> ## 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.

# Nomic

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 Nomic's embedding API. This embedding function runs remotely on Nomic's servers, and requires an API key. You can get an API key by signing up for an account at [Nomic](https://atlas.nomic.ai/).

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

    ```python theme={null}
    from chromadb.utils.embedding_functions import NomicEmbeddingFunction
    import os

    os.environ["NOMIC_API_KEY"] = "YOUR_API_KEY"
    nomic_ef = NomicEmbeddingFunction(
        model="nomic-embed-text-v1",
        task_type="search_document",
        query_config={"task_type": "search_query"}
    )

    texts = ["Hello, world!", "How are you?"]
    embeddings = nomic_ef(texts)
    ```

    You must pass in a `model` argument and `task_type` argument. The `task_type` can be one of:

    * `search_document`: Used to encode large documents in retrieval tasks at indexing time
    * `search_query`: Used to encode user queries or questions in retrieval tasks
    * `classification`: Used to encode text for text classification tasks
    * `clustering`: Used for clustering or reranking tasks

    The `query_config` parameter allows you to specify a different task type for queries, which is useful when you want to use `search_document` for documents and `search_query` for queries.
  </Tab>
</Tabs>

<Callout>
  Visit Nomic [documentation](https://docs.nomic.ai/platform/embeddings-and-retrieval/text-embedding) for more information on available models and task types.
</Callout>