rboto-transcribe-streaming

rboto is an independent project maintained by Ferrumio. It is not affiliated with, sponsored by, or endorsed by Amazon Web Services (AWS).

Preview (Alpha). rboto is under active development. APIs may change between releases.

rboto provides an async-only, typed Python client for Amazon Transcribe Streaming, powered by Rust. This package contains TranscribeStreamingClient and 5 operations.

Installation

Requires Python 3.12 or newer and a native wheel for your Python version and platform.

python -m pip install "rboto[transcribe-streaming]"

You can also install rboto-transcribe-streaming directly; it installs the matching rboto package. Only the selected service is installed.

These are the package names to use when a release is available on your package index. If your index has no release yet, follow the source installation instructions.

Usage

Configure credentials through your environment, shared profile, or workload role. The example uses us-east-1; select a region where your service and resources are available. Resource names, identifiers, input files, and model IDs in the example are placeholders to replace with your own.

import asyncio
import wave
from collections.abc import AsyncIterator

from rboto import TranscribeStreamingClient
from rboto_transcribe_streaming.types import AudioStream


async def audio_events() -> AsyncIterator[AudioStream]:
    audio = await asyncio.to_thread(wave.open, "speech.wav", "rb")
    try:
        if (audio.getnchannels(), audio.getsampwidth(), audio.getframerate()) != (1, 2, 16000):
            raise ValueError("Use mono, 16-bit PCM audio sampled at 16 kHz")
        while chunk := await asyncio.to_thread(audio.readframes, 1600):
            yield {"audio_event": {"audio_chunk": chunk}}
            await asyncio.sleep(0.1)
    finally:
        await asyncio.to_thread(audio.close)


async def main() -> None:
    client = TranscribeStreamingClient(region="us-east-1")
    response = await client.start_stream_transcription(
        language_code="en-US",
        media_sample_rate_hertz=16000,
        media_encoding="pcm",
        audio_stream=audio_events(),
    )
    async for event in response["transcript_result_stream"]:
        print(event)


if __name__ == "__main__":
    asyncio.run(main())

In an application with an event loop, call await main() instead of asyncio.run(main()). Reuse the client across calls. Constructing a client does not send a request.

API conventions

• Import the client with from rboto import TranscribeStreamingClient.

• Every operation is asynchronous: use await client.method(...).

• Operation arguments are keyword-only and use the Python names listed below.

• Structured inputs use typed dictionaries and tagged unions from rboto_transcribe_streaming.types.

• Regular responses expose typed attributes; response.to_dict() converts them to a dictionary.

• Event-stream responses may be typed dictionaries containing async iterators. Follow the declared return type; consume event streams with async for.

• Byte streams are consumed asynchronously. await stream.read() buffers the complete body; iterate the stream when processing a large response.

• Direct operation calls return one page.

• Catch modeled exceptions from rboto_transcribe_streaming.exceptions. Their error_code, message, and operation_name identify service failures.

Clients also accept profile, endpoint_url, or shared Session settings. See configuration, errors, and streaming.

Operations

This is the complete operation catalog for this generated package. “Required arguments” lists arguments without defaults in the Python signature. Service-side conditions may require additional arguments. Each method links to its complete signature, including optional arguments. Nested input definitions are in rboto_transcribe_streaming.types; native response definitions are in the package's _native.pyi.

Complete signatures

get_medical_scribe_stream

async def get_medical_scribe_stream(
    *,
    session_id: str,
) -> GetMedicalScribeStreamOutput: ...

start_call_analytics_stream_transcription

async def start_call_analytics_stream_transcription(
    *,
    media_sample_rate_hertz: int,
    media_encoding: MediaEncoding,
    audio_stream: AsyncIterator[AudioStream],
    language_code: CallAnalyticsLanguageCode | None = None,
    vocabulary_name: str | None = None,
    session_id: str | None = None,
    vocabulary_filter_name: str | None = None,
    vocabulary_filter_method: VocabularyFilterMethod | None = None,
    language_model_name: str | None = None,
    identify_language: bool | None = None,
    language_options: str | None = None,
    preferred_language: CallAnalyticsLanguageCode | None = None,
    vocabulary_names: str | None = None,
    vocabulary_filter_names: str | None = None,
    enable_partial_results_stabilization: bool | None = None,
    partial_results_stability: PartialResultsStability | None = None,
    content_identification_type: ContentIdentificationType | None = None,
    content_redaction_type: ContentRedactionType | None = None,
    pii_entity_types: str | None = None,
) -> StartCallAnalyticsStreamTranscriptionOutput: ...

start_medical_scribe_stream

async def start_medical_scribe_stream(
    *,
    language_code: MedicalScribeLanguageCode,
    media_sample_rate_hertz: int,
    media_encoding: MedicalScribeMediaEncoding,
    input_stream: AsyncIterator[MedicalScribeInputStream],
    session_id: str | None = None,
) -> StartMedicalScribeStreamOutput: ...

start_medical_stream_transcription

async def start_medical_stream_transcription(
    *,
    language_code: LanguageCode,
    media_sample_rate_hertz: int,
    media_encoding: MediaEncoding,
    specialty: Specialty,
    type: Type,
    audio_stream: AsyncIterator[AudioStream],
    vocabulary_name: str | None = None,
    show_speaker_label: bool | None = None,
    session_id: str | None = None,
    enable_channel_identification: bool | None = None,
    number_of_channels: int | None = None,
    content_identification_type: MedicalContentIdentificationType | None = None,
) -> StartMedicalStreamTranscriptionOutput: ...

start_stream_transcription

async def start_stream_transcription(
    *,
    media_sample_rate_hertz: int,
    media_encoding: MediaEncoding,
    audio_stream: AsyncIterator[AudioStream],
    language_code: LanguageCode | None = None,
    vocabulary_name: str | None = None,
    session_id: str | None = None,
    vocabulary_filter_name: str | None = None,
    vocabulary_filter_method: VocabularyFilterMethod | None = None,
    show_speaker_label: bool | None = None,
    enable_channel_identification: bool | None = None,
    number_of_channels: int | None = None,
    enable_partial_results_stabilization: bool | None = None,
    partial_results_stability: PartialResultsStability | None = None,
    content_identification_type: ContentIdentificationType | None = None,
    content_redaction_type: ContentRedactionType | None = None,
    pii_entity_types: str | None = None,
    language_model_name: str | None = None,
    identify_language: bool | None = None,
    language_options: str | None = None,
    preferred_language: LanguageCode | None = None,
    identify_multiple_languages: bool | None = None,
    vocabulary_names: str | None = None,
    vocabulary_filter_names: str | None = None,
    session_resume_window: int | None = None,
    transcript_format: TranscriptFormat | None = None,
) -> StartStreamTranscriptionOutput: ...

Links

• Service guide
• Repository
• Issues
• Releases

Licensed under Apache-2.0.