llmchess 1.0.1

Play international chess against AI opponents powered by local LLMs

LLM Chess

Play international chess against AI opponents powered by local large language models (LLMs).

Features

• Interactive chess board with move highlighting and last-move indicators
• Pawn promotion dialog
• Undo moves support
• FEN display and SAN move history
• Dark theme Catppuccin-style UI
• Game status detection (checkmate, stalemate, draw, etc.)

Supported LLM Backends

Connects to any OpenAI-compatible API endpoint:

Backend	Default URL	Notes
Ollama	http://localhost:11434	ollama serve
llama.cpp Server	http://localhost:8080	./llama-server -m model.gguf --port 8080
LM Studio	http://localhost:1234	Enable "Local Server" in Developer tab
Custom	Any URL	Configure in Settings

Installation

From DEB package (Ubuntu/Debian)

sudo dpkg -i llmchess_1.0.0_all.deb
llmchess

From source

# Install dependencies
pip install PyQt6 python-chess httpx

# Run
python3 main.py

Build DEB package

bash build_deb.sh
sudo dpkg -i llmchess_1.0.0_all.deb

Usage

1. Start your LLM server (Ollama, llama.cpp, or LM Studio)
2. Launch LLM Chess (llmchess or from application menu)
3. Click Settings to configure your LLM connection
4. Select White (you move first) or Black (AI moves first)
5. Click a piece, then click the destination square to move

Settings

• Provider: Select your backend (Ollama, llama.cpp, LM Studio, or Custom)
• Base URL: API endpoint (auto-filled for presets)
• Model: Model name to use
• Temperature: Lower = more deterministic moves (default 0.3)
• Max Tokens: Maximum response length (default 512)
• Test Connection: Verify connectivity before playing

Project Structure

LLMChess/
├── main.py                    # Application entry point
├── requirements.txt           # Python dependencies
├── build_deb.sh              # DEB package build script
├── chess_app/
│   ├── board_widget.py       # Chess board UI (PyQt6)
│   ├── llm_connector.py      # LLM API connector
│   ├── game_controller.py    # Main window & game controller
│   └── settings_dialog.py    # LLM connection settings
└── deb_pkg/                  # DEB packaging files

How It Works

1. Each turn, the current board state is sent to the LLM as a FEN string plus a list of legal moves in UCI format
2. The LLM is prompted to respond with only one UCI move (e.g., e2e4, g1f3)
3. The response is parsed to extract the UCI move and validated against legal moves
4. If the LLM returns an invalid or empty response, the first legal move is used as fallback

Requirements

• Python 3.9+
• PyQt6
• python-chess
• httpx
• A running LLM server (Ollama, llama.cpp, or LM Studio)

License

MIT License