Add building guide for the ggml plugin (#205)

* Add building guide for the ggml plugin

Signed-off-by: hydai <[email protected]>

* Add TensorFlow Lite

Signed-off-by: hydai <[email protected]>

---------

Signed-off-by: hydai <[email protected]>

Author: hydai

docs/contribute/source/plugin/wasi_nn.md

@@ -8,7 +8,7 @@ The WASI-NN plug-in is a proposed WebAssembly System Interface (WASI) API for ma
 
 ## Prerequisites
 
-Currently, WasmEdge used OpenVINO™ or PyTorch as the WASI-NN backend implementation. For using WASI-NN on WasmEdge, you need to install [OpenVINO™](https://docs.openvino.ai/2023.0/openvino_docs_install_guides_installing_openvino_apt.html)(2023) or [PyTorch 1.8.2 LTS](https://pytorch.org/get-started/locally/) for the backend.
+Currently, WasmEdge used OpenVINO™, PyTorch, TensorFlow Lite, or llama.cpp as the WASI-NN backend implementation. For using WASI-NN on WasmEdge, you need to install [OpenVINO™](https://docs.openvino.ai/2023.0/openvino_docs_install_guides_installing_openvino_apt.html)(2023), [TensorFlow Lite](https://www.tensorflow.org/install/lang_c), or [PyTorch 1.8.2 LTS](https://pytorch.org/get-started/locally/) for the backend.
 
 By default, we don't enable any WASI-NN backend in WasmEdge. Therefore developers should [build the WasmEdge from source](../os/linux.md) with the cmake option `WASMEDGE_PLUGIN_WASI_NN_BACKEND` to enable the backends.
 
@@ -128,4 +128,190 @@ Or set the environment variable `export LD_LIBRARY_PATH=$(pwd):${LD_LIBRARY_PATH
 We also provided the `darwin_x86_64`, `darwin_arm64`, and `manylinux_aarch64` versions of the TensorFlow-Lite pre-built shared libraries.
 :::
 
