#
# Copyright (c) 2024–2025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
from typing import Optional
from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription
from pipecat.transcriptions.language import Language
[docs]
class OpenAISTTService(BaseWhisperSTTService):
"""OpenAI Speech-to-Text service that generates text from audio.
Uses OpenAI's transcription API to convert audio to text. Requires an OpenAI API key
set via the api_key parameter or OPENAI_API_KEY environment variable.
Args:
model: Model to use — either gpt-4o or Whisper. Defaults to "gpt-4o-transcribe".
api_key: OpenAI API key. Defaults to None.
base_url: API base URL. Defaults to None.
language: Language of the audio input. Defaults to English.
prompt: Optional text to guide the model's style or continue a previous segment.
temperature: Optional sampling temperature between 0 and 1. Defaults to 0.0.
**kwargs: Additional arguments passed to BaseWhisperSTTService.
"""
def __init__(
self,
*,
model: str = "gpt-4o-transcribe",
api_key: Optional[str] = None,
base_url: Optional[str] = None,
language: Optional[Language] = Language.EN,
prompt: Optional[str] = None,
temperature: Optional[float] = None,
**kwargs,
):
super().__init__(
model=model,
api_key=api_key,
base_url=base_url,
language=language,
prompt=prompt,
temperature=temperature,
**kwargs,
)
async def _transcribe(self, audio: bytes) -> Transcription:
assert self._language is not None # Assigned in the BaseWhisperSTTService class
# Build kwargs dict with only set parameters
kwargs = {
"file": ("audio.wav", audio, "audio/wav"),
"model": self.model_name,
"language": self._language,
}
if self._prompt is not None:
kwargs["prompt"] = self._prompt
if self._temperature is not None:
kwargs["temperature"] = self._temperature
return await self._client.audio.transcriptions.create(**kwargs)