OpenAiEmbeddingClient

db-ally provides an OpenAIEmbeddingClient class that can be used to create text embeddings using the OpenAI API.

dbally.embedding_client.OpenAiEmbeddingClient

OpenAiEmbeddingClient(api_key: str, model: str = 'text-embedding-3-small', openai_options: Optional[Dict] = None)

Bases: EmbeddingClient

Client for creating text embeddings using OpenAI API.

Initializes the OpenAiEmbeddingClient.

PARAMETER	DESCRIPTION
api_key	The OpenAI API key. TYPE: str
model	The model to use for embeddings. TYPE: str DEFAULT: 'text-embedding-3-small'
openai_options	Additional options to pass to the OpenAI API. TYPE: Optional[Dict] DEFAULT: None

Source code in src/dbally/embedding_client/openai.py

def __init__(self, api_key: str, model: str = "text-embedding-3-small", openai_options: Optional[Dict] = None):
    """
    Initializes the OpenAiEmbeddingClient.

    Args:
        api_key: The OpenAI API key.
        model: The model to use for embeddings.
        openai_options: Additional options to pass to the OpenAI API.
    """
    super().__init__()
    self.api_key = api_key
    self.model = model
    self.openai_options = openai_options

    try:
        from openai import AsyncOpenAI  # pylint: disable=import-outside-toplevel
    except ImportError as exc:
        raise ImportError("You need to install openai package to use GPT models") from exc

    self._openai = AsyncOpenAI(api_key=self.api_key)

api_key instance-attribute

api_key = api_key

model instance-attribute

model = model

openai_options instance-attribute

openai_options = openai_options

get_embeddings async

get_embeddings(data: List[str]) -> List[List[float]]

For a given list of strings returns a list of embeddings.

PARAMETER	DESCRIPTION
data	List of strings to get embeddings for. TYPE: List[str]

RETURNS	DESCRIPTION
List[List[float]]	List of embeddings for the given strings.

Source code in src/dbally/embedding_client/openai.py

async def get_embeddings(self, data: List[str]) -> List[List[float]]:
    """
    For a given list of strings returns a list of embeddings.

    Args:
        data: List of strings to get embeddings for.

    Returns:
        List of embeddings for the given strings.
    """
    kwargs: Dict[str, Any] = {
        "model": self.model,
    }
    if self.openai_options:
        kwargs.update(self.openai_options)

    response = await self._openai.embeddings.create(
        input=data,
        **kwargs,
    )
    return [embedding.embedding for embedding in response.data]