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

119 lines
4.3 KiB
JavaScript

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.DeepInfraEmbeddings = 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");
/**
* The default model name to use for generating embeddings.
*/
const DEFAULT_MODEL_NAME = "sentence-transformers/clip-ViT-B-32";
/**
* The default batch size to use for generating embeddings.
* This is limited by the DeepInfra API to a maximum of 1024.
*/
const DEFAULT_BATCH_SIZE = 1024;
/**
* Environment variable name for the DeepInfra API token.
*/
const API_TOKEN_ENV_VAR = "DEEPINFRA_API_TOKEN";
/**
* A class for generating embeddings using the DeepInfra API.
* @example
* ```typescript
* // Embed a query using the DeepInfraEmbeddings class
* const model = new DeepInfraEmbeddings();
* const res = await model.embedQuery(
* "What would be a good company name for a company that makes colorful socks?",
* );
* console.log({ res });
* ```
*/
class DeepInfraEmbeddings extends embeddings_1.Embeddings {
/**
* Constructor for the DeepInfraEmbeddings class.
* @param fields - An optional object with properties to configure the instance.
*/
constructor(fields) {
const fieldsWithDefaults = {
modelName: DEFAULT_MODEL_NAME,
batchSize: DEFAULT_BATCH_SIZE,
...fields,
};
super(fieldsWithDefaults);
Object.defineProperty(this, "apiToken", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "batchSize", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "modelName", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
const apiKey = fieldsWithDefaults?.apiToken || (0, env_1.getEnvironmentVariable)(API_TOKEN_ENV_VAR);
if (!apiKey) {
throw new Error("DeepInfra API token not found");
}
this.modelName = fieldsWithDefaults?.modelName ?? this.modelName;
this.batchSize = fieldsWithDefaults?.batchSize ?? this.batchSize;
this.apiToken = apiKey;
}
/**
* Generates embeddings for an array of texts.
* @param inputs - An array of strings to generate embeddings for.
* @returns A Promise that resolves to an array of embeddings.
*/
async embedDocuments(inputs) {
const batches = (0, chunk_array_1.chunkArray)(inputs, this.batchSize);
const batchRequests = batches.map((batch) => this.embeddingWithRetry({
inputs: batch,
}));
const batchResponses = await Promise.all(batchRequests);
const out = [];
for (let i = 0; i < batchResponses.length; i += 1) {
const batch = batches[i];
const { embeddings } = batchResponses[i];
for (let j = 0; j < batch.length; j += 1) {
out.push(embeddings[j]);
}
}
return out;
}
/**
* Generates an embedding for a single text.
* @param text - A string to generate an embedding for.
* @returns A Promise that resolves to an array of numbers representing the embedding.
*/
async embedQuery(text) {
const { embeddings } = await this.embeddingWithRetry({
inputs: [text],
});
return embeddings[0];
}
/**
* Generates embeddings with retry capabilities.
* @param request - An object containing the request parameters for generating embeddings.
* @returns A Promise that resolves to the API response.
*/
async embeddingWithRetry(request) {
const response = await this.caller.call(() => fetch(`https://api.deepinfra.com/v1/inference/${this.modelName}`, {
method: "POST",
headers: {
Authorization: `Bearer ${this.apiToken}`,
"Content-Type": "application/json",
},
body: JSON.stringify(request),
}).then((res) => res.json()));
return response;
}
}
exports.DeepInfraEmbeddings = DeepInfraEmbeddings;