speechcortex-sdk 0.1.4

The official Python SDK for SpeechCortex ASR platform.

SpeechCortex Python SDK

Official Python SDK for SpeechCortex ASR (Automatic Speech Recognition) platform.

Features

• Real-time Speech Recognition: WebSocket-based streaming ASR
• Batch/Post-Call Transcription: REST API for batch processing with file upload or presigned URLs
• Easy Integration: Simple, intuitive API
• Async Support: Full async/await support for modern Python applications

Requirements

• Python 3.10 or higher

Installation

pip install "git+https://github.com/speechcortex/speechcortex-sdk.git@package_init"

export SPEECHCORTEX_API_KEY=your_api_key_here
export SPEECHCORTEX_HOST=wss://api.speechcortex.com

Quick Start

Real-time Transcription

from speechcortex import SpeechCortexClient, LiveTranscriptionEvents, LiveOptions

# Initialize the client
speechcortex = SpeechCortexClient(api_key="your_api_key_here")

# Get WebSocket connection
connection = speechcortex.listen.websocket.v("1")

# Set up event handlers
def on_message(self, result, **kwargs):
    sentence = result.channel.alternatives[0].transcript
    if result.is_final:
        print(f"Final: {sentence}")
    else:
        print(f"Interim: {sentence}")

def on_error(self, error, **kwargs):
    print(f"Error: {error}")

# Register event handlers
connection.on(LiveTranscriptionEvents.Transcript, on_message)
connection.on(LiveTranscriptionEvents.Error, on_error)

# Configure options
options = LiveOptions(
    model="zeus-v1",
    language="en-US",
    smart_format=True,
)

# Start the connection
connection.start(options)

# Send audio data
connection.send(audio_data)

# Close when done
connection.finish()

Using with Microphone

from speechcortex import SpeechCortexClient, LiveTranscriptionEvents, LiveOptions, Microphone

speechcortex = SpeechCortexClient()
connection = speechcortex.listen.websocket.v("1")

# Set up event handlers...
connection.on(LiveTranscriptionEvents.Transcript, on_message)

# Start connection
options = LiveOptions(model="zeus-v1", smart_format=True)
connection.start(options)

# Use microphone helper
microphone = Microphone(connection.send)
microphone.start()

# Microphone will stream audio automatically
# Press Ctrl+C to stop

microphone.finish()
connection.finish()

Batch/Post-Call Transcription

import asyncio
from speechcortex import SpeechCortexClient, BatchOptions, TranscriptionConfig

async def main():
    client = SpeechCortexClient(api_key="your_api_key_here")
    batch = client.transcribe.batch()

    async with batch:
        # Method 1: Submit with presigned URL
        job = await batch.submit_job(
            presigned_url="https://your-bucket.s3.amazonaws.com/audio.mp3?X-Amz-Algorithm=...",
            language="en-US",
            model="batch-zeus",
            diarize=True,
            punctuate=True,
        )

        # Wait for completion
        result = await batch.wait_for_completion(job.job_id, timeout=300.0)
        print(result.transcription)

        # Method 2: Upload file directly
        job = await batch.submit_job(
            audio_file="path/to/audio.mp3",
            language="en-US",
        )

        # Method 3: Convenience method (submit + wait in one call)
        result = await batch.transcribe(
            presigned_url="https://example.com/audio.mp3",
            language="en-US",
            timeout=300.0,
        )
        print(result.transcription)

asyncio.run(main())

Batch Transcription with Configuration

import asyncio
from speechcortex import SpeechCortexClient, BatchOptions, TranscriptionConfig

async def main():
    client = SpeechCortexClient()
    batch = client.transcribe.batch()

    async with batch:
        # Create transcription config
        config = TranscriptionConfig(
            language="en-US",
            model="batch-zeus",
            diarize=True,
            punctuate=True,
            smart_format=True,
            channel=2,
        )

        # Create batch options
        options = BatchOptions(
            polling_interval=5.0,
            timeout=600.0,
        )

        # Submit job
        job = await batch.submit_job(
            presigned_url="https://example.com/audio.mp3",
            config=config,
        )

        # Wait with custom options
        result = await batch.wait_for_completion(job.job_id, options=options)

asyncio.run(main())

Manual Status Polling

import asyncio
from speechcortex import SpeechCortexClient

async def main():
    client = SpeechCortexClient()
    batch = client.transcribe.batch()

    async with batch:
        # Submit job
        job = await batch.submit_job(
            presigned_url="https://example.com/audio.mp3",
            language="en-US",
        )

        # Manually poll for status
        while True:
            status = await batch.get_status(job.job_id)
            print(f"Status: {status.status}")

            if status.status.upper() == "COMPLETED":
                result = await batch.get_transcription(job.job_id)
                print(result.transcription)
                break
            elif status.status.upper() == "FAILED":
                print(f"Job failed: {status.error_message}")
                break

            await asyncio.sleep(3)

asyncio.run(main())

Configuration

API Key

Set your API key via environment variable:

export SPEECHCORTEX_API_KEY=your_api_key_here

Or pass it directly:

speechcortex = SpeechCortexClient(api_key="your_api_key_here")

Custom Endpoints

from speechcortex import SpeechCortexClient, SpeechCortexClientOptions

config = SpeechCortexClientOptions(
    api_key="your_api_key",
    url="https://custom-api.speechcortex.com"
)
speechcortex = SpeechCortexClient(config=config)

Features

Real-time Transcription Options

• model: ASR model to use (e.g., "zeus-v1")
• language: Language code (e.g., "en-US")
• smart_format: Enable smart formatting
• punctuate: Enable punctuation
• interim_results: Receive interim results
• utterance_end_ms: Utterance end timeout in milliseconds
• vad_events: Enable voice activity detection events

Batch Transcription Options

• language: Language code (e.g., "en-US", "ENGLISH")
• model: Transcription model (default: "batch-zeus")
• diarize: Enable speaker diarization (default: False)
• punctuate: Enable punctuation (default: True)
• smart_format: Enable smart formatting (default: True)
• channel: Number of audio channels (default: 2)
• polling_interval: Time between status checks in seconds (default: 3.0)
• timeout: Maximum time to wait for completion in seconds (default: None)

Events

• Open: Connection opened
• Transcript: Transcription result received
• Metadata: Metadata received
• SpeechStarted: Speech detected
• UtteranceEnd: End of utterance detected
• Close: Connection closed
• Error: Error occurred
• Unhandled: Unhandled message received

Development

Setup Development Environment

# Clone the repository
git clone https://github.com/speechcortex/speechcortex-sdk.git
cd speechcortex-sdk

# Install dependencies
pip install -r requirements-dev.txt

# Run tests
pytest

# Run linting
pylint speechcortex/

# Format code
black speechcortex/

License

MIT License - see LICENSE file for details.

Support

For issues, questions, or contributions, please visit our GitHub repository.