I recently built VoiceIQ — a complete Voice AI pipeline that listens to your voice, thinks using an LLM, and speaks the answer back. The best part? It costs nothing.

The Stack

• Whisper Large V3 (via Groq API) → Speech to Text.
• LLaMA 3.1 8B Instant (via Groq API) → Language Model.
• gTTS → Text to Speech.
• Streamlit → Web UI.

Feature: Conversation Memory
By default, every LLM call is stateless. I fixed this by building a ConversationMemory class that stores the last 8 turns and passes full history with every request.

Real Bug I Hit
Mid-development, Groq deprecated llama3-8b-8192. App threw a 400 error. Fix was simple — switch to llama-3.1-8b-instant. But it taught me to never hardcode model strings!

Why Groq over OpenAI?

Groq offers free tier with very fast inference. For a voice assistant, speed matters more than marginal accuracy gains.

Watch the Full Demo
I made a complete video walkthrough showing the live pipeline:
👉

Happy to discuss the implementation in comments!