/* eslint-disable n8n-nodes-base/node-dirname-against-convention */
import {
NodeConnectionType,
type INodeType,
type INodeTypeDescription,
type ISupplyDataFunctions,
type SupplyData,
} from 'n8n-workflow';
import { CohereEmbeddings } from '@langchain/cohere';
import { logWrapper } from '../../../utils/logWrapper';
import { getConnectionHintNoticeField } from '../../../utils/sharedFields';
export class EmbeddingsCohere implements INodeType {
description: INodeTypeDescription = {
displayName: 'Embeddings Cohere',
name: 'embeddingsCohere',
icon: { light: 'file:cohere.svg', dark: 'file:cohere.dark.svg' },
group: ['transform'],
version: 1,
description: 'Use Cohere Embeddings',
defaults: {
name: 'Embeddings Cohere',
},
requestDefaults: {
ignoreHttpStatusErrors: true,
baseURL: '={{ $credentials.host }}',
},
credentials: [
{
name: 'cohereApi',
required: true,
},
],
codex: {
categories: ['AI'],
subcategories: {
AI: ['Embeddings'],
},
resources: {
primaryDocumentation: [
{
url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.embeddingscohere/',
},
],
},
},
// 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:
'Each model is using different dimensional density for embeddings. Please make sure to use the same dimensionality for your vector store. The default model is using 768-dimensional embeddings.',
name: 'notice',
type: 'notice',
default: '',
},
{
displayName: 'Model',
name: 'modelName',
type: 'options',
description:
'The model which will generate the embeddings. Learn more.',
default: 'embed-english-v2.0',
options: [
{
name: 'Embed-English-Light-v2.0 (1024 Dimensions)',
value: 'embed-english-light-v2.0',
},
{
name: 'Embed-English-Light-v3.0 (384 Dimensions)',
value: 'embed-english-light-v3.0',
},
{
name: 'Embed-English-v2.0 (4096 Dimensions)',
value: 'embed-english-v2.0',
},
{
name: 'Embed-English-v3.0 (1024 Dimensions)',
value: 'embed-english-v3.0',
},
{
name: 'Embed-Multilingual-Light-v3.0 (384 Dimensions)',
value: 'embed-multilingual-light-v3.0',
},
{
name: 'Embed-Multilingual-v2.0 (768 Dimensions)',
value: 'embed-multilingual-v2.0',
},
{
name: 'Embed-Multilingual-v3.0 (1024 Dimensions)',
value: 'embed-multilingual-v3.0',
},
],
},
],
};
async supplyData(this: ISupplyDataFunctions, itemIndex: number): Promise {
this.logger.debug('Supply data for embeddings Cohere');
const modelName = this.getNodeParameter('modelName', itemIndex, 'embed-english-v2.0') as string;
const credentials = await this.getCredentials<{ apiKey: string }>('cohereApi');
const embeddings = new CohereEmbeddings({
apiKey: credentials.apiKey,
model: modelName,
});
return {
response: logWrapper(embeddings, this),
};
}
}