Build A Talking AI with LLAMA 3

In this video, viewers are guided through the process of building a talking AI using LLAMA 3, AssemblyAI, and ElevenLabs. The tutorial, led by Smitha, starts by demonstrating the final product, where LLAMA 3 interacts with users through speech. The project comprises three main components: real-time speech-to-text with AssemblyAI, language processing with LLAMA 3 via Ollama, and text-to-speech conversion using ElevenLabs. AssemblyAI’s streaming speech-to-text service is highlighted for its high accuracy and low latency, essential for creating an effective AI voice bot. The tutorial emphasizes the importance of the real-time final transcript from AssemblyAI, which signals when to pass the transcript to the large language model. Ollama is introduced as the tool for running LLAMA 3 locally, and ElevenLabs is used for generating speech from text. The video then walks through the installation of necessary Python libraries, including AssemblyAI, PortAudio, and ElevenLabs, and provides instructions for downloading and setting up Ollama. Smitha explains how to initialize API keys for AssemblyAI and ElevenLabs and create a transcription object to store the conversation. The tutorial also covers writing code for real-time speech-to-text, handling real-time final transcripts, and generating AI responses with LLAMA 3. The process of streaming audio with ElevenLabs to minimize latency is explained, and the video concludes with a demonstration of running the AI assistant, ensuring all functions are correctly implemented. Viewers are encouraged to add humor and other enhancements to make their AI voice chatbot more engaging.