Google Gemini LLM

Overview

Google Gemini models are available in LiveKit Agents through LiveKit Inference and the Gemini plugin. Pricing for LiveKit Inference is available on the pricing page.

LiveKit Inference

Use LiveKit Inference to access Gemini models without a separate Google API key.

Usage

To use Gemini, use the LLM class from the inference module:

from livekit.agents import AgentSession, inference

session = AgentSession(
    llm=inference.LLM(
        model="google/gemini-2.5-flash-lite",
        extra_kwargs={
            "max_completion_tokens": 1000
        }
    ),
    # ... tts, stt, vad, turn_detection, etc.
)

import { AgentSession, inference } from '@livekit/agents';

session = new AgentSession({
    llm: new inference.LLM({ 
        model: "google/gemini-2.5-flash-lite", 
        modelOptions: { 
            max_completion_tokens: 1000 
        }
    }),
    // ... tts, stt, vad, turn_detection, etc.
});

Parameters

String descriptors

As a shortcut, you can also pass a model descriptor string directly to the llm argument in your AgentSession:

from livekit.agents import AgentSession

session = AgentSession(
    llm="google/gemini-2.5-flash-lite",
    # ... tts, stt, vad, turn_detection, etc.
)

import { AgentSession } from '@livekit/agents';

session = new AgentSession({
    llm: "google/gemini-2.5-flash-lite",
    // ... tts, stt, vad, turn_detection, etc.
});

Plugin

Use the Google plugin to connect directly to Google's Gemini API with your own API key.

Installation

Install the plugin from PyPI:

uv add "livekit-agents[google]~=1.4"

pnpm add @livekit/agents-plugin-google@1.x

Authentication

The Google plugin requires authentication based on your chosen service:

• For Vertex AI, you must set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path of the service account key file. For more information about mounting files as secrets when deploying to LiveKit Cloud, see File-mounted secrets.
• For Google Gemini API, set the GOOGLE_API_KEY environment variable.

Usage

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

from livekit.plugins import google

session = AgentSession(
    llm=google.LLM(
        model="gemini-3-flash-preview",
    ),
    # ... tts, stt, vad, turn_detection, etc.
)

import { voice } from '@livekit/agents';
import * as google from '@livekit/agents-plugin-google';

const session = new voice.AgentSession({
    llm: new google.LLM({
        model: "gemini-3-flash-preview",
    }),
    // ... 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.

Provider tools

Google Gemini supports the following provider tools that enable the model to use built-in capabilities executed on the model server. These tools can be used alongside function tools defined in your agent's codebase.

from livekit.plugins import google

agent = MyAgent(
    llm=google.LLM(model="gemini-2.5-flash"),
    tools=[google.tools.GoogleSearch()],  # replace with any supported provider tool
)

Additional resources

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

Python plugin

ReferenceGitHubPyPI

Node.js plugin

ReferenceGitHubNPM

Gemini docs

Google Gemini documentation.

Voice AI quickstart

Get started with LiveKit Agents and Google Gemini.

Google AI ecosystem guide

Overview of the entire Google AI and LiveKit Agents integration.