livekit_langgraph

This is a simple example to talk with a langgraph agent in realtime using speech with livekit.

Setup

cp example.env .env

Fill in the values in the .env file.

uv sync

To install the dependencies.

Usage

1. Create an account in livekit to get the url and api-key/secret

2. Before your first run, you must download certain models such as Silero VAD and the LiveKit turn detector:

   • uv run livekit_agent.py download-files

3. Next, run this command to speak to your agent directly in your terminal:

   • uv run livekit_agent.py console

4. To run the agent for use with a frontend or telephony, use the dev command:

   • uv run livekit_agent.py dev

5. In production, use the start command:

   • uv run livekit_agent.py start

6. Frontend starter templates:

   • Use the pre-built frontend starter apps from livekit to speak to the agent from frontend.

     • Eg. Web voice AI assistant with React & Next.js: https://github.com/livekit-examples/agent-starter-react
     • git clone https://github.com/livekit-examples/agent-starter-react.git
     • cd agent-starter-react
     • npm install
     • npm run dev

   • Run the agent in dev or production mode to chat through frontend

     • uv run livekit_agent.py dev
     • uv run livekit_agent.py start