@n8n/n8n-nodes-langchain
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JavaScript
;
var __defProp = Object.defineProperty;
var __getOwnPropDesc = Object.getOwnPropertyDescriptor;
var __getOwnPropNames = Object.getOwnPropertyNames;
var __hasOwnProp = Object.prototype.hasOwnProperty;
var __export = (target, all) => {
for (var name in all)
__defProp(target, name, { get: all[name], enumerable: true });
};
var __copyProps = (to, from, except, desc) => {
if (from && typeof from === "object" || typeof from === "function") {
for (let key of __getOwnPropNames(from))
if (!__hasOwnProp.call(to, key) && key !== except)
__defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });
}
return to;
};
var __toCommonJS = (mod) => __copyProps(__defProp({}, "__esModule", { value: true }), mod);
var EmbeddingsOpenAi_node_exports = {};
__export(EmbeddingsOpenAi_node_exports, {
EmbeddingsOpenAi: () => EmbeddingsOpenAi
});
module.exports = __toCommonJS(EmbeddingsOpenAi_node_exports);
var import_openai = require("@langchain/openai");
var import_n8n_workflow = require("n8n-workflow");
var import_logWrapper = require("../../../utils/logWrapper");
var import_httpProxyAgent = require("../../../utils/httpProxyAgent");
var import_sharedFields = require("../../../utils/sharedFields");
var import_di = require("@n8n/di");
var import_config = require("@n8n/config");
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() || $credentials?.url?.split("/").slice(-1).pop() || "v1" }}/models'
},
output: {
postReceive: [
{
type: "rootProperty",
properties: {
property: "data"
}
},
{
type: "filter",
properties: {
// If the baseURL is not set or is set to api.openai.com, include only embedding models
pass: `={{
($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: [import_n8n_workflow.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, import_sharedFields.getConnectionHintNoticeField)([import_n8n_workflow.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: void 0,
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: void 0,
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 = void 0;
}
const { openAiDefaultHeaders: defaultHeaders } = import_di.Container.get(import_config.AiConfig);
const configuration = {
defaultHeaders
};
if (options.baseURL) {
configuration.baseURL = options.baseURL;
} else if (credentials.url) {
configuration.baseURL = credentials.url;
}
if (configuration.baseURL) {
configuration.fetchOptions = {
dispatcher: (0, import_httpProxyAgent.getProxyAgent)(configuration.baseURL ?? "https://api.openai.com/v1")
};
}
const embeddings = new import_openai.OpenAIEmbeddings({
model: this.getNodeParameter("model", itemIndex, "text-embedding-3-small"),
apiKey: credentials.apiKey,
...options,
configuration
});
return {
response: (0, import_logWrapper.logWrapper)(embeddings, this)
};
}
}
// Annotate the CommonJS export names for ESM import in node:
0 && (module.exports = {
EmbeddingsOpenAi
});
//# sourceMappingURL=EmbeddingsOpenAi.node.js.map