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.
- 🗣 Spin up a conversation with your system audio
- ➡️ 📞 Set up a phone number that responds with a LLM-based agent
- 📞 ➡️ Send out phone calls from your phone number managed by an LLM-based agent
- 🧑💻 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!
We'd love for you all to build on top of our abstractions to enable new and better LLM voice applications!
You can extend our BaseAgent, BaseTranscriber, and BaseSynthesizer abstractions to integrate with new LLM APIs, speech recognition and speech synthesis providers. More detail here.
You can also work with our BaseInputDevice and BaseOutputDevice abstractions to set up voice applications on new surfaces/platforms. More guides for this coming soon!
Because our StreamingConversation runs locally, it's relatively quick to develop on! Feel free to fork and create a PR and we will get it merged as soon as possible. And we'd love to talk to you on Discord!
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())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())