@n8n/n8n-nodes-langchain
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JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
exports.LmOpenHuggingFaceInference = void 0;
const hf_1 = require("@langchain/community/llms/hf");
const n8n_workflow_1 = require("n8n-workflow");
const ai_utilities_1 = require("@n8n/ai-utilities");
class LmOpenHuggingFaceInference {
constructor() {
this.description = {
displayName: 'Hugging Face Inference Model',
name: 'lmOpenHuggingFaceInference',
icon: 'file:huggingface.svg',
group: ['transform'],
version: 1,
description: 'Language Model HuggingFaceInference',
defaults: {
name: 'Hugging Face Inference Model',
},
codex: {
categories: ['AI'],
subcategories: {
AI: ['Language Models', 'Root Nodes'],
'Language Models': ['Text Completion Models'],
},
resources: {
primaryDocumentation: [
{
url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmopenhuggingfaceinference/',
},
],
},
},
inputs: [],
outputs: [n8n_workflow_1.NodeConnectionTypes.AiLanguageModel],
outputNames: ['Model'],
credentials: [
{
name: 'huggingFaceApi',
required: true,
},
],
properties: [
(0, ai_utilities_1.getConnectionHintNoticeField)([n8n_workflow_1.NodeConnectionTypes.AiChain, n8n_workflow_1.NodeConnectionTypes.AiAgent]),
{
displayName: 'Model',
name: 'model',
type: 'string',
default: 'mistralai/Mistral-Nemo-Base-2407',
},
{
displayName: 'Options',
name: 'options',
placeholder: 'Add Option',
description: 'Additional options to add',
type: 'collection',
default: {},
options: [
{
displayName: 'Custom Inference Endpoint',
name: 'endpointUrl',
default: '',
description: 'Custom endpoint URL',
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: 128,
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: '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: 1,
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: 'Top K',
name: 'topK',
default: 1,
typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
description: 'Controls the top tokens to consider within the sample operation to create new text',
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('huggingFaceApi');
const modelName = this.getNodeParameter('model', itemIndex);
const options = this.getNodeParameter('options', itemIndex, {});
const model = new hf_1.HuggingFaceInference({
model: modelName,
apiKey: credentials.apiKey,
...options,
callbacks: [new ai_utilities_1.N8nLlmTracing(this)],
onFailedAttempt: (0, ai_utilities_1.makeN8nLlmFailedAttemptHandler)(this),
});
return {
response: model,
};
}
}
exports.LmOpenHuggingFaceInference = LmOpenHuggingFaceInference;
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