Merge pull request #114 from dminnear-rh/fix-chart-lock #5

Workflow file for this run

.github/workflows/e2e-tests.yaml at 2e4ff06

	name: E2E Tests

	on:
	pull_request:
	branches:
	- main
	paths:
	- 'frontend/**'
	- 'deploy/helm/**'
	- 'tests/**'
	- '.github/workflows/e2e-tests.yaml'
	push:
	branches:
	- main
	workflow_dispatch:

	# MaaS configuration - can be overridden with repository secrets for different environments
	env:
	MAAS_ENDPOINT: "https://llama-3-2-3b-maas-apicast-production.apps.prod.rhoai.rh-aiservices-bu.com:443/v1"
	MAAS_MODEL_ID: "llama-3-2-3b"
	# MAAS_API_KEY is passed as a secret in the helm install step

	jobs:
	unit-tests:
	name: Unit Tests
	runs-on: ubuntu-latest
	timeout-minutes: 10

	steps:
	- name: Checkout repository
	uses: actions/checkout@v4

	- name: Set up Python
	uses: actions/setup-python@v5
	with:
	python-version: '3.11'

	- name: Install unit test dependencies
	run: \|
	pip install -r tests/unit/requirements.txt

	- name: Run unit tests
	run: \|
	pytest tests/unit/ -v --tb=short --cov=frontend --cov-report=term-missing

	- name: Upload unit test results
	if: always()
	uses: actions/upload-artifact@v4
	with:
	name: unit-test-results
	path: \|
	.coverage
	htmlcov/

	integration-tests:
	name: Integration Tests (Streamlit App)
	runs-on: ubuntu-latest
	timeout-minutes: 15
	needs: unit-tests

	steps:
	- name: Checkout repository
	uses: actions/checkout@v4

	- name: Set up Python
	uses: actions/setup-python@v5
	with:
	python-version: '3.11'

	- name: Install integration test dependencies
	run: \|
	pip install -r tests/integration/requirements.txt

	- name: Run integration tests
	run: \|
	pytest tests/integration/test_*.py -v --tb=short

	- name: Upload integration test results
	if: always()
	uses: actions/upload-artifact@v4
	with:
	name: integration-test-results
	path: pytest-results/

	llamastack-integration-tests:
	name: LlamaStack Integration Tests
	runs-on: ubuntu-latest
	timeout-minutes: 60
	needs: unit-tests

	steps:
	- name: Checkout repository
	uses: actions/checkout@v4

	- name: Set up Python
	uses: actions/setup-python@v5
	with:
	python-version: '3.11'

	- name: Install test dependencies
	run: \|
	pip install -r tests/integration/llamastack/requirements.txt

	- name: Create Kind cluster config file
	run: \|
	cat <<EOF > kind-config.yaml
	kind: Cluster
	apiVersion: kind.x-k8s.io/v1alpha4
	nodes:
	- role: control-plane
	extraPortMappings:
	- containerPort: 30080
	hostPort: 8501
	protocol: TCP
	- containerPort: 30081
	hostPort: 8321
	protocol: TCP
	EOF

	- name: Create Kind cluster
	uses: helm/kind-action@v1
	with:
	cluster_name: rag-e2e
	config: kind-config.yaml

	- name: Install Required CRDs
	run: \|
	echo "Installing CRDs required by helm chart subcomponents..."

	# OpenShift Route CRD
	kubectl apply -f - <<EOF
	apiVersion: apiextensions.k8s.io/v1
	kind: CustomResourceDefinition
	metadata:
	name: routes.route.openshift.io
	spec:
	group: route.openshift.io
	names:
	kind: Route
	listKind: RouteList
	plural: routes
	singular: route
	scope: Namespaced
	versions:
	- name: v1
	served: true
	storage: true
	schema:
	openAPIV3Schema:
	type: object
	x-kubernetes-preserve-unknown-fields: true
	EOF

	# KServe InferenceService CRD
	kubectl apply -f - <<EOF
	apiVersion: apiextensions.k8s.io/v1
	kind: CustomResourceDefinition
	metadata:
	name: inferenceservices.serving.kserve.io
	spec:
	group: serving.kserve.io
	names:
	kind: InferenceService
	listKind: InferenceServiceList
	plural: inferenceservices
	singular: inferenceservice
	scope: Namespaced
	versions:
	- name: v1beta1
	served: true
	storage: true
	schema:
	openAPIV3Schema:
	type: object
	x-kubernetes-preserve-unknown-fields: true
	EOF

