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This tutorial demonstrates how to build a real-time voice chat console application that compares three lightweight AI models: Microsoft Phi-2, TinyLlama, and Qwen2-1.5B. Follow along as these compact LLMs handle speech recognition, text generation, and text-to-speech functionality in real-time, showcasing both their capabilities and limitations. Learn the complete Python implementation using speech_recognition for microphone input, the transformers library for text generation, and gTTS with pygame for audio responses. The comprehensive walkthrough covers the entire development process and provides guidance on customizing the application for your own use. Perfect for AI enthusiasts, Python developers, or anyone interested in exploring the practical applications and constraints of small-scale language models in interactive voice applications.
