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lint-and-deploy.yaml
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name: Lint and Deploy Charts
on: pull_request
jobs:
lint-and-deploy:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
with:
fetch-depth: 0
- name: Set up Helm
uses: azure/setup-helm@fe7b79cd5ee1e45176fcad797de68ecaf3ca4814 # v4.2.0
with:
version: v3.14.4
#Python is required because ct lint runs Yamale and yamllint which require Python.
- uses: actions/setup-python@0b93645e9fea7318ecaed2b359559ac225c90a2b # v5.3.0
with:
python-version: '3.13'
- name: Set up chart-testing
uses: helm/chart-testing-action@e6669bcd63d7cb57cb4380c33043eebe5d111992 # v2.6.1
with:
version: v3.10.1
- name: Run chart-testing (lint)
run: ct lint --target-branch ${{ github.event.repository.default_branch }} --chart-dirs examples/chart-helm --charts examples/chart-helm
- name: Setup minio
run: |
docker network create vllm-net
docker run -d -p 9000:9000 --name minio --net vllm-net \
-e "MINIO_ACCESS_KEY=minioadmin" \
-e "MINIO_SECRET_KEY=minioadmin" \
-v /tmp/data:/data \
-v /tmp/config:/root/.minio \
minio/minio server /data
export AWS_ACCESS_KEY_ID=minioadmin
export AWS_SECRET_ACCESS_KEY=minioadmin
export AWS_EC2_METADATA_DISABLED=true
mkdir opt-125m
cd opt-125m && curl -O -Ls "https://huggingface.co/facebook/opt-125m/resolve/main/{pytorch_model.bin,config.json,generation_config.json,merges.txt,special_tokens_map.json,tokenizer_config.json,vocab.json}" && cd ..
aws --endpoint-url http://127.0.0.1:9000/ s3 mb s3://testbucket
aws --endpoint-url http://127.0.0.1:9000/ s3 cp opt-125m/ s3://testbucket/opt-125m --recursive
- name: Create kind cluster
uses: helm/kind-action@0025e74a8c7512023d06dc019c617aa3cf561fde # v1.10.0
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@c47758b77c9736f4b2ef4073d4d51994fabfe349 # v3.7.1
- name: Build and push the Docker image vllm cpu
uses: docker/build-push-action@48aba3b46d1b1fec4febb7c5d0c644b249a11355 # v6.10.0
with:
context: .
file: Dockerfile.cpu
tags: vllm-cpu-env:latest
- name: Configuration of docker images, network and namespace for the kind cluster
run: |
docker pull amazon/aws-cli:2.6.4
kind load docker-image amazon/aws-cli:2.6.4 --name chart-testing
kind load docker-image vllm-cpu-env:latest --name chart-testing
docker network connect vllm-net "$(docker ps -aqf "name=chart-testing-control-plane")"
kubectl create ns ns-vllm
- name: Run chart-testing (install)
run: |
export AWS_ACCESS_KEY_ID=minioadmin
export AWS_SECRET_ACCESS_KEY=minioadmin
helm install --wait --wait-for-jobs --timeout 5m0s --debug --create-namespace --namespace=ns-vllm test-vllm examples/chart-helm -f examples/chart-helm/values.yaml --set secrets.s3endpoint=http://minio:9000 --set secrets.s3bucketname=testbucket --set secrets.s3accesskeyid=$AWS_ACCESS_KEY_ID --set secrets.s3accesskey=$AWS_SECRET_ACCESS_KEY --set resources.requests.cpu=1 --set resources.requests.memory=4Gi --set resources.limits.cpu=2 --set resources.limits.memory=5Gi --set image.env[0].name=VLLM_CPU_KVCACHE_SPACE --set image.env[1].name=VLLM_LOGGING_LEVEL --set-string image.env[0].value="1" --set-string image.env[1].value="DEBUG" --set-string extraInit.s3modelpath="opt-125m/" --set-string 'resources.limits.nvidia\.com/gpu=0' --set-string 'resources.requests.nvidia\.com/gpu=0' --set-string image.repository="vllm-cpu-env"
- name: curl test
run: |
kubectl -n ns-vllm port-forward service/test-vllm-service 8001:80 &
sleep 10
CODE="$(curl -v -f --location http://localhost:8001/v1/completions \
--header "Content-Type: application/json" \
--data '{
"model": "opt-125m",
"prompt": "San Francisco is a",
"max_tokens": 7,
"temperature": 0
}'):$CODE"
echo "$CODE"