Building a Voice-Controlled Local AI Agent with Whisper, Groq & Streamlit

Building a Voice-Controlled Local AI Agent with Whisper, Groq & Streamlit For my Mem0 AI/ML internship assignment, I built a fully working voice-controlled AI agent that accepts audio input, classifies intent, executes local tools, and displays everything in a clean UI. Here's how I built it and what I learned. What It Does You speak (or type) a command → the agent transcribes it → classifies your intent → executes the right action → shows the result. All in one pipeline. Supported intents: create_file — creates a new file in the output/ folder write_code — generates code using LLM and saves it summarize — summarizes provided text general_chat — conversational Q&A compound — multiple commands in one utterance Architecture Audio Input → STT (Whisper/Groq) → Intent Classification (LLM) → Tool Execution → Streamlit UI Tech Stack Component Tool Speech-to-Text Groq Whisper API Intent + Generation Groq (llama-3.3-70b) UI Streamlit Language Python Model Choices & Why STT — Groq Whisper API :