🧩 Leetdle

A daily coding challenge game inspired by Wordle — but for code. Every day at midnight (Paris time), a new AI-generated coding challenge is published. Players solve it in Python, JavaScript, TypeScript, or Rust, with their code executed in secure, sandboxed Docker containers.

---

🎯 Project Overview

Leetdle is a full-stack web application where users:

1. Read a daily coding challenge with description, examples, and test cases
2. Write a solution in their preferred language using an in-browser Monaco editor
3. Submit their code, which runs against hidden test cases inside an isolated Docker container
4. Compete — solve it in fewer tries and less time, then share results

The challenge is automatically generated by AI (GPT-4.1), validated by running AI-generated solutions against the test cases, and saved to a SQLite database — all without human intervention.

---

🏗️ Architecture

graph TB
    subgraph Frontend["Frontend (Next.js)"]
        SSR["Server-Side Rendering<br/>page.tsx"]
        GC["GameClient.tsx<br/>Monaco Editor + UI"]
    end

    subgraph Backend["Backend (Hono + Node.js)"]
        API["REST API<br/>/api/challenge<br/>/api/execute<br/>/api/submissions"]
        AI["AI Service<br/>GPT-4.1"]
        EXEC["Executor Service"]
        FETCH["Fetcher Job<br/>Midnight Scheduler"]
        DB["SQLite<br/>Drizzle ORM"]
    end

    subgraph Executors["Docker Executor Containers"]
        PY["🐍 leetdle-python<br/>Alpine + Python3"]
        JS["📜 leetdle-javascript<br/>Alpine + Node.js"]
        TS["🔷 leetdle-typescript<br/>Alpine + Node.js + ts-node"]
        RS["🦀 leetdle-rust<br/>rust:alpine + Cargo"]
    end

    SSR -->|"fetch /api/challenge/daily"| API
    GC -->|"POST /api/execute"| API
    GC -->|"POST /api/submissions"| API
    API --> EXEC
    API --> DB
    FETCH -->|"Midnight Paris"| AI
    AI -->|"Validate solutions"| EXEC
    FETCH --> DB
    EXEC -->|"docker run --rm"| PY
    EXEC -->|"docker run --rm"| JS
    EXEC -->|"docker run --rm"| TS
    EXEC -->|"docker run --rm"| RS

    style Frontend fill:#1a1a2e,stroke:#7c3aed,color:#fff
    style Backend fill:#1a1a2e,stroke:#06b6d4,color:#fff
    style Executors fill:#1a1a2e,stroke:#ef4444,color:#fff

---

⚙️ Challenge Generation & Validation Pipeline

Every day at midnight (Europe/Paris), the Fetcher Job triggers a fully automated pipeline:

flowchart TD
    A["⏰ Midnight Paris<br/>Fetcher Job triggers"] --> B{"Today's challenge<br/>exists?"}
    B -->|Yes| SKIP["Skip — already done"]
    B -->|No| C["Request challenge from<br/>GPT-4.1"]

    C --> D["Parse JSON response<br/>title, description, difficulty,<br/>testCases, solutions, stubs"]

    D --> E["🔄 Validation Loop<br/>(for each language)"]

    E --> F["Generate AI test runner<br/>for language"]
    F --> G["Run AI solution in<br/>Docker sandbox"]
    G --> H{"All tests pass?"}
    H -->|Yes| I["✅ Language validated"]
    H -->|No| J{"Fix attempts<br/>remaining?"}
    J -->|Yes| K["Ask AI to fix<br/>the solution"]
    K --> G
    J -->|No| L["❌ Language failed"]

    I --> M{"All 4 languages<br/>passed?"}
    L --> M
    M -->|Yes| N["💾 Save to SQLite"]
    M -->|No| O{"Generation attempts<br/>remaining? (max 3)"}
    O -->|Yes| C
    O -->|No| P["🚨 Generation failed"]

    style A fill:#7c3aed,stroke:#7c3aed,color:#fff
    style N fill:#22c55e,stroke:#22c55e,color:#fff
    style P fill:#ef4444,stroke:#ef4444,color:#fff

Key Details

Step	Description
AI Prompt	GPT-4.1 receives a detailed prompt with format requirements, past challenge titles (to avoid duplicates), and rules for test case diversity
Test Runner Generation	A separate AI call generates a per-language test runner script with a {{USER_CODE}} placeholder
Validation	AI-generated solutions are executed inside the same Docker sandbox used for user submissions
Fix Loop	If a solution fails, the AI gets the error message and retries up to 2 times per language
Retry	If any language still fails, the entire challenge is discarded and regenerated (up to 3 total attempts)

