n8n-nodes-tushare
Version:
n8n custom node for Tushare
230 lines • 8.42 kB
JavaScript
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.EmbeddingsSelf = void 0;
const SelfEmbeddings_1 = require("./SelfEmbeddings");
const n8n_workflow_1 = require("n8n-workflow");
const modelParameter = {
displayName: 'Model',
name: 'model',
type: 'options',
description: 'The model which will generate the embeddings. <a href="https://llm.local.cn/ai">Learn more</a>.',
options: [
{
name: 'Bge Large En',
value: 'bge-large-en',
},
{
name: 'Bge Large Zh',
value: 'bge-large-zh',
},
{
name: 'Conan V1',
value: 'conan-v1',
},
{
name: 'M3e Base',
value: 'm3e-base',
},
{
name: 'M3e Batch',
value: 'm3e-batch',
},
{
name: 'Text Embedding 3 Large',
value: 'text-embedding-3-large',
},
{
name: 'Text Embedding 3 Small',
value: 'text-embedding-3-small',
},
{
name: 'Text Embedding Ada 002',
value: 'text-embedding-ada-002',
},
],
routing: {
send: {
type: 'body',
property: 'model',
},
},
default: 'm3e-base',
};
class EmbeddingsSelf {
constructor() {
this.description = {
displayName: 'Embeddings Self',
name: 'embeddingsSelf',
icon: { light: 'file:llm.svg', dark: 'file:llm.svg' },
documentationUrl: 'https://llm.local.cn/ai',
credentials: [
{
name: 'selfLLMApi',
required: true,
},
],
group: ['transform'],
version: [1, 1.1, 1.2],
description: '使用 Self 统一向量服务接口，支持多种模型',
defaults: {
name: 'Embeddings Self',
},
codex: {
categories: ['AI'],
subcategories: {
AI: ['Embeddings'],
},
resources: {
primaryDocumentation: [
{
url: 'https://llm.local.cn/ai',
},
],
},
},
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("/") || "http://llm.local.cn/ai" }}',
},
properties: [
{
displayName: 'Connection Hint',
name: 'connectionHint',
type: 'notice',
default: 'This node can be connected to a Vector Store node.',
displayOptions: {
show: {
'@version': [1, 1.1, 1.2],
},
},
},
{
...modelParameter,
default: 'text-embedding-ada-002',
displayOptions: {
show: {
'@version': [1],
},
},
},
{
...modelParameter,
default: 'm3e-base',
displayOptions: {
hide: {
'@version': [1],
},
},
},
{
displayName: 'Options',
name: 'options',
placeholder: 'Add Option',
description: 'Additional options to add',
type: 'collection',
default: {},
options: [
{
displayName: 'Base URL',
name: 'baseURL',
default: 'http://llm.local.cn/ai',
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: 'Dimensions',
name: 'dimensions',
default: 1024,
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: '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(itemIndex) {
this.logger.debug('Supply data for embeddings');
const credentials = await this.getCredentials('selfLLMApi');
const options = this.getNodeParameter('options', itemIndex, {});
if (options.timeout === -1) {
options.timeout = undefined;
}
const configuration = {};
if (options.baseURL) {
configuration.baseURL = options.baseURL;
}
else if (credentials.url) {
configuration.baseURL = credentials.url;
}
else {
configuration.baseURL = 'http://llm.local.cn/ai';
}
const embeddings = new SelfEmbeddings_1.SelfEmbeddings({
model: this.getNodeParameter('model', itemIndex, 'm3e-base'),
apiKey: credentials.apiKey,
baseURL: configuration.baseURL,
timeout: options.timeout,
stripNewLines: options.stripNewLines,
dimensions: options.dimensions,
batchSize: options.batchSize,
});
return {
response: embeddings,
};
}
}
exports.EmbeddingsSelf = EmbeddingsSelf;
//# sourceMappingURL=EmbeddingsSelf.node.js.map