@langchain/openai
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OpenAI integrations for LangChain.js
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{"version":3,"file":"embeddings.cjs","names":["Embeddings","fields?: Partial<OpenAIEmbeddingsParams> & {\n verbose?: boolean;\n /**\n * The OpenAI API key to use.\n * Alias for `apiKey`.\n */\n openAIApiKey?: OpenAIApiKey;\n /** The OpenAI API key to use. */\n apiKey?: OpenAIApiKey;\n configuration?: ClientOptions;\n }","texts: string[]","params: OpenAIClient.EmbeddingCreateParams","embeddings: TOutput[]","text: string","request: OpenAIClient.EmbeddingCreateParams","openAIEndpointConfig: OpenAIEndpointConfig","getEndpoint","getHeadersWithUserAgent","OpenAIClient","wrapOpenAIClientError"],"sources":["../src/embeddings.ts"],"sourcesContent":["import { type ClientOptions, OpenAI as OpenAIClient } from \"openai\";\nimport { getEnvironmentVariable } from \"@langchain/core/utils/env\";\nimport { Embeddings, type EmbeddingsParams } from \"@langchain/core/embeddings\";\nimport { chunkArray } from \"@langchain/core/utils/chunk_array\";\nimport type { OpenAIApiKey } from \"./types.js\";\nimport {\n getEndpoint,\n OpenAIEndpointConfig,\n getHeadersWithUserAgent,\n} from \"./utils/azure.js\";\nimport { wrapOpenAIClientError } from \"./utils/client.js\";\n\n/**\n * @see https://platform.openai.com/docs/guides/embeddings#embedding-models\n */\nexport type OpenAIEmbeddingModelId =\n | OpenAIClient.EmbeddingModel\n | (string & NonNullable<unknown>);\n\n/**\n * Interface for OpenAIEmbeddings parameters. Extends EmbeddingsParams and\n * defines additional parameters specific to the OpenAIEmbeddings class.\n */\nexport interface OpenAIEmbeddingsParams extends EmbeddingsParams {\n /**\n * Model name to use\n * Alias for `model`\n * @deprecated Use \"model\" instead.\n */\n modelName: OpenAIEmbeddingModelId;\n /** Model name to use */\n model: OpenAIEmbeddingModelId;\n\n /**\n * The number of dimensions the resulting output embeddings should have.\n * Only supported in `text-embedding-3` and later models.\n */\n dimensions?: number;\n\n /**\n * Timeout to use when making requests to OpenAI.\n */\n timeout?: number;\n\n /**\n * The maximum number of documents to embed in a single request. This is\n * limited by the OpenAI API to a maximum of 2048.\n */\n batchSize?: number;\n\n /**\n * Whether to strip new lines from the input text. This is recommended by\n * OpenAI for older models, but may not be suitable for all use cases.\n * See: https://github.com/openai/openai-python/issues/418#issuecomment-1525939500\n */\n stripNewLines?: boolean;\n\n /**\n * The format to return the embeddings in. Can be either 'float' or 'base64'.\n */\n encodingFormat?: \"float\" | \"base64\";\n}\n\n/**\n * Class for generating embeddings using the OpenAI API.\n *\n * To use with Azure, import the `AzureOpenAIEmbeddings` class.\n *\n * @example\n * ```typescript\n * // Embed a query using OpenAIEmbeddings to generate embeddings for a given text\n * const model = new OpenAIEmbeddings();\n * const res = await model.embedQuery(\n * \"What would be a good company name for a company that makes colorful socks?