| .github/ISSUE_TEMPLATE | ||
| examples | ||
| models | ||
| prompts | ||
| spm-headers | ||
| tests | ||
| .gitignore | ||
| cblas.h | ||
| convert-ggml-to-pth.py | ||
| convert-gpt4all-to-ggml.py | ||
| convert-gptq-to-ggml.py | ||
| convert-pth-to-ggml.py | ||
| convert-unversioned-ggml-to-ggml.py | ||
| expose.cpp | ||
| extra.cpp | ||
| extra.h | ||
| ggml.c | ||
| ggml.h | ||
| klite.embd | ||
| libopenblas.dll | ||
| libopenblas.lib | ||
| LICENSE.md | ||
| llama.cpp | ||
| llama.h | ||
| llamacpp.dll | ||
| llamacpp_blas.dll | ||
| llamacpp_for_kobold.py | ||
| main.exe | ||
| make_pyinstaller.bat | ||
| Makefile | ||
| MIT_LICENSE_GGML_LLAMACPP_ONLY | ||
| niko.ico | ||
| openblas_config.h | ||
| Package.swift | ||
| preview.png | ||
| quantize.exe | ||
| quantize.py | ||
| README.md | ||
| SHA256SUMS | ||
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.
Usage
- Download the latest release here 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.exeto 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.binfile 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 checkllamacpp-for-kobold.exe --help - If you are having crashes or issues with OpenBLAS, please try the
--noblasflag.
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 which, if resolved, will actually make this viable.