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Precompiled Rust deck recommendation engine for Python and LunaBot integrations

Project description

allium-sekai-deck

Precompiled Python bindings for the Allium Sekai deck recommendation engine. The package includes the Rust card-pool, rule evaluation, and DFS search logic, so users do not need Rust, Cargo, or a local compiler.

It provides two Python interfaces:

  • allium_deck: a compact API for new integrations.
  • sekai_deck_recommend_cpp: the object and import surface used by LunaBot's C++ deck recommendation integration.

Installation

pip install allium-sekai-deck

Precompiled abi3 wheels support CPython 3.10 and newer on:

  • Linux x86_64 and aarch64
  • Windows x86_64
  • macOS x86_64 and Apple Silicon

Imports

from allium_deck import Engine, RecommendOptions, RecommendResult, UserData

Existing LunaBot integrations can keep their current namespace:

from sekai_deck_recommend_cpp import (
    DeckRecommendOptions,
    DeckRecommendUserData,
    SekaiDeckRecommend,
)

Masterdata, music metadata, and user data remain runtime inputs and are not bundled into the wheel. The recommendation engine uses Allium's DFS search.

Version 0.0.3 tracks allium-deck 0.0.6, including the optimized pool construction path, explicit AVX-512 dispatch on supported x86-64 CPUs, and portable scalar fallbacks for other targets. Performance depends on the CPU, account data, activity rules, and candidate pool shape.

API coverage

The sekai_deck_recommend_cpp interface includes the complete LunaBot deck workflow:

  • mutable option, user-data, card, deck, support-deck, and result objects
  • single and batch recommendation
  • World Bloom support-deck calculation
  • area-item upgrade recommendation
  • per-music score and event-point calculation
  • note-level exact live calculation
  • configurable batch worker count

Each recommendation result includes cost_ms, the wall-clock time spent in the native search itself. Batch results report this value independently for every request.

License

MIT

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