Create Transcription

client.audio.transcriptions.create(
    file: FileTypes,
    model: str,
    language: Optional[str] = None,
    prompt: Optional[str] = None,
    response_format: Optional[str] = None,
    temperature: Optional[float] = None
) -> TranscriptionCreateResponse

from dedalus_labs import DedalusLabs

client = DedalusLabs()

# Basic transcription
with open("audio.mp3", "rb") as audio_file:
    transcription = client.audio.transcriptions.create(
        file=audio_file,
        model="openai/whisper-1"
    )

print(transcription.text)

# Transcription with language hint for better accuracy
with open("spanish_audio.wav", "rb") as audio_file:
    transcription = client.audio.transcriptions.create(
        file=audio_file,
        model="openai/whisper-1",
        language="es"
    )

print(transcription.text)

# Get detailed transcription with timestamps
with open("interview.m4a", "rb") as audio_file:
    transcription = client.audio.transcriptions.create(
        file=audio_file,
        model="openai/whisper-1",
        response_format="verbose_json"
    )

print(f"Language: {transcription.language}")
print(f"Duration: {transcription.duration}s")

for word in transcription.words:
    print(f"{word.start:.2f}s - {word.end:.2f}s: {word.word}")

# Generate SRT subtitle file
with open("video_audio.mp3", "rb") as audio_file:
    srt_output = client.audio.transcriptions.create(
        file=audio_file,
        model="openai/whisper-1",
        response_format="srt"
    )

with open("subtitles.srt", "w") as f:
    f.write(srt_output.text)

# Use prompt to guide transcription style
with open("meeting.wav", "rb") as audio_file:
    transcription = client.audio.transcriptions.create(
        file=audio_file,
        model="openai/whisper-1",
        prompt="This is a business meeting discussing Q4 results and strategy.",
        temperature=0.2
    )

print(transcription.text)