/* 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),
};
}
}