I built the AI-Voice-Assistant repository on my GitHub. It is a voice‑based learning app that uses Next.js for the frontend, FastAPI + Uvicorn for the backend, MySQL + SQLAlchemy for storage, and the Groq API (llama-3.3-70b‑versatile) as the LLM. The browser handles speech‑to‑text and text‑to‑speech via the Web Speech API (STT + TTS).
profile.github.repo.AI-Voice-Assistant.backend = FastAPI + Uvicorn
profile.github.repo.AI-Voice-Assistant.database = MySQL + SQLAlchemy
profile.github.repo.AI-Voice-Assistant.llm = Groq API (llama-3.3-70b-versatile)
profile.github.repo.AI-Voice-Assistant.voice_handling = Web Speech API (STT + TTS)
profile.github.repo.AI-Voice-Assistant.start_date = 2026-03
profile.github.repo.AI-Voice-Assistant.last_update = 2026-03
Setup commands: cd backend python3 -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate pip install fastapi uvicorn sqlalchemy pymysql openai python-dotenv cp .env.example .env # then fill in your Groq key and DB password uvicorn main:app --reload cd ../frontend npm install cp .env.local.example .env.local npm run dev