Ignore agents directory in book build workflow #4
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| name: Deploy Edmund Agent | ||
| on: | ||
| push: | ||
| branches: [ main ] | ||
| paths: | ||
| - 'agents/edmund/**' | ||
| pull_request: | ||
| branches: [ main ] | ||
| paths: | ||
| - 'agents/edmund/**' | ||
| workflow_dispatch: | ||
| env: | ||
| AZURE_SUBSCRIPTION_ID: ${{ secrets.AZURE_SUBSCRIPTION_ID }} | ||
| AZURE_RESOURCE_GROUP: copilot-edmund | ||
| AZURE_LOCATION: eastus | ||
| AGENT_NAME: edmund-engineer | ||
| AI_FOUNDRY_PROJECT: edmund-tminus15-project | ||
| AZURE_OPENAI_ENDPOINT: "https://copilot-edmund.openai.azure.com/" | ||
| AZURE_OPENAI_API_VERSION: "2024-12-01-preview" | ||
| AZURE_OPENAI_DEPLOYMENT_NAME: "gpt-4o" | ||
| jobs: | ||
| validate: | ||
| runs-on: ubuntu-latest | ||
| steps: | ||
| - uses: actions/checkout@v4 | ||
| - name: Set up Python | ||
| uses: actions/setup-python@v4 | ||
| with: | ||
| python-version: '3.11' | ||
| - name: Install dependencies | ||
| run: | | ||
| python -m pip install --upgrade pip | ||
| pip install jsonschema pyyaml | ||
| - name: Validate agent configuration | ||
| run: | | ||
| python -c " | ||
| import json | ||
| import yaml | ||
| # Validate agent-config.json | ||
| with open('agents/edmund/agent-config.json', 'r') as f: | ||
| config = json.load(f) | ||
| print('✓ agent-config.json is valid JSON') | ||
| # Validate deployment.yaml | ||
| with open('agents/edmund/deployment.yaml', 'r') as f: | ||
| deployment = yaml.safe_load_all(f) | ||
| for doc in deployment: | ||
| if doc: | ||
| print('✓ deployment.yaml document is valid YAML') | ||
| # Check required fields | ||
| required_fields = ['agent', 'model', 'instructions'] | ||
| for field in required_fields: | ||
| if field not in config: | ||
| raise ValueError(f'Missing required field: {field}') | ||
| print('✓ All configuration files are valid') | ||
| " | ||
| - name: Test configuration syntax | ||
| run: | | ||
| cd agents/edmund | ||
| python -m json.tool agent-config.json > /dev/null | ||
| echo "✓ agent-config.json syntax is valid" | ||
| deploy-dev: | ||
| runs-on: ubuntu-latest | ||
| needs: validate | ||
| if: github.ref == 'refs/heads/main' | ||
| environment: DEMO | ||
| steps: | ||
| - uses: actions/checkout@v4 | ||
| - name: Azure Login | ||
| uses: azure/login@v1 | ||
| with: | ||
| creds: ${{ secrets.AZURE_CREDENTIALS }} | ||
| - name: Set up Azure CLI extensions | ||
| run: | | ||
| az extension add --name ml --version 2.22.0 --yes | ||
| az extension add --name ai-examples --yes | ||
| az version | ||
| - name: Verify Azure subscription and resource group | ||
| run: | | ||
| echo "Checking Azure subscription..." | ||
| az account show --output table | ||
| echo "Checking resource group..." | ||
| az group show --name $AZURE_RESOURCE_GROUP --output table || { | ||
| echo "Creating resource group $AZURE_RESOURCE_GROUP..." | ||
| az group create --name $AZURE_RESOURCE_GROUP --location $AZURE_LOCATION | ||
| } | ||
| - name: Create or update AI Foundry project | ||
| run: | | ||
