#chess-engine #chess #artificial-intelligence #chess-board #uci #move-generation #ai

bin+lib timecat

A NNUE-based chess engine that implements the Negamax algorithm and can be integrated into any project as a library. It features move generation, advanced position evaluation through NNUE, and move searching capabilities.

148 stable releases

1.36.3 Sep 20, 2024
1.36.2 Sep 18, 2024
1.34.0 Aug 31, 2024
1.31.1 Jul 29, 2024
0.1.0 May 24, 2024

#41 in Game dev

Download history 1202/week @ 2024-07-11 555/week @ 2024-07-18 1080/week @ 2024-07-25 301/week @ 2024-08-01 508/week @ 2024-08-08 372/week @ 2024-08-15 207/week @ 2024-08-22 311/week @ 2024-08-29 773/week @ 2024-09-05 887/week @ 2024-09-12 512/week @ 2024-09-19 386/week @ 2024-09-26 192/week @ 2024-10-03

320 downloads per month

Custom license

5MB
227K SLoC

Timecat Chess Engine

Timecat is a UCI-compatible chess engine designed in Rust that combines powerful algorithms and advanced evaluation techniques to deliver top-notch chess analysis and game play. Using alpha-beta pruning with the negamax algorithm and the NNUE evaluation method, Timecat achieves enhanced depth and accuracy in game analysis.

Timecat as a Library

Timecat was originally conceived as a personal project. However, with the onset of a new chess-related project, I realized the benefits of publishing Timecat as a library to avoid excessive code duplication. Initially designed for personal use, Timecat will now be refined and updated to enhance its functionality and usability as a library, making it more accessible and beneficial for other users. Also the documentation will be further improved.

Make sure to always update rust to the latest version to use this library.

⚠️ Beta Version Notice

This chess engine is currently in beta and actively under development. Please be aware that breaking changes may occur as new features are added and improvements are made. Your feedback and contributions are greatly appreciated as I continue to refine and enhance the engine.

Key Features

  • UCI Compatibility: Fully compatible with the Universal Chess Interface (UCI) standard.
  • Advanced Algorithms: Utilizes alpha-beta pruning and the negamax algorithm for efficient move searching.
  • NNUE Evaluation: Incorporates NNUE (efficiently updatable neural network) for state-of-the-art position evaluation.
  • Customizable Builds: Supports tailored builds through configurable cargo features.

Integration of the Chess Library

Initially, Timecat was dependent on the external chess library, which is available at https://github.com/jordanbray/chess. To align more closely with specific requirements, the library was integrated directly into Timecat. This integration permitted significant modifications and extensions to its functionalities, thereby enhancing the engine's overall capabilities. Such integration demonstrates a commitment to adapting and evolving the tools to secure the best possible performance and accuracy in chess analytics.

User Controls

In the library, only pub or non-pub visibility modifiers are used (unless extremely necessary to prevent users from making catastrophic errors). This approach ensures that all potentially useful functions and structures are accessible to the user, avoiding the situation where a pub(crate) might restrict access to valuable components—a problem I've encountered while using the chess library. Therefore, only the features that is considered essential are included in timecat::prelude; all other functionalities are available for direct import from the timecat library.

Also several cargo features have been introduced to provide users with complete control over the code's behavior.

NNUE Support

Timecat currently utilizes the Stockfish NNUE for evaluation (only HalfKP supported). Plans are in place to transition to a custom-trained NNUE in the future.

Engine Strength

Although it hasn't been thoroughly tested yet, but my chess engine is capable of defeating chess.com's max bot, which has an Elo rating of 3200.

Installation

Installing as a Binary

Optimize your setup for the best performance:

RUSTFLAGS="-C target-cpu=native" cargo install timecat

Compilation from Source

Clone the repository and compile with native optimizations:

git clone https://github.com/Gourab-Ghosh/timecat-rs.git
cd timecat-rs
RUSTFLAGS="-C target-cpu=native" cargo run --release

Compilation with Docker

Clone the repository and compile with native optimizations:

git clone https://github.com/Gourab-Ghosh/timecat-rs.git
cd timecat-rs
sudo docker build -t timecat .
sudo docker run -it --rm timecat

Usage as a Library

Minimal Dependency Integration

Integrate Timecat into your Rust projects with minimal dependencies:

cargo add timecat --no-default-features

Examples

This example demonstrates how to set up a chess board, make moves, evaluate board positions, and utilize the inbuilt engine to find optimal moves using the timecat library. Some optional features needs to be enabled.

