/* eslint-disable n8n-nodes-base/node-dirname-against-convention */ import { NodeConnectionType, type IExecuteFunctions, type INodeType, type INodeTypeDescription, type SupplyData, } from 'n8n-workflow'; import type { ClientOptions } from 'openai'; import { ChatOpenAI } from 'langchain/chat_models/openai'; import { logWrapper } from '../../../utils/logWrapper'; import { getConnectionHintNoticeField } from '../../../utils/sharedFields'; export class LmChatOpenAi implements INodeType { description: INodeTypeDescription = { displayName: 'OpenAI Chat Model', // eslint-disable-next-line n8n-nodes-base/node-class-description-name-miscased name: 'lmChatOpenAi', icon: 'file:openAi.svg', group: ['transform'], version: 1, description: 'For advanced usage with an AI chain', defaults: { name: 'OpenAI Chat Model', }, codex: { categories: ['AI'], subcategories: { AI: ['Language Models'], }, resources: { primaryDocumentation: [ { url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatopenai/', }, ], }, }, // 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: [ { name: 'openAiApi', required: true, }, ], requestDefaults: { ignoreHttpStatusErrors: true, baseURL: '={{ $parameter.options?.baseURL?.split("/").slice(0,-1).join("/") || "https://api.openai.com" }}', }, properties: [ getConnectionHintNoticeField([NodeConnectionType.AiChain, NodeConnectionType.AiAgent]), { displayName: 'If using JSON response format, you must include word "json" in the prompt in your chain or agent. Also, make sure to select latest models released post November 2023.', name: 'notice', type: 'notice', default: '', displayOptions: { show: { '/options.responseFormat': ['json_object'], }, }, }, { displayName: 'Model', name: 'model', type: 'options', description: 'The model which will generate the completion. Learn more.', typeOptions: { loadOptions: { routing: { request: { method: 'GET', url: '={{ $parameter.options?.baseURL?.split("/").slice(-1).pop() || "v1" }}/models', }, output: { postReceive: [ { type: 'rootProperty', properties: { property: 'data', }, }, { type: 'filter', properties: { pass: "={{ $responseItem.id.startsWith('gpt-') && !$responseItem.id.includes('instruct') }}", }, }, { type: 'setKeyValue', properties: { name: '={{$responseItem.id}}', value: '={{$responseItem.id}}', }, }, { type: 'sort', properties: { key: 'name', }, }, ], }, }, }, }, routing: { send: { type: 'body', property: 'model', }, }, default: 'gpt-3.5-turbo', }, { displayName: 'Options', name: 'options', placeholder: 'Add Option', description: 'Additional options to add', type: 'collection', default: {}, options: [ { displayName: 'Base URL', name: 'baseURL', default: 'https://api.openai.com/v1', description: 'Override the default base URL for the API', type: 'string', }, { displayName: 'Frequency Penalty', name: 'frequencyPenalty', default: 0, typeOptions: { maxValue: 2, minValue: -2, numberPrecision: 1 }, description: "Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim", type: 'number', }, { displayName: 'Maximum Number of Tokens', name: 'maxTokens', default: -1, description: 'The maximum number of tokens to generate in the completion. Most models have a context length of 2048 tokens (except for the newest models, which support 32,768).', type: 'number', typeOptions: { maxValue: 32768, }, }, { displayName: 'Response Format', name: 'responseFormat', default: 'text', type: 'options', options: [ { name: 'Text', value: 'text', description: 'Regular text response', }, { name: 'JSON', value: 'json_object', description: 'Enables JSON mode, which should guarantee the message the model generates is valid JSON', }, ], }, { displayName: 'Presence Penalty', name: 'presencePenalty', default: 0, typeOptions: { maxValue: 2, minValue: -2, numberPrecision: 1 }, description: "Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics", 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', }, { displayName: 'Timeout', name: 'timeout', default: 60000, description: 'Maximum amount of time a request is allowed to take in milliseconds', type: 'number', }, { displayName: 'Max Retries', name: 'maxRetries', default: 2, description: 'Maximum number of retries to attempt', type: 'number', }, { displayName: 'Top P', name: 'topP', default: 1, typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 }, description: 'Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.', type: 'number', }, ], }, ], }; async supplyData(this: IExecuteFunctions, itemIndex: number): Promise { const credentials = await this.getCredentials('openAiApi'); const modelName = this.getNodeParameter('model', itemIndex) as string; const options = this.getNodeParameter('options', itemIndex, {}) as { baseURL?: string; frequencyPenalty?: number; maxTokens?: number; maxRetries: number; timeout: number; presencePenalty?: number; temperature?: number; topP?: number; responseFormat?: 'text' | 'json_object'; }; const configuration: ClientOptions = {}; if (options.baseURL) { configuration.baseURL = options.baseURL; } const model = new ChatOpenAI({ openAIApiKey: credentials.apiKey as string, modelName, ...options, timeout: options.timeout ?? 60000, maxRetries: options.maxRetries ?? 2, configuration, modelKwargs: options.responseFormat ? { response_format: { type: options.responseFormat }, } : undefined, }); return { response: logWrapper(model, this), }; } }