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 to “HUGGINGFACEHUB_API_TOKEN” environment variable.

Deploy On Xeon

cd GenAIExamples/FaqGen/kubernetes/intel/cpu/xeon/manifest
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/manifest
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."
     }'