QM2 Evolution: From Static Engine to AI-Powered Intelligence
QM2 Evolution: From Static Engine to AI-Powered Intelligence
A few weeks ago, I introduced QM2 v1.0.25 — a high-performance CLI quiz engine built for speed and reliability. It was a solid foundation with 330+ tests, but it had one major “friction” point: content creation. Writing 50 questions about Kubernetes or React manually is tedious.
After taking a short detour to build my event-driven portfolio with Hugo and Supabase, I returned to QM2 to solve the content problem. Today, I’m excited to announce QM2 v1.1.0. I’ve officially added a “brain” to the engine by integrating Google Gemini AI.
The Vision: Zero-Friction Learning
The mission was simple: Go from a blank screen to a 20-question, high-quality quiz in under 10 seconds. By leveraging the Gemini 1.5 & 2.0 Flash models, QM2 can now generate comprehensive study materials on any topic instantly, directly from your terminal.
New Tech in the Stack
To support AI generation without compromising the “brutalist” speed of the CLI, I added:
- Google GenAI SDK: For seamless communication with Gemini models.
- Exponential Backoff Logic: Ensuring the app handles API rate limits gracefully.
- Advanced JSON Sanitization: A custom module that strips AI “chatter” and extracts pure, valid quiz schemas.
Engineering for Reliability (Part 2)
Adding AI shouldn’t mean breaking the 84% test coverage. I had to solve two main challenges:
Mocked AI Testing: I used unittest.mock to simulate Gemini API responses. This allows the CI/CD pipeline to verify JSON parsing and fallback logic without needing a real API key or spending tokens.
The Fallback Chain: Reliability is key. If the Gemini 2.0 Flash model is busy or hits a limit, QM2 automatically retries with 1.5 Flash or 1.5 Pro. The user experience remains uninterrupted.
New AI Features
Topic-to-Quiz: Just enter a topic like “Advanced Python Decorators” or “World War II History”.
Multi-Type Support: Unlike simple AI wrappers, QM2 forces the AI to generate all 4 supported types: Multiple Choice, True/False, Fill-in-the-blank, and even complex Matching pairs.
Smart Retries: Built-in logic to handle network jitters and API quotas.
Quick Start with AI
If you already have QM2, just upgrade:
pip install --upgrade qm2Set your key and run:
export GEMINI_API_KEY="your_google_ai_key"
qm2Fulfilling the Roadmap
In my previous QM2 deep dive, I promised AI integration. With v1.1.0, that promise is kept. The core engine is now more than just a player; it’s a creator. This bridges the gap between a simple CLI tool and a complete educational platform.
Links & Support
QM2 is now officially AI-powered. If you find it useful for your study sessions, a ⭐ on GitHub would be the best way to support the project!
What’s your take on AI-generated educational content? Is it the future of personalized learning? Let’s talk in the comments!
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