ani-tui, a TUI frontend for ani-cli #1610
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logando-al
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Hi everyone,
I have been a long-time
ani-cliuser and still love how fast and direct it is.At the same time, I wanted a more visual way to browse my watch history, resume shows, and discover something new without leaving the terminal.
That led me to build
ani-tui: a production-ready terminal UI written in pure Rust that wrapsani-cliand adds a richer local browsing experience on top of it.Why I built it
ani-cliis excellent at staying fast, lightweight, and keyboard-friendly.What I wanted was not to replace that, but to add:
So
ani-tuiusesani-clias the playback handoff engine, while handling the UI, local state, and browsing flow itself.Key features
Curated home screen
Continue WatchingWatchlistTrendingPopularTop RatedSeasonalThese rows are powered by AniList GraphQL metadata and local SQLite state.
Heuristic recommendation engine
There is a local-first
Because You Watchedflow and aMore Like Thisstrip on the detail view.Recommendations are based on weighted signals such as:
The goal is to keep recommendations fast, explainable, and useful without depending on an external recommendation service.
SQLite caching
Anime metadata is cached locally with TTL-based freshness rules.
That gives:
Modern terminal support
On supported terminals,
ani-tuican render real cover art using terminal image protocols.Where that is not stable or not available, it falls back to a half-block renderer so the UI stays consistent.
Integrated watch history
Episodes are marked as watched as you play them, and progress persists across sessions.
That makes resume behavior feel natural the next time you open the app.
The stack
ani-cli(via subprocess orchestration)Installation
It is available on crates.io:
Then run:
ani-cliis still required at runtime, along with a supported player (mpv,iina, orvlc).Feedback welcome
I would love feedback from other
ani-cliusers.In particular, I would be interested in:
ani-cliGitHub: logando-al/ani-tui
If there is interest, I can also share more implementation details about the local caching and recommendation heuristics.
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