Video by Hugging Face via YouTube
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.
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🤓 *Topics Covered*
– Tau terminal coding agent overview
– Coding agent architecture layers
– Hugging Face inference providers setup
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🔗 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`
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👋 Connect with me
– My website: https://alejandro-ao.com/
– X (Twitter): https://x.com/_alejandroao
– LinkedIn: https://www.linkedin.com/in/alejandro-ao/
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⏱️ 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