\",\n * );\n * console.log({ res });\n *\n * ```\n */\nexport class OpenAIEmbeddings<TOutput = number[]>\n extends Embeddings<TOutput>\n implements Partial<OpenAIEmbeddingsParams>\n{\n model = \"text-embedding-ada-002\";\n\n /** @deprecated Use \"model\" instead */\n modelName: string;\n\n batchSize = 512;\n\n // TODO: Update to `false` on next minor release (see: https://github.com/langchain-ai/langchainjs/pull/3612)\n stripNewLines = true;\n\n /**\n * The number of dimensions the resulting output embeddings should have.\n * Only supported in `text-embedding-3` and later models.\n */\n dimensions?: number;\n\n timeout?: number;\n\n organization?: string;\n\n encodingFormat?: \"float\" | \"base64\";\n\n protected client: OpenAIClient;\n\n protected clientConfig: ClientOptions;\n\n protected apiKey?: OpenAIApiKey;\n\n constructor(\n fields?: Partial<OpenAIEmbeddingsParams> & {\n verbose?: boolean;\n /**\n * The OpenAI API key to use.\n * Alias for `apiKey`.\n */\n openAIApiKey?: OpenAIApiKey;\n /** The OpenAI API key to use. */\n apiKey?: OpenAIApiKey;\n configuration?: ClientOptions;\n }\n ) {\n const fieldsWithDefaults = { maxConcurrency: 2, ...fields };\n\n super(fieldsWithDefaults);\n\n const apiKey =\n fieldsWithDefaults?.apiKey ??\n fieldsWithDefaults?.openAIApiKey ??\n getEnvironmentVariable(\"OPENAI_API_KEY\");\n\n this.organization =\n fieldsWithDefaults?.configuration?.organization ??\n getEnvironmentVariable(\"OPENAI_ORGANIZATION\");\n\n this.model =\n fieldsWithDefaults?.model ?? fieldsWithDefaults?.modelName ?? this.model;\n this.modelName = this.model;\n this.batchSize = fieldsWithDefaults?.batchSize ?? this.batchSize;\n this.stripNewLines =\n fieldsWithDefaults?.stripNewLines ?? this.stripNewLines;\n this.timeout = fieldsWithDefaults?.timeout;\n this.dimensions = fieldsWithDefaults?.dimensions;\n this.encodingFormat = fieldsWithDefaults?.encodingFormat;\n\n this.clientConfig = {\n apiKey,\n organization: this.organization,\n dangerouslyAllowBrowser: true,\n ...fields?.configuration,\n };\n }\n\n /**\n * Method to generate embeddings for an array of documents. Splits the\n * documents into batches and makes requests to the OpenAI API to generate\n * embeddings.\n * @param texts Array of documents to generate embeddings for.\n * @returns Promise that resolves to a 2D array of embeddings for each document.\n */\n async embedDocuments(texts: string[]): Promise<TOutput[]> {\n const batches = chunkArray(\n this.stripNewLines ? texts.map((t) => t.replace(/\\n/g, \" \")) : texts,\n this.batchSize\n );\n\n const batchRequests = batches.map((batch) => {\n const params: OpenAIClient.EmbeddingCreateParams = {\n model: this.model,\n input: batch,\n };\n if (this.dimensions) {\n params.dimensions = this.dimensions;\n }\n if (this.encodingFormat) {\n params.encoding_format = this.encodingFormat;\n }\n return this.embeddingWithRetry(params);\n });\n const batchResponses = await Promise.all(batchRequests);\n\n const embeddings: TOutput[] = [];\n for (let i = 0; i < batchResponses.length; i += 1) {\n const batch = batches[i];\n const { data: batchResponse } = batchResponses[i];\n for (let j = 0; j < batch.length; j += 1) {\n embeddings.push(batchResponse[j].embedding as TOutput);\n }\n }\n return embeddings;\n }\n\n /**\n * Method to generate an embedding for a single document. Calls the\n * embeddingWithRetry method with the document as the input.\n * @param text Document to generate an embedding for.\n * @returns Promise that resolves to an embedding for the document.