-For more information, you can refer to the [GitHub repository](https://github.com/WasmEdge/WasmEdge/tree/master/plugins/wasi_nn).
+For more information, you can refer to the [GitHub repository](https://github.com/WasmEdge/WasmEdge/tree/master/plugins/wasi_nn).
+
+## Build WasmEdge with WASI-NN llama.cpp Backend
+
+You don't need to install any llama.cpp libraries. WasmEdge will download it during the building period.
+
+Due to the acceleration frameworks being various, you will need to use different compilation options to build this plugin. Please make sure you are following the same OS section to do this.
+
+### macOS
+
+#### Intel Model
+
+If you are using the Intel Model macOS, we won't enable any acceleration framework. It is a pure CPU mode plugin.
+
+```bash
+cd <path/to/your/wasmedge/source/folder>
+# Disable BLAS and METAL on x86_64 macOS.
+cmake -GNinja -Bbuild -DCMAKE_BUILD_TYPE=Release \
+  -DWASMEDGE_PLUGIN_WASI_NN_BACKEND="GGML" \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_METAL=OFF \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_BLAS=OFF \
+  .
+cmake --build build
+# For the WASI-NN plugin, you should install this project.
+cmake --install build
+```
+
+#### Apple Silicon Model
+
+You can build and install WasmEdge from source directly on the macOS arm64 platform. It will use the built-in GPU by default.
+
+```bash
+cd <path/to/your/wasmedge/source/folder>
+# Enable METAL on arm64 macOS.
+cmake -GNinja -Bbuild -DCMAKE_BUILD_TYPE=Release \
+  -DWASMEDGE_PLUGIN_WASI_NN_BACKEND="GGML" \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_METAL=ON \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_BLAS=OFF \
+  .
+cmake --build build
+# For the WASI-NN plugin, you should install this project.
+cmake --install build
+```
+
+### Linux
+
+#### Ubuntu/Debian with CUDA 12
+
+Please follow the official guide provided by NVIDIA for installing the CUDA framework: https://developer.nvidia.com/cuda-12-2-0-download-archive
+
+```bash
+cd <path/to/your/wasmedge/source/folder>
+
+# You may need to install dependencies
+apt update
+apt install -y software-properties-common lsb-release \
+  cmake unzip pkg-config
+
+# Due to cuda-related files, it will produce some warning.
+# Disable the warning as an error to avoid failures.
+export CXXFLAGS="-Wno-error"
+# Please make sure you set up the correct CUDAARCHS.
+# We use `60;61;70` for maximum compatibility.
+export CUDAARCHS="60;61;70"
+
+# BLAS cannot work with CUBLAS
+cmake -GNinja -Bbuild -DCMAKE_BUILD_TYPE=Release \
+  -DCMAKE_CUDA_ARCHITECTURES="60;61;70" \
+  -DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc \
+  -DWASMEDGE_PLUGIN_WASI_NN_BACKEND="GGML" \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_BLAS=OFF \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_CUBLAS=ON \
+  .
+
+cmake --build build
+
+# For the WASI-NN plugin, you should install this project.
+cmake --install build
+```
+
+#### Ubuntu on NVIDIA Jetson AGX Orin
+
+You should use the pre-built OS image from the NVIDIA official site.
+
+```bash
+cd <path/to/your/wasmedge/source/folder>
+
+# Due to cuda-related files, it will produce some warning.
+# Disable the warning as an error to avoid failures.
+export CXXFLAGS="-Wno-error"
+# Please make sure you set up the correct CUDAARCHS.
+# 72 is for NVIDIA Jetson AGX Orin
+export CUDAARCHS=72
+
+# BLAS cannot work with CUBLAS
+cmake -GNinja -Bbuild -DCMAKE_BUILD_TYPE=Release \
+  -DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc \
+  -DWASMEDGE_PLUGIN_WASI_NN_BACKEND="GGML" \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_BLAS=OFF \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_CUBLAS=ON \
+  .
+
+cmake --build build
+
+# For the WASI-NN plugin, you should install this project.
+cmake --install build
+```
+
+#### Ubuntu/Debian with OpenBLAS
+
+Please install OpenBLAS before building the plugin.
+
+```bash
+cd <path/to/your/wasmedge/source/folder>
+
+# You may need to install dependencies
+apt update
+apt install -y software-properties-common lsb-release \
+  cmake unzip pkg-config
+# You must install OpenBLAS
+apt install libopenblas-dev
+
+cmake -GNinja -Bbuild -DCMAKE_BUILD_TYPE=Release \
+  -DWASMEDGE_PLUGIN_WASI_NN_BACKEND="GGML" \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_BLAS=ON \
+  .
+
+cmake --build build
+
+# For the WASI-NN plugin, you should install this project.
+cmake --install build
+```
+
+#### General Linux without any acceleration framework
+
+```bash
+cd <path/to/your/wasmedge/source/folder>
+
+cmake -GNinja -Bbuild -DCMAKE_BUILD_TYPE=Release \
+  -DWASMEDGE_PLUGIN_WASI_NN_BACKEND="GGML" \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_BLAS=OFF \
+  .
+
+cmake --build build
+
+# For the WASI-NN plugin, you should install this project.
+cmake --install build
+```
+
+#### Apple Silicon Model
+
+You can build and install WasmEdge from source directly on the macOS arm64 platform. It will use the built-in GPU by default.
+
+```bash
+cd <path/to/your/wasmedge/source/folder>
+# Enable METAL on arm64 macOS.
+cmake -GNinja -Bbuild -DCMAKE_BUILD_TYPE=Release \
+  -DWASMEDGE_PLUGIN_WASI_NN_BACKEND="GGML" \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_METAL=ON \
+  -DWASMEDGE_PLUGIN_WASI_NN_GGML_LLAMA_BLAS=OFF \
+  .
+cmake --build build
+# For the WASI-NN plugin, you should install this project.
+cmake --install build
+```
+
+### Appendix
+
+<!-- prettier-ignore -->
+:::note
+If the built `wasmedge` CLI tool cannot find the WASI-NN plugin, you can set the `WASMEDGE_PLUGIN_PATH` environment variable to the plugin installation path (such as `/usr/local/lib/wasmedge/` or the built plugin path `build/plugins/wasi_nn/`) to try to fix this issue.
+:::
+
+<!-- prettier-ignore -->
+:::note
+We also provided the pre-built ggml plugins on the following platforms:
+- darwin\_x86\_64: Intel Model macOS
+- darwin\_arm64: Apple Silicon Model macOS
+- ubuntu20.04\_x86\_64: x86\_64 Linux (the glibc is using Ubuntu20.04 one)
+- ubuntu20.04\_aarch64: aarch64 Linux (the glibc is using Ubuntu20.04 one)
+- ubuntu20.04\_blas\_x86\_64: x86\_64 Linux with OpenBLAS support (the glibc is using Ubuntu20.04 one)
+- ubuntu20.04\_blas\_aarch64: aarch64 Linux with OpenBLAS support (the glibc is using Ubuntu20.04 one)
+- ubuntu20.04\_cuda\_x86\_64: x86\_64 Linux with CUDA 12 support (the glibc is using Ubuntu20.04 one)
+- ubuntu20.04\_cuda\_aarch64: aarch64 Linux with CUDA 11 support (the glibc is using Ubuntu20.04 one), for NVIDIA Jetson AGX Orin
+- manylinux2014\_x86\_64: x86\_64 Linux (the glibc is using CentOS 7 one)
+- manylinux2014\_aarch64: aarch64 Linux (the glibc is using CentOS 7 one)
+:::