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

from __future__ import annotations

from typing import List, Union, Optional
from typing_extensions import Literal

import httpx

from ..types import embedding_create_params
from .._types import NOT_GIVEN, Body, Query, Headers, NotGiven
from .._utils import (
    maybe_transform,
    async_maybe_transform,
)
from .._compat import cached_property
from .._resource import SyncAPIResource, AsyncAPIResource
from .._response import (
    to_raw_response_wrapper,
    to_streamed_response_wrapper,
    async_to_raw_response_wrapper,
    async_to_streamed_response_wrapper,
)
from .._base_client import (
    make_request_options,
)
from ..types.create_embedding_response import CreateEmbeddingResponse

__all__ = ["Embeddings", "AsyncEmbeddings"]


class Embeddings(SyncAPIResource):
    @cached_property
    def with_raw_response(self) -> EmbeddingsWithRawResponse:
        return EmbeddingsWithRawResponse(self)

    @cached_property
    def with_streaming_response(self) -> EmbeddingsWithStreamingResponse:
        return EmbeddingsWithStreamingResponse(self)

    def create(
        self,
        *,
        input: Union[str, List[str]],
        model: Union[str, Literal["nomic-embed-text-v1_5"]],
        encoding_format: Literal["float", "base64"] | NotGiven = NOT_GIVEN,
        user: Optional[str] | NotGiven = NOT_GIVEN,
        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
        # The extra values given here take precedence over values defined on the client or passed to this method.
        extra_headers: Headers | None = None,
        extra_query: Query | None = None,
        extra_body: Body | None = None,
        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
    ) -> CreateEmbeddingResponse:
        """
        Creates an embedding vector representing the input text.

        Args:
          input: 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, cannot be an empty
              string, and any array must be 2048 dimensions or less.

          model: ID of the model to use.

          encoding_format: The format to return the embeddings in. Can only be `float` or `base64`.

          user: A unique identifier representing your end-user, which can help us monitor and
              detect abuse.

          extra_headers: Send extra headers

          extra_query: Add additional query parameters to the request

          extra_body: Add additional JSON properties to the request

          timeout: Override the client-level default timeout for this request, in seconds
        """
        return self._post(
            "/openai/v1/embeddings",
            body=maybe_transform(
                {
                    "input": input,
                    "model": model,
                    "encoding_format": encoding_format,
                    "user": user,
                },
                embedding_create_params.EmbeddingCreateParams,
            ),
            options=make_request_options(
                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
            ),
            cast_to=CreateEmbeddingResponse,
        )


class AsyncEmbeddings(AsyncAPIResource):
    @cached_property
    def with_raw_response(self) -> AsyncEmbeddingsWithRawResponse:
        return AsyncEmbeddingsWithRawResponse(self)

    @cached_property
    def with_streaming_response(self) -> AsyncEmbeddingsWithStreamingResponse:
        return AsyncEmbeddingsWithStreamingResponse(self)

    async def create(
        self,
        *,
        input: Union[str, List[str]],
        model: Union[str, Literal["nomic-embed-text-v1_5"]],
        encoding_format: Literal["float", "base64"] | NotGiven = NOT_GIVEN,
        user: Optional[str] | NotGiven = NOT_GIVEN,
        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
        # The extra values given here take precedence over values defined on the client or passed to this method.
        extra_headers: Headers | None = None,
        extra_query: Query | None = None,
        extra_body: Body | None = None,
        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
    ) -> CreateEmbeddingResponse:
        """
        Creates an embedding vector representing the input text.

        Args:
          input: 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, cannot be an empty
              string, and any array must be 2048 dimensions or less.

          model: ID of the model to use.

          encoding_format: The format to return the embeddings in. Can only be `float` or `base64`.

          user: A unique identifier representing your end-user, which can help us monitor and
              detect abuse.

          extra_headers: Send extra headers

          extra_query: Add additional query parameters to the request

          extra_body: Add additional JSON properties to the request

          timeout: Override the client-level default timeout for this request, in seconds
        """
        return await self._post(
            "/openai/v1/embeddings",
            body=await async_maybe_transform(
                {
                    "input": input,
                    "model": model,
                    "encoding_format": encoding_format,
                    "user": user,
                },
                embedding_create_params.EmbeddingCreateParams,
            ),
            options=make_request_options(
                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
            ),
            cast_to=CreateEmbeddingResponse,
        )


class EmbeddingsWithRawResponse:
    def __init__(self, embeddings: Embeddings) -> None:
        self._embeddings = embeddings

        self.create = to_raw_response_wrapper(
            embeddings.create,
        )


class AsyncEmbeddingsWithRawResponse:
    def __init__(self, embeddings: AsyncEmbeddings) -> None:
        self._embeddings = embeddings

        self.create = async_to_raw_response_wrapper(
            embeddings.create,
        )


class EmbeddingsWithStreamingResponse:
    def __init__(self, embeddings: Embeddings) -> None:
        self._embeddings = embeddings

        self.create = to_streamed_response_wrapper(
            embeddings.create,
        )


class AsyncEmbeddingsWithStreamingResponse:
    def __init__(self, embeddings: AsyncEmbeddings) -> None:
        self._embeddings = embeddings

        self.create = async_to_streamed_response_wrapper(
            embeddings.create,
        )