	# KServe ServingRuntime CRD
	kubectl apply -f - <<EOF
	apiVersion: apiextensions.k8s.io/v1
	kind: CustomResourceDefinition
	metadata:
	name: servingruntimes.serving.kserve.io
	spec:
	group: serving.kserve.io
	names:
	kind: ServingRuntime
	listKind: ServingRuntimeList
	plural: servingruntimes
	singular: servingruntime
	scope: Namespaced
	versions:
	- name: v1alpha1
	served: true
	storage: true
	schema:
	openAPIV3Schema:
	type: object
	x-kubernetes-preserve-unknown-fields: true
	EOF

	# OpenDataHub DataSciencePipelinesApplication CRD
	kubectl apply -f - <<EOF
	apiVersion: apiextensions.k8s.io/v1
	kind: CustomResourceDefinition
	metadata:
	name: datasciencepipelinesapplications.datasciencepipelinesapplications.opendatahub.io
	spec:
	group: datasciencepipelinesapplications.opendatahub.io
	names:
	kind: DataSciencePipelinesApplication
	listKind: DataSciencePipelinesApplicationList
	plural: datasciencepipelinesapplications
	singular: datasciencepipelinesapplication
	scope: Namespaced
	versions:
	- name: v1
	served: true
	storage: true
	schema:
	openAPIV3Schema:
	type: object
	x-kubernetes-preserve-unknown-fields: true
	EOF

	# Kubeflow Notebook CRD
	kubectl apply -f - <<EOF
	apiVersion: apiextensions.k8s.io/v1
	kind: CustomResourceDefinition
	metadata:
	name: notebooks.kubeflow.org
	spec:
	group: kubeflow.org
	names:
	kind: Notebook
	listKind: NotebookList
	plural: notebooks
	singular: notebook
	scope: Namespaced
	versions:
	- name: v1
	served: true
	storage: true
	schema:
	openAPIV3Schema:
	type: object
	x-kubernetes-preserve-unknown-fields: true
	EOF

	echo "Waiting for all CRDs to be established..."
	kubectl wait --for condition=established --timeout=60s crd/routes.route.openshift.io
	kubectl wait --for condition=established --timeout=60s crd/inferenceservices.serving.kserve.io
	kubectl wait --for condition=established --timeout=60s crd/servingruntimes.serving.kserve.io
	kubectl wait --for condition=established --timeout=60s crd/datasciencepipelinesapplications.datasciencepipelinesapplications.opendatahub.io
	kubectl wait --for condition=established --timeout=60s crd/notebooks.kubeflow.org

	echo "✅ All required CRDs installed successfully"

	- name: Verify cluster
	run: \|
	kubectl cluster-info
	kubectl get nodes
	kubectl get pods -A
	kubectl get crds \| grep route \|\| echo "Route CRD check"

	- name: Add Helm repository
	run: \|
	helm repo add rag-charts https://rh-ai-quickstart.github.io/ai-architecture-charts
	helm repo update

	- name: Build Helm dependencies
	run: \|
	cd deploy/helm/rag
	helm dependency build

	- name: Display MaaS configuration
	run: \|
	echo "========================================="
	echo "MaaS Configuration (Public)"
	echo "========================================="
	echo "Model ID: ${MAAS_MODEL_ID}"
	echo "Endpoint: ${MAAS_ENDPOINT}"
	echo "========================================="

	- name: Validate MaaS API key
	env:
	MAAS_API_KEY: ${{ secrets.MAAS_API_KEY }}
	run: \|
	# Check if MAAS_API_KEY secret is set
	if [ -z "${MAAS_API_KEY}" ]; then
	echo ""
	echo "❌ ERROR: MAAS_API_KEY secret is not configured!"
	echo ""
	echo "To fix this, add the MAAS_API_KEY secret to your repository:"
	echo "1. Go to: Settings > Secrets and variables > Actions"
	echo "2. Click 'New repository secret'"
	echo "3. Name: MAAS_API_KEY"
	echo "4. Value: Your Red Hat MaaS API key"
	echo ""
	echo "For more information, see:"
	echo "https://docs.github.com/en/actions/security-guides/using-secrets-in-github-actions"
	echo ""
	exit 1
	fi

	echo "✅ MaaS API key is configured"

