def get_embeddings()

in services/openai.py [0:0]

• 9 lines of code
• 3 McCabe index (conditional complexity)

def get_embeddings(texts: List[str]) -> List[List[float]]:
    """
    Embed texts using OpenAI's ada model.

    Args:
        texts: The list of texts to embed.

    Returns:
        A list of embeddings, each of which is a list of floats.

    Raises:
        Exception: If the OpenAI API call fails.
    """
    # Call the OpenAI API to get the embeddings
    # NOTE: Azure Open AI requires deployment id
    deployment = os.environ.get("OPENAI_EMBEDDINGMODEL_DEPLOYMENTID")

    response = {}
    if deployment is None:
        response = openai.Embedding.create(input=texts, model=EMBEDDING_MODEL, dimensions=EMBEDDING_DIMENSION)
    else:
        response = openai.Embedding.create(input=texts, deployment_id=deployment)

    # Extract the embedding data from the response
    data = response["data"]  # type: ignore

    # Return the embeddings as a list of lists of floats
    return [result["embedding"] for result in data]