\n */\n async embedQuery(text: string): Promise<TOutput> {\n const params: OpenAIClient.EmbeddingCreateParams = {\n model: this.model,\n input: this.stripNewLines ? text.replace(/\\n/g, \" \") : text,\n };\n if (this.dimensions) {\n params.dimensions = this.dimensions;\n }\n if (this.encodingFormat) {\n params.encoding_format = this.encodingFormat;\n }\n const { data } = await this.embeddingWithRetry(params);\n return data[0].embedding as TOutput;\n }\n\n /**\n * Private method to make a request to the OpenAI API to generate\n * embeddings. Handles the retry logic and returns the response from the\n * API.\n * @param request Request to send to the OpenAI API.\n * @returns Promise that resolves to the response from the API.\n */\n protected async embeddingWithRetry(\n request: OpenAIClient.EmbeddingCreateParams\n ) {\n if (!this.client) {\n const openAIEndpointConfig: OpenAIEndpointConfig = {\n baseURL: this.clientConfig.baseURL,\n };\n\n const endpoint = getEndpoint(openAIEndpointConfig);\n\n const params = {\n ...this.clientConfig,\n baseURL: endpoint,\n timeout: this.timeout,\n maxRetries: 0,\n };\n\n if (!params.baseURL) {\n delete params.baseURL;\n }\n\n params.defaultHeaders = getHeadersWithUserAgent(params.defaultHeaders);\n\n this.client = new OpenAIClient(params);\n }\n const requestOptions = {};\n\n return this.caller.call(async () => {\n try {\n const res = await this.client.embeddings.create(\n request,\n requestOptions\n );\n return res;\n } catch (e) {\n const error = wrapOpenAIClientError(e);\n throw error;\n }\n });\n }\n}\n"],"mappings":";;;;;;;;;;;;;;;;;;;;;;;;;AA+EA,IAAa,mBAAb,cACUA,uCAEV;CACE,QAAQ;;CAGR;CAEA,YAAY;CAGZ,gBAAgB;;;;;CAMhB;CAEA;CAEA;CAEA;CAEA,AAAU;CAEV,AAAU;CAEV,AAAU;CAEV,YACEC,QAWA;EACA,MAAM,qBAAqB;GAAE,gBAAgB;GAAG,GAAG;EAAQ;EAE3D,MAAM,mBAAmB;EAEzB,MAAM,SACJ,oBAAoB,UACpB,oBAAoB,uEACG,iBAAiB;EAE1C,KAAK,eACH,oBAAoB,eAAe,uEACZ,sBAAsB;EAE/C,KAAK,QACH,oBAAoB,SAAS,oBAAoB,aAAa,KAAK;EACrE,KAAK,YAAY,KAAK;EACtB,KAAK,YAAY,oBAAoB,aAAa,KAAK;EACvD,KAAK,gBACH,oBAAoB,iBAAiB,KAAK;EAC5C,KAAK,UAAU,oBAAoB;EACnC,KAAK,aAAa,oBAAoB;EACtC,KAAK,iBAAiB,oBAAoB;EAE1C,KAAK,eAAe;GAClB;GACA,cAAc,KAAK;GACnB,yBAAyB;GACzB,GAAG,QAAQ;EACZ;CACF;;;;;;;;CASD,MAAM,eAAeC,OAAqC;EACxD,MAAM,6DACJ,KAAK,gBAAgB,MAAM,IAAI,CAAC,MAAM,EAAE,QAAQ,OAAO,IAAI,CAAC,GAAG,OAC/D,KAAK,UACN;EAED,MAAM,gBAAgB,QAAQ,IAAI,CAAC,UAAU;GAC3C,MAAMC,SAA6C;IACjD,OAAO,KAAK;IACZ,OAAO;GACR;AACD,OAAI,KAAK,YACP,OAAO,aAAa,KAAK;AAE3B,OAAI,KAAK,gBACP,OAAO,kBAAkB,KAAK;AAEhC,UAAO,KAAK,mBAAmB,OAAO;EACvC,EAAC;EACF,MAAM,iBAAiB,MAAM,QAAQ,IAAI,cAAc;EAEvD,MAAMC,aAAwB,CAAE;AAChC,OAAK,IAAI,IAAI,GAAG,IAAI,eAAe,QAAQ,KAAK,GAAG;GACjD,MAAM,QAAQ,QAAQ;GACtB,MAAM,EAAE,MAAM,eAAe,GAAG,eAAe;AAC/C,QAAK,IAAI,IAAI,GAAG,IAAI,MAAM,QAAQ,KAAK,GACrC,WAAW,KAAK,cAAc,GAAG,UAAqB;EAEzD;AACD,SAAO;CACR;;;;;;;CAQD,MAAM,WAAWC,MAAgC;EAC/C,MAAMF,SAA6C;GACjD,OAAO,KAAK;GACZ,OAAO,KAAK,gBAAgB,KAAK,QAAQ,OAAO,IAAI,GAAG;EACxD;AACD,MAAI,KAAK,YACP,OAAO,aAAa,KAAK;AAE3B,MAAI,KAAK,gBACP,OAAO,kBAAkB,KAAK;EAEhC,MAAM,EAAE,MAAM,GAAG,MAAM,KAAK,mBAAmB,OAAO;AACtD,SAAO,KAAK,GAAG;CAChB;;;;;;;;CASD,MAAgB,mBACdG,SACA;AACA,MAAI,CAAC,KAAK,QAAQ;GAChB,MAAMC,uBAA6C,EACjD,SAAS,KAAK,aAAa,QAC5B;GAED,MAAM,WAAWC,0BAAY,qBAAqB;GAElD,MAAM,SAAS;IACb,GAAG,KAAK;IACR,SAAS;IACT,SAAS,KAAK;IACd,YAAY;GACb;AAED,OAAI,CAAC,OAAO,SACV,OAAO,OAAO;GAGhB,OAAO,iBAAiBC,sCAAwB,OAAO,eAAe;GAEtE,KAAK,SAAS,IAAIC,cAAa;EAChC;EACD,MAAM,iBAAiB,CAAE;AAEzB,SAAO,KAAK,OAAO,KAAK,YAAY;AAClC,OAAI;IACF,MAAM,MAAM,MAAM,KAAK,OAAO,WAAW,OACvC,SACA,eACD;AACD,WAAO;GACR,SAAQ,GAAG;IACV,MAAM,QAAQC,qCAAsB,EAAE;AACtC,UAAM;GACP;EACF,EAAC;CACH;AACF"}