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breakpilot-pwa/admin-v2/.woodpecker/auto-fix.yml
BreakPilot Dev 557305db5d
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feat: Add Academy, Whistleblower, Incidents SDK modules, pitch-deck, blog and CI/CD config
- Academy, Whistleblower, Incidents frontend pages with API proxies and types
- Vendor compliance API proxy route
- Go backend handlers and models for all new SDK modules
- Investor pitch-deck app with interactive slides
- Blog section with DSGVO, AI Act, NIS2, glossary articles
- MkDocs documentation site
- CI/CD pipelines (Woodpecker, GitHub Actions), security scanning config
- Planning and implementation documentation

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-13 21:12:16 +01:00

133 lines
4.0 KiB
YAML

# Woodpecker CI Auto-Fix Pipeline
# Automatische Reparatur fehlgeschlagener Tests
#
# Laeuft taeglich um 2:00 Uhr nachts
# Analysiert offene Backlog-Items und versucht automatische Fixes
when:
- event: cron
cron: "0 2 * * *" # Taeglich um 2:00 Uhr
clone:
git:
image: woodpeckerci/plugin-git
settings:
depth: 1
extra_hosts:
- macmini:192.168.178.100
steps:
# ========================================
# 1. Fetch Failed Tests from Backlog
# ========================================
fetch-backlog:
image: curlimages/curl:latest
commands:
- |
curl -s "http://backend:8000/api/tests/backlog?status=open&priority=critical" \
-o backlog-critical.json
curl -s "http://backend:8000/api/tests/backlog?status=open&priority=high" \
-o backlog-high.json
- echo "=== Kritische Tests ==="
- cat backlog-critical.json | head -50
- echo "=== Hohe Prioritaet ==="
- cat backlog-high.json | head -50
# ========================================
# 2. Analyze and Classify Errors
# ========================================
analyze-errors:
image: python:3.12-slim
commands:
- pip install --quiet jq-py
- |
python3 << 'EOF'
import json
import os
def classify_error(error_type, error_msg):
"""Klassifiziert Fehler nach Auto-Fix-Potential"""
auto_fixable = {
'nil_pointer': 'high',
'import_error': 'high',
'undefined_variable': 'medium',
'type_error': 'medium',
'assertion': 'low',
'timeout': 'low',
'logic_error': 'manual'
}
return auto_fixable.get(error_type, 'manual')
# Lade Backlog
try:
with open('backlog-critical.json') as f:
critical = json.load(f)
with open('backlog-high.json') as f:
high = json.load(f)
except:
print("Keine Backlog-Daten gefunden")
exit(0)
all_items = critical.get('items', []) + high.get('items', [])
auto_fix_candidates = []
for item in all_items:
fix_potential = classify_error(
item.get('error_type', 'unknown'),
item.get('error_message', '')
)
if fix_potential in ['high', 'medium']:
auto_fix_candidates.append({
'id': item.get('id'),
'test_name': item.get('test_name'),
'error_type': item.get('error_type'),
'fix_potential': fix_potential
})
print(f"Auto-Fix Kandidaten: {len(auto_fix_candidates)}")
with open('auto-fix-candidates.json', 'w') as f:
json.dump(auto_fix_candidates, f, indent=2)
EOF
depends_on:
- fetch-backlog
# ========================================
# 3. Generate Fix Suggestions (Placeholder)
# ========================================
generate-fixes:
image: python:3.12-slim
commands:
- |
echo "Auto-Fix Generation ist in Phase 4 geplant"
echo "Aktuell werden nur Vorschlaege generiert"
# Hier wuerde Claude API oder anderer LLM aufgerufen werden
# python3 scripts/auto-fix-agent.py auto-fix-candidates.json
echo "Fix-Vorschlaege wuerden hier generiert werden"
depends_on:
- analyze-errors
# ========================================
# 4. Report Results
# ========================================
report-results:
image: curlimages/curl:latest
commands:
- |
curl -X POST "http://backend:8000/api/tests/auto-fix/report" \
-H "Content-Type: application/json" \
-d "{
\"run_date\": \"$(date -Iseconds)\",
\"candidates_found\": $(cat auto-fix-candidates.json | wc -l),
\"fixes_attempted\": 0,
\"fixes_successful\": 0,
\"status\": \"analysis_only\"
}" || true
when:
status: [success, failure]