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

277 lines
11 KiB
JavaScript

import { OpenAI as OpenAIClient } from "openai";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { Embeddings } from "@langchain/core/embeddings";
import { chunkArray } from "@langchain/core/utils/chunk_array";
import { getEndpoint } from "./utils/azure.js";
import { wrapOpenAIClientError } from "./utils/openai.js";
/**
* Class for generating embeddings using the OpenAI API. Extends the
* Embeddings class and implements OpenAIEmbeddingsParams and
* AzureOpenAIInput.
* @example
* ```typescript
* // Embed a query using OpenAIEmbeddings to generate embeddings for a given text
* const model = new OpenAIEmbeddings();
* const res = await model.embedQuery(
* "What would be a good company name for a company that makes colorful socks?",
* );
* console.log({ res });
*
* ```
*/
export class OpenAIEmbeddings extends Embeddings {
constructor(fields, configuration) {
const fieldsWithDefaults = { maxConcurrency: 2, ...fields };
super(fieldsWithDefaults);
Object.defineProperty(this, "modelName", {
enumerable: true,
configurable: true,
writable: true,
value: "text-embedding-ada-002"
});
Object.defineProperty(this, "model", {
enumerable: true,
configurable: true,
writable: true,
value: "text-embedding-ada-002"
});
Object.defineProperty(this, "batchSize", {
enumerable: true,
configurable: true,
writable: true,
value: 512
});
// TODO: Update to `false` on next minor release (see: https://github.com/langchain-ai/langchainjs/pull/3612)
Object.defineProperty(this, "stripNewLines", {
enumerable: true,
configurable: true,
writable: true,
value: true
});
/**
* The number of dimensions the resulting output embeddings should have.
* Only supported in `text-embedding-3` and later models.
*/
Object.defineProperty(this, "dimensions", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "timeout", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "azureOpenAIApiVersion", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "azureOpenAIApiKey", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "azureADTokenProvider", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "azureOpenAIApiInstanceName", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "azureOpenAIApiDeploymentName", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "azureOpenAIBasePath", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "organization", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "client", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "clientConfig", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
let apiKey = fieldsWithDefaults?.apiKey ??
fieldsWithDefaults?.openAIApiKey ??
getEnvironmentVariable("OPENAI_API_KEY");
const azureApiKey = fieldsWithDefaults?.azureOpenAIApiKey ??
getEnvironmentVariable("AZURE_OPENAI_API_KEY");
this.azureADTokenProvider = fields?.azureADTokenProvider ?? undefined;
if (!azureApiKey && !apiKey && !this.azureADTokenProvider) {
throw new Error("OpenAI or Azure OpenAI API key or Token Provider not found");
}
const azureApiInstanceName = fieldsWithDefaults?.azureOpenAIApiInstanceName ??
getEnvironmentVariable("AZURE_OPENAI_API_INSTANCE_NAME");
const azureApiDeploymentName = (fieldsWithDefaults?.azureOpenAIApiEmbeddingsDeploymentName ||
fieldsWithDefaults?.azureOpenAIApiDeploymentName) ??
(getEnvironmentVariable("AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME") ||
getEnvironmentVariable("AZURE_OPENAI_API_DEPLOYMENT_NAME"));
const azureApiVersion = fieldsWithDefaults?.azureOpenAIApiVersion ??
getEnvironmentVariable("AZURE_OPENAI_API_VERSION");
this.azureOpenAIBasePath =
fieldsWithDefaults?.azureOpenAIBasePath ??
getEnvironmentVariable("AZURE_OPENAI_BASE_PATH");
this.organization =
fieldsWithDefaults?.configuration?.organization ??
getEnvironmentVariable("OPENAI_ORGANIZATION");
this.modelName =
fieldsWithDefaults?.model ?? fieldsWithDefaults?.modelName ?? this.model;
this.model = this.modelName;
this.batchSize =
fieldsWithDefaults?.batchSize ?? (azureApiKey ? 1 : this.batchSize);
this.stripNewLines =
fieldsWithDefaults?.stripNewLines ?? this.stripNewLines;
this.timeout = fieldsWithDefaults?.timeout;
this.dimensions = fieldsWithDefaults?.dimensions;
this.azureOpenAIApiVersion = azureApiVersion;
this.azureOpenAIApiKey = azureApiKey;
this.azureOpenAIApiInstanceName = azureApiInstanceName;
this.azureOpenAIApiDeploymentName = azureApiDeploymentName;
if (this.azureOpenAIApiKey || this.azureADTokenProvider) {
if (!this.azureOpenAIApiInstanceName && !this.azureOpenAIBasePath) {
throw new Error("Azure OpenAI API instance name not found");
}
if (!this.azureOpenAIApiDeploymentName) {
throw new Error("Azure OpenAI API deployment name not found");
}
if (!this.azureOpenAIApiVersion) {
throw new Error("Azure OpenAI API version not found");
}
apiKey = apiKey ?? "";
}
this.clientConfig = {
apiKey,
organization: this.organization,
baseURL: configuration?.basePath,
dangerouslyAllowBrowser: true,
defaultHeaders: configuration?.baseOptions?.headers,
defaultQuery: configuration?.baseOptions?.params,
...configuration,
...fields?.configuration,
};
}
/**
* Method to generate embeddings for an array of documents. Splits the
* documents into batches and makes requests to the OpenAI 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 batches = chunkArray(this.stripNewLines ? texts.map((t) => t.replace(/\n/g, " ")) : texts, this.batchSize);
const batchRequests = batches.map((batch) => {
const params = {
model: this.model,
input: batch,
};
if (this.dimensions) {
params.dimensions = this.dimensions;
}
return this.embeddingWithRetry(params);
});
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
* embeddingWithRetry 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 params = {
model: this.model,
input: this.stripNewLines ? text.replace(/\n/g, " ") : text,
};
if (this.dimensions) {
params.dimensions = this.dimensions;
}
const { data } = await this.embeddingWithRetry(params);
return data[0].embedding;
}
/**
* Private method to make a request to the OpenAI API to generate
* embeddings. Handles the retry logic and returns the response from the
* API.
* @param request Request to send to the OpenAI API.
* @returns Promise that resolves to the response from the API.
*/
async embeddingWithRetry(request) {
if (!this.client) {
const openAIEndpointConfig = {
azureOpenAIApiDeploymentName: this.azureOpenAIApiDeploymentName,
azureOpenAIApiInstanceName: this.azureOpenAIApiInstanceName,
azureOpenAIApiKey: this.azureOpenAIApiKey,
azureOpenAIBasePath: this.azureOpenAIBasePath,
baseURL: this.clientConfig.baseURL,
};
const endpoint = getEndpoint(openAIEndpointConfig);
const params = {
...this.clientConfig,
baseURL: endpoint,
timeout: this.timeout,
maxRetries: 0,
};
if (!params.baseURL) {
delete params.baseURL;
}
this.client = new OpenAIClient(params);
}
const requestOptions = {};
if (this.azureOpenAIApiKey) {
requestOptions.headers = {
"api-key": this.azureOpenAIApiKey,
...requestOptions.headers,
};
requestOptions.query = {
"api-version": this.azureOpenAIApiVersion,
...requestOptions.query,
};
}
return this.caller.call(async () => {
try {
const res = await this.client.embeddings.create(request, requestOptions);
return res;
}
catch (e) {
const error = wrapOpenAIClientError(e);
throw error;
}
});
}
}