dtamind-components
Version:
DTAmindai Components
180 lines • 6.11 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
const openai_1 = require("@langchain/openai");
const utils_1 = require("../../../src/utils");
const modelLoader_1 = require("../../../src/modelLoader");
class OpenAI_LLMs {
constructor() {
//@ts-ignore
this.loadMethods = {
async listModels() {
return await (0, modelLoader_1.getModels)(modelLoader_1.MODEL_TYPE.LLM, 'openAI');
}
};
this.label = 'OpenAI';
this.name = 'openAI';
this.version = 4.0;
this.type = 'OpenAI';
this.icon = 'openai.svg';
this.category = 'LLMs';
this.description = 'Wrapper around OpenAI large language models';
this.baseClasses = [this.type, ...(0, utils_1.getBaseClasses)(openai_1.OpenAI)];
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['openAIApi']
};
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
type: 'asyncOptions',
loadMethod: 'listModels',
default: 'gpt-3.5-turbo-instruct'
},
{
label: 'Temperature',
name: 'temperature',
type: 'number',
step: 0.1,
default: 0.7,
optional: true
},
{
label: 'Max Tokens',
name: 'maxTokens',
type: 'number',
step: 1,
optional: true,
additionalParams: true
},
{
label: 'Top Probability',
name: 'topP',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true
},
{
label: 'Best Of',
name: 'bestOf',
type: 'number',
step: 1,
optional: true,
additionalParams: true
},
{
label: 'Frequency Penalty',
name: 'frequencyPenalty',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true
},
{
label: 'Presence Penalty',
name: 'presencePenalty',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true
},
{
label: 'Batch Size',
name: 'batchSize',
type: 'number',
step: 1,
optional: true,
additionalParams: true
},
{
label: 'Timeout',
name: 'timeout',
type: 'number',
step: 1,
optional: true,
additionalParams: true
},
{
label: 'BasePath',
name: 'basepath',
type: 'string',
optional: true,
additionalParams: true
},
{
label: 'BaseOptions',
name: 'baseOptions',
type: 'json',
optional: true,
additionalParams: true
}
];
}
async init(nodeData, _, options) {
const temperature = nodeData.inputs?.temperature;
const modelName = nodeData.inputs?.modelName;
const maxTokens = nodeData.inputs?.maxTokens;
const topP = nodeData.inputs?.topP;
const frequencyPenalty = nodeData.inputs?.frequencyPenalty;
const presencePenalty = nodeData.inputs?.presencePenalty;
const timeout = nodeData.inputs?.timeout;
const batchSize = nodeData.inputs?.batchSize;
const bestOf = nodeData.inputs?.bestOf;
const streaming = nodeData.inputs?.streaming;
const basePath = nodeData.inputs?.basepath;
const baseOptions = nodeData.inputs?.baseOptions;
const credentialData = await (0, utils_1.getCredentialData)(nodeData.credential ?? '', options);
const openAIApiKey = (0, utils_1.getCredentialParam)('openAIApiKey', credentialData, nodeData);
const cache = nodeData.inputs?.cache;
const obj = {
temperature: parseFloat(temperature),
modelName,
openAIApiKey,
streaming: streaming ?? true
};
if (maxTokens)
obj.maxTokens = parseInt(maxTokens, 10);
if (topP)
obj.topP = parseFloat(topP);
if (frequencyPenalty)
obj.frequencyPenalty = parseFloat(frequencyPenalty);
if (presencePenalty)
obj.presencePenalty = parseFloat(presencePenalty);
if (timeout)
obj.timeout = parseInt(timeout, 10);
if (batchSize)
obj.batchSize = parseInt(batchSize, 10);
if (bestOf)
obj.bestOf = parseInt(bestOf, 10);
if (cache)
obj.cache = cache;
let parsedBaseOptions = undefined;
if (baseOptions) {
try {
parsedBaseOptions = typeof baseOptions === 'object' ? baseOptions : JSON.parse(baseOptions);
}
catch (exception) {
throw new Error("Invalid JSON in the OpenAI's BaseOptions: " + exception);
}
}
if (basePath || parsedBaseOptions) {
obj.configuration = {
baseURL: basePath,
defaultHeaders: parsedBaseOptions
};
}
const model = new openai_1.OpenAI(obj);
return model;
}
}
module.exports = { nodeClass: OpenAI_LLMs };
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