# llamacpp-for-kobold A self contained distributable from Concedo that exposes llama.cpp function bindings, allowing it to be used via a simulated Kobold API endpoint. What does it mean? You get llama.cpp with a fancy UI, persistent stories, editing tools, save formats, memory, world info, author's note, characters, scenarios and everything Kobold and Kobold Lite have to offer. In a tiny package under 1 MB in size, excluding model weights. ![Preview](preview.png) ## Usage - [Download the latest release here](https://github.com/LostRuins/llamacpp-for-kobold/releases/latest) or clone the repo. - Windows binaries are provided in the form of **llamacpp-for-kobold.exe**, which is a pyinstaller wrapper for **llamacpp.dll** and **llamacpp_for_kobold.py**. If you feel concerned, you may prefer to rebuild it yourself with the provided makefiles and scripts. - Weights are not included, you can use the `quantize.exe` to generate them from your official weight files (or download them from other places). - To run, execute **llamacpp-for-kobold.exe** or drag and drop your quantized `ggml_model.bin` file onto the .exe, and then connect with Kobold or Kobold Lite. - By default, you can connect to http://localhost:5001 - You can also run it using the command line `llamacpp-for-kobold.exe [ggml_model.bin] [port]`. For info, please check `llamacpp-for-kobold.exe --help` - If you are having crashes or issues with OpenBLAS, please try the `--noblas` flag. ## OSX and Linux - You will have to compile your binaries from source. A makefile is provided, simply run `make` - After all binaries are built, you can run the python script with the command `llamacpp_for_kobold.py [ggml_model.bin] [port]` ## Considerations - Don't want to use pybind11 due to dependencies on MSVCC - ZERO or MINIMAL changes as possible to main.cpp - do not move their function declarations elsewhere! - Leave main.cpp UNTOUCHED, We want to be able to update the repo and pull any changes automatically. - No dynamic memory allocation! Setup structs with FIXED (known) shapes and sizes for ALL output fields. Python will ALWAYS provide the memory, we just write to it. - No external libraries or dependencies. That means no Flask, Pybind and whatever. All You Need Is Python. - Since v1.0.6, requires libopenblas, the prebuilt windows binaries are included in this repo. If not found, it will fall back to a mode without BLAS. ## License - The original GGML library and llama.cpp by ggerganov are licensed under the MIT License - However, Kobold Lite is licensed under the AGPL v3.0 License - The provided python ctypes bindings in llamacpp.dll are also under the AGPL v3.0 License ## Notes - There is a fundamental flaw with llama.cpp, which causes generation delay to scale linearly with original prompt length. If you care, **please contribute to [this discussion](https://github.com/ggerganov/llama.cpp/discussions/229)** which, if resolved, will actually make this viable.