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GenAIExamples/FaqGen/kubernetes/intel/README.md
XinyaoWa d2bab99835 refine readme for reorg (#782)
Signed-off-by: Xinyao Wang <xinyao.wang@intel.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2024-09-11 14:57:29 +08:00

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# Deploy FaqGen in Kubernetes Cluster
> [NOTE]
> The following values must be set before you can deploy:
> HUGGINGFACEHUB_API_TOKEN
> You can also customize the "MODEL_ID" and "model-volume".
## Required Models
We set "meta-llama/Meta-Llama-3-8B-Instruct" as default model, if you want to use other models, change arguments "--model-id" in `xeon/faqgen.yaml` or `gaudi/faqgen.yaml`.
```
- --model-id
- 'meta-llama/Meta-Llama-3-8B-Instruct'
```
If use gated models, you also need to provide [huggingface token](https://huggingface.co/docs/hub/security-tokens) to "HUGGINGFACEHUB_API_TOKEN" environment variable.
## Deploy On Xeon
```
cd GenAIExamples/FaqGen/kubernetes/intel/cpu/xeon/manifests
export HUGGINGFACEHUB_API_TOKEN="YourOwnToken"
sed -i "s/insert-your-huggingface-token-here/${HUGGINGFACEHUB_API_TOKEN}/g" faqgen.yaml
kubectl apply -f faqgen.yaml
```
## Deploy On Gaudi
```
cd GenAIExamples/FaqGen/kubernetes/intel/hpu/gaudi/manifests
export HUGGINGFACEHUB_API_TOKEN="YourOwnToken"
sed -i "s/insert-your-huggingface-token-here/${HUGGINGFACEHUB_API_TOKEN}/g" faqgen.yaml
kubectl apply -f faqgen.yaml
```
## Deploy UI
```
cd GenAIExamples/FaqGen/kubernetes/manifests/
kubectl get svc # get ip address
ip_address="" # according to your svc address
sed -i "s/insert_your_ip_here/${ip_address}/g" ui.yaml
kubectl apply -f ui.yaml
```
## Verify Services
Make sure all the pods are running, and restart the faqgen-xxxx pod if necessary.
```
kubectl get pods
port=7779 # 7779 for gaudi, 7778 for xeon
curl http://${host_ip}:7779/v1/faqgen -H "Content-Type: application/json" -d '{
"messages": "Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."
}'
```