hkuds/deeptutor

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🤝 We welcome any kinds of contributing! Vote on roadmap items or propose new ones at Roadmap, and see our Contributing Guide for branching strategy, coding standards, and how to get started.

📦 Releases

[2026.6.30] v1.4.15 — A native Mattermost channel for Partners, plus fixes so Guided Learning multiple-choice questions grade correctly and a configured zero chunk overlap is honored.

[2026.6.29] v1.4.14 — Click an assigned partner to chat in one step, Deep Research flags partial reports, LightRAG indexes without MinerU, FAISS handles non-ASCII paths, and PocketBase sessions are isolated per user.

[2026.6.27] v1.4.13 — Partners support non-Latin names and become assignable to users, logos render after login (#599), tiny knowledge bases retrieve reliably, and containers start cleanly under rootless Podman.

[2026.6.24] v1.4.12 — A new LightRAG Server retrieval engine, a lightweight PyMuPDF4LLM parsing engine, and a FAISS vector backend that makes large knowledge-base retrieval dramatically faster.

📰 News

• 2026-05-22 🌐 Official docs site live at deeptutor.info — guides, references, and capability tours in one place.
• 2026-04-19 🎉 20k stars in 111 days! Thank you for the support toward truly personalized, intelligent tutoring.
• 2026-04-10 📄 Our paper is live on arXiv — read the preprint for the design and ideas behind DeepTutor.
• 2026-02-06 🚀 10k stars in just 39 days! A huge thank you to our incredible community.
• 2026-01-01 🎊 Happy New Year! Join our Discord, WeChat, or Discussions — let’s shape DeepTutor together.
• 2025-12-29 🎓 DeepTutor is officially released!

✨ Key Features

DeepTutor is an agent-native learning workspace that connects tutoring, problem solving, quiz generation, research, visualization, and mastery practice in one extensible system.

• One runtime for every mode — Chat, Quiz, Research, Visualize, Solve, and Mastery Path run on the same agent loop, so you switch the objective, not the engine, and context moves with the learner.
• Connected learning context — Knowledge bases, books, Co-Writer drafts, notebooks, question banks, personas, and Memory stay available across every workflow instead of living in isolated tools.
• Subagents and Partners — consult a live Claude Code, Codex, or Partner from any turn (or import their past conversations), and run persistent IM companions on the same brain.
• Multi-engine knowledge — versioned RAG libraries across LlamaIndex, PageIndex, GraphRAG, LightRAG, or a linked Obsidian vault, with pluggable document parsing.
• Extensible tools and skills — built-in tools, MCP servers, image / video / voice generation models, and installable community skills from EduHub.
• Inspectable memory — L1 traces, L2 surface summaries, and L3 synthesis make personalization visible and editable, with a Memory Graph that traces every claim back to its evidence.

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🚀 Get Started

DeepTutor ships four installation paths. They all share one workspace layout: settings live in data/user/settings/ under the directory you launch from (or under DEEPTUTOR_HOME / deeptutor start --home if you set one explicitly). For the full app, the recommended flow is pick a workspace directory → install → deeptutor init → deeptutor start.

The local deeptutor-cli install ships no Web assets or server dependencies. Keep the source checkout around — the editable install points to it. To add the Web app later, install the PyPI package (Option 1) and run deeptutor init + deeptutor start from the same workspace.

📖 Explore DeepTutor

Start with the main surfaces you will use day to day: Chat, Partners, My Agents, Co-Writer, Book, Knowledge Center, Learning Space, Memory, and Settings. The tour then covers Multi-User deployments for shared, isolated workspaces.

⌨️ DeepTutor CLI — Agent-Native Interface

One deeptutor binary, two ways in: an interactive REPL for people who live in the terminal, and structured JSON for other agents that drive DeepTutor as a tool. Same capabilities, tools, and knowledge bases either way.

🧩 Ecosystem — EduHub & the Skills Community

DeepTutor skills use the open Agent-Skills format — a folder with a SKILL.md playbook (YAML frontmatter + Markdown) and optional reference files. Nothing about it is DeepTutor-specific, so any registry that speaks the format becomes a source for your library. DeepTutor ships with EduHub — our own education-focused skill registry — wired in as the default hub.

🌐 Community

📮 Contact

DeepTutor is an open-source project led by Bingxi Zhao within the HKUDS Group, and it iterates in a fully open-source form, built together with the community. So far, we DO NOT have paid online products of any form. Feel free to reach out at [email protected] for discussions, ideas, or collaboration.

🙏 Appreciation

Heartfelt thanks to Chao Huang, director of the Data Intelligence Lab @ HKU, and to our HKUDS labmates for their warm support — especially Jiahao Zhang, Zirui Guo, and Xubin Ren. We’re also deeply grateful to the open-source community: your stars, issues, pull requests, and discussions shape DeepTutor every single day.

DeepTutor also stands on the shoulders of outstanding open-source projects that gave us both tools and inspiration:

🗺️ Roadmap & Contribute

We want DeepTutor to keep iterating and improving — and ultimately to become a gift we give back to the open-source community. Our roadmap is updated continuously; vote on items there or propose new ones. If you’d like to contribute, see the Contributing Guide for branching strategy, coding standards, and how to get started.