| echo "Setting up AI Foundry project..." | ||
| # Check if project exists | ||
| if ! az ml workspace show --name $AI_FOUNDRY_PROJECT --resource-group $AZURE_RESOURCE_GROUP >/dev/null 2>&1; then | ||
| echo "Creating new AI Foundry project..." | ||
| az ml workspace create \ | ||
| --name $AI_FOUNDRY_PROJECT \ | ||
| --resource-group $AZURE_RESOURCE_GROUP \ | ||
| --location $AZURE_LOCATION \ | ||
| --display-name "Edmund T-Minus-15 Agent Project" \ | ||
| --description "AI Foundry project for Edmund, the Engineering Agent from T-Minus-15 methodology" | ||
| else | ||
| echo "AI Foundry project already exists" | ||
| fi | ||
| - name: Configure workspace connection | ||
| run: | | ||
| echo "Configuring AI Foundry workspace connection..." | ||
| az configure --defaults group=$AZURE_RESOURCE_GROUP workspace=$AI_FOUNDRY_PROJECT | ||
| - name: Deploy agent configuration | ||
| run: | | ||
| cd agents/edmund | ||
| echo "Preparing agent deployment..." | ||
| # Create a deployment package | ||
| mkdir -p deployment-package | ||
| cp agent-config.json deployment-package/ | ||
| cp deployment.yaml deployment-package/ | ||
| cp knowledge-sources.json deployment-package/ 2>/dev/null || echo "knowledge-sources.json not found, skipping" | ||
| echo "Agent configuration prepared for deployment" | ||
| # Deploy using Azure OpenAI integration (skip model deployment as it already exists) | ||
| echo "Configuring Edmund agent with existing Azure OpenAI deployment..." | ||
| # Create endpoint first | ||
| az ml online-endpoint create \ | ||
| --name $AGENT_NAME-endpoint \ | ||
| --resource-group $AZURE_RESOURCE_GROUP \ | ||
| --workspace-name $AI_FOUNDRY_PROJECT \ | ||
| --auth-mode key || echo "Endpoint may already exist" | ||
| # Create a simple deployment configuration without model path | ||
| cat > simple-deployment.yaml << EOF | ||
| name: $AGENT_NAME-$(date +%Y%m%d-%H%M%S) | ||
| endpoint_name: $AGENT_NAME-endpoint | ||
| code_configuration: | ||
| code: . | ||
| scoring_script: scoring.py | ||
| environment: | ||
| conda_file: conda.yaml | ||
| image: mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu20.04:latest | ||
| instance_type: Standard_DS3_v2 | ||
| instance_count: 1 | ||
| app_insights_enabled: true | ||
| request_settings: | ||
| request_timeout_ms: 90000 | ||
| max_concurrent_requests_per_instance: 1 | ||
| max_queue_wait_ms: 500 | ||
| environment_variables: | ||
| AZURE_OPENAI_ENDPOINT: "${{ env.AZURE_OPENAI_ENDPOINT }}" | ||
| AZURE_OPENAI_API_KEY: \${{ secrets.AZURE_OPENAI_API_KEY }} | ||
| AZURE_OPENAI_API_VERSION: "${{ env.AZURE_OPENAI_API_VERSION }}" | ||
| AZURE_OPENAI_DEPLOYMENT_NAME: "${{ env.AZURE_OPENAI_DEPLOYMENT_NAME }}" | ||
| AGENT_CONFIG_PATH: "./agent-config.json" | ||
| LOG_LEVEL: "INFO" | ||
| DEPLOYMENT_ENVIRONMENT: "production" | ||
| EOF | ||
| # Deploy using the simplified configuration | ||
| az ml online-deployment create \ | ||
| --file simple-deployment.yaml \ | ||
| --endpoint-name $AGENT_NAME-endpoint \ | ||
| --resource-group $AZURE_RESOURCE_GROUP \ | ||
| --workspace-name $AI_FOUNDRY_PROJECT | ||
| - name: Test deployment | ||
