vocode
Build voice-based LLM apps in minutes
Vocode is an open source library that makes it easy to build voice-based LLM apps. Using Vocode, you can build real-time streaming conversations with LLMs and deploy them to phone calls, Zoom meetings, and more. You can also build personal assistants or apps like voice-based chess. Vocode provides easy abstractions and integrations so that everything you need is in a single library.
We're actively looking for community maintainers, so please reach out if interested!
βοΈ Features
- π£ Spin up a conversation with your system audio
- β‘οΈ π Set up a phone number that responds with a LLM-based agent
- π β‘οΈ Send out phone calls from your phone number managed by an LLM-based agent
- π§βπ» Dial into a Zoom call
- Out of the box integrations with:
- Transcription services, including:
- LLMs, including:
- Synthesis services, including:
Check out our React SDK here!
π« Contribution
We're an open source project and are extremely open to contributors adding new features, integrations, and documentation! Please don't hesitate to reach out and get started building with us.
For more information on contributing, see our Contribution Guide.
And we'd love to talk to you on Discord!
π Quickstart (Self-hosted)
pip install 'vocode[io]'
import asyncio
import signal
import vocode
from vocode.streaming.streaming_conversation import StreamingConversation
from vocode.helpers import create_microphone_input_and_speaker_output
from vocode.streaming.models.transcriber import (
DeepgramTranscriberConfig,
PunctuationEndpointingConfig,
)
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.synthesizer.azure_synthesizer import AzureSynthesizer
from vocode.streaming.transcriber.deepgram_transcriber import DeepgramTranscriber
# these can also be set as environment variables
vocode.setenv(
OPENAI_API_KEY="<your OpenAI key>",
DEEPGRAM_API_KEY="<your Deepgram key>",
AZURE_SPEECH_KEY="<your Azure key>",
AZURE_SPEECH_REGION="<your Azure region>",
)
async def main():
microphone_input, speaker_output = create_microphone_input_and_speaker_output(
streaming=True, use_default_devices=False
)
conversation = StreamingConversation(
output_device=speaker_output,
transcriber=DeepgramTranscriber(
DeepgramTranscriberConfig.from_input_device(
microphone_input, endpointing_config=PunctuationEndpointingConfig()
)
),
agent=ChatGPTAgent(
ChatGPTAgentConfig(
initial_message=BaseMessage(text="Hello!"),
prompt_preamble="Have a pleasant conversation about life",
),
),
synthesizer=AzureSynthesizer(
AzureSynthesizerConfig.from_output_device(speaker_output)
),
)
await conversation.start()
print("Conversation started, press Ctrl+C to end")
signal.signal(signal.SIGINT, lambda _0, _1: conversation.terminate())
while conversation.is_active():
chunk = microphone_input.get_audio()
if chunk:
conversation.receive_audio(chunk)
await asyncio.sleep(0)
if __name__ == "__main__":
asyncio.run(main())
βοΈ Quickstart (Hosted)
First, get a free API key from our dashboard.
pip install 'vocode[io]'
import asyncio
import signal
import vocode
from vocode.streaming.hosted_streaming_conversation import HostedStreamingConversation
from vocode.streaming.streaming_conversation import StreamingConversation
from vocode.helpers import create_microphone_input_and_speaker_output
from vocode.streaming.models.transcriber import (
DeepgramTranscriberConfig,
PunctuationEndpointingConfig,
)
from vocode.streaming.models.agent import ChatGPTAgentConfig
from vocode.streaming.models.message import BaseMessage
from vocode.streaming.models.synthesizer import AzureSynthesizerConfig
vocode.api_key = "<your API key>"
if __name__ == "__main__":
microphone_input, speaker_output = create_microphone_input_and_speaker_output(
streaming=True, use_default_devices=False
)
conversation = HostedStreamingConversation(
input_device=microphone_input,
output_device=speaker_output,
transcriber_config=DeepgramTranscriberConfig.from_input_device(
microphone_input,
endpointing_config=PunctuationEndpointingConfig(),
),
agent_config=ChatGPTAgentConfig(
initial_message=BaseMessage(text="Hello!"),
prompt_preamble="Have a pleasant conversation about life",
),
synthesizer_config=AzureSynthesizerConfig.from_output_device(speaker_output),
)
signal.signal(signal.SIGINT, lambda _0, _1: conversation.deactivate())
asyncio.run(conversation.start())