
name: '3072',
value: 3072,
},
],
},
{
displayName: 'Base URL',
name: 'baseURL',
default: 'https://api.openai.com/v1',
description: 'Override the default base URL for the API',
type: 'string',
displayOptions: {
hide: {
'@version': [{ _cnd: { gte: 1.2 } }],
},
},
},
{
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',
},
{
displayName: 'Encoding Format',
name: 'encodingFormat',
type: 'options',
description: 'The format to return the embeddings in',
default: 'float',
options: [
{
name: 'Float',
value: 'float',
},
{
name: 'Base64',
value: 'base64',
},
],
},
],
},
],
};
}
async supplyData(itemIndex) {
this.logger.debug('Supply data for embeddings');
const credentials = await this.getCredentials('openAiApi');
const options = this.getNodeParameter('options', itemIndex, {});
if (options.timeout === -1) {
options.timeout = undefined;
}
const { openAiDefaultHeaders: defaultHeaders } = di_1.Container.get(config_1.AiConfig);
const configuration = {
defaultHeaders,
};
if (options.baseURL) {
(0, checkDomainRestrictions_1.checkDomainRestrictions)(this, credentials, options.baseURL);
configuration.baseURL = options.baseURL;
}
else if (credentials.url) {
configuration.baseURL = credentials.url;
}
configuration.fetchOptions = {
dispatcher: (0, ai_utilities_1.getProxyAgent)(configuration.baseURL ?? 'https://api.openai.com/v1', {}),
};
configuration.defaultHeaders = (0, helpers_1.mergeCustomHeaders)(credentials, (configuration.defaultHeaders ?? {}));
const embeddings = new openai_1.OpenAIEmbeddings({
model: this.getNodeParameter('model', itemIndex, 'text-embedding-3-small'),
apiKey: credentials.apiKey,
...options,
configuration,
});
return {
response: (0, ai_utilities_1.logWrapper)(embeddings, this),
};
}
}
exports.EmbeddingsOpenAi = EmbeddingsOpenAi;
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