The original title is "I built AutoML for quantum machine learning — here's the architecture"

Short summary

QuOptuna is an open-source AutoML tool for quantum machine learning that searches across 21 quantum and classical classifiers using Optuna, with built-in fairness auditing via fairlearn and SHAP explainability. It bundles a Next.js frontend into a Python wheel so users run it with a single command—no Node.js required. The tool is a PhD project at Western Michigan University, currently in beta with simulator-only quantum backends.

• •AutoML tool searching 17 quantum + 4 classical classifiers with conditional Optuna search spaces
• •Fairness auditing integrated into optimization via constrained and multi-objective modes using fairlearn metrics
• •Single-command deployment bundles Next.js UI into Python wheel; optional LLM report generation with user-provided API keys

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