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fix(e2e): fix e2e tests #196

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19 changes: 16 additions & 3 deletions .github/workflows/e2e-tests.yaml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@ on:
branches:
- dev
- main

push:
branches:
- dev
Expand Down Expand Up @@ -335,18 +336,24 @@ jobs:
# 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
# wait-for-models init is rendered when a MaaS model is registered; the subchart
# ignores initContainers/skipModelWait in values. Patch it out after install.
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='[]' \
--wait=false \
--skip-crds \
--timeout 20m \
--debug

kubectl patch deployment llamastack -n rag-e2e --type=json \
-p='[{"op":"replace","path":"/spec/template/spec/initContainers","value":[]}]'
kubectl rollout restart deployment/llamastack -n rag-e2e

- name: Wait for core services to be ready
run: |
echo "========================================="
Expand Down Expand Up @@ -459,7 +466,7 @@ jobs:
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) ==="
echo "=== Llama Stack logs ==="
kubectl logs -l app.kubernetes.io/name=llamastack -n rag-e2e --tail=300 || echo "No Llama Stack logs available"

echo "=== Llama Stack pod details ==="
Expand Down Expand Up @@ -618,18 +625,24 @@ jobs:
run: |
kubectl create namespace rag-e2e-ui || true

# wait-for-models init is rendered when a MaaS model is registered; the subchart
# ignores initContainers/skipModelWait in values. Patch it out after install.
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='[]' \
--wait=false \
--skip-crds \
--timeout 20m \
--debug

kubectl patch deployment llamastack -n rag-e2e-ui --type=json \
-p='[{"op":"replace","path":"/spec/template/spec/initContainers","value":[]}]'
kubectl rollout restart deployment/llamastack -n rag-e2e-ui

- name: Wait for services to be ready
run: |
kubectl wait --for=condition=available --timeout=600s \
Expand Down
72 changes: 51 additions & 21 deletions tests/e2e/values-e2e.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -47,15 +47,9 @@ volumeMounts:

# Configure models to use Red Hat MaaS
# All MaaS configuration (url, id, enabled, apiToken) will be injected via helm --set in GitHub Actions
# This allows flexible configuration from workflow environment variables
# The workflow patches out wait-for-models init after install (subchart ignores skipModelWait here)
global:
models: {}
# Example structure (populated by workflow):
# llama-3-2-3b:
# url: "https://maas-endpoint/v1"
# id: "llama-3-2-3b"
# enabled: true
# apiToken: "secret-key"

# PostgreSQL + PGVector configuration
pgvector:
Expand All @@ -68,31 +62,67 @@ pgvector:
port: "5432"
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
limits:
memory: "1Gi"
cpu: "1"

# Llama Stack configuration for MaaS
# Default chart PVC is 5Gi — too heavy for Kind on GHA runners
volumeClaimTemplates:
- metadata:
name: pg-data
spec:
accessModes: ["ReadWriteOnce"]
resources:
requests:
storage: 1Gi

# Llama Stack configuration for MaaS (ogxai/distribution-starter via llama-stack 0.8.x)
llama-stack:
enabled: true
secrets:
TAVILY_SEARCH_API_KEY: ""


initContainers: []
skipModelWait: true

# OGX starter needs more headroom than the old llamastack image in Kind CI
resources:
requests:
memory: "512Mi"
memory: "1Gi"
cpu: "500m"
limits:
memory: "1Gi"
memory: "2Gi"
cpu: "1"

# Skip waiting for models since we're using external MaaS
# Override init containers to prevent waiting for local models
initContainers: []
# Don't wait for models - they're external via MaaS
skipModelWait: true

readinessProbe:
httpGet:
path: /v1/health
port: 8321
initialDelaySeconds: 60
periodSeconds: 15
timeoutSeconds: 10
failureThreshold: 10

livenessProbe:
httpGet:
path: /v1/health
port: 8321
initialDelaySeconds: 120
periodSeconds: 30
timeoutSeconds: 10
failureThreshold: 10

# Avoid llama-stack-data PVC (2Gi RWO) — use emptyDir in Kind CI
volumes:
- configMap:
defaultMode: 420
name: run-config
name: run-config-volume
- emptyDir: {}
name: dot-llama
- emptyDir: {}
name: cache

fileProcessors:
enabled: true
Expand Down
69 changes: 48 additions & 21 deletions tests/integration/llamastack/values-e2e.yaml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -48,15 +48,9 @@ volumeMounts:

# Configure models to use Red Hat MaaS
# All MaaS configuration (url, id, enabled, apiToken) will be injected via helm --set in GitHub Actions
# This allows flexible configuration from workflow environment variables
# The workflow patches out wait-for-models init after install (subchart ignores skipModelWait here)
global:
models: {}
# Example structure (populated by workflow):
# llama-3-2-3b:
# url: "https://maas-endpoint/v1"
# id: "llama-3-2-3b"
# enabled: true
# apiToken: "secret-key"

# PostgreSQL + PGVector configuration
pgvector:
Expand All @@ -69,31 +63,64 @@ pgvector:
port: "5432"
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
limits:
memory: "1Gi"
cpu: "1"

# Llama Stack configuration for MaaS
volumeClaimTemplates:
- metadata:
name: pg-data
spec:
accessModes: ["ReadWriteOnce"]
resources:
requests:
storage: 1Gi

# Llama Stack configuration for MaaS (ogxai/distribution-starter via llama-stack 0.8.x)
llama-stack:
enabled: true
secrets:
TAVILY_SEARCH_API_KEY: ""


initContainers: []
skipModelWait: true

resources:
requests:
memory: "512Mi"
memory: "1Gi"
cpu: "500m"
limits:
memory: "1Gi"
memory: "2Gi"
cpu: "1"

# Skip waiting for models since we're using external MaaS
# Override init containers to prevent waiting for local models
initContainers: []
# Don't wait for models - they're external via MaaS
skipModelWait: true

readinessProbe:
httpGet:
path: /v1/health
port: 8321
initialDelaySeconds: 60
periodSeconds: 15
timeoutSeconds: 10
failureThreshold: 10

livenessProbe:
httpGet:
path: /v1/health
port: 8321
initialDelaySeconds: 120
periodSeconds: 30
timeoutSeconds: 10
failureThreshold: 10

volumes:
- configMap:
defaultMode: 420
name: run-config
name: run-config-volume
- emptyDir: {}
name: dot-llama
- emptyDir: {}
name: cache

fileProcessors:
enabled: true
Expand Down
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