Unified GUI + engine for GGUF models: local LLM server, image generation and GGUF editing/quantization, all on one bundled gguf.cpp engine
Project description
gguf-cpp
One package for working with GGUF models locally: an OpenAI-compatible LLM server, a diffusion image/video/audio generator and a GGUF metadata/tensor editor with a built-in quantizer — three panels on one GUI, powered by one unified gguf.cpp engine compiled in a single build with a shared set of ggml kernels.
Install
pip install gguf-cpp
The build compiles the bundled engine (CPU by default, Metal on macOS). GPU backends are opt-in at install time:
GGUF_CPP_CUDA=1 pip install gguf-cpp # NVIDIA
GGUF_CPP_HIP=1 pip install gguf-cpp # AMD ROCm
GGUF_CPP_VULKAN=1 pip install gguf-cpp # Vulkan
Run
gguf-cpp # unified GUI — Server / Diffuser / Editor panels
python -m gguf_cpp # same thing
Each panel also runs on its own, exactly like the standalone gguf-server / gguf-diffusion / gguf-editor packages did:
gguf-cpp server # LLM server GUI
gguf-cpp diffuser # image generation GUI
gguf-cpp editor # GGUF editor GUI
And the engines are directly scriptable from the CLI:
gguf-cpp server engine -- --model model.gguf --port 8888
gguf-cpp diffuser engine -- -m sd.gguf -p "a lighthouse at dusk" -o out.png
gguf-cpp editor quantize -m in.gguf -o out-q4_k.gguf --type q4_k
gguf-cpp editor devices
Layout
vendor/engine/ the unified gguf.cpp engine (one CMake build)
kernels/ shared ggml kernels (CPU + optional GPU backends)
src/ common/ mtmd/ GGUF LLM runtime
app/ the gguf-server HTTP server
diffusion/ diffusion runtime + CLI
quantizer/ quantizer shared library (shares the kernels above)
src/gguf_cpp/ the Python package
server/ diffuser/ editor/ the three panels (backend + web frontend each)
gui.py static/ the unified 3-panel GUI shell
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