@n8n/n8n-nodes-langchain
Version:
160 lines • 6.25 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
exports.LmChatGoogleGemini = void 0;
const google_genai_1 = require("@langchain/google-genai");
const n8n_workflow_1 = require("n8n-workflow");
const additional_options_1 = require("../gemini-common/additional-options");
const ai_utilities_1 = require("@n8n/ai-utilities");
function errorDescriptionMapper(error) {
if (error.description?.includes('properties: should be non-empty for OBJECT type')) {
return 'Google Gemini requires at least one <a href="https://docs.n8n.io/advanced-ai/examples/using-the-fromai-function/" target="_blank">dynamic parameter</a> when using tools';
}
return error.description ?? 'Unknown error';
}
const modelRLC = {
displayName: 'Model',
name: 'modelName',
type: 'options',
description: 'The model which will generate the completion. <a href="https://developers.generativeai.google/api/rest/generativelanguage/models/list">Learn more</a>.',
typeOptions: {
loadOptions: {
routing: {
request: {
method: 'GET',
url: '/v1beta/models',
},
output: {
postReceive: [
{
type: 'rootProperty',
properties: {
property: 'models',
},
},
{
type: 'filter',
properties: {
pass: "={{ !$responseItem.name.includes('embedding') }}",
},
},
{
type: 'setKeyValue',
properties: {
name: '={{$responseItem.name}}',
value: '={{$responseItem.name}}',
description: '={{$responseItem.description}}',
},
},
{
type: 'sort',
properties: {
key: 'name',
},
},
],
},
},
},
},
routing: {
send: {
type: 'body',
property: 'model',
},
},
default: 'models/gemini-2.5-flash',
builderHint: {
message: 'Default to the latest flagship Gemini (models/gemini-3.1-pro-preview). Use models/gemini-3.1-flash-lite for cost-efficient builds. Avoid Gemini 2.x, 1.x, and earlier.',
},
};
class LmChatGoogleGemini {
constructor() {
this.description = {
displayName: 'Google Gemini Chat Model',
name: 'lmChatGoogleGemini',
icon: 'file:google.svg',
group: ['transform'],
version: [1, 1.1],
description: 'Chat Model Google Gemini',
defaults: {
name: 'Google Gemini 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.lmchatgooglegemini/',
},
],
},
},
inputs: [],
outputs: [n8n_workflow_1.NodeConnectionTypes.AiLanguageModel],
outputNames: ['Model'],
credentials: [
{
name: 'googlePalmApi',
required: true,
},
],
requestDefaults: {
ignoreHttpStatusErrors: true,
baseURL: '={{ $credentials.host }}',
},
properties: [
(0, ai_utilities_1.getConnectionHintNoticeField)([n8n_workflow_1.NodeConnectionTypes.AiChain, n8n_workflow_1.NodeConnectionTypes.AiAgent]),
{
...modelRLC,
displayOptions: {
show: {
'@version': [{ _cnd: { eq: 1 } }],
},
},
},
{
...modelRLC,
default: 'models/gemini-3-flash-preview',
displayOptions: {
show: {
'@version': [{ _cnd: { gte: 1.1 } }],
},
},
},
(0, additional_options_1.getAdditionalOptions)({ supportsThinkingBudget: false }),
],
};
}
async supplyData(itemIndex) {
const credentials = await this.getCredentials('googlePalmApi');
const modelName = this.getNodeParameter('modelName', itemIndex);
const options = this.getNodeParameter('options', itemIndex, {
maxOutputTokens: 1024,
temperature: 0.7,
topK: 40,
topP: 0.9,
});
const safetySettings = this.getNodeParameter('options.safetySettings.values', itemIndex, null);
const model = new google_genai_1.ChatGoogleGenerativeAI({
apiKey: credentials.apiKey,
baseUrl: credentials.host,
model: modelName,
topK: options.topK,
topP: options.topP,
temperature: options.temperature,
maxOutputTokens: options.maxOutputTokens,
safetySettings,
callbacks: [new ai_utilities_1.N8nLlmTracing(this, { errorDescriptionMapper })],
onFailedAttempt: (0, ai_utilities_1.makeN8nLlmFailedAttemptHandler)(this),
});
return {
response: model,
};
}
}
exports.LmChatGoogleGemini = LmChatGoogleGemini;
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