langgraph-voice-call-agent

Name: langgraph-voice-call-agent
Author: ahmad2b

ahmad2b August 22, 2025

36 copies 0 downloads

A real-time voice/call AI agent that lets you talk to a LangGraph agent over LiveKit — similar to "voice mode" experiences in ChatGPT Voice, OpenAI Realtime API sessions, and Gemini Live. This repo demonstrates adapting any LangGraph agent into a full-duplex, low-latency voice assistant using LiveKit Agents.

LangGraph Voice Call Agent

A real-time voice/call AI agent that lets you talk to a LangGraph agent over LiveKit, similar to "voice mode" experiences in Gemini Voice, OpenAI Realtime API sessions, and Gemini Live. This repo demonstrates adapting any LangGraph agent into a full-duplex, low-latency voice assistant using LiveKit's real-time communication infrastructure.

This backend provides the core voice processing and AI agent functionality, built to work seamlessly with LiveKit's real-time infra and any frontend that supports LiveKit client connections.

Features

Real-time voice interaction with LangGraph agents
Full-duplex communication with low-latency audio processing
Flexible LangGraph integration - works with any LangGraph agent
Comprehensive audio pipeline including VAD, STT, TTS, and turn detection
Thread-based conversation continuity via participant metadata

Project Structure

langgraph-voice-call-agent/
├── src/                         # Main source code
│   ├── livekit/                 # LiveKit agent implementation
│   │   ├── agent.py             # Main agent entrypoint
│   │   └── adapter/             # LangGraph integration
│   │       └── langgraph.py     # LangGraph adapter for LiveKit
│   └── langgraph/               # LangGraph Agent Sdefinitions
│       └── agent.py             # An example agent
├── compose.yml                  # Docker Compose for local LiveKit server
├── pyproject.toml               # Python project configuration
├── uv.lock                      # uv dependency lock file
└── Makefile                     # Development commands

How it works (high level)

Agent Initialization → LiveKit agent connects to room and waits for participants
Audio Pipeline Setup → VAD, STT, TTS, and turn detection models are loaded and configured
LangGraph Integration → Connect to LangGraph server
Voice Processing → Real-time audio is processed through the pipeline:

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