🛠️ QuizDSL Studio: AI-Powered Model-Driven Framework

QuizDSL Studio is an advanced end-to-end ecosystem for Model-Driven Software Development (MDSD). It leverages a custom Domain-Specific Language (DSL) built with Xtext, orchestrated by an ASP.NET Core 10 management studio, and powered by Local LLMs (Ollama) to transform natural language prompts into fully functional Python/Flask web applications.

📂 Repository Structure

1. AiModel

The AI intelligence layer. This folder contains the blueprints for the LLM to understand and write our custom DSL.

Modelfile: The configuration to build the quiz-master model (base on gemma3:12b) in Ollama.
dotnethub.quiz: A real-world example of DSL code generated by the AI based on a complex Farsi prompt for a .NET Developer assessment platform.
dotnethub/: The final generated source code (Python/Flask) produced from the DSL.

2. EclipseWorkSpace

The core grammar and language infrastructure.

org.example.quiz: The base project containing the Xtext Grammar (QuizDSL.xtext) and the Ecore Metamodel.
QuizDSLGenerator.java: The Xtend-based transformation engine that converts DSL models into Python code.
QuizCompiler.java: The source for the standalone compiler tool used to build the .jar binary.
model/generated/: Contains the Ecore Metamodel and the Generated Class Diagram (quizDSL class diagram.png).

3. ModelManager

The "Studio" — A modern web dashboard built with ASP.NET Core 10.

Orchestration: Manages the lifecycle of a quiz: AI Prompting → DSL Generation → Java Compilation → Python Execution.
Background Jobs: Uses Hangfire to manage long-running compilation and AI tasks.
Static Assets: Contains QuizCompiler.jar (the transpiler) and the UI built with Bootstrap.

4. runtime-EclipseApplication

The Eclipse Runtime workspace used during development to test the DSL editor, providing live validation and syntax highlighting for .quiz files.

⚙️ Technical Architecture

The project implements a 4-tier pipeline:

Natural Language Input: User provides a prompt (e.g., "Create a Senior .NET quiz with Vazir font and dark theme").
AI Generation (Ollama): The quiz-master model interprets the prompt and writes syntactically correct .quiz code.
DSL Compilation (Java): The QuizCompiler.jar (Xtext/Xtend) parses the model and generates a Python/Flask web app.
Deployment: The Studio executes the Python app on a dedicated port and captures an automated preview screenshot.

🌍 Localization & Extensibility

The current implementation is pre-configured for Persian (RTL) environments. While it's not a "one-click" setting yet, the framework is architecturally ready for global use:

AI Adaptability: To switch languages, the Modelfile can be edited to retrain the LLM's prompting logic for English DSL generation.
Code Generation: The Xtend Transformer code is modular, allowing developers to modify the templates to generate LTR layouts and English UI components.
Customization: By editing the core generator logic and the AI blueprints, the entire pipeline can be repurposed for any language or regional requirement.

🎥 Live Demo

See the QuizDSL Studio in action: From AI prompting to automated DSL generation and web deployment.

ModelManager.mp4

💡 Visual Overview:

DSL-Generated Live Demo: Watch how the DSL transforms into a functional website.

Live Monitoring & Process Control: Real-time logs and easy build management.

Another Perspective: Switching between different generated models seamlessly.

📊 Metamodel & Grammar

The language is formally defined using an Ecore metamodel. You can find the visual representation here:

The grammar supports:

Multiple Quiz levels (Junior, Mid-level, Senior).
Dynamic scoring and variable time limits per difficulty.
UI Customization (Fonts like "Vazirmatn", Themes, Shuffling).

🚀 Installation & Setup

Prerequisites

Ollama: For AI features.
Java JRE 21+: To run the compiler.
ASP.NET Core 10 Runtime: To run the Studio.
Python 3.x: To run the generated apps.

Step 1: Build the AI Model

cd AiModel
ollama create quiz-master -f Modelfile

Step 2: Configure the Studio

Navigate to ModelManager/.
Ensure QuizCompiler.jar is present in the root.
Run the application:

dotnet run --urls "http://localhost:5005"

Step 3: Run a Build

Access the dashboard at http://localhost:5005. Create a "New Model", enter your prompt, and click Generate by AI followed by Build Model.

📝 Example Input (Prompt)

"A platform named 'DotNetHub' for assessing developers. Include 3 levels: Basic (Junior), Medium (Mid-level), and Advanced (Senior). 5 questions each. Scoring out of 20. Advanced level must be very difficult. Time limits: 3, 4, and 5 minutes respectively. Use 'Vazirmatn' font and a .NET-themed UI."

🛠 Built With

Xtext/Xtend - Language Development & Code Generation
ASP.NET Core 10 - Management Dashboard
Ollama (LLM) - Local AI Orchestration
Python/Flask - Target Runtime Environment
Hangfire - Background Job Processing

Developed by Ali Soleimani

AliSoleimaniNet/QuizDSL-Studio