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Installation

Install the vocode package: 
pip install vocode

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Getting started

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Working with system audio

We provide helper methods to hook into your system audio. 
microphone_input, speaker_output = create_microphone_input_and_speaker_output(
    use_default_devices=True
)
If the default I/O devices are not being set properly, set use_default_devices to False to select them before kicking off the conversation.

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Environments

Vocode provides a unified interface across various speech transcription, speech synthesis, and AI/NLU providers. To use these providers with Vocode, you’ll need to grab credentials from these providers and set them in the Vocode environment. You can either set the following parameters as environment variables (e.g. by specifying them in a .env file and using a package like python-dotenv to load), or set them manually in the pydantic settings (see below). For AZURE_SPEECH_REGION you should use the URL format. For example, if you’re using the “East US” region, the value should be “eastus”. See Azure Region list.

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StreamingConversation example

This can also be found in the quickstarts directory of the repo. 
import asyncio
import signal

from pydantic_settings import BaseSettings, SettingsConfigDict

from vocode.helpers import create_streaming_microphone_input_and_speaker_output
from vocode.logging import configure_pretty_logging
from vocode.streaming.agent.chat_gpt_agent import ChatGPTAgent
from vocode.streaming.models.agent import ChatGPTAgentConfig
from vocode.streaming.models.message import BaseMessage
from vocode.streaming.models.synthesizer import AzureSynthesizerConfig
from vocode.streaming.models.transcriber import (
    DeepgramTranscriberConfig,
    PunctuationEndpointingConfig,
)
from vocode.streaming.streaming_conversation import StreamingConversation
from vocode.streaming.synthesizer.azure_synthesizer import AzureSynthesizer
from vocode.streaming.transcriber.deepgram_transcriber import DeepgramTranscriber

configure_pretty_logging()


class Settings(BaseSettings):
    """
    Settings for the streaming conversation quickstart.
    These parameters can be configured with environment variables.
    """

    openai_api_key: str = "ENTER_YOUR_OPENAI_API_KEY_HERE"
    azure_speech_key: str = "ENTER_YOUR_AZURE_KEY_HERE"
    deepgram_api_key: str = "ENTER_YOUR_DEEPGRAM_API_KEY_HERE"

    azure_speech_region: str = "eastus"

    # This means a .env file can be used to overload these settings
    # ex: "OPENAI_API_KEY=my_key" will set openai_api_key over the default above
    model_config = SettingsConfigDict(
        env_file=".env",
        env_file_encoding="utf-8",
        extra="ignore"
    )


settings = Settings()


async def main():
    (
        microphone_input,
        speaker_output,
    ) = create_streaming_microphone_input_and_speaker_output(
        use_default_devices=False,
        use_blocking_speaker_output=True,  # this moves the playback to a separate thread, set to False to use the main thread
    )

    conversation = StreamingConversation(
        output_device=speaker_output,
        transcriber=DeepgramTranscriber(
            DeepgramTranscriberConfig.from_input_device(
                microphone_input,
                endpointing_config=PunctuationEndpointingConfig(),
                api_key=settings.deepgram_api_key,
            ),
        ),
        agent=ChatGPTAgent(
            ChatGPTAgentConfig(
                openai_api_key=settings.openai_api_key,
                initial_message=BaseMessage(text="What up"),
                prompt_preamble="""The AI is having a pleasant conversation about life""",
            )
        ),
        synthesizer=AzureSynthesizer(
            AzureSynthesizerConfig.from_output_device(speaker_output),
            azure_speech_key=settings.azure_speech_key,
            azure_speech_region=settings.azure_speech_region,
        ),
    )
    await conversation.start()
    print("Conversation started, press Ctrl+C to end")
    signal.signal(signal.SIGINT, lambda _0, _1: asyncio.create_task(conversation.terminate()))
    while conversation.is_active():
        chunk = await microphone_input.get_audio()
        conversation.receive_audio(chunk)


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

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A note on echo cancellation

As of now, there is no default echo cancellation enabled for system audio conversation, so this works best with headphones, otherwise the bot audio feeds back into the input audio stream. On some speakers (eg phone calls) this is handled by the device itself. Another fix for this is to pipe your microphone / speaker to Krisp.AI. Download their application and select the Krisp virtual audio devices when running the script! Stay tuned for updates here, tracking in this GitHub issue.