@n8n/n8n-nodes-langchain
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JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
exports.LmChatMinimax = 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");
class LmChatMinimax {
constructor() {
this.description = {
displayName: 'MiniMax Chat Model',
name: 'lmChatMinimax',
icon: 'file:minimax.svg',
group: ['transform'],
version: [1],
description: 'For advanced usage with an AI chain',
defaults: {
name: 'MiniMax 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.lmchatminimax/',
},
],
},
alias: ['minimax'],
},
inputs: [],
outputs: [n8n_workflow_1.NodeConnectionTypes.AiLanguageModel],
outputNames: ['Model'],
credentials: [
{
name: 'minimaxApi',
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: 'Model',
name: 'model',
type: 'options',
description: 'The model which will generate the completion. <a href="https://platform.minimax.io/docs/api-reference/text-openai-api">Learn more</a>.',
options: [
{ name: 'MiniMax-M2', value: 'MiniMax-M2' },
{ name: 'MiniMax-M2.1', value: 'MiniMax-M2.1' },
{ name: 'MiniMax-M2.1-Highspeed', value: 'MiniMax-M2.1-highspeed' },
{ name: 'MiniMax-M2.5', value: 'MiniMax-M2.5' },
{ name: 'MiniMax-M2.5-Highspeed', value: 'MiniMax-M2.5-highspeed' },
{ name: 'MiniMax-M2.7', value: 'MiniMax-M2.7' },
{ name: 'MiniMax-M2.7-Highspeed', value: 'MiniMax-M2.7-highspeed' },
],
default: 'MiniMax-M2.7',
builderHint: {
message: 'Default to the latest MiniMax-M2.x flagship (MiniMax-M2.7). Avoid MiniMax-M2 and earlier.',
},
},
{
displayName: 'Options',
name: 'options',
placeholder: 'Add Option',
description: 'Additional options to add',
type: 'collection',
default: {},
options: [
{
displayName: 'Hide Thinking',
name: 'hideThinking',
default: true,
type: 'boolean',
description: 'Whether to strip chain-of-thought reasoning from the response, returning only the final answer',
},
{
displayName: 'Maximum Number of Tokens',
name: 'maxTokens',
default: -1,
description: 'The maximum number of tokens to generate in the completion. The limit depends on the selected model.',
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: 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('minimaxApi');
const modelName = this.getNodeParameter('model', itemIndex);
const options = this.getNodeParameter('options', itemIndex, {});
const hideThinking = options.hideThinking ?? true;
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,
model: modelName,
...options,
timeout,
maxRetries: options.maxRetries ?? 2,
configuration,
callbacks: [new ai_utilities_1.N8nLlmTracing(this)],
modelKwargs: hideThinking ? { reasoning_split: true } : undefined,
onFailedAttempt: (0, ai_utilities_1.makeN8nLlmFailedAttemptHandler)(this, error_handling_1.openAiFailedAttemptHandler),
});
return {
response: model,
};
}
}
exports.LmChatMinimax = LmChatMinimax;
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