	- name: Install RAG application with MaaS
	env:
	MAAS_API_KEY: ${{ secrets.MAAS_API_KEY }}
	run: \|
	# Create namespace
	kubectl create namespace rag-e2e \|\| true

	echo "========================================="
	echo "Installing RAG application with MaaS"
	echo "========================================="
	echo "Using model: ${MAAS_MODEL_ID}"
	echo "Helm chart: deploy/helm/rag"
	echo "Namespace: rag-e2e"
	echo "Values: tests/e2e/values-e2e.yaml"
	echo "========================================="

	# Install the chart with e2e values
	# Override MaaS configuration from environment variables
	# Note: All MaaS settings (endpoint, model ID, API key) passed via --set
	# Some values may appear as *** in logs due to GitHub Actions secret masking
	helm install rag deploy/helm/rag \
	--namespace rag-e2e \
	--values tests/e2e/values-e2e.yaml \
	--set global.models.${MAAS_MODEL_ID}.url="${MAAS_ENDPOINT}" \
	--set global.models.${MAAS_MODEL_ID}.id="${MAAS_MODEL_ID}" \
	--set global.models.${MAAS_MODEL_ID}.enabled=true \
	--set global.models.${MAAS_MODEL_ID}.apiToken="${MAAS_API_KEY}" \
	--set-json llama-stack.initContainers='[]' \
	--skip-crds \
	--timeout 20m \
	--debug

	- name: Wait for core services to be ready
	run: \|
	echo "========================================="
	echo "Listing all resources in namespace..."
	echo "========================================="
	kubectl get all -n rag-e2e

	echo ""
	echo "========================================="
	echo "Checking deployments..."
	echo "========================================="
	kubectl get deployments -n rag-e2e -o wide

	echo ""
	echo "========================================="
	echo "Checking pods..."
	echo "========================================="
	kubectl get pods -n rag-e2e -o wide

	echo ""
	echo "========================================="
	echo "Waiting for Llama Stack deployment (10min timeout)..."
	echo "========================================="
	kubectl wait --for=condition=available --timeout=600s \
	deployment/llamastack -n rag-e2e \|\| {
	echo "❌ Llama Stack deployment failed to become available"
	echo "Pod status:"
	kubectl get pods -l app.kubernetes.io/name=llamastack -n rag-e2e
	echo "Pod logs:"
	kubectl logs -l app.kubernetes.io/name=llamastack -n rag-e2e --tail=100
	exit 1
	}

	echo ""
	echo "========================================="
	echo "Waiting for RAG UI deployment (5min timeout)..."
	echo "========================================="
	kubectl wait --for=condition=available --timeout=300s \
	deployment/rag -n rag-e2e \|\| {
	echo "❌ RAG UI deployment failed to become available"
	echo "Pod status:"
	kubectl get pods -l app.kubernetes.io/name=rag -n rag-e2e
	echo "Pod logs:"
	kubectl logs -l app.kubernetes.io/name=rag -n rag-e2e --tail=100
	exit 1
	}

	echo ""
	echo "========================================="
	echo "Waiting for pods to be ready..."
	echo "========================================="
	kubectl wait --for=condition=ready --timeout=600s \
	pod -l app.kubernetes.io/name=llamastack -n rag-e2e
	kubectl wait --for=condition=ready --timeout=300s \
	pod -l app.kubernetes.io/name=rag -n rag-e2e

	echo ""
	echo "========================================="
	echo "✅ ALL CORE SERVICES ARE READY!"
	echo "========================================="
	kubectl get pods -n rag-e2e -o wide

	- name: Expose services via NodePort
	run: \|
	# Expose RAG UI
	kubectl patch service rag -n rag-e2e -p '{"spec":{"type":"NodePort","ports":[{"port":8501,"nodePort":30080}]}}'

	# Expose Llama Stack
	kubectl patch service llamastack -n rag-e2e -p '{"spec":{"type":"NodePort","ports":[{"port":8321,"nodePort":30081}]}}'

	# Verify services
	kubectl get services -n rag-e2e

	- name: Port forward services
	run: \|
	# Start port forwarding in background
	kubectl port-forward -n rag-e2e svc/rag 8501:8501 &
	kubectl port-forward -n rag-e2e svc/llamastack 8321:8321 &

