LiveKit Agents Docs • LiveKit Cloud • Blog

This example demonstrates an full workflow of an AI agent that makes outbound calls. It uses LiveKit SIP and Python Agents Framework.

It can use a pipeline of STT, LLM, and TTS models, or a realtime speech-to-speech model. (such as ones from OpenAI and Gemini).

This example builds on concepts from the Outbound Calls section of the docs. Ensure that a SIP outbound trunk is configured before proceeding.

This example demonstrates the following features:

• Making outbound calls
• Detecting voicemail
• Looking up availability via function calling
• Transferring to a human operator
• Detecting intent to end the call
• Uses Krisp background voice cancellation to handle noisy environments

Clone the repository and install dependencies to a virtual environment:

git clone https://github.com/livekit-examples/outbound-caller-python.git
cd outbound-caller-python
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python agent.py download-files

Set up the environment by copying .env.example to .env.local and filling in the required values:

• LIVEKIT_URL
• LIVEKIT_API_KEY
• LIVEKIT_API_SECRET
• OPENAI_API_KEY
• SIP_OUTBOUND_TRUNK_ID
• DEEPGRAM_API_KEY - optional, only needed when using pipelined models
• CARTESIA_API_KEY - optional, only needed when using pipelined models

Run the agent:

python3 agent.py dev

Now, your worker is running, and waiting for dispatches in order to make outbound calls.

You can dispatch an agent to make a call by using the lk CLI:

lk dispatch create \
  --new-room \
  --agent-name outbound-caller \
  --metadata '{"phone_number": "+1234567890", "transfer_to": "+9876543210"}'