Bloom

Hire a private AI tutor for anything you want to learn.

Your AI reads how you actually learn — and teaches the next lesson just for you.Built on Bloom's 2-Sigma research: 1-on-1 tutoring = top 2%.

🌐 Website · Chinese · English

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In 1984, educational psychologist Benjamin Bloom discovered that students receiving one-on-one tutoring scored 2 standard deviations (+2σ) above the classroom average — jumping to the top 2%. Bloom called this the "2 Sigma Problem": the effect is proven, but personal tutors don't scale.

Bloom solves this with AI. It generates a structured syllabus, delivers lessons one at a time, reads your annotations and feedback, then tailors the next lesson to your exact understanding level — just like a real tutor would.

Two Ways to Use

Mode	Setup	Best for
CLI	Claude Code + terminal	Power users who like Markdown editors
Web	Browser (React + FastAPI)	Visual learners, shareable setup

Both follow the same flow: syllabus → lesson → annotate → feedback → next lesson → evaluation → summary.

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Quick Start: CLI Mode

Requires only Claude Code. No backend.

git clone https://github.com/Li-Evan/Bloom.git
cd Bloom

# Install the tutor skill locally for this clone
mkdir -p .claude/skills
cp -R skills/bloom-tutor .claude/skills/

claude

Then say: Create a new folder and help me learn [any topic]

Or install it as a plugin (bundles bloom-tutor plus the learn-* skills) — in Claude Code:

/plugin marketplace add Li-Evan/Bloom
/plugin install bloom@li-evan

See GUIDE.md for the full walkthrough.

Quick Start: Web Mode

Prerequisites

• Python 3.11+ with uv
• Node.js 18+
• An OpenAI-compatible LLM API key (e.g. DashScope, OpenAI, etc.)

Setup

git clone https://github.com/Li-Evan/Bloom.git
cd Bloom

# Configure
cp .env.example .env
# Edit .env — fill in LLM_API_KEY

# Backend
cd backend && uv sync && uv run uvicorn app.main:app --reload --port 8000

# Frontend (new terminal)
cd frontend && npm install && npm run dev

Open http://localhost:5173. Click New Course, choose Topic, Source Upload, or Project Files, and start learning.

Docker

cp .env.example .env   # fill in API key
docker compose up -d   # visit http://localhost:3000

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How It Works

Topic Mode

Create course → AI generates syllabus + lesson 01
                        ↓
        Read lesson → highlight text → add annotations
                        ↓
        Write feedback → answer thought questions
                        ↓
        Click "Done Reading" → AI generates next lesson
        (answer review + annotation responses + new content)
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        Repeat until all mastery items checked ✅
                        ↓
        Auto-generate evaluation → then summary

Source Mode

Upload PDF / TXT / MD → AI generates syllabus + source-reading chapter
                          ↓
       Read source → highlight text → ask and get an immediate answer
                          ↓
       Click "Done Reading" → AI reads the full source + Q&A, then generates the next lesson
                          ↓
       Continue with the normal adaptive lesson flow