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            *   [Dealing with rate limits](/v0.1/docs/modules/data_connection/text_embedding/rate_limits/)
            *   [Adding a timeout](/v0.1/docs/modules/data_connection/text_embedding/timeouts/)
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*   [Retrieval](/v0.1/docs/modules/data_connection/)
*   [Text embedding models](/v0.1/docs/modules/data_connection/text_embedding/)
*   Adding a timeout

Adding a timeout
================

By default, LangChain will wait indefinitely for a response from the model provider. If you want to add a timeout, you can pass a `timeout` option, in milliseconds, when you instantiate the model. For example, for OpenAI:

tip

See [this section for general instructions on installing integration packages](/v0.1/docs/get_started/installation/#installing-integration-packages).

*   npm
*   Yarn
*   pnpm

    npm install @langchain/openai

    yarn add @langchain/openai

    pnpm add @langchain/openai

    import { OpenAIEmbeddings } from "@langchain/openai";const embeddings = new OpenAIEmbeddings({  timeout: 1000, // 1s timeout});/* Embed queries */const res = await embeddings.embedQuery("Hello world");console.log(res);/* Embed documents */const documentRes = await embeddings.embedDocuments(["Hello world", "Bye bye"]);console.log({ documentRes });

#### API Reference:

*   [OpenAIEmbeddings](https://api.js.langchain.com/classes/langchain_openai.OpenAIEmbeddings.html) from `@langchain/openai`

Currently, the timeout option is only supported for OpenAI models.

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