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launcher built with Rust, providing a graphical interface to manage and run llama.cpp servers. It supports visual configuration, RPC mode, preset management, real-time logs, and a multi-language interface.\u003C\u002Fp>\n\u003Ch2 id=\"key-features\">Key Features\u003C\u002Fh2>\u003Cul>\n\u003Cli>\u003Cstrong>Cross-platform GUI\u003C\u002Fstrong>: Built on eframe\u002Fegui\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Visual configuration\u003C\u002Fstrong>: Configure llama.cpp server parameters (port, threads, GPU layers, etc.)\u003C\u002Fli>\n\u003Cli>\u003Cstrong>File browser\u003C\u002Fstrong>: Select model files (.gguf format)\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Preset system\u003C\u002Fstrong>: Save and load common configurations\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Real-time log display\u003C\u002Fstrong>: File logging support\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Chinese\u002FEnglish UI\u003C\u002Fstrong>: Auto-detects system language\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Auto-start on boot\u003C\u002Fstrong> (Windows)\u003C\u002Fli>\n\u003Cli>\u003Cstrong>GPU layer management\u003C\u002Fstrong>: Auto\u002FAll\u002FManual modes\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Auto-calculates max context from available VRAM\u003C\u002Fstrong>\u003C\u002Fli>\n\u003Cli>\u003Cstrong>RPC mode\u003C\u002Fstrong>: Distributed inference\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Web UI integration\u003C\u002Fstrong>: Supports opening the web client\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Model file color label parsing\u003C\u002Fstrong>: Auto-detects parameter count, quantization type, etc.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Launch command preview\u003C\u002Fstrong>: Read-only display of the final command\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"target-audience\">Target Audience\u003C\u002Fh2>\u003Cul>\n\u003Cli>Users who need to run llama.cpp servers on Windows or Linux\u003C\u002Fli>\n\u003Cli>Users who prefer a GUI over the command line for managing llama.cpp\u003C\u002Fli>\n\u003Cli>Developers and tech enthusiasts interested in local LLM inference\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"quick-start\">Quick Start\u003C\u002Fh2>\u003Col>\n\u003Cli>Download the llama.cpp release and extract it\u003C\u002Fli>\n\u003Cli>Place the launcher in the same directory as llama.cpp\u003C\u002Fli>\n\u003Cli>Launch the application and select the Server panel\u003C\u002Fli>\n\u003Cli>Click "Auto Detect" and the program will automatically find the llama.cpp server executable\u003C\u002Fli>\n\u003Cli>Configure server parameters and select a model file (.gguf format)\u003C\u002Fli>\n\u003Cli>Click "Start Server"; once the "Open Web Client" button lights up, click it to open the Web interface\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Ch2 id=\"core-advantages\">Core Advantages\u003C\u002Fh2>\u003Cul>\n\u003Cli>Graphical interface, no need to memorize complex command-line parameters\u003C\u002Fli>\n\u003Cli>Supports RPC mode (distributed inference)\u003C\u002Fli>\n\u003Cli>Preset system and model file color label parsing for convenient management\u003C\u002Fli>\n\u003Cli>Chinese\u002FEnglish UI with automatic system language detection\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"system-requirements\">System Requirements\u003C\u002Fh2>\u003Cul>\n\u003Cli>OS: Windows, Linux\u003C\u002Fli>\n\u003Cli>Additional dependencies: Rust 1.70+ for building from source; Visual Studio Build Tools or MinGW on Windows; X11 development libraries on Linux\u003C\u002Fli>\n\u003C\u002Ful>\n",1792451001632]