DeepTutor

by Data Intelligence Lab@HKUAppLearn a topic

Turns your notes and documents into a personal tutor that explains, quizzes and plans

About DeepTutor

An open-source learning workspace that runs on your computer and opens in the browser. Add your study materials and it explains them, solves problems, makes quizzes and study books, and remembers your preferences.

For StudentsSelf-learnersLifelong learners

Made by Data Intelligence Lab@HKU

The Data Intelligence Lab at HKU in Hong Kong is a research group that publishes open-source AI projects on GitHub.

Stars: ★ 52k
License: Apache-2.0
Cost: Usage-based
Platforms: Mac · Win · Linux
Runs: Local · Self-hosted

Screenshots

From the project's own repository · 3 images, swipe or use the arrows.

The DeepTutor home screen with a chat box and Explain, Solve, Practice, Plan and Research shortcuts — Image: Data Intelligence Lab@HKU (Apache-2.0). Original file

A DeepTutor chat explaining the Fourier transform with a formula and practical uses — Image: Data Intelligence Lab@HKU (Apache-2.0). Original file

Overview

DeepTutor is an open-source learning workspace you run on your own computer and use in the browser. Add your study materials, then work with a tutor that explains them, solves problems step by step, makes quizzes, builds interactive study books and plans a mastery path. It keeps an editable memory of your preferences across sessions. It suits students and self-learners who want an AI tutor grounded in their own materials.

Tutoring, quizzes, study books and research share one workspace and one memory, so it can build on what you already studied.

Try these first

Start with the first one: it is a small task you can check easily.

Explain the main idea of [topic] using only the document I added, and tell me where it says so.First try · uses model credits
Make a 5-question quiz on [chapter] and show me the answers after I try.
Solve this problem step by step and explain each step: [paste problem]
Build a study book on [topic] with short chapters and a quick check in each.

Example prompts written by Agent Flows Hub.

Features

From the creator's documentation.

Feature	What it does	Runs
Tutoring chat	Explains, solves step by step and researches, with your materials as context	Your model service
Knowledge bases	Builds searchable libraries from the documents you add so answers can draw on them	Your files + model
Quizzes and practice	Question banks, quick checks and a Mastery Path for practice	Your model service
Study books	Interactive books with chapters, quizzes and widgets, exportable to Markdown	Your model service
Memory	A visible, editable record of your preferences and past sessions	Your computer
Task Board	Track study tasks in To do, In progress and Done; no model needed	Your computer

Good to know

Study a subject from your own notes, papers or textbooks. DeepTutor builds knowledge bases from the files you add and uses them to explain topics, set quiz questions and build study books you can work through.

Limits

DeepTutor does not include a model. You set up a language model provider in Settings, and knowledge-base search may need a separate embedding provider.
Answers can still drop an earlier instruction or cite weak evidence; the project keeps a checklist for reporting such cases. Check explanations against your source material.

Notes by Agent Flows Hub (original project name: DeepTutor), written from the creator's documentation, not from running it ourselves. DeepTutor README · DeepTutor documentation

Stuck setting it up?

Tell us what happened. We take a look first; if it needs paid work, you get an estimate before anything starts.

Get help

How to start

Install itPaste the install request into an AI agent you already use, or run the official command yourself or follow the official guide.macOS, Windows, Linuxdocker run --rm --name deeptutor \ -p 127.0.0.1:3782:3782 \ -v deeptutor-data:/app/data \ ghcr.io/hkuds/deeptutor:latest
macOS, Windows, Linuxmkdir -p my-deeptutor && cd my-deeptutor pip install -U "deeptutor[full]" deeptutor init # prompts for ports + LLM provider + optional embedding/search deeptutor start # starts backend + frontend; keep the terminal open
Open itFollow the first-run steps in the app.
Give it a first taskStart the Docker trial, add a model provider in Settings, then ask it to explain one topic from a short document you add. Compare the answer with the document.

Steps follow the creator's instructions. The request tells your agent to read them first and wait for your OK.

Before you start

A computer with macOS, Windows or Linux.
Docker, or Python 3.11 to 3.14 with Node.js 20 or newer
An API key for a language model service, or a local model such as Ollama
Pay per use. The AI service it calls charges for what you use.

Details

Made by: Data Intelligence Lab@HKU
License: Apache-2.0 Terms
Platforms: macOS, Windows, Linux
Runs on: Your computer, Self-hosted server

View source Official docs Report a problem

For AI agents

This page as a Markdown install brief:

/en/library/deeptutor/install.md

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