| run: | | ||
| echo "Testing agent deployment..." | ||
| # Wait for deployment to be ready | ||
| sleep 30 | ||
| # Test agent endpoint | ||
| az ml online-endpoint invoke \ | ||
| --name $AGENT_NAME-endpoint \ | ||
| --resource-group $AZURE_RESOURCE_GROUP \ | ||
| --workspace-name $AI_FOUNDRY_PROJECT \ | ||
| --request-file - <<EOF || echo "Deployment test completed (may need additional configuration)" | ||
| { | ||
| "messages": [ | ||
| { | ||
| "role": "user", | ||
| "content": "Hello Edmund, can you help me with a quick engineering question?" | ||
| } | ||
| ] | ||
| } | ||
| EOF | ||
| - name: Update traffic allocation | ||
| run: | | ||
| echo "Setting traffic allocation to latest deployment..." | ||
| # Get the latest deployment name | ||
| LATEST_DEPLOYMENT=$(az ml online-deployment list \ | ||
| --endpoint-name $AGENT_NAME-endpoint \ | ||
| --resource-group $AZURE_RESOURCE_GROUP \ | ||
| --workspace-name $AI_FOUNDRY_PROJECT \ | ||
| --query "[0].name" -o tsv) | ||
| if [ ! -z "$LATEST_DEPLOYMENT" ]; then | ||
| az ml online-endpoint update \ | ||
| --name $AGENT_NAME-endpoint \ | ||
| --resource-group $AZURE_RESOURCE_GROUP \ | ||
| --workspace-name $AI_FOUNDRY_PROJECT \ | ||
| --traffic "$LATEST_DEPLOYMENT=100" | ||
| echo "Traffic allocated to deployment: $LATEST_DEPLOYMENT" | ||
| fi | ||
| - name: Output deployment information | ||
| run: | | ||
| echo "=== Deployment Summary ===" | ||
| echo "Agent Name: $AGENT_NAME" | ||
| echo "Resource Group: $AZURE_RESOURCE_GROUP" | ||
| echo "AI Foundry Project: $AI_FOUNDRY_PROJECT" | ||
| echo "Location: $AZURE_LOCATION" | ||
| # Get endpoint details | ||
| az ml online-endpoint show \ | ||
| --name $AGENT_NAME-endpoint \ | ||
| --resource-group $AZURE_RESOURCE_GROUP \ | ||
| --workspace-name $AI_FOUNDRY_PROJECT \ | ||
| --output table || echo "Could not retrieve endpoint details" | ||
| echo "=== Deployment Complete ===" | ||
| cleanup-old-deployments: | ||
| runs-on: ubuntu-latest | ||
| needs: deploy-dev | ||
| if: github.ref == 'refs/heads/main' | ||
| steps: | ||
| - name: Azure Login | ||
| uses: azure/login@v1 | ||
| with: | ||
| creds: ${{ secrets.AZURE_CREDENTIALS }} | ||
| - name: Clean up old deployments | ||
| run: | | ||
| echo "Cleaning up old deployments (keeping latest 3)..." | ||
| # Get all deployments for the endpoint | ||
| DEPLOYMENTS=$(az ml online-deployment list \ | ||
| --endpoint-name $AGENT_NAME-endpoint \ | ||
| --resource-group $AZURE_RESOURCE_GROUP \ | ||
| --workspace-name $AI_FOUNDRY_PROJECT \ | ||
| --query "[].name" -o tsv | sort -r) | ||
| # Keep only the latest 3, delete the rest | ||
| echo "$DEPLOYMENTS" | tail -n +4 | while read deployment; do | ||
| if [ ! -z "$deployment" ]; then | ||
| echo "Deleting old deployment: $deployment" | ||
| az ml online-deployment delete \ | ||
| --name $deployment \ | ||
| --endpoint-name $AGENT_NAME-endpoint \ | ||
| --resource-group $AZURE_RESOURCE_GROUP \ | ||
| --workspace-name $AI_FOUNDRY_PROJECT \ | ||
| --yes --no-wait || echo "Could not delete deployment: $deployment" | ||
| fi | ||
| done | ||
