dtamind-components
Version:
Apps integration for Dtamind. Contain Nodes and Credentials.
107 lines • 3.77 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 OpenAIEmbedding_Embeddings {
constructor() {
//@ts-ignore
this.loadMethods = {
async listModels() {
return await (0, modelLoader_1.getModels)(modelLoader_1.MODEL_TYPE.EMBEDDING, 'openAIEmbeddings');
}
};
this.label = 'OpenAI Embeddings';
this.name = 'openAIEmbeddings';
this.version = 4.0;
this.type = 'OpenAIEmbeddings';
this.icon = 'openai.svg';
this.category = 'Embeddings';
this.description = 'OpenAI API to generate embeddings for a given text';
this.baseClasses = [this.type, ...(0, utils_1.getBaseClasses)(openai_1.OpenAIEmbeddings)];
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['openAIApi']
};
this.inputs = [
{
label: 'Model Name',
name: 'modelName',
type: 'asyncOptions',
loadMethod: 'listModels',
default: 'text-embedding-ada-002'
},
{
label: 'Strip New Lines',
name: 'stripNewLines',
type: 'boolean',
optional: true,
additionalParams: true
},
{
label: 'Batch Size',
name: 'batchSize',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'Timeout',
name: 'timeout',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'BasePath',
name: 'basepath',
type: 'string',
optional: true,
additionalParams: true
},
{
label: 'Dimensions',
name: 'dimensions',
type: 'number',
optional: true,
additionalParams: true
}
];
}
async init(nodeData, _, options) {
const stripNewLines = nodeData.inputs?.stripNewLines;
const batchSize = nodeData.inputs?.batchSize;
const timeout = nodeData.inputs?.timeout;
const basePath = nodeData.inputs?.basepath;
const modelName = nodeData.inputs?.modelName;
const dimensions = nodeData.inputs?.dimensions;
if (nodeData.inputs?.credentialId) {
nodeData.credential = nodeData.inputs?.credentialId;
}
const credentialData = await (0, utils_1.getCredentialData)(nodeData.credential ?? '', options);
const openAIApiKey = (0, utils_1.getCredentialParam)('openAIApiKey', credentialData, nodeData);
const obj = {
openAIApiKey,
modelName
};
if (stripNewLines)
obj.stripNewLines = stripNewLines;
if (batchSize)
obj.batchSize = parseInt(batchSize, 10);
if (timeout)
obj.timeout = parseInt(timeout, 10);
if (dimensions)
obj.dimensions = parseInt(dimensions, 10);
if (basePath) {
obj.configuration = {
baseURL: basePath
};
}
const model = new openai_1.OpenAIEmbeddings(obj);
return model;
}
}
module.exports = { nodeClass: OpenAIEmbedding_Embeddings };
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