docs(MLX): add README

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

Author: grorge123

wasmedge-mlx/whisper/README.md

@@ -0,0 +1,51 @@
+# Whisper example with WasmEdge WASI-NN MLX plugin
+
+This example demonstrates using WasmEdge WASI-NN MLX plugin to perform an inference task with whisper model.
+
+## Install WasmEdge with WASI-NN MLX plugin
+
+The MLX backend relies on [MLX](https://github.com/ml-explore/mlx), but we will auto-download MLX when you build WasmEdge. You do not need to install it yourself. If you want to custom MLX, install it yourself or set the `CMAKE_PREFIX_PATH` variable when configuring cmake.
+
+Build and install WasmEdge from source:
+
+``` bash
+cd <path/to/your/wasmedge/source/folder>
+
+cmake -GNinja -Bbuild -DCMAKE_BUILD_TYPE=Release -DWASMEDGE_PLUGIN_WASI_NN_BACKEND="mlx"
+cmake --build build
+
+# For the WASI-NN plugin, you should install this project.
+cmake --install build
+```
+
+Then you will have an executable `wasmedge` runtime under `/usr/local/bin` and the WASI-NN with MLX backend plug-in under `/usr/local/lib/wasmedge/libwasmedgePluginWasiNN.so` after installation.
+
+## Download the model and tokenizer
+
+In this example, we will use `whisper-tiny`.
+
+``` bash
+git clone https://huggingface.co/grorge123/whisper-tiny
+cp -r whisper-tiny/assets .
+wget https://raw.githubusercontent.com/ml-explore/mlx-examples/refs/heads/main/whisper/mlx_whisper/assets/multilingual.tiktoken -P assets
+```
+
+## Build wasm
+
+Run the following command to build wasm, the output WASM file will be at `target/wasm32-wasip1/release/`.
+Then we use AOT-compiled WASM to improve the performance.
+
+```bash
+cargo build --target wasm32-wasip1 --release
+```
+## Execute 
+
+Download the audio and save as `audio.mp3`
+
+Execute the WASM with the `wasmedge` using nn-preload to load model. 
+
+``` bash
+wasmedge --dir .:. \
+--nn-preload default:mlx:AUTO:whisper-tiny/weights.safetensors \
+target/wasm32-wasip1/release/wasmedge-whisper.wasm default whisper-tiny audio.mp3
+```

wasmedge-mlx/whisper/src/main.rs

@@ -32,9 +32,9 @@ fn read_json(path: &str) -> io::Result<Value> {
 }
 fn main() {
     let args: Vec<String> = env::args().collect();
-    let audio = "audio.mp3";
     let model_name: &str = &args[1];
     let model_dir = &args[2];
+    let audio = &args[3];
     let config = read_json(&format!("{}/config.json", model_dir)).unwrap();
     let graph = GraphBuilder::new(GraphEncoding::Mlx, ExecutionTarget::AUTO)
         .config(config.to_string())