# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details. from __future__ import annotations from typing import List, Union, Mapping, cast from typing_extensions import Literal import httpx from ..._types import NOT_GIVEN, Body, Query, Headers, NotGiven, FileTypes from ..._utils import ( extract_files, maybe_transform, deepcopy_minimal, 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 transcription_create_params from ..._base_client import make_request_options from ...types.audio.transcription import Transcription __all__ = ["Transcriptions", "AsyncTranscriptions"] class Transcriptions(SyncAPIResource): @cached_property def with_raw_response(self) -> TranscriptionsWithRawResponse: """ 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 TranscriptionsWithRawResponse(self) @cached_property def with_streaming_response(self) -> TranscriptionsWithStreamingResponse: """ 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 TranscriptionsWithStreamingResponse(self) def create( self, *, model: Union[str, Literal["whisper-large-v3"]], file: FileTypes | NotGiven = NOT_GIVEN, language: Union[ str, Literal[ "en", "zh", "de", "es", "ru", "ko", "fr", "ja", "pt", "tr", "pl", "ca", "nl", "ar", "sv", "it", "id", "hi", "fi", "vi", "he", "uk", "el", "ms", "cs", "ro", "da", "hu", "ta", "no", "th", "ur", "hr", "bg", "lt", "la", "mi", "ml", "cy", "sk", "te", "fa", "lv", "bn", "sr", "az", "sl", "kn", "et", "mk", "br", "eu", "is", "hy", "ne", "mn", "bs", "kk", "sq", "sw", "gl", "mr", "pa", "si", "km", "sn", "yo", "so", "af", "oc", "ka", "be", "tg", "sd", "gu", "am", "yi", "lo", "uz", "fo", "ht", "ps", "tk", "nn", "mt", "sa", "lb", "my", "bo", "tl", "mg", "as", "tt", "haw", "ln", "ha", "ba", "jv", "su", "yue", ], ] | NotGiven = NOT_GIVEN, prompt: str | NotGiven = NOT_GIVEN, response_format: Literal["json", "text", "verbose_json"] | NotGiven = NOT_GIVEN, temperature: float | NotGiven = NOT_GIVEN, timestamp_granularities: List[Literal["word", "segment"]] | NotGiven = NOT_GIVEN, url: 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, ) -> Transcription: """ Transcribes audio into the input language. Args: model: ID of the model to use. Only `whisper-large-v3` is currently available. file: The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm. Either a file or a URL must be provided. Note that the file field is not supported in Batch API requests. language: The language of the input audio. Supplying the input language in [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) format will improve accuracy and latency. prompt: An optional text to guide the model's style or continue a previous audio segment. The [prompt](/docs/speech-text) should match the audio language. 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. timestamp_granularities: The timestamp granularities to populate for this transcription. `response_format` must be set `verbose_json` to use timestamp granularities. Either or both of these options are supported: `word`, or `segment`. Note: There is no additional latency for segment timestamps, but generating word timestamps incurs additional latency. url: The audio URL to translate/transcribe (supports Base64URL). Either a file or a URL must be provided. For Batch API requests, the URL field is required since the file field is not 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_minimal( { "model": model, "file": file, "language": language, "prompt": prompt, "response_format": response_format, "temperature": temperature, "timestamp_granularities": timestamp_granularities, "url": url, } ) 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/transcriptions", body=maybe_transform(body, transcription_create_params.TranscriptionCreateParams), files=files, options=make_request_options( extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout ), cast_to=Transcription, ) class AsyncTranscriptions(AsyncAPIResource): @cached_property def with_raw_response(self) -> AsyncTranscriptionsWithRawResponse: """ 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 AsyncTranscriptionsWithRawResponse(self) @cached_property def with_streaming_response(self) -> AsyncTranscriptionsWithStreamingResponse: """ 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 AsyncTranscriptionsWithStreamingResponse(self) async def create( self, *, model: Union[str, Literal["whisper-large-v3"]], file: FileTypes | NotGiven = NOT_GIVEN, language: Union[ str, Literal[ "en", "zh", "de", "es", "ru", "ko", "fr", "ja", "pt", "tr", "pl", "ca", "nl", "ar", "sv", "it", "id", "hi", "fi", "vi", "he", "uk", "el", "ms", "cs", "ro", "da", "hu", "ta", "no", "th", "ur", "hr", "bg", "lt", "la", "mi", "ml", "cy", "sk", "te", "fa", "lv", "bn", "sr", "az", "sl", "kn", "et", "mk", "br", "eu", "is", "hy", "ne", "mn", "bs", "kk", "sq", "sw", "gl", "mr", "pa", "si", "km", "sn", "yo", "so", "af", "oc", "ka", "be", "tg", "sd", "gu", "am", "yi", "lo", "uz", "fo", "ht", "ps", "tk", "nn", "mt", "sa", "lb", "my", "bo", "tl", "mg", "as", "tt", "haw", "ln", "ha", "ba", "jv", "su", "yue", ], ] | NotGiven = NOT_GIVEN, prompt: str | NotGiven = NOT_GIVEN, response_format: Literal["json", "text", "verbose_json"] | NotGiven = NOT_GIVEN, temperature: float | NotGiven = NOT_GIVEN, timestamp_granularities: List[Literal["word", "segment"]] | NotGiven = NOT_GIVEN, url: 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, ) -> Transcription: """ Transcribes audio into the input language. Args: model: ID of the model to use. Only `whisper-large-v3` is currently available. file: The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm. Either a file or a URL must be provided. Note that the file field is not supported in Batch API requests. language: The language of the input audio. Supplying the input language in [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) format will improve accuracy and latency. prompt: An optional text to guide the model's style or continue a previous audio segment. The [prompt](/docs/speech-text) should match the audio language. 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. timestamp_granularities: The timestamp granularities to populate for this transcription. `response_format` must be set `verbose_json` to use timestamp granularities. Either or both of these options are supported: `word`, or `segment`. Note: There is no additional latency for segment timestamps, but generating word timestamps incurs additional latency. url: The audio URL to translate/transcribe (supports Base64URL). Either a file or a URL must be provided. For Batch API requests, the URL field is required since the file field is not 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_minimal( { "model": model, "file": file, "language": language, "prompt": prompt, "response_format": response_format, "temperature": temperature, "timestamp_granularities": timestamp_granularities, "url": url, } ) 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/transcriptions", body=await async_maybe_transform(body, transcription_create_params.TranscriptionCreateParams), files=files, options=make_request_options( extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout ), cast_to=Transcription, ) class TranscriptionsWithRawResponse: def __init__(self, transcriptions: Transcriptions) -> None: self._transcriptions = transcriptions self.create = to_raw_response_wrapper( transcriptions.create, ) class AsyncTranscriptionsWithRawResponse: def __init__(self, transcriptions: AsyncTranscriptions) -> None: self._transcriptions = transcriptions self.create = async_to_raw_response_wrapper( transcriptions.create, ) class TranscriptionsWithStreamingResponse: def __init__(self, transcriptions: Transcriptions) -> None: self._transcriptions = transcriptions self.create = to_streamed_response_wrapper( transcriptions.create, ) class AsyncTranscriptionsWithStreamingResponse: def __init__(self, transcriptions: AsyncTranscriptions) -> None: self._transcriptions = transcriptions self.create = async_to_streamed_response_wrapper( transcriptions.create, )