/* eslint-disable n8n-nodes-base/node-dirname-against-convention */ import { NodeConnectionType, type IExecuteFunctions, type INodeType, type INodeTypeDescription, type SupplyData, } from 'n8n-workflow'; import { BedrockChat } from '@langchain/community/chat_models/bedrock'; import { getConnectionHintNoticeField } from '../../../utils/sharedFields'; // Dependencies needed underneath the hood. We add them // here only to track where what dependency is used import '@aws-sdk/credential-provider-node'; import '@aws-sdk/client-bedrock-runtime'; import { N8nLlmTracing } from '../N8nLlmTracing'; export class LmChatAwsBedrock implements INodeType { description: INodeTypeDescription = { displayName: 'AWS Bedrock Chat Model', // eslint-disable-next-line n8n-nodes-base/node-class-description-name-miscased name: 'lmChatAwsBedrock', icon: 'file:bedrock.svg', group: ['transform'], version: 1, description: 'Language Model AWS Bedrock', defaults: { name: 'AWS Bedrock Chat Model', }, codex: { categories: ['AI'], subcategories: { AI: ['Language Models', 'Root Nodes'], 'Language Models': ['Chat Models (Recommended)'], }, resources: { primaryDocumentation: [ { url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatawsbedrock/', }, ], }, }, // 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.AiLanguageModel], outputNames: ['Model'], credentials: [ { // eslint-disable-next-line n8n-nodes-base/node-class-description-credentials-name-unsuffixed name: 'aws', required: true, }, ], requestDefaults: { ignoreHttpStatusErrors: true, baseURL: '=https://bedrock.{{$credentials?.region ?? "eu-central-1"}}.amazonaws.com', }, properties: [ getConnectionHintNoticeField([NodeConnectionType.AiChain, NodeConnectionType.AiChain]), { displayName: 'Model', name: 'model', type: 'options', description: 'The model which will generate the completion. Learn more.', typeOptions: { loadOptions: { routing: { request: { method: 'GET', url: '/foundation-models?&byOutputModality=TEXT&byInferenceType=ON_DEMAND', }, output: { postReceive: [ { type: 'rootProperty', properties: { property: 'modelSummaries', }, }, { type: 'setKeyValue', properties: { name: '={{$responseItem.modelName}}', description: '={{$responseItem.modelArn}}', value: '={{$responseItem.modelId}}', }, }, { type: 'sort', properties: { key: 'name', }, }, ], }, }, }, }, routing: { send: { type: 'body', property: 'model', }, }, default: '', }, { displayName: 'Options', name: 'options', placeholder: 'Add Option', description: 'Additional options to add', type: 'collection', default: {}, options: [ { displayName: 'Maximum Number of Tokens', name: 'maxTokensToSample', default: 2000, description: 'The maximum number of tokens to generate in the completion', type: 'number', }, { displayName: 'Sampling Temperature', name: 'temperature', default: 0.7, typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 }, description: 'Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.', type: 'number', }, ], }, ], }; async supplyData(this: IExecuteFunctions, itemIndex: number): Promise { const credentials = await this.getCredentials('aws'); const modelName = this.getNodeParameter('model', itemIndex) as string; const options = this.getNodeParameter('options', itemIndex, {}) as { temperature: number; maxTokensToSample: number; }; const model = new BedrockChat({ region: credentials.region as string, model: modelName, temperature: options.temperature, maxTokens: options.maxTokensToSample, credentials: { secretAccessKey: credentials.secretAccessKey as string, accessKeyId: credentials.accessKeyId as string, sessionToken: credentials.sessionToken as string, }, callbacks: [new N8nLlmTracing(this)], }); return { response: model, }; } }