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OpenAI LLM plugin guide

How to use the OpenAI LLM plugin for LiveKit Agents.

Available in
Python
|
Node.js

Overview

This plugin allows you to use the OpenAI platform as an LLM provider for your voice agents.

LiveKit Inference

OpenAI models are also available in LiveKit Inference with billing and integration handled automatically. See the docs for more information.

OpenAI Responses API (Recommended)

The OpenAI plugin supports the Responses API, which provides support for OpenAI's provider tools (WebSearch, FileSearch, CodeInterpreter) and is the recommended approach for direct OpenAI usage. Use openai.responses.LLM() to access the Responses API. The Chat Completions API is available via openai.LLM() and is used for OpenAI-compatible endpoints (like openai.LLM.with_cerebras()). See API modes for more information.

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:

uv add "livekit-agents[openai]~=1.3"
pnpm add @livekit/agents-plugin-openai@1.x

Authentication

The OpenAI plugin requires an OpenAI API key.

Set OPENAI_API_KEY in your .env file.

Usage

Use OpenAI 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 openai
# Use Responses API (recommended)
session = AgentSession(
llm=openai.responses.LLM(
model="gpt-4o-mini"
),
# ... tts, stt, vad, turn_detection, etc.
)
import * as openai from '@livekit/agents-plugin-openai';
// Use Responses API (recommended)
const session = new voice.AgentSession({
llm: openai.responses.LLM({
model: "gpt-4o-mini"
}),
// ... tts, stt, vad, turn_detection, etc.
});

API modes

The OpenAI plugin supports two API modes: Responses API and Chat Completions API.

The Responses API is the recommended mode. It provides:

  • Support for OpenAI's provider tools (WebSearch, FileSearch, CodeInterpreter)
  • Better performance and features
  • Access to the latest OpenAI capabilities
  • Lower costs

Use openai.responses.LLM() to access the Responses API:

from livekit.plugins import openai
# Use Responses API (recommended)
session = AgentSession(
llm=openai.responses.LLM(model="gpt-4o-mini"),
# ... tts, stt, vad, turn_detection, etc.
)
import * as openai from '@livekit/agents-plugin-openai';
// Use Responses API (recommended)
const session = new voice.AgentSession({
llm: openai.responses.LLM({ model: "gpt-4o-mini" }),
// ... tts, stt, vad, turn_detection, etc.
});

Chat Completions API

The Chat Completions API is available via openai.LLM(). This API mode is used for:

  • OpenAI-compatible endpoints: Providers like Cerebras, Fireworks, Groq, etc. use openai.LLM.with_*() methods which rely on the Chat Completions API format (see OpenAI-compatible endpoints)
  • Legacy code compatibility: Existing code that uses openai.LLM() directly
For direct OpenAI usage

For direct OpenAI platform usage, use openai.responses.LLM() instead of openai.LLM(). The Responses API provides better features and performance.

To use Chat Completions mode directly with OpenAI (not recommended for new projects):

from livekit.plugins import openai
# Chat Completions API (use openai.responses.LLM() for new projects)
session = AgentSession(
llm=openai.LLM(model="gpt-4o-mini"),
# ... tts, stt, vad, turn_detection, etc.
)
import * as openai from '@livekit/agents-plugin-openai';
// Chat Completions API (use openai.responses.LLM() for new projects)
const session = new voice.AgentSession({
llm: openai.LLM({ model: "gpt-4o-mini" }),
// ... tts, stt, vad, turn_detection, etc.
});

OpenAI-compatible endpoints

When using OpenAI-compatible endpoints with providers using Chat Completions mode, you should use openai.LLM() with the provider's with_*() method. These providers include:

  • Cerebras: openai.LLM.with_cerebras()
  • Fireworks: openai.LLM.with_fireworks()
  • Groq: openai.LLM.with_groq()
  • Perplexity: openai.LLM.with_perplexity()
  • Telnyx: openai.LLM.with_telnyx()
  • Together AI: openai.LLM.with_together()
  • xAI: openai.LLM.with_x_ai()
  • DeepSeek: openai.LLM.with_deepseek()

These providers are built on the Chat Completions API format, so they use openai.LLM() (not openai.responses.LLM()). The with_*() methods automatically configure the correct API mode. See the individual provider documentation for specific usage examples.

Parameters

This section describes some of the available parameters. See the plugin reference links in the Additional resources section for a complete list of all available parameters.

modelstringOptionalDefault: gpt-4o-mini

The model to use for the LLM. For more information, see the OpenAI documentation.

temperaturefloatOptionalDefault: 0.8

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.

Valid values are between 0 and 2.

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 OpenAI with LiveKit Agents.