Recipe-driven recommender systems on irspack — one YAML = one model = one recommendation API. Train writes a signed artifact; serve mounts it with hot-swap. Single binary, no database.
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Updated
Jul 11, 2026 - Python
Recipe-driven recommender systems on irspack — one YAML = one model = one recommendation API. Train writes a signed artifact; serve mounts it with hot-swap. Single binary, no database.
Lightweight anime recommendation API powered by AniList. Random picks or filter by genre and format.
This is the backend for "StylistExpert", a robust, rule-based expert system for fashion recommendations, built with FastAPI and Python.
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