The all-in-one voice SDK
Project description
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.
⭐️ Features
- 🗣 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!
🚀 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.models.agent import ChatGPTAgentConfig
from vocode.streaming.models.message import BaseMessage
from vocode.streaming.models.synthesizer import AzureSynthesizerConfig
# 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_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),
)
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())
☁️ 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())
📞 Phone call quickstarts
🌱 Documentation
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