n8n/.github/workflows/test-evals-instance-ai.yml

name: 'Test: Instance AI Exec Evals'

on:
  workflow_call:
    inputs:
      branch:
        description: 'GitHub branch to test'
        required: false
        type: string
        default: 'master'
      filter:
        description: 'Filter test cases by name (e.g. "contact-form")'
        required: false
        type: string
        default: ''
  workflow_dispatch:
    inputs:
      branch:
        description: 'GitHub branch to test'
        required: false
        default: 'master'
      filter:
        description: 'Filter test cases by name (e.g. "contact-form")'
        required: false
        default: ''

jobs:
  run-evals:
    name: 'Run Evals'
    runs-on: blacksmith-4vcpu-ubuntu-2204
    timeout-minutes: 45
    env:
      # Each port hosts an independent n8n container. The eval CLI's
      # work-stealing allocator dispatches builds across them, capped per-lane.
      # 9 lanes on 4vcpu — builds are LLM-bound so CPU headroom is sufficient;
      # bump back to 8vcpu if contention shows up.
      LANE_PORTS: '5678,5679,5680,5681,5682,5683,5684,5685,5686'
    permissions:
      contents: read
      pull-requests: write

    steps:
      - name: Checkout
        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
        with:
          ref: ${{ inputs.branch || github.ref }}
          fetch-depth: 1

      - name: Setup Environment
        uses: ./.github/actions/setup-nodejs
        with:
          build-command: 'pnpm build'

      # Cache populated by prepare-docker; fallback covers PRs that only touch this workflow file.
      - name: Load n8n Docker image
        id: load-image
        continue-on-error: true
        uses: ./.github/actions/load-n8n-docker

      - name: Build Docker image (fallback on cache miss)
        if: steps.load-image.outcome == 'failure'
        run: pnpm build:docker
        env:
          INCLUDE_TEST_CONTROLLER: 'true'

      - name: Start n8n containers
        env:
          EVALS_ANTHROPIC_KEY: ${{ secrets.EVALS_ANTHROPIC_KEY }}
          N8N_LICENSE_ACTIVATION_KEY: ${{ secrets.N8N_LICENSE_ACTIVATION_KEY }}
          N8N_LICENSE_CERT: ${{ secrets.N8N_LICENSE_CERT }}
          N8N_ENCRYPTION_KEY: ${{ secrets.N8N_ENCRYPTION_KEY }}
          DAYTONA_API_KEY: ${{ secrets.DAYTONA_API_KEY }}
        run: |
          IFS=',' read -ra PORTS <<< "$LANE_PORTS"
          for i in "${!PORTS[@]}"; do
            port="${PORTS[$i]}"
            docker run -d --name "n8n-eval-$((i+1))" \
              -e E2E_TESTS=true \
              -e N8N_ENABLED_MODULES=instance-ai \
              -e N8N_AI_ENABLED=true \
              -e N8N_INSTANCE_AI_MODEL_API_KEY="$EVALS_ANTHROPIC_KEY" \
              -e N8N_AI_ASSISTANT_BASE_URL="" \
              -e N8N_INSTANCE_AI_SANDBOX_ENABLED=true \
              -e N8N_INSTANCE_AI_SANDBOX_PROVIDER=daytona \
              -e DAYTONA_API_URL=https://app.daytona.io/api \
              -e DAYTONA_API_KEY="$DAYTONA_API_KEY" \
              -e N8N_LICENSE_ACTIVATION_KEY="$N8N_LICENSE_ACTIVATION_KEY" \
              -e N8N_LICENSE_CERT="$N8N_LICENSE_CERT" \
              -e N8N_ENCRYPTION_KEY="$N8N_ENCRYPTION_KEY" \
              -p "$port:5678" \
              n8nio/n8n:local
          done
          # 120s budget per port: containers booting in parallel on a shared
          # 4vcpu runner contend for CPU/disk during n8n's startup (DB migrations,
          # license init), so each takes longer than a solo boot.
          for port in "${PORTS[@]}"; do
            ready=false
            for i in $(seq 1 120); do
              if curl -s "http://localhost:$port/healthz/readiness" -o /dev/null -w "%{http_code}" | grep -q 200; then
                echo "n8n on port $port ready after ${i}s"
                ready=true
                break
              fi
              sleep 1
            done
            if [ "$ready" != "true" ]; then
              echo "::error::n8n on port $port failed to start within 120s"
              for n in $(docker ps -aq --filter "name=n8n-eval-"); do
                echo "Logs for $n:"
                docker logs "$n" --tail 30 || true
              done
              exit 1
            fi
          done          

