[#35] AI 디버깅을 위한 consumer workflow artifact를 구성한다#37
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This pull request introduces a debug artifact feature to help trace AI predictions and branch selection reasons during workflow execution. It adds options to upload debug artifacts, refactors branch selection to track exclusion reasons, and implements a debug observer pattern in the AI prediction runner. The feedback suggests wrapping debug artifact I/O operations and debug observer callbacks in try-catch blocks to ensure that any failures in these auxiliary diagnostic tools do not disrupt the main workflow execution.
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🔗 연관된 이슈
🎯 의도
AI prediction이 실패하거나 기대와 다른 판단을 만들었을 때 consumer repository의 GitHub Actions run에서 원인 추적용 artifact를 확인할 수 있도록 구성
📝 작업 내용
📌 요약
upload_debug_artifactopt-in input과actions/upload-artifact@v4업로드 step 추가🔍 상세
WATCHER_DEBUG_ARTIFACT_DIR가 설정된 경우에만 debug artifact 파일 생성run.json,branch-selection.json,deterministic-evidence.json,ai-target-selection.json,ai-prompt.json,ai-response.json,ai-error.json,ai-result.json,report.md기록upload_debug_artifact기본값은false로 유지하여 일반 실행에서는 artifact 업로드 비활성watcher-debug이름으로 업로드GITHUB_TOKEN,WATCHER_GITHUB_TOKEN,OPENAI_API_KEY,DISCORD_WEBHOOK_URL, raw file content, raw diff 전문 미기록📸 영상 / 이미지 (Optional)