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

from __future__ import annotations

from typing import Union, Mapping, cast
from typing_extensions import Literal

import httpx

from ..._files import deepcopy_with_paths
from ..._types import Body, Omit, Query, Headers, NotGiven, FileTypes, omit, not_given
from ..._utils import extract_files, 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 ...types.audio import translation_create_params
from ..._base_client import make_request_options
from ...types.audio.translation import Translation

__all__ = ["Translations", "AsyncTranslations"]


class Translations(SyncAPIResource):
    @cached_property
    def with_raw_response(self) -> TranslationsWithRawResponse:
        """
        This property can be used as a prefix for any HTTP method call to return
        the raw response object instead of the parsed content.

        For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
        """
        return TranslationsWithRawResponse(self)

    @cached_property
    def with_streaming_response(self) -> TranslationsWithStreamingResponse:
        """
        An alternative to `.with_raw_response` that doesn't eagerly read the response body.

        For more information, see https://www.github.com/groq/groq-python#with_streaming_response
        """
        return TranslationsWithStreamingResponse(self)

    def create(
        self,
        *,
        model: Union[str, Literal["whisper-large-v3", "whisper-large-v3-turbo"]],
        file: FileTypes | Omit = omit,
        prompt: str | Omit = omit,
        response_format: Literal["json", "text", "verbose_json"] | Omit = omit,
        temperature: float | Omit = omit,
        url: str | Omit = omit,
        # 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,
    ) -> Translation:
        """Translates audio into English.

        Args:
          model: ID of the model to use.

        `whisper-large-v3` and `whisper-large-v3-turbo` are
              currently available.

          file: The audio file object (not file name) translate, in one of these formats: flac,
              mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.

          prompt: An optional text to guide the model's style or continue a previous audio
              segment. The [prompt](/docs/guides/speech-to-text/prompting) should be in
              English.

          response_format: The format of the transcript output, in one of these options: `json`, `text`, or
              `verbose_json`.

          temperature: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the
              output more random, while lower values like 0.2 will make it more focused and
              deterministic. If set to 0, the model will use
              [log probability](https://en.wikipedia.org/wiki/Log_probability) to
              automatically increase the temperature until certain thresholds are hit.

          url: The audio URL to translate/transcribe (supports Base64URL). Either file or url
              must be provided. When using the Batch API only url is supported.

          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
        """
        body = deepcopy_with_paths(
            {
                "model": model,
                "file": file,
                "prompt": prompt,
                "response_format": response_format,
                "temperature": temperature,
                "url": url,
            },
            [["file"]],
        )
        files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])
        # It should be noted that the actual Content-Type header that will be
        # sent to the server will contain a `boundary` parameter, e.g.
        # multipart/form-data; boundary=---abc--
        extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
        return self._post(
            "/openai/v1/audio/translations",
            body=maybe_transform(body, translation_create_params.TranslationCreateParams),
            files=files,
            options=make_request_options(
                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
            ),
            cast_to=Translation,
        )


class AsyncTranslations(AsyncAPIResource):
    @cached_property
    def with_raw_response(self) -> AsyncTranslationsWithRawResponse:
        """
        This property can be used as a prefix for any HTTP method call to return
        the raw response object instead of the parsed content.

        For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
        """
        return AsyncTranslationsWithRawResponse(self)

    @cached_property
    def with_streaming_response(self) -> AsyncTranslationsWithStreamingResponse:
        """
        An alternative to `.with_raw_response` that doesn't eagerly read the response body.

        For more information, see https://www.github.com/groq/groq-python#with_streaming_response
        """
        return AsyncTranslationsWithStreamingResponse(self)

    async def create(
        self,
        *,
        model: Union[str, Literal["whisper-large-v3", "whisper-large-v3-turbo"]],
        file: FileTypes | Omit = omit,
        prompt: str | Omit = omit,
        response_format: Literal["json", "text", "verbose_json"] | Omit = omit,
        temperature: float | Omit = omit,
        url: str | Omit = omit,
        # 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,
    ) -> Translation:
        """Translates audio into English.

        Args:
          model: ID of the model to use.

        `whisper-large-v3` and `whisper-large-v3-turbo` are
              currently available.

          file: The audio file object (not file name) translate, in one of these formats: flac,
              mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.

          prompt: An optional text to guide the model's style or continue a previous audio
              segment. The [prompt](/docs/guides/speech-to-text/prompting) should be in
              English.

          response_format: The format of the transcript output, in one of these options: `json`, `text`, or
              `verbose_json`.

          temperature: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the
              output more random, while lower values like 0.2 will make it more focused and
              deterministic. If set to 0, the model will use
              [log probability](https://en.wikipedia.org/wiki/Log_probability) to
              automatically increase the temperature until certain thresholds are hit.

          url: The audio URL to translate/transcribe (supports Base64URL). Either file or url
              must be provided. When using the Batch API only url is supported.

          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
        """
        body = deepcopy_with_paths(
            {
                "model": model,
                "file": file,
                "prompt": prompt,
                "response_format": response_format,
                "temperature": temperature,
                "url": url,
            },
            [["file"]],
        )
        files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])
        # It should be noted that the actual Content-Type header that will be
        # sent to the server will contain a `boundary` parameter, e.g.
        # multipart/form-data; boundary=---abc--
        extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
        return await self._post(
            "/openai/v1/audio/translations",
            body=await async_maybe_transform(body, translation_create_params.TranslationCreateParams),
            files=files,
            options=make_request_options(
                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
            ),
            cast_to=Translation,
        )


class TranslationsWithRawResponse:
    def __init__(self, translations: Translations) -> None:
        self._translations = translations

        self.create = to_raw_response_wrapper(
            translations.create,
        )


class AsyncTranslationsWithRawResponse:
    def __init__(self, translations: AsyncTranslations) -> None:
        self._translations = translations

        self.create = async_to_raw_response_wrapper(
            translations.create,
        )


class TranslationsWithStreamingResponse:
    def __init__(self, translations: Translations) -> None:
        self._translations = translations

        self.create = to_streamed_response_wrapper(
            translations.create,
        )


class AsyncTranslationsWithStreamingResponse:
    def __init__(self, translations: AsyncTranslations) -> None:
        self._translations = translations

        self.create = async_to_streamed_response_wrapper(
            translations.create,
        )
