# speecht5 Helm chart for deploying speecht5 service. ## Installing the Chart To install the chart, run the following: ```console export MODELDIR=/mnt/opea-models helm install speecht5 speecht5 --set global.modelUseHostPath=${MODELDIR} ``` ### Install the microservice in air gapped (offline) mode To run `speecht5` microservice in an air gapped environment, users are required to pre-download the models `microsoft/speecht5_tts` and `microsoft/speecht5_hifigan` to a shared storage. Below is an example for using node level local directory to download the model data: Assuming the model data is shared using node-local directory `/mnt/opea-models`. ``` # On every K8s node, run the following command: export MODEL_DIR=/mnt/opea-models # Download model, assumes Python huggingface_hub[cli] module is already installed huggingface-cli download --cache-dir "${MODEL_DIR}" microsoft/speecht5_tts huggingface-cli download --cache-dir "${MODEL_DIR}" microsoft/speecht5_hifigan # On K8s master node, run the following command: # Install using Helm with the following additional parameters: helm install ... --set global.offline=true,global.modelUseHostPath=${MODEL_DIR} ``` Assuming we share the offline data on cluster level using a persistent volume (PV), first we need to create the persistent volume claim (PVC) with name `opea-model-pvc` to store the model data. ``` # Download model openai/whisper-small at the root directory of the corresponding PV # ... # Install using Helm with the following additional parameters: # export MODEL_PVC=opea-model-pvc # helm install ... --set global.offline=true,global.modelUsePVC=${MODEL_PVC} ``` ## Verify Use port-forward to access it from localhost. ```console kubectl port-forward service/speecht5 1234:7055 & curl http://localhost:1234/v1/tts \ -XPOST \ -d '{"text": "Who are you?"}' \ -H 'Content-Type: application/json' ``` ## Values | Key | Type | Default | Description | | ---------------- | ------ | ----------------- | ----------- | | image.repository | string | `"opea/speecht5"` | | | service.port | string | `"7055"` | |