# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.

from __future__ import annotations

from typing_extensions import Literal, Required, TypedDict

__all__ = ["EmbeddingConfigBaseParam"]


class EmbeddingConfigBaseParam(TypedDict, total=False):
    embedding_model: Required[
        Literal[
            "sentence-transformers/all-MiniLM-L12-v2",
            "sentence-transformers/all-mpnet-base-v2",
            "sentence-transformers/multi-qa-distilbert-cos-v1",
            "sentence-transformers/paraphrase-multilingual-mpnet-base-v2",
            "openai/text-embedding-ada-002",
            "openai/text-embedding-3-small",
            "openai/text-embedding-3-large",
            "embed-english-v3.0",
            "embed-english-light-v3.0",
            "embed-multilingual-v3.0",
            "gemini/text-embedding-005",
            "gemini/text-multilingual-embedding-002",
            "gemini/gemini-embedding-001",
        ]
    ]
    """The name of the base embedding model to use.

    To use custom models, change to type 'models'.
    """

    type: Literal["base"]
    """The type of the embedding configuration."""
