Transcribe audio to text with multiple providers.
Quick Start
python
from ai_infra import STT
stt = STT()
result = stt.transcribe("audio.mp3")
print(result.text) # "Hello, world!"Supported Providers
| Provider | Models | Languages | Streaming |
|---|---|---|---|
| OpenAI | whisper-1 | 50+ | [X] |
| Deepgram | nova-2, nova | 30+ | [OK] |
| Multiple | 100+ | [OK] |
Basic Usage
Auto-Detect Provider
python
from ai_infra import STT
# Auto-detects from env vars (OpenAI -> Deepgram -> Google)
stt = STT()
result = stt.transcribe("recording.mp3")
print(result.text)Explicit Provider
python
stt = STT(provider="deepgram")
result = stt.transcribe("recording.mp3")Input Formats
From File
python
stt = STT()
# MP3, WAV, M4A, WEBM, and more
result = stt.transcribe("audio.mp3")
result = stt.transcribe("audio.wav")
result = stt.transcribe("audio.m4a")From Bytes
python
with open("audio.mp3", "rb") as f:
audio_bytes = f.read()
result = stt.transcribe(audio_bytes)From URL
python
result = stt.transcribe("https://example.com/audio.mp3")OpenAI Whisper
python
from ai_infra import STT
stt = STT(provider="openai")
result = stt.transcribe("audio.mp3")
# Whisper-1 is the only model
print(result.text)
print(result.language) # Detected languageWith Language Hint
python
result = stt.transcribe("audio.mp3", language="es")Deepgram
python
from ai_infra import STT
stt = STT(provider="deepgram")
# High accuracy
result = stt.transcribe("audio.mp3", model="nova-2")
# With features
result = stt.transcribe(
"audio.mp3",
punctuate=True,
diarize=True, # Speaker detection
smart_format=True,
)Streaming with Deepgram
python
async def transcribe_stream(audio_stream):
stt = STT(provider="deepgram")
async for result in stt.stream(audio_stream):
print(result.text, end="", flush=True)Google STT
python
from ai_infra import STT
stt = STT(provider="google_genai")
result = stt.transcribe("audio.mp3")Transcription Result
python
result = stt.transcribe("audio.mp3")
# Basic result
print(result.text) # Full transcription
print(result.language) # Detected language code
# Detailed result (if available)
print(result.confidence) # Confidence score
print(result.duration) # Audio duration in seconds
print(result.words) # Word-level timestamps (if supported)Word Timestamps
python
result = stt.transcribe("audio.mp3", timestamps=True)
for word in result.words:
print(f"{word.text}: {word.start}s - {word.end}s")Async Usage
python
import asyncio
from ai_infra import STT
async def main():
stt = STT()
result = await stt.atranscribe("audio.mp3")
print(result.text)
asyncio.run(main())Configuration
python
stt = STT(
provider="deepgram",
model="nova-2",
language="en",
)Error Handling
python
from ai_infra import STT
from ai_infra.errors import AIInfraError, ProviderError
try:
stt = STT()
result = stt.transcribe("audio.mp3")
except ProviderError as e:
print(f"Provider error: {e}")
except AIInfraError as e:
print(f"STT error: {e}")