	# Wait for port forwarding to establish
	sleep 10

	- name: Run LlamaStack integration tests with MaaS inference
	env:
	LLAMA_STACK_ENDPOINT: http://localhost:8321
	RAG_UI_ENDPOINT: http://localhost:8501
	INFERENCE_MODEL: ${{ env.MAAS_MODEL_ID }}
	SKIP_MODEL_TESTS: "false" # Enable inference tests with MaaS
	run: \|
	echo "Starting LlamaStack integration tests with MaaS-enabled inference..."
	echo "Model: ${INFERENCE_MODEL}"
	echo "MaaS Endpoint: ${MAAS_ENDPOINT}"
	pytest tests/integration/llamastack/ -v --tb=short

	- name: Debug - Get pod logs on failure
	if: failure()
	run: \|
	echo "=== Deployment status ==="
	kubectl get deployments -n rag-e2e

	echo "=== Pod status ==="
	kubectl get pods -n rag-e2e -o wide

	echo "=== Service status ==="
	kubectl get services -n rag-e2e

	echo "=== Events ==="
	kubectl get events -n rag-e2e --sort-by='.lastTimestamp'

	echo "=== RAG UI logs ==="
	kubectl logs -l app.kubernetes.io/name=rag -n rag-e2e --tail=200 \|\| echo "No RAG UI logs available"

	echo "=== Llama Stack logs (CRITICAL - Check model registration) ==="
	kubectl logs -l app.kubernetes.io/name=llamastack -n rag-e2e --tail=300 \|\| echo "No Llama Stack logs available"

	echo "=== Llama Stack pod details ==="
	kubectl describe pod -l app.kubernetes.io/name=llamastack -n rag-e2e \|\| echo "No pod details"

	echo "=== PGVector logs ==="
	kubectl logs -l app.kubernetes.io/name=pgvector -n rag-e2e --tail=100 \|\| echo "No PGVector logs available"

	echo "=== MinIO logs ==="
	kubectl logs -l app.kubernetes.io/name=minio -n rag-e2e --tail=100 \|\| echo "No MinIO logs available"

	echo "=== Ingestion Pipeline logs (if enabled) ==="
	kubectl logs -l app.kubernetes.io/name=ingestion-pipeline -n rag-e2e --tail=100 \|\| echo "No ingestion pipeline logs"

	- name: Upload test results
	if: always()
	uses: actions/upload-artifact@v4
	with:
	name: llamastack-integration-test-results
	path: pytest-results/

	- name: Cleanup
	if: always()
	run: \|
	# Kill port-forward processes
	pkill -f "kubectl port-forward" \|\| true

	# Optional: Uncomment to delete cluster
	# kind delete cluster --name rag-e2e

	ui-e2e-tests:
	name: UI E2E Tests (Playwright)
	runs-on: ubuntu-latest
	timeout-minutes: 60
	needs: [unit-tests, integration-tests]

	steps:
	- name: Checkout repository
	uses: actions/checkout@v4

	- name: Set up Python
	uses: actions/setup-python@v5
	with:
	python-version: '3.11'

	- name: Install UI test dependencies
	run: \|
	pip install -r tests/e2e_ui/requirements.txt

	- name: Install Playwright browsers
	run: \|
	playwright install chromium

	- name: Create Kind cluster config file
	run: \|
	cat <<EOF > kind-config.yaml
	kind: Cluster
	apiVersion: kind.x-k8s.io/v1alpha4
	nodes:
	- role: control-plane
	extraPortMappings:
	- containerPort: 30080
	hostPort: 8501
	protocol: TCP
	- containerPort: 30081
	hostPort: 8321
	protocol: TCP
	EOF

	- name: Create Kind cluster
	uses: helm/kind-action@v1
	with:
	cluster_name: rag-e2e-ui
	config: kind-config.yaml

	- name: Install Required CRDs
	run: \|
	echo "Installing CRDs required by helm chart subcomponents..."

