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Feature overview

QuOptuna combines quantum and classical machine learning under a single hyperparameter-optimization workflow built on Optuna and PennyLane. This page is a hub: a short description of each major capability with a link to the page that covers it in depth.

Running optimizations

Section titled “Running optimizations”
  • Guided wizard — a 6-step Next.js UI walks you from dataset to report. See Architecture for how the UI, server, and engine connect.
  • Headless CLI — drive the same pipeline for scripted, reproducible runs. See the CLI reference.
  • Python API — use the Optimizer engine directly in your own code. See How the optimization engine works.

Search and tuning

Section titled “Search and tuning”
  • Conditional search space — the objective suggests model_type first, then only that model’s relevant parameters, keeping the TPE model clean. See How the optimization engine works.
  • Samplers and pruners — tpe/random/grid samplers and asha/hyperband/none pruners, with early stopping for iterative quantum models. See How the optimization engine works.
  • Fairness-aware search — off, constrained (feasibility constraint on disparity), or multi-objective (F1 vs disparity Pareto front), using equal-opportunity, disparate-impact, and demographic-parity metrics on a sensitive feature. See How the optimization engine works.
  • Multiclass and One-vs-Rest — macro-F1 scoring with OvR-wrapped variational models for K-class problems. See How the optimization engine works.

Analysis and reporting

Section titled “Analysis and reporting”
  • SHAP and XAI — SHAP plots and feature-importance analysis for the best model. See The workflow engine.
  • LLM reports — analyst + reviewer agents (OpenAI/Gemini/Anthropic providers) generate a written report of results. See The workflow engine.

Data and persistence

Section titled “Data and persistence”
  • UCI + CSV ingestion — load data from an uploaded CSV or a UCI dataset. See The workflow engine.
  • Persistence and crash rehydration — durable SQLite stores (run_store, analysis_store, dataset_registry) plus Optuna studies as source of truth; stale runs are recovered on restart. See Architecture.

Deployment and access

Section titled “Deployment and access”
  • Optional Auth0 — cookie-session authentication that is a no-op when unconfigured, so local runs stay unauthenticated. See Architecture.
  • Single-port packaged deploy — uvx quoptuna serves the built UI and API from one uvicorn process. See Architecture.
  • Legacy Streamlit UI — a fallback dashboard kept for compatibility. See Legacy Streamlit UI.

Next steps

Section titled “Next steps”