Focalors is a chess engine and learning app I built in Rust. It runs entirely offline - local play against the engine, post-game review with explanations, puzzles drawn from your own mistakes, and a stats view that lives in a small SQLite file on your machine. No accounts, no cloud, no telemetry.
The thing I wanted to figure out is whether you can have both a strong engine and readable explanations of what it's doing. Most engines optimize one or the other. Focalors keeps two evaluations side by side: an NNUE network drives playing strength during search, and a hand-crafted evaluation runs alongside it whenever the app needs to explain why a move was bad - a hanging piece, a worsening pawn structure, lost king safety. The same core powers the desktop GUI and a standard UCI engine for other front-ends.
My goal with this project is to make the learning experience for chess possible without the need of having a permanent internet connection or paying a subscription. As earlier mentioned, I want users to be capable of having the full control over their data, games and progress, all on their own machine, always accessible. While of course the strength of the engine is to be further improved, this project does not aim to be "the strongest" or compete with state-of-the-art engines such as Stockfish. The engine just needs to be strong enough to teach human understandable positions and help the average, advanced, or possibly even masters improve their understanding. (With the sole exception of Satoru Gojo aka Magnus Carlsen) I love chess and wanna do a small contribution to people trying to get further into the game. (I also lack the hardware for training huge NNUE nets so if anybody wanna help feel free lol. More to that in TECHNICAL.md further mentioned below)
The simplest path is to grab a prebuilt binary from the Releases page - Linux, macOS, and Windows builds are attached to each tagged release. Run the binary and the GUI opens.
If you'd rather build from source you'll need a Rust toolchain, then:
cargo build --release
./target/release/focalors guiIf you want to plug Focalors into another chess GUI, focalors uci runs the standard UCI protocol on stdio.
docs/TECHNICAL.md has the engine internals, evaluation design, and the NNUE training workflow. CONTRIBUTING.md has the practical workflow if you want to send a patch.
GPL-3.0-or-later. The chess piece graphics in assets/pieces/ are CC BY-SA 3.0 by Colin M.L. Burnett — see CREDITS.md for the full attribution.