Building a Voice-Controlled Local AI Agent with Whisper, LLaMA 3 and Streamlit

📰 Dev.to AI

Learn to build a voice-controlled local AI agent using Whisper, LLaMA 3, and Streamlit to convert speech to text and execute actions

intermediate Published 13 Apr 2026

Action Steps

Install Whisper and LLaMA 3 libraries using pip
Configure Streamlit to create a web UI for the AI agent
Build a speech-to-text pipeline using Whisper
Integrate LLaMA 3 to understand user intent and execute actions
Test the AI agent using a microphone or uploaded audio file

Who Needs to Know This

This project benefits developers and data scientists who want to explore voice-controlled AI agents and build local machine learning models. It's ideal for teams working on voice assistants or automated systems

Key Insight

💡 You can build a voice-controlled AI agent that runs entirely on your local machine using open-source libraries like Whisper and LLaMA 3