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

133 lines
4.9 KiB
JavaScript

import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { Embeddings } from "@langchain/core/embeddings";
import { chunkArray } from "@langchain/core/utils/chunk_array";
/**
* A class for generating embeddings using the Fireworks AI API.
*/
export class FireworksEmbeddings extends Embeddings {
/**
* Constructor for the FireworksEmbeddings class.
* @param fields - An optional object with properties to configure the instance.
*/
constructor(fields) {
const fieldsWithDefaults = { ...fields };
super(fieldsWithDefaults);
/**
* @deprecated Use `model` instead.
*/
Object.defineProperty(this, "modelName", {
enumerable: true,
configurable: true,
writable: true,
value: "nomic-ai/nomic-embed-text-v1.5"
});
Object.defineProperty(this, "model", {
enumerable: true,
configurable: true,
writable: true,
value: "nomic-ai/nomic-embed-text-v1.5"
});
Object.defineProperty(this, "batchSize", {
enumerable: true,
configurable: true,
writable: true,
value: 8
});
Object.defineProperty(this, "apiKey", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "basePath", {
enumerable: true,
configurable: true,
writable: true,
value: "https://api.fireworks.ai/inference/v1"
});
Object.defineProperty(this, "apiUrl", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "headers", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
const apiKey = fieldsWithDefaults?.apiKey || getEnvironmentVariable("FIREWORKS_API_KEY");
if (!apiKey) {
throw new Error("Fireworks AI API key not found");
}
this.model = fieldsWithDefaults?.model ?? this.model;
this.modelName = this.model;
this.batchSize = fieldsWithDefaults?.batchSize ?? this.batchSize;
this.apiKey = apiKey;
this.apiUrl = `${this.basePath}/embeddings`;
}
/**
* Generates embeddings for an array of texts.
* @param texts - An array of strings to generate embeddings for.
* @returns A Promise that resolves to an array of embeddings.
*/
async embedDocuments(texts) {
const batches = chunkArray(texts, this.batchSize);
const batchRequests = batches.map((batch) => this.embeddingWithRetry({
model: this.model,
input: batch,
}));
const batchResponses = await Promise.all(batchRequests);
const embeddings = [];
for (let i = 0; i < batchResponses.length; i += 1) {
const batch = batches[i];
const { data: batchResponse } = batchResponses[i];
for (let j = 0; j < batch.length; j += 1) {
embeddings.push(batchResponse[j].embedding);
}
}
return embeddings;
}
/**
* Generates an embedding for a single text.
* @param text - A string to generate an embedding for.
* @returns A Promise that resolves to an array of numbers representing the embedding.
*/
async embedQuery(text) {
const { data } = await this.embeddingWithRetry({
model: this.model,
input: text,
});
return data[0].embedding;
}
/**
* Makes a request to the Fireworks AI API to generate embeddings for an array of texts.
* @param request - An object with properties to configure the request.
* @returns A Promise that resolves to the response from the Fireworks AI API.
*/
async embeddingWithRetry(request) {
const makeCompletionRequest = async () => {
const url = `${this.apiUrl}`;
const response = await fetch(url, {
method: "POST",
headers: {
"Content-Type": "application/json",
Authorization: `Bearer ${this.apiKey}`,
...this.headers,
},
body: JSON.stringify(request),
});
if (!response.ok) {
const { error: message } = await response.json();
const error = new Error(`Error ${response.status}: ${message ?? "Unspecified error"}`);
// eslint-disable-next-line @typescript-eslint/no-explicit-any
error.response = response;
throw error;
}
const json = await response.json();
return json;
};
return this.caller.call(makeCompletionRequest);
}
}