      - name: Create test users
        run: |
          IFS=',' read -ra PORTS <<< "$LANE_PORTS"
          for port in "${PORTS[@]}"; do
            curl -sf -X POST "http://localhost:$port/rest/e2e/reset" \
              -H "Content-Type: application/json" \
              -d '{
                "owner":{"email":"nathan@n8n.io","password":"PlaywrightTest123","firstName":"Eval","lastName":"Owner"},
                "admin":{"email":"admin@n8n.io","password":"PlaywrightTest123","firstName":"Admin","lastName":"User"},
                "members":[],
                "chat":{"email":"chat@n8n.io","password":"PlaywrightTest123","firstName":"Chat","lastName":"User"}
              }'
          done          

      # Belt-and-suspenders: env vars set sandbox config but persisted admin
      # settings can override. Per-lane assertion catches env-injection hiccups
      # or unexpected DB-side state. A single misconfigured lane would
      # silently route some builds through tool mode and pollute results.
      - name: Assert sandbox is enabled on every lane
        run: |
          IFS=',' read -ra PORTS <<< "$LANE_PORTS"
          bad=0
          for i in "${!PORTS[@]}"; do
            port="${PORTS[$i]}"
            lane="$((i+1))"
            curl -sf -X POST "http://localhost:$port/rest/login" \
              -H "Content-Type: application/json" \
              -d '{"emailOrLdapLoginId":"nathan@n8n.io","password":"PlaywrightTest123"}' \
              -c "/tmp/cookies-$port.txt" -o /dev/null
            cfg=$(curl -sf -b "/tmp/cookies-$port.txt" \
              "http://localhost:$port/rest/instance-ai/settings" \
              | jq -r '.data | "\(.sandboxEnabled) \(.sandboxProvider)"')
            if [ "$cfg" != "true daytona" ]; then
              echo "::error::lane $lane (port $port): expected 'true daytona', got '$cfg'"
              bad=$((bad+1))
            else
              echo "  lane $lane: sandboxEnabled=true sandboxProvider=daytona ok"
            fi
          done
          if [ "$bad" -gt 0 ]; then
            echo "::error::$bad lane(s) misconfigured - eval would mix sandbox + tool-mode builds"
            exit 1
          fi          

      - name: Run Instance AI Evals
        continue-on-error: true
        working-directory: packages/@n8n/instance-ai
        env:
          N8N_INSTANCE_AI_MODEL_API_KEY: ${{ secrets.EVALS_ANTHROPIC_KEY }}
          LANGSMITH_TRACING: 'true'
          LANGSMITH_ENDPOINT: ${{ secrets.EVALS_LANGSMITH_ENDPOINT }}
          LANGSMITH_API_KEY: ${{ secrets.EVALS_LANGSMITH_API_KEY }}
          LANGSMITH_REVISION_ID: ${{ github.sha }}
          LANGSMITH_BRANCH: ${{ github.head_ref || github.ref_name }}
        run: |
          IFS=',' read -ra PORTS <<< "$LANE_PORTS"
          URLS=()
          for port in "${PORTS[@]}"; do
            URLS+=("http://localhost:$port")
          done
          BASE_URLS=$(IFS=,; printf '%s' "${URLS[*]}")
          pnpm eval:instance-ai \
            --base-url "$BASE_URLS" \
            --concurrency 32 \
            --verbose \
            --iterations 5 \
            ${{ inputs.filter && format('--filter "{0}"', inputs.filter) || '' }}          

