Solos debuts an even lighter version of its camera-less smart glasses

Introduction

In this tutorial, you'll learn how to create a basic voice-controlled AI assistant interface that mimics the functionality of the new Solos AirGo A6 smart glasses. These glasses eliminate cameras for a lighter design while relying on voice interactions with an AI assistant. We'll build a simple command-line interface that processes voice commands and responds with AI-generated text, similar to what the glasses might do.

Prerequisites

Before starting this tutorial, you'll need:

• A computer with Python installed (version 3.7 or higher)
• Internet access for downloading libraries
• Basic understanding of command-line operations
• Optional: Microphone and speakers for testing voice input

Step-by-Step Instructions

1. Set up your Python environment

First, create a new directory for our project and navigate to it:

mkdir airgo_assistant
 cd airgo_assistant

This creates a dedicated folder for our smart glasses AI assistant project.

2. Install required Python libraries

We'll need several libraries to handle voice recognition, text processing, and AI interactions:

pip install SpeechRecognition pyttsx3 openai

These libraries provide voice recognition, text-to-speech conversion, and OpenAI API integration respectively.

3. Create the main assistant class

Create a new file called airgo_assistant.py and add the following code:

import speech_recognition as sr
import pyttsx3
import openai
import os

class AirGoAssistant:
    def __init__(self):
        # Initialize speech recognition
        self.recognizer = sr.Recognizer()
        
        # Initialize text-to-speech
        self.tts_engine = pyttsx3.init()
        
        # Set up OpenAI API (you'll need to add your API key)
        openai.api_key = os.getenv('OPENAI_API_KEY')
        
        # Configure voice settings
        self.tts_engine.setProperty('rate', 150)
        self.tts_engine.setProperty('volume', 0.9)

    def listen(self):
        """Listen for voice commands"""
        with sr.Microphone() as source:
            print("Listening...")
            try:
                audio = self.recognizer.listen(source, timeout=5)
                command = self.recognizer.recognize_google(audio)
                print(f"You said: {command}")
                return command
            except sr.WaitTimeoutError:
                print("No speech detected")
                return None
            except sr.UnknownValueError:
                print("Could not understand audio")
                return None

    def speak(self, text):
        """Convert text to speech"""
        print(f"Assistant: {text}")
        self.tts_engine.say(text)
        self.tts_engine.runAndWait()

    def get_ai_response(self, prompt):
        """Get response from OpenAI API"""
        try:
            response = openai.ChatCompletion.create(
                model="gpt-3.5-turbo",
                messages=[{"role": "user", "content": prompt}]
            )
            return response.choices[0].message.content
        except Exception as e:
            return f"Sorry, I encountered an error: {str(e)}"

    def process_command(self, command):
        """Process voice command and generate response"""
        if command is None:
            return
        
        # Generate AI response
        response = self.get_ai_response(command)
        
        # Speak the response
        self.speak(response)

    def run(self):
        """Main loop to run the assistant"""
        print("AirGo Assistant is ready. Say 'hello' to start.")
        
        while True:
            command = self.listen()
            if command and 'hello' in command.lower():
                self.speak("Hello! How can I help you today?")
                # Listen for next command
                next_command = self.listen()
                self.process_command(next_command)
            elif command and 'quit' in command.lower():
                self.speak("Goodbye!")
                break

This creates the core assistant class that handles voice input, text-to-speech output, and AI responses.

4. Get your OpenAI API key

Visit https://platform.openai.com/ to create an account and generate your API key. This key allows our assistant to access OpenAI's language models.

5. Set up environment variables

Create a file called .env in your project directory and add your API key:

OPENAI_API_KEY=your_actual_api_key_here

Remember to replace your_actual_api_key_here with your real API key.

6. Test the assistant

Run your assistant with:

python airgo_assistant.py

When prompted, say "hello" and then ask a question like "What is artificial intelligence?" The assistant will listen, process your request, and respond with an AI-generated answer.

7. Customize the assistant

You can enhance your assistant by modifying the process_command method to handle specific commands. For example:

def process_command(self, command):
    if command is None:
        return
    
    if 'time' in command.lower():
        import datetime
        current_time = datetime.datetime.now().strftime("%H:%M")
        self.speak(f"The current time is {current_time}")
        return
    
    # Generate AI response for other commands
    response = self.get_ai_response(command)
    self.speak(response)

This modification adds a simple time-checking feature to your assistant.

Summary

In this tutorial, you've built a voice-controlled AI assistant that mimics the functionality of the Solos AirGo A6 smart glasses. You learned how to handle voice input using SpeechRecognition, convert text to speech with pyttsx3, and integrate with OpenAI's language models. The assistant can listen for commands, process them, and respond with intelligent AI-generated text. This project demonstrates the core technologies behind camera-less smart glasses that rely purely on voice interactions for user experience.

The simplicity of this implementation reflects how the new AirGo A6 glasses prioritize lightweight design and voice-based interaction over visual elements, making it a practical demonstration of the technology mentioned in the news article.