	# OpenShift Route CRD
	kubectl apply -f - <<EOF
	apiVersion: apiextensions.k8s.io/v1
	kind: CustomResourceDefinition
	metadata:
	name: routes.route.openshift.io
	spec:
	group: route.openshift.io
	names:
	kind: Route
	listKind: RouteList
	plural: routes
	singular: route
	scope: Namespaced
	versions:
	- name: v1
	served: true
	storage: true
	schema:
	openAPIV3Schema:
	type: object
	x-kubernetes-preserve-unknown-fields: true
	EOF

	kubectl wait --for condition=established --timeout=60s crd/routes.route.openshift.io
	echo "✅ All required CRDs installed successfully"

	- name: Add Helm repository
	run: \|
	helm repo add rag-charts https://rh-ai-quickstart.github.io/ai-architecture-charts
	helm repo update

	- name: Build Helm dependencies
	run: \|
	cd deploy/helm/rag
	helm dependency build

	- name: Install RAG application
	env:
	MAAS_API_KEY: ${{ secrets.MAAS_API_KEY }}
	run: \|
	kubectl create namespace rag-e2e-ui \|\| true

	helm install rag deploy/helm/rag \
	--namespace rag-e2e-ui \
	--values tests/e2e/values-e2e.yaml \
	--set global.models.${MAAS_MODEL_ID}.url="${MAAS_ENDPOINT}" \
	--set global.models.${MAAS_MODEL_ID}.id="${MAAS_MODEL_ID}" \
	--set global.models.${MAAS_MODEL_ID}.enabled=true \
	--set global.models.${MAAS_MODEL_ID}.apiToken="${MAAS_API_KEY}" \
	--set-json llama-stack.initContainers='[]' \
	--skip-crds \
	--timeout 20m \
	--debug

	- name: Wait for services to be ready
	run: \|
	kubectl wait --for=condition=available --timeout=600s \
	deployment/llamastack -n rag-e2e-ui
	kubectl wait --for=condition=available --timeout=300s \
	deployment/rag -n rag-e2e-ui

	- name: Expose services via NodePort
	run: \|
	kubectl patch service rag -n rag-e2e-ui -p '{"spec":{"type":"NodePort","ports":[{"port":8501,"nodePort":30080}]}}'
	kubectl patch service llamastack -n rag-e2e-ui -p '{"spec":{"type":"NodePort","ports":[{"port":8321,"nodePort":30081}]}}'

	- name: Port forward services
	run: \|
	kubectl port-forward -n rag-e2e-ui svc/rag 8501:8501 &
	kubectl port-forward -n rag-e2e-ui svc/llamastack 8321:8321 &
	sleep 10

	- name: Run UI E2E tests with Playwright
	env:
	RAG_UI_ENDPOINT: http://localhost:8501
	LLAMA_STACK_ENDPOINT: http://localhost:8321
	MAAS_ENDPOINT: ${{ env.MAAS_ENDPOINT }}
	MAAS_MODEL_ID: ${{ env.MAAS_MODEL_ID }}
	SKIP_MODEL_TESTS: "false" # Enable MaaS inference tests in UI
	run: \|
	echo "Running UI E2E tests with MaaS integration..."
	echo "MaaS Endpoint: ${MAAS_ENDPOINT}"
	echo "MaaS Model ID: ${MAAS_MODEL_ID}"
	pytest tests/e2e_ui/ -v --tb=short --browser chromium

	- name: Upload Playwright test results
	if: always()
	uses: actions/upload-artifact@v4
	with:
	name: playwright-test-results
	path: \|
	test-results/
	playwright-report/

	- name: Upload Playwright screenshots
	if: failure()
	uses: actions/upload-artifact@v4
	with:
	name: playwright-screenshots
	path: test-results/

	- name: Debug - Get pod logs on failure
	if: failure()
	run: \|
	echo "=== RAG UI logs ==="
	kubectl logs -l app.kubernetes.io/name=rag -n rag-e2e-ui --tail=200 \|\| echo "No RAG UI logs"

	echo "=== Llama Stack logs ==="
	kubectl logs -l app.kubernetes.io/name=llamastack -n rag-e2e-ui --tail=300 \|\| echo "No Llama Stack logs"

	- name: Cleanup UI tests
	if: always()
	run: \|
	pkill -f "kubectl port-forward" \|\| true
	# kind delete cluster --name rag-e2e-ui

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Merge pull request #114 from dminnear-rh/fix-chart-lock #5

Workflow file

Merge pull request #114 from dminnear-rh/fix-chart-lock #5

Uh oh!

Workflow file for this run