What Gets Stored (per challenge)

Field	Description
title	Challenge name
description	Markdown-formatted problem statement
difficulty	Easy / Medium / Hard
testCases	JSON array of {input, expected} objects
stubs	Per-language starter code shown in the editor
solutions	AI-validated solutions (viewable after solving/failing)
languageTests	Per-language test runner scripts

---

🔒 Secure Docker Isolation

User-submitted code runs in ephemeral Docker containers with multiple layers of security:

flowchart LR
    subgraph Backend
        EXEC["Executor<br/>Service"]
    end

    subgraph Sandbox["Ephemeral Container"]
        CODE["User Code<br/>Execution"]
    end

    EXEC -->|"docker run --rm ..."| Sandbox

    style Sandbox fill:#7f1d1d,stroke:#ef4444,color:#fff
    style Backend fill:#1a1a2e,stroke:#06b6d4,color:#fff

Security Flags

Flag	Purpose
--rm	Container is automatically deleted after execution
--network none	No internet access — code cannot make outbound requests
--cap-drop ALL	All Linux capabilities are dropped (no ptrace, chown, kill, etc.)
--memory 128m/256m	Hard memory limit (128 MB for Python/JS, 256 MB for TS/Rust)
--cpus 0.5/1.0	CPU throttling (0.5 cores for Python/JS, 1.0 for TS/Rust)
Non-root user	All containers run as the leetdle user, not root
20s timeout	The backend kills the container after 20 seconds if it hasn't exited

Executor Images

Each language has its own minimal Alpine-based Docker image:

Image	Base	Installed
leetdle-python	alpine:latest	python3
leetdle-javascript	alpine:latest	nodejs
leetdle-typescript	alpine:latest	nodejs, npm, typescript, ts-node
leetdle-rust	rust:alpine	musl-dev, pre-compiled serde/serde_json deps

These images are pre-built by Docker Compose but never run as daemons — they only serve as base images for the ephemeral docker run containers spawned by the backend.

---

🌐 Frontend ↔ Backend Communication

Server-Side (SSR)

The Next.js page.tsx fetches today's challenge server-side at render time:

page.tsx  →  GET http://backend:5000/api/challenge/daily  →  renders GameClient

This uses Docker's internal DNS (backend hostname) since both containers are on the same leetdle_web bridge network.

Client-Side (Browser)

The GameClient.tsx component makes API calls from the browser via Next.js rewrites:

Action	Method	Endpoint
Run code	POST	/api/execute
Save submission	POST	/api/submissions
Get challenge stats	GET	/api/submissions/stats/:id
Get solution	GET	/api/challenge/solution/:id
List all challenges	GET	/api/challenge/all

The next.config.js rewrites /api/* to http://backend:5000/api/*, so the browser's requests are proxied through the frontend container to the backend.

---

🚀 Getting Started

Prerequisites

• Docker & Docker Compose
• An OpenAI API key (for challenge generation)

Setup

# 1. Clone the repository
git clone <repo-url> && cd leetdle

# 2. Create a .env file
cp .env.example .env
# Edit .env and set your OPENAI_API_KEY

# 3. Build and start everything
docker compose up --build -d

# 4. Open in your browser
# http://localhost:3000

On first startup, the backend will automatically generate today's challenge using the AI pipeline. This takes ~1-2 minutes as it validates solutions across all 4 languages.

Project Structure

leetdle/
├── frontend/          # Next.js 14 app
│   ├── app/
│   │   ├── page.tsx           # SSR entry — fetches daily challenge
│   │   ├── GameClient.tsx     # Main game UI (Monaco editor, timer, modals)
│   │   ├── StatsButton.tsx    # Landing page stats component
│   │   └── challenges/       # Previous challenges page
│   └── Dockerfile
├── backend/           # Hono + Node.js API
│   └── src/
│       ├── index.ts           # App entrypoint
│       ├── routes/            # API route handlers
│       ├── services/
│       │   ├── ai.ts          # OpenAI API integration
│       │   ├── executor.ts    # Docker container orchestration
│       │   ├── challenge.ts   # Challenge CRUD + validation pipeline
│       │   └── submission.ts  # Submission tracking & stats
│       ├── jobs/
│       │   └── fetcher.ts     # Midnight scheduler
│       └── db/
│           ├── schema.ts      # Drizzle ORM schema
│           └── index.ts       # Database connection
├── executor/          # Language-specific Docker images
│   ├── python/Dockerfile
│   ├── javascript/Dockerfile
│   ├── typescript/Dockerfile
│   └── rust/Dockerfile
├── docker-compose.yml
└── .env.example