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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from typing import List, Union, Iterable
from typing_extensions import Literal, Required, TypedDict
__all__ = ["EmbeddingCreateParams"]
class EmbeddingCreateParams(TypedDict, total=False):
input: Required[Union[str, List[str], Iterable[int], Iterable[Iterable[int]]]]
"""Input text to embed, encoded as a string or array of tokens.
To embed multiple inputs in a single request, pass an array of strings or array
of token arrays. The input must not exceed the max input tokens for the model
(8192 tokens for `text-embedding-ada-002`), cannot be an empty string, and any
array must be 2048 dimensions or less.
[Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken)
for counting tokens.
"""
model: Required[Union[str, Literal["text-embedding-ada-002", "text-embedding-3-small", "text-embedding-3-large"]]]
"""ID of the model to use.
You can use the
[List models](https://platform.openai.com/docs/api-reference/models/list) API to
see all of your available models, or see our
[Model overview](https://platform.openai.com/docs/models/overview) for
descriptions of them.
"""
dimensions: int
"""The number of dimensions the resulting output embeddings should have.
Only supported in `text-embedding-3` and later models.
"""
encoding_format: Literal["float", "base64"]
"""The format to return the embeddings in.
Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).
"""
user: str
"""
A unique identifier representing your end-user, which can help OpenAI to monitor
and detect abuse.
[Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids).
"""