Pre-Tasks for LFX Mentorship project " Support piper as a new backend of the WASI-NN WasmEdge plugin"

This repo contains the record of pre-qualifying task for the LFX Mentorship project under WasmEdge project. I am currently using Debian 12 Bookworm

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Operating System: Debian GNU/Linux 12 (bookworm)  
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My previous contribution to Piper Framework :

• rhasspy/piper#503

---

1. Build Piper Framework and Run sample applications

To build the piper Framework first we need to have Piper-phonemize in the lib/linux-x86_64/ directory.

I cloned the forked repo from my github and build using docker :

docker buildx build . -t piper-phonemize --output 'type=local,dest=dist'

then I copied the piper-phonemize folder into the /lib/x86_64-linux-gnu/ folder.

Clone the fork of Piper to my local directory. I then made a build folder inside piper directory.

mkdir build
cd build/

since the CMakeLists.txt is in the folder above.

cmake .. && make . &&> piper_build_logs.txt

build logs for piper can be found here

checking if piper is installed correctly :

> ./piper --version
     1.2.0

after the build was successfull I downloaded a voice and a config file and placed it inside the same folder. I chose "lessac_en_US" voice.

then I Ran a sample tts in piper with the followwing command :

echo 'Welcome to the world of speech synthesis!, the build has been successfull' | \
  ./piper --model en_US-lessac-medium.onnx --output_file welcome.wav

The output audio file welcome.wav

---

Now Lets Run a Sample application, lets convert the Paragraph 3 of Beyond Good and Evil by Fredrich nietzche from here using a different "high model" voice en_US-ryan-high

According to README.md file from piper we have to format the text in json format as text object with text field in .json file :

{ "text": "First sentence to speak." }
{ "text": "Second sentence to speak." }

to pass the JSON file as input we have to specify with --json-input flag.

cat bge_nietzche.json | ./piper --model en_US-ryan-high.onnx --json-input --output_file bge_nietzche.wav 

the output file can be found here

---

2. Build WasmEdge with llama.cpp

To build WasmEdge I followed the following guide

docker pull wasmedge/wasmedge
docker rub -it --rm \
    -v /home/azm/projects/WasmEdge/:/root/wasmedge \
    wasmedge/wasmedge:latest

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

cmake --install build

The build logs for WasmEdge with llama.cpp Can be found here

then I tested the build by running tests :

LD_LIBRARY_PATH=$(pwd)/lib/api ctest

To run llama2-7b I followed the following repo

Compiling the application to Wasm :

cd llama
cargo build --target wasm32-wasi --release

Downloading Model :

curl -LO https://huggingface.co/TheBloke/Llama-2-7b-Chat-GGUF/resolve/main/llama-2-7b-chat.Q5_K_M.gguf

Running the Llama-2-7b-Chat-GGUF model :

wasmedge --dir .:. \
  --nn-preload default:GGML:AUTO:llama-2-7b-chat.Q5_K_M.gguf \
  wasmedge-ggml-llama.wasm default