How to build a real-time AI assistant (with voice and vision)

How to Build a Real-Time AI Assistant (with Voice and Vision)

As AI technologies rapidly evolve, one intriguing arena is the development of real-time AI assistants that can interact through both voice and vision. In this article, I will guide you through the step-by-step process of creating such an AI assistant using various APIs like OpenAI's GPT-4, Deepgram, and a platform called Life Kit. This tutorial aims to replicate an AI assistant that can converse, recognize objects, and even respond to visual prompts.

Introduction

In an earlier video, I demonstrated an AI assistant constructed using a microphone and webcam, and people loved it. However, a company named Life Kit reached out to me, challenging me to create something even better using their platform. Life Kit supports OpenAI's ChatGPT assistant and provides incredible functionality for developing realistic AI agents.

Getting Started

Below are the details for setting up your development environment and initializing the AI assistant:

1. Create a Virtual Environment: This involves installing the necessary libraries and setting up environment variables.
2. APIs Required: You'll need API keys from Life Kit, Deepgram (for audio-to-text), and OpenAI (for using GPT-4).

Source Code Overview

The core of this AI assistant consists of 139 lines of code with detailed comments for ease of understanding. Here's an overview of some critical parts:

1. Initializing the Chat Context: The chat context includes system messages that define the assistant's personality.
2. Designing the Assistant Class: This class supports function calling and other essential features. It extends the FunctionContext class, enabling the assistant to call functions as needed.
3. Handling User Queries: The assistant analyzes whether an image is required to answer a question. If needed, it calls a function that captures an image and re-queries GPT-4 with the image and text.

Running the Assistant

After setting up your code, use a playground provided by Life Kit to connect your microphone and webcam to the AI assistant. The assistant will respond to both voice inquiries and visual prompts, displaying its ability to analyze images for providing accurate responses.

Practical Demonstration

Below are some fun real-time interactions you can try:

1. Voice Interaction: Ask the assistant simple queries like its name or to tell a joke.
2. Visual Interaction: Show objects to the webcam and ask the assistant to identify them. The assistant will capture the image and use it for its analysis.

Conclusion

By following this tutorial, you can build a dynamic AI assistant capable of real-time voice and vision interactions. For more details, you can refer to the source code on GitHub linked in the description.

Keywords

• AI Assistant
• Real-Time Interaction
• Voice Recognition
• Image Analysis
• OpenAI GPT-4
• Deepgram
• Life Kit

FAQ

Q1: What APIs are necessary for building the AI assistant? A: You'll need API keys from Life Kit, Deepgram, and OpenAI.

Q2: How do I set up my development environment? A: Create a virtual environment, install necessary libraries, and set up environment variables provided by Life Kit, Deepgram, and OpenAI.

Q3: What languages and libraries are used in the source code? A: The source code is written in Python and uses libraries like Life Kit's SDK, Deepgram SDK, and OpenAI's GPT-4 API.

Q4: Can the assistant handle both audio and visual queries simultaneously? A: Yes, the assistant can take voice commands and analyze visual inputs based on the context of the user's queries.

Q5: How do function calls work in this AI assistant? A: The assistant uses function calls to determine if additional data, like images, are needed to answer a query. This helps optimize data usage and improve response accuracy.

Q6: Where can I find the complete source code for this AI assistant? A: The source code is available on GitHub, linked in the video description.

By following this detailed guide, you can replicate and customize your AI assistant to enhance its functionality further. Enjoy building your real-time AI assistant!