Python AI Voice Assistant & Agent - Full Tutorial

Introduction

In this comprehensive tutorial, we will learn how to develop an AI Voice Assistant using Python that works similarly to OpenAI's voice mode. This assistant will leverage OpenAI in the background and include additional functionalities, such as interacting with external environments like adjusting room temperatures.

Introduction to the AI Voice Assistant

The AI Voice Assistant we will create can respond to user queries using voice commands and can connect to various external functions. By tapping into libraries such as LiveKit and OpenAI, we can set up infrastructure for real-time voice communication.

Tools and Technologies

LiveKit

LiveKit is a real-time audio and video communication platform that is open-source and offers ultra-low latency streaming. It powers services for numerous reputable companies and is free to use under certain tiers. In this tutorial, we will set up a LiveKit application to manage communication between our voice assistant and users.

OpenAI

For AI functionalities, we will integrate OpenAI's powerful models. You'll need to create an API key to access its services, which may involve credit card information.

Setting Your Environment

Step 1: Create a Python Virtual Environment

To get started, we will create a virtual environment and install the necessary dependencies:

python3 -m venv AI
source AI/bin/activate  # Use the respective command for your OS
pip install livekit agents livekit plugins openai livekit das plugins solero python-dotenv

Step 2: Create Required Files

You’ll need the following files:

• main.py - The main application logic.
• api.py - For handler functions (e.g., managing temperatures).
• .env file - To store sensitive API keys and connection strings.

Step 3: Configure Environment Variables

Fill out your .env file with necessary keys including LiveKit and OpenAI API keys. You can obtain these from the respective platforms.

Building the Assistant

Step 4: Set Up Your Application

In main.py, import necessary modules and begin coding the AI Voice Assistant functionalities:

import asyncio
from dotenv import load_dotenv
from livekit.agents import VoiceAssistant
from livekit.plugins import openai, solero

async def entry_point(ctx):
    # Your assistant logic/code
    ...
    
if __name__ == "__main__":
    asyncio.run(entry_point(...))

Step 5: Create the AI Agent Functionality

Set up a separate file, api.py, to manage the assistant's functionalities. Create methods to get and set temperatures, structured as callable functions:

from livekit.agent import llm

class AssistantFunction(llm):
    ...
    @llm.callable
    def set_temperature(self, zone: str, temp: int):
        ...
    @llm.callable
    def get_temperature(self, zone: str):
        ...

Running the Voice Assistant

Once everything is coded:

1. Run your application using:

   python3 main.py start
   

2. Use the provided LiveKit playground to connect to your agent and interact with it.

Adding Agent Functionalities

To enhance your assistant, implement more functions for various agent tasks (like adjusting light controls or fetching weather data). Each function should be well-defined and annotated for the AI to recognize when to call them.

Test and Expand

After implementing, test your assistant's capabilities. You can assess its efficiency and explore adding more sophisticated functionalities, expanding the types of queries it can handle.

Conclusion

This tutorial illustrated how to develop a basic AI Voice Assistant with Python, focusing on setting up a foundational structure using LiveKit and OpenAI. With our assistant, users can enjoy voice-driven interactions with the potential for broader integrations.

Keywords

• Python
• AI Voice Assistant
• OpenAI
• LiveKit
• Voice Recognition
• Agent Functionality
• Environment Variables
• Real-time Communication

FAQ

Q1: What is LiveKit?
LiveKit is an open-source platform that enables low-latency audio and video streaming, ideal for creating real-time communication applications.

Q2: Can I use other AI models besides OpenAI?
Yes, you can integrate different language models or services based on your preferences and requirements.

Q3: Do I need programming experience to follow this tutorial?
While some familiarity with Python would be beneficial, the tutorial is constructed to guide you through each step in detail.

Q4: Is there a cost associated with using LiveKit or OpenAI?
LiveKit offers a free tier, but usage beyond certain limits may incur costs. OpenAI also requires an API key, which may have associated charges.

Q5: How can I expand the assistant's functionality?
You can add more functions or integrate APIs for various services, allowing for a richer interaction experience.