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Groq LLM integration guide

How to use the Groq LLM plugin for LiveKit Agents.

Available in
Python
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See our voice assistant playground using Groq STT, LLM, and TTS

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Overview

Groq provides fast LLM inference using open models from Llama, DeepSeek, and more. With LiveKit's Groq integration and the Agents framework, you can build low-latency voice AI applications.

Quick reference

This section includes a basic usage example and some reference material. For links to more detailed documentation, see Additional resources.

Installation

Install the plugin from PyPI:

pip install "livekit-agents[groq]~=1.2"

Authentication

The Groq plugin requires a Groq API key.

Set GROQ_API_KEY in your .env file.

Usage

Use a Groq LLM in your AgentSession or as a standalone LLM service. For example, you can use this LLM in the Voice AI quickstart.

from livekit.plugins import groq
session = AgentSession(
llm=groq.LLM(
model="llama3-8b-8192"
),
# ... tts, stt, vad, turn_detection, etc.
)

Parameters

This section describes some of the available parameters. For a complete reference of all available parameters, see the plugin reference.

modelstringOptionalDefault: llama-3.3-70b-versatile

Name of the LLM model to use. For all options, see the Groq model list.

temperaturefloatOptionalDefault: 1.0

Controls the randomness of the model's output. Higher values, for example 0.8, make the output more random, while lower values, for example 0.2, make it more focused and deterministic.

parallel_tool_callsboolOptional

Controls whether the model can make multiple tool calls in parallel. When enabled, the model can make multiple tool calls simultaneously, which can improve performance for complex tasks.

tool_choiceToolChoice | Literal['auto', 'required', 'none']OptionalDefault: auto

Controls how the model uses tools. Set to 'auto' to let the model decide, 'required' to force tool usage, or 'none' to disable tool usage.

Additional resources

The following resources provide more information about using Groq with LiveKit Agents.