@n8n/n8n-nodes-langchain
Version:
242 lines • 11.4 kB
JavaScript
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.LmChatNvidia = void 0;
const openai_1 = require("@langchain/openai");
const ai_utilities_1 = require("@n8n/ai-utilities");
const n8n_workflow_1 = require("n8n-workflow");
const error_handling_1 = require("../../vendors/OpenAi/helpers/error-handling");
const NEMOTRON_SUPPORTED_MODELS = [
'nvidia/llama-3.1-nemotron-nano-8b-v1',
'nvidia/llama-3.3-nemotron-super-49b-v1',
'nvidia/llama-3.3-nemotron-super-49b-v1.5',
'nvidia/nemotron-3-nano-30b-a3b',
'nvidia/nemotron-3-nano-omni-30b-a3b-reasoning',
'nvidia/nemotron-3-super-120b-a12b',
'nvidia/nemotron-nano-12b-v2-vl',
'nvidia/nvidia-nemotron-nano-9b-v2',
];
class LmChatNvidia {
constructor() {
this.description = {
displayName: 'NVIDIA Nemotron Chat Model',
name: 'lmChatNvidia',
icon: { light: 'file:nvidia.svg', dark: 'file:nvidia.dark.svg' },
group: ['transform'],
version: [1],
description: 'NVIDIA Nemotron models from build.nvidia.com or self-hosted NIM',
defaults: {
name: 'NVIDIA Nemotron 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.lmchatnvidia/',
},
],
},
},
inputs: [],
outputs: [n8n_workflow_1.NodeConnectionTypes.AiLanguageModel],
outputNames: ['Model'],
credentials: [
{
name: 'nvidiaApi',
required: true,
},
],
requestDefaults: {
ignoreHttpStatusErrors: true,
baseURL: '={{ $credentials?.url }}',
},
properties: [
(0, ai_utilities_1.getConnectionHintNoticeField)([n8n_workflow_1.NodeConnectionTypes.AiChain, n8n_workflow_1.NodeConnectionTypes.AiAgent]),
{
displayName: 'If using JSON response format, you must include word "json" in the prompt in your chain or agent.',
name: 'notice',
type: 'notice',
default: '',
displayOptions: {
show: {
'/options.responseFormat': ['json_object'],
},
},
},
{
displayName: 'Model',
name: 'model',
type: 'options',
description: 'The Nemotron model which will generate the completion. <a href="https://build.nvidia.com/models">Learn more</a>.',
typeOptions: {
loadOptions: {
routing: {
request: {
method: 'GET',
url: '/models',
},
output: {
postReceive: [
{
type: 'rootProperty',
properties: {
property: 'data',
},
},
{
type: 'filter',
properties: {
pass: `={{ ${JSON.stringify(NEMOTRON_SUPPORTED_MODELS)}.includes($responseItem.id) }}`,
},
},
{
type: 'setKeyValue',
properties: {
name: '={{$responseItem.id}}',
value: '={{$responseItem.id}}',
},
},
{
type: 'sort',
properties: {
key: 'name',
},
},
],
},
},
},
},
routing: {
send: {
type: 'body',
property: 'model',
},
},
default: 'nvidia/llama-3.3-nemotron-super-49b-v1',
options: NEMOTRON_SUPPORTED_MODELS.map((id) => ({ name: id, value: id })),
},
{
displayName: 'Options',
name: 'options',
placeholder: 'Add Option',
description: 'Additional options to add',
type: 'collection',
default: {},
options: [
{
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. Use -1 for the model default.',
type: 'number',
},
{
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: 2, 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: 360000,
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(itemIndex) {
const credentials = await this.getCredentials('nvidiaApi');
const modelName = this.getNodeParameter('model', itemIndex);
const options = this.getNodeParameter('options', itemIndex, {});
const timeout = options.timeout;
const configuration = {
baseURL: credentials.url,
fetchOptions: {
dispatcher: (0, ai_utilities_1.getProxyAgent)(credentials.url, {
headersTimeout: timeout,
bodyTimeout: timeout,
}),
},
};
const model = new openai_1.ChatOpenAI({
apiKey: credentials.apiKey || 'unused',
model: modelName,
...options,
timeout,
maxRetries: options.maxRetries ?? 2,
configuration,
callbacks: [new ai_utilities_1.N8nLlmTracing(this)],
modelKwargs: options.responseFormat
? {
response_format: { type: options.responseFormat },
}
: undefined,
onFailedAttempt: (0, ai_utilities_1.makeN8nLlmFailedAttemptHandler)(this, error_handling_1.openAiFailedAttemptHandler),
});
return {
response: model,
};
}
}
exports.LmChatNvidia = LmChatNvidia;
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