Overview
Telnyx provides access to Llama 3.1 and other models through their inference API. These models are multilingual and text-only, making them suitable for a variety of agent applications.
Usage
Install the OpenAI plugin to add Telnyx support:
pip install "livekit-agents[openai]~=1.2"
pnpm add @livekit/agents-plugin-openai@1.x
Set the following environment variable in your .env file:
TELNYX_API_KEY=<your-telnyx-api-key>
Create a Telnyx LLM using the with_telnyx method:
from livekit.plugins import openaisession = AgentSession(llm=openai.LLM.with_telnyx(model="meta-llama/Meta-Llama-3.1-70B-Instruct",),# ... tts, stt, vad, turn_detection, etc.)
import * as openai from '@livekit/agents-plugin-openai';const session = new voice.AgentSession({llm: openai.LLM.withTelnyx({model: "meta-llama/Meta-Llama-3.1-70B-Instruct",}),// ... 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 links in the Additional resources section.
Model to use for inference. To learn more, see supported models.
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.
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.
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 links provide more information about the Telnyx LLM integration.
