d2bab99835
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>
42 lines
1.6 KiB
Markdown
42 lines
1.6 KiB
Markdown
# Deploy DocSum in Kubernetes Cluster
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> [NOTE]
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> The following values must be set before you can deploy:
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> HUGGINGFACEHUB_API_TOKEN
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>
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> You can also customize the "MODEL_ID" and "model-volume"
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>
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> You need to make sure you have created the directory `/mnt/opea-models` to save the cached model on the node where the DocSum workload is running. Otherwise, you need to modify the `docsum.yaml` file to change the `model-volume` to a directory that exists on the node.
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## Deploy On Xeon
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```
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cd GenAIExamples/DocSum/kubernetes/intel/cpu/xeon/manifests
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export HUGGINGFACEHUB_API_TOKEN="YourOwnToken"
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sed -i "s/insert-your-huggingface-token-here/${HUGGINGFACEHUB_API_TOKEN}/g" docsum.yaml
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kubectl apply -f docsum.yaml
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```
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## Deploy On Gaudi
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```
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cd GenAIExamples/DocSum/kubernetes/intel/hpu/gaudi/manifests
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export HUGGINGFACEHUB_API_TOKEN="YourOwnToken"
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sed -i "s/insert-your-huggingface-token-here/${HUGGINGFACEHUB_API_TOKEN}/g" docsum.yaml
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kubectl apply -f docsum.yaml
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```
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## Verify Services
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To verify the installation, run the command `kubectl get pod` to make sure all pods are running.
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Then run the command `kubectl port-forward svc/docsum 8888:8888` to expose the DocSum service for access.
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Open another terminal and run the following command to verify the service if working:
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```console
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curl http://localhost:8888/v1/docsum \
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-H 'Content-Type: application/json' \
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-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."}'
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```
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