agsamantha/node_modules/@langchain/community/dist/embeddings/cohere.cjs

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2024-10-02 15:15:21 -05:00
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.CohereEmbeddings = 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");
/**
* A class for generating embeddings using the Cohere API.
* @example
* ```typescript
* // Embed a query using the CohereEmbeddings class
* const model = new ChatOpenAI();
* const res = await model.embedQuery(
* "What would be a good company name for a company that makes colorful socks?",
* );
* console.log({ res });
* ```
* @deprecated Use `CohereEmbeddings` from `@langchain/cohere` instead.
*/
class CohereEmbeddings extends embeddings_1.Embeddings {
/**
* Constructor for the CohereEmbeddings class.
* @param fields - An optional object with properties to configure the instance.
*/
constructor(fields) {
const fieldsWithDefaults = { maxConcurrency: 2, ...fields };
super(fieldsWithDefaults);
Object.defineProperty(this, "modelName", {
enumerable: true,
configurable: true,
writable: true,
value: "small"
});
Object.defineProperty(this, "batchSize", {
enumerable: true,
configurable: true,
writable: true,
value: 48
});
Object.defineProperty(this, "apiKey", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "client", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
const apiKey = fieldsWithDefaults?.apiKey || (0, env_1.getEnvironmentVariable)("COHERE_API_KEY");
if (!apiKey) {
throw new Error("Cohere API key not found");
}
this.modelName = fieldsWithDefaults?.modelName ?? this.modelName;
this.batchSize = fieldsWithDefaults?.batchSize ?? this.batchSize;
this.apiKey = apiKey;
}
/**
* 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) {
await this.maybeInitClient();
const batches = (0, chunk_array_1.chunkArray)(texts, this.batchSize);
const batchRequests = batches.map((batch) => this.embeddingWithRetry({
model: this.modelName,
texts: batch,
}));
const batchResponses = await Promise.all(batchRequests);
const embeddings = [];
for (let i = 0; i < batchResponses.length; i += 1) {
const batch = batches[i];
const { body: batchResponse } = batchResponses[i];
for (let j = 0; j < batch.length; j += 1) {
embeddings.push(batchResponse.embeddings[j]);
}
}
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) {
await this.maybeInitClient();
const { body } = await this.embeddingWithRetry({
model: this.modelName,
texts: [text],
});
return body.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) {
await this.maybeInitClient();
return this.caller.call(this.client.embed.bind(this.client), request);
}
/**
* Initializes the Cohere client if it hasn't been initialized already.
*/
async maybeInitClient() {
if (!this.client) {
const { cohere } = await CohereEmbeddings.imports();
this.client = cohere;
this.client.init(this.apiKey);
}
}
/** @ignore */
static async imports() {
try {
const { default: cohere } = await import("cohere-ai");
return { cohere };
}
catch (e) {
throw new Error("Please install cohere-ai as a dependency with, e.g. `yarn add cohere-ai`");
}
}
}
exports.CohereEmbeddings = CohereEmbeddings;