speecht5¶
Helm chart for deploying speecht5 service.
Installing the Chart¶
To install the chart, run the following:
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.
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 |
|
|
service.port |
string |
|