chore(client): clean up custom translations code

Author: dtmeadows

src/openai/resources/audio/transcriptions.py

@@ -69,9 +69,10 @@ def create(
         model: Union[str, AudioModel],
         chunking_strategy: Optional[transcription_create_params.ChunkingStrategy] | Omit = omit,
         include: List[TranscriptionInclude] | Omit = omit,
-        response_format: Union[Literal["json"], Omit] = omit,
         language: str | Omit = omit,
         prompt: str | Omit = omit,
+        response_format: Union[Literal["json"], Omit] = omit,
+        stream: Optional[Literal[False]] | Omit = omit,
         temperature: float | Omit = omit,
         timestamp_granularities: List[Literal["word", "segment"]] | Omit = omit,
         # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
@@ -80,7 +81,68 @@ def create(
         extra_query: Query | None = None,
         extra_body: Body | None = None,
         timeout: float | httpx.Timeout | None | NotGiven = not_given,
-    ) -> Transcription: ...
+    ) -> Transcription:
+        """
+        Transcribes audio into the input language.
+
+        Args:
+          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.
+
+          model: ID of the model to use. The options are `gpt-4o-transcribe`,
+              `gpt-4o-mini-transcribe`, and `whisper-1` (which is powered by our open source
+              Whisper V2 model).
+
+          chunking_strategy: Controls how the audio is cut into chunks. When set to `"auto"`, the server
+              first normalizes loudness and then uses voice activity detection (VAD) to choose
+              boundaries. `server_vad` object can be provided to tweak VAD detection
+              parameters manually. If unset, the audio is transcribed as a single block.
+
+          include: Additional information to include in the transcription response. `logprobs` will
+              return the log probabilities of the tokens in the response to understand the
+              model's confidence in the transcription. `logprobs` only works with
+              response_format set to `json` and only with the models `gpt-4o-transcribe` and
+              `gpt-4o-mini-transcribe`.
+
+          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) (e.g. `en`)
+              format will improve accuracy and latency.
+
+          prompt: An optional text to guide the model's style or continue a previous audio
+              segment. The
+              [prompt](https://platform.openai.com/docs/guides/speech-to-text#prompting)
+              should match the audio language.
+
+          response_format: The format of the output, in one of these options: `json`, `text`, `srt`,
+              `verbose_json`, or `vtt`. For `gpt-4o-transcribe` and `gpt-4o-mini-transcribe`,
+              the only supported format is `json`.
+
+          stream: If set to true, the model response data will be streamed to the client as it is
+              generated using
+              [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).
+              See the
+              [Streaming section of the Speech-to-Text guide](https://platform.openai.com/docs/guides/speech-to-text?lang=curl#streaming-transcriptions)
+              for more information.
+
+              Note: Streaming is not supported for the `whisper-1` model and will be ignored.
+
+          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.
+
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+        """
 
     @overload
     def create(