First, add the timecat crate to your project with the necessary features enabled:

cargo add timecat --no-default-features --features "inbuilt_nnue extras"

Then, you can proceed with the following Rust code:

use timecat::prelude::*;

fn main() {
    // Initialize a chess board with the default starting position.
    let mut board = Board::default();

    // Apply moves in standard algebraic notation.
    board.push_san("e4").expect("Failed to make move: e4");
    board.push_san("e5").expect("Failed to make move: e5");

    // Evaluate the current board position using the inbuilt_nnue feature.
    let evaluation = board.evaluate();
    println!("Current Evaluation: {}\n", evaluation);

    // Initialize the engine with the current board state.
    let mut engine = Engine::from_board(board);

    // Configure the engine to search for the best move up to a depth of 10 plies.
    let response = engine.go_verbose(&GoCommand::from_depth(10).into());
    let best_move = response.get_best_move().expect("No best move found");

    // Output the best move found by the engine.
    println!(
        "\nBest Move: {}",
        best_move
            .san(engine.get_board())
            .expect("Failed to generate SAN")
    );
}

You can use UCI commands, although it's not recommended in production environments due to potential parsing delays. The inbuilt_nnue optional feature is also required in this context.

As previous, add the timecat crate to your project:

cargo add timecat --no-default-features --features inbuilt_nnue

Then, you can proceed with the following Rust code:

use timecat::prelude::*;
use std::error::Error;

fn main() -> Result<(), Box<dyn Error>> {
    // Create the default engine initialized with the standard starting position.
    let mut runner = timecat::TimecatBuilder::<Engine>::default().build();

    // List of UCI commands to be executed on the chess engine.
    let uci_commands = [
        // Checks if the engine is ready to receive commands.
        "isready",
        // Sets the move overhead option.
        "setoption name move overhead value 200",
        // Display the current state of the chess board.
        "d",
        // Sets a new game position by applying the moves.
        "position startpos moves e2e4 e7e5",
        // Instructs the engine to calculate the best move within 3000 milliseconds.
        "go movetime 3000",
    ];

    // Process each UCI command and handle potential errors.
    for command in uci_commands {
        runner.run_uci_command(command)?;
    }

    Ok(())
}

Or just enjoy the engine play against itself:

use timecat::prelude::*;
use std::time::Duration;
use std::error::Error;

fn main() -> Result<(), Box<dyn Error>> {
    self_play(
        &mut Engine::default(),
        // Take 10 milliseconds per move
        &GoCommand::from_millis(10).into(),
        // set to verbose mode (true/false)
        true,
        // Limit to number of moves to play (u16/Some(u16)/None), None denoting no limit
        100,
    )?;

    Ok(())
}

The selfplay command works on the binary as well.

Cargo Features

  • binread: Binread support.
  • nnue_reader: Adds support for NNUE evaluation by reading nnue files.
  • inbuilt_nnue: Integrate built-in NNUE evaluation support by including the nnue file directly into the binary, fetched using the minreq library.
  • extras: Adds some functionalities not needed in binary, to get better insights of the behavior of the code. These feature is disabled by default because they requires some computations which are not needed in the binary.
  • colored: Displays all information in a visually appealing colored format for enhanced readability.
  • serde: Enables serialization and deserialization support via serde.
  • wasm: Webassembly support (Still in Testing phase).
  • pyo3: Python support (Still in Testing phase).
  • debug: Intended solely for development use.
  • experimental: Codes under development for upcoming features.

Default features include inbuilt_nnue and colored.

TODO

  • Implement other variants of chess.
  • Implement Syzygy Tablebase.
  • Organize the Polyglot Table codes to make it usable.
  • Organize the pgn related codes to make it usable.
  • Implement xboard feature.
  • Add svg feature like the python library chess for better visualization.

License

Timecat is open-sourced under the GNU GENERAL PUBLIC LICENSE. You are free to use, modify, and distribute it under the same license.

Contributing

Feel free to fork the repository, make improvements, and submit pull requests. You can also report issues or suggest features through the GitHub issue tracker.

Support the developer

If you like Timecat, please consider a little donation.

GitHub Link PayPal Link

Dependencies

~0.5–11MB
~72K SLoC