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OpenAI

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.

ModelsInputDimensionalityContext Size
ada-002English15362048

Basic Usage​

Python​

pip install openai

from chromadb.utils import embedding_functions

embedder = embedding_functions.OpenAIEmbeddingFunction(
        api_key="YOUR_API_KEY")

collection = client.create_collection(
        name="oai_ef", 
        embedding_function=embedder)

Javascript​

yarn add openai
import { ChromaClient, OpenAIEmbeddingFunction } from 'chromadb'

const embedder = new OpenAIEmbeddingFunction({
    openai_api_key: "YOUR_API_KEY"
})

const collection = await client.createCollection({
    name: "oai_ef", 
    embeddingFunction: embedder
})

Advanced Usage​

Call directly​

By passing the embedding function to a Collection, Chroma handles the embedding of documents and queries for you. However in some cases you may want to generate the embeddings outside and handle them yourself.

Python​

embeddings = embedder(["document1","document2"])
# [[0.04565250128507614, 0.01611952856183052...], [0.030171213671565056, 0.007690359838306904...]]

Javascript​

const embeddings = embedder.generate(["document1","document2"])
// [[0.04565250128507614, 0.01611952856183052...], [0.030171213671565056, 0.007690359838306904...]]

Using a different model​

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. You can see a list of all available models here.

Run with Azure​

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

openai_ef = embedding_functions.OpenAIEmbeddingFunction(
                api_key="YOUR_API_KEY",
                api_base="YOUR_API_BASE_PATH",
                api_type="azure",
                api_version="YOUR_API_VERSION",
                model_name="text-embedding-ada-002"
            )