      # Captures sandbox/builder/Daytona signals that surface during the eval
      # (after migrations finish). Two layers of secret-leak defense:
      #
      #   1. Filter to specific diagnostic patterns — never tail raw output.
      #      The grep allowlist scopes the log surface to lines we care
      #      about for debugging (sandbox lifecycle, builder, errors).
      #
      #   2. Re-register secrets via ::add-mask:: so any line that does
      #      match the allowlist has the secret values replaced with ***
      #      before reaching the GH Actions log. GitHub auto-masks
      #      ${{ secrets.X }} references, but the masking is fragile
      #      against transformed or split values; explicit registration
      #      reinforces it.
      #
      # Runs even on eval failure so we have the post-mortem regardless.
      - name: Capture n8n container logs (debug)
        if: ${{ always() }}
        env:
          EVALS_ANTHROPIC_KEY: ${{ secrets.EVALS_ANTHROPIC_KEY }}
          DAYTONA_API_KEY: ${{ secrets.DAYTONA_API_KEY }}
          N8N_LICENSE_ACTIVATION_KEY: ${{ secrets.N8N_LICENSE_ACTIVATION_KEY }}
          N8N_LICENSE_CERT: ${{ secrets.N8N_LICENSE_CERT }}
          N8N_ENCRYPTION_KEY: ${{ secrets.N8N_ENCRYPTION_KEY }}
        run: |
          # Layer 2 — defense in depth: explicitly mask each secret's value.
          # ::add-mask:: is a single-line workflow command. Multi-line secrets
          # (e.g. N8N_LICENSE_CERT is PEM-encoded) must be masked one line at
          # a time, otherwise only the first line is registered.
          for v in "$EVALS_ANTHROPIC_KEY" "$DAYTONA_API_KEY" \
                   "$N8N_LICENSE_ACTIVATION_KEY" "$N8N_LICENSE_CERT" \
                   "$N8N_ENCRYPTION_KEY"; do
            [ -z "$v" ] && continue
            while IFS= read -r line; do
              [ -n "$line" ] && echo "::add-mask::$line"
            done <<< "$v"
          done

          # Layer 1 — accuracy filter: only surface diagnostic signals.
          # `tail -100` after the filter so we get the LATEST matching lines
          # (post-eval failure signal), not the earliest startup-time ones.
          SIGNALS='sandbox|builder|daytona|instance.?ai|error|warn|reject|exception|fail'
          for c in $(docker ps -aq --filter "name=n8n-eval-"); do
            name=$(docker inspect --format '{{.Name}}' "$c" | sed 's|^/||')
            echo ""
            echo "============================================================"
            echo "=== $name (filtered diagnostic signals, last 100 lines) ==="
            echo "============================================================"
            docker logs "$c" 2>&1 \
              | grep -ivE 'migration' \
              | grep -iE "$SIGNALS" \
              | tail -100 \
              || true
          done          

      - name: Stop n8n containers
        if: ${{ always() }}
        run: |
          mapfile -t ids < <(docker ps -aq --filter "name=n8n-eval-")
          if [ "${#ids[@]}" -gt 0 ]; then
            docker stop "${ids[@]}" 2>/dev/null || true
            docker rm "${ids[@]}" 2>/dev/null || true
          fi          

      - name: Post eval results to PR
        if: ${{ always() && github.event_name == 'pull_request' }}
        env:
          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
        run: |
          # The eval CLI writes the full PR comment as eval-pr-comment.md
          # (see comparison/format.ts:formatComparisonMarkdown). It includes
          # the alert, aggregate, comparison sections, per-test-case results
          # collapsed, and failure details collapsed. CI just relays it.
          COMMENT_FILE="packages/@n8n/instance-ai/eval-pr-comment.md"
          if [ ! -f "$COMMENT_FILE" ]; then
            echo "No PR comment file found (eval likely cancelled before writing results)"
            exit 0
          fi
          cp "$COMMENT_FILE" /tmp/eval-comment.md

          # Find and update existing eval comment, or create new one
          COMMENT_ID=$(gh api "repos/${{ github.repository }}/issues/${{ github.event.pull_request.number }}/comments" \
            --jq '.[] | select(.body | startswith("### Instance AI Workflow Eval")) | .id' | tail -1)

          if [ -n "$COMMENT_ID" ]; then
            gh api "repos/${{ github.repository }}/issues/comments/${COMMENT_ID}" -X PATCH -F body=@/tmp/eval-comment.md
          else
            gh pr comment "${{ github.event.pull_request.number }}" --body-file /tmp/eval-comment.md
          fi          

      - name: Upload Results
        if: ${{ always() }}
        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
        with:
          name: instance-ai-workflow-eval-results
          path: |
            packages/@n8n/instance-ai/eval-results.json
            packages/@n8n/instance-ai/.data/workflow-eval-report.html            
          retention-days: 14