bodhi-sdk 1.2.0

Bodhi Python SDK for Streaming Speech Recognition

Bodhi Python SDK

Bodhi Python SDK provides a client for Navana's streaming speech recognition API.

Installation

pip install bodhi-sdk

Usage

To use the Bodhi Python SDK, follow these steps:

1. Installation: Install the SDK using pip:

   pip install bodhi-sdk
   

2. Initialization: Create a BodhiClient instance with your API key and customer ID:

   from bodhi import BodhiClient
   
   client = BodhiClient(api_key="YOUR_API_KEY", customer_id="YOUR_CUSTOMER_ID")
   

3. Transcription: Use the client methods to transcribe audio. The SDK supports transcription from local files, remote URLs, and streams.

   • Local File Transcription:

     config = TranscriptionConfig(
       model="hi-banking-v2-8khz",
       at_start_lid=False,    # Enable language identification at start (default: False)
       transliterate=False,   # Enable transliteration output (default: False)
     )
     response = client.transcribe_local_file(audio_file_path, config=config)
     print(response.text)
     

   • Remote URL Transcription:

     config = TranscriptionConfig(
       model="hi-banking-v2-8khz",
       at_start_lid=False,    # Enable language identification at start (default: False)
       transliterate=False,   # Enable transliteration output (default: False)
     )
     response = client.transcribe_remote_url("http://example.com/audio.wav", config)
     print(response.text)
     

   • Streaming Transcription: Refer to the examples for detailed instructions on setting up streaming transcription.

4. Event Handling: You can register event listeners to handle different stages of the transcription process using the client.on method and the LiveTranscriptionEvents enum. This is particularly useful for streaming and remote URL transcriptions where events are emitted asynchronously.

   from bodhi import LiveTranscriptionEvents
   
   async def on_transcript(response):
       print(f"Transcript: {response.text}")
   
   async def on_utterance_end(response):
       print(f"UtteranceEnd: {response}")
   
   async def on_speech_started(response):
       print(f"SpeechStarted: {response}")
   
   async def on_error(e):
       print(f"Error: {str(e)}")
   
   client.on(LiveTranscriptionEvents.Transcript, on_transcript)
   client.on(LiveTranscriptionEvents.UtteranceEnd, on_utterance_end)
   client.on(LiveTranscriptionEvents.SpeechStarted, on_speech_started)
   client.on(LiveTranscriptionEvents.Error, on_error)
   

   Common events include:

   • LiveTranscriptionEvents.Transcript: Emitted when a new transcription segment is available.
   • LiveTranscriptionEvents.UtteranceEnd: Emitted when an utterance is detected as complete.
   • LiveTranscriptionEvents.SpeechStarted: Emitted when speech activity is detected.
   • LiveTranscriptionEvents.Error: Emitted when an error occurs during transcription.
   • LiveTranscriptionEvents.Close: Emitted when the WebSocket connection is closed.

For complete code examples and detailed usage instructions for various scenarios, please refer to the official documentation.