> ## Documentation Index
> Fetch the complete documentation index at: https://docs.trychroma.com/llms.txt
> Use this file to discover all available pages before exploring further.

# OpenAI

export const Callout = ({title, children}) => <div className="my-6">
    <div className="relative pr-1.5 pb-1.5">
      <div className="absolute top-1.5 left-1.5 right-0 bottom-0 bg-blue-500 dark:bg-blue-600" />
      <div className="relative border border-black dark:border-gray-500 px-5 py-4 bg-white dark:bg-neutral-900">
        {title && <p className="block mb-2"><strong>{title}</strong></p>}
        {children}
      </div>
    </div>
  </div>;

Chroma provides a convenient wrapper around OpenAI's embedding API. This embedding function runs remotely on OpenAI's servers, and requires an API key. You can get an API key by signing up for an account at [OpenAI](https://openai.com/api/).

The following OpenAI Embedding Models are supported:

* `text-embedding-ada-002`
* `text-embedding-3-small`
* `text-embedding-3-large`

<Callout>
  Visit OpenAI Embeddings [documentation](https://platform.openai.com/docs/guides/embeddings) for more information.
</Callout>

<Tabs>
  <Tab title="Python" icon="python">
    This embedding function relies on the `openai` python package, which you can install with `pip install openai`.

    You can pass in an optional `model_name` argument, which lets you choose which OpenAI embeddings model to use. By default, Chroma uses `text-embedding-ada-002`.

    ```python theme={null}
    import chromadb.utils.embedding_functions as embedding_functions
    openai_ef = embedding_functions.OpenAIEmbeddingFunction(
        api_key_env_var="OPENAI_API_KEY",
        model_name="text-embedding-3-small"
    )
    ```

    To use the OpenAI embedding models on other platforms such as Azure, you can use the `api_base` and `api_type` parameters:

    ```python theme={null}
    import chromadb.utils.embedding_functions as embedding_functions
    openai_ef = embedding_functions.OpenAIEmbeddingFunction(
        api_key_env_var="OPENAI_API_KEY",
        api_base="YOUR_API_BASE_PATH",
        api_type="azure",
        api_version="YOUR_API_VERSION",
        model_name="text-embedding-3-small"
    )
    ```
  </Tab>

  <Tab title="TypeScript" icon="js">
    You can pass in an optional `model` argument, which lets you choose which OpenAI embeddings model to use. By default, Chroma uses `text-embedding-3-small`.

    ```typescript theme={null}
    // npm install @chroma-core/openai

    import { OpenAIEmbeddingFunction } from "@chroma-core/openai";

    const embeddingFunction = new OpenAIEmbeddingFunction({
        apiKeyEnvVar: "OPENAI_API_KEY",
        modelName: "text-embedding-3-small",
        // Optional: specify API base (e.g. for Azure OpenAI)
        apiBase: "your-api-base"
    });

    // use directly
    const embeddings = embeddingFunction.generate(["document1", "document2"]);

    // pass documents to query for .add and .query
    let collection = await client.createCollection({
        name: "name",
        embeddingFunction: embeddingFunction,
    });
    collection = await client.getCollection({
        name: "name",
        embeddingFunction: embeddingFunction,
    });
    ```
  </Tab>
</Tabs>