agsamantha/node_modules/@langchain/community/dist/embeddings/premai.cjs
2024-10-02 15:15:21 -05:00

108 lines
4.2 KiB
JavaScript

"use strict";
var __importDefault = (this && this.__importDefault) || function (mod) {
return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.PremEmbeddings = void 0;
const env_1 = require("@langchain/core/utils/env");
const embeddings_1 = require("@langchain/core/embeddings");
const chunk_array_1 = require("@langchain/core/utils/chunk_array");
const prem_sdk_1 = __importDefault(require("@premai/prem-sdk"));
/**
* Class for generating embeddings using the Prem AI's API. Extends the
* Embeddings class and implements PremEmbeddingsParams and
*/
class PremEmbeddings extends embeddings_1.Embeddings {
constructor(fields) {
super(fields);
Object.defineProperty(this, "client", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "batchSize", {
enumerable: true,
configurable: true,
writable: true,
value: 128
});
Object.defineProperty(this, "apiKey", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "project_id", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "model", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "encoding_format", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
const apiKey = fields?.apiKey || (0, env_1.getEnvironmentVariable)("PREM_API_KEY");
if (!apiKey) {
throw new Error(`Prem API key not found. Please set the PREM_API_KEY environment variable or provide the key into "apiKey"`);
}
const projectId = fields?.project_id ??
parseInt((0, env_1.getEnvironmentVariable)("PREM_PROJECT_ID") ?? "-1", 10);
if (!projectId || projectId === -1 || typeof projectId !== "number") {
throw new Error(`Prem project ID not found. Please set the PREM_PROJECT_ID environment variable or provide the key into "project_id"`);
}
this.client = new prem_sdk_1.default({
apiKey,
});
this.project_id = projectId;
this.model = fields.model ?? this.model;
this.encoding_format = fields.encoding_format ?? this.encoding_format;
}
/**
* Method to generate embeddings for an array of documents. Splits the
* documents into batches and makes requests to the Prem API to generate
* embeddings.
* @param texts Array of documents to generate embeddings for.
* @returns Promise that resolves to a 2D array of embeddings for each document.
*/
async embedDocuments(texts) {
const mappedTexts = texts.map((text) => text);
const batches = (0, chunk_array_1.chunkArray)(mappedTexts, this.batchSize);
const batchRequests = batches.map((batch) => this.caller.call(async () => this.client.embeddings.create({
input: batch,
model: this.model,
encoding_format: this.encoding_format,
project_id: this.project_id,
})));
const batchResponses = await Promise.all(batchRequests);
const embeddings = [];
for (let i = 0; i < batchResponses.length; i += 1) {
const batch = batches[i];
const { data: batchResponse } = batchResponses[i];
for (let j = 0; j < batch.length; j += 1) {
embeddings.push(batchResponse[j].embedding);
}
}
return embeddings;
}
/**
* Method to generate an embedding for a single document. Calls the
* embedDocuments method with the document as the input.
* @param text Document to generate an embedding for.
* @returns Promise that resolves to an embedding for the document.
*/
async embedQuery(text) {
const data = await this.embedDocuments([text]);
return data[0];
}
}
exports.PremEmbeddings = PremEmbeddings;