Introducing Tau: An Educational Coding Agent
Meet Tau — a small, readable coding agent written in Python. In this quick tour, I introduce Tau, show how to install and run it, configure model providers (Hugging Face Inference Providers, GLM 5.2, Minimax, Kimi), resume durable sessions, and walk through its three-layer architecture: tau_ai (provider-neutral model streaming), tau_agent (the reusable agent loop/harness), and tau_coding (the TUI, tools, sessions, and coding-agent environment). Tau is designed as an educational reference inspired by Pi — minimal, modular, and easy to build on. If you want to understand how coding agents actually work, this is a great place to start. --- 🤓 *Topics Covered* - Tau terminal coding agent overview - Coding agent architecture layers - Hugging Face inference providers setup --- 🔗 Links - Tau website: https://twotimespi.dev - Tau repo (contributions welcome!): https://github.com/huggingface/tau - Pi (architectural inspiration): https://pi.dev - Install Tau: `uv tool install tau-ai` --- 👋 Connect with me - My website: https://alejandro-ao.com/ - X (Twitter): https://x.com/_alejandroao - LinkedIn: https://www.linkedin.com/in/alejandro-ao/ --- ⏱️ Timestamps 0:00 Introduction 2:04 Quick tour: install & launch 3:47 Login & model providers 4:19 Select a model 4:32 Scoped models 5:27 Sessions & resume 5:56 Thinking levels 6:33 Contributing & upcoming tutorials 7:34 Architecture: tau_ai, tau_agent, tau_coding 8:58 Closing
