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This PR adds a comprehensive execution analytics admin endpoint that generates AI-powered activity summaries and correctness scores for graph executions, with proper feature flag bypass for admin use. ### Changes 🏗️ **Backend Changes:** - Added admin endpoint: `/api/executions/admin/execution_analytics` - Implemented feature flag bypass with `skip_feature_flag=True` parameter for admin operations - Fixed async database client usage (`get_db_async_client`) to resolve async/await errors - Added batch processing with configurable size limits to handle large datasets - Comprehensive error handling and logging for troubleshooting - Renamed entire feature from "Activity Backfill" to "Execution Analytics" for clarity **Frontend Changes:** - Created clean admin UI for execution analytics generation at `/admin/execution-analytics` - Built form with graph ID input, model selection dropdown, and optional filters - Implemented results table with status badges and detailed execution information - Added CSV export functionality for analytics results - Integrated with generated TypeScript API client for proper authentication - Added proper error handling with toast notifications and loading states **Database & API:** - Fixed critical async/await issue by switching from sync to async database client - Updated router configuration and endpoint naming for consistency - Generated proper TypeScript types and API client integration - Applied feature flag filtering at API level while bypassing for admin operations ### Checklist 📋 #### For code changes: - [x] I have clearly listed my changes in the PR description - [x] I have made a test plan - [x] I have tested my changes according to the test plan: **Test Plan:** - [x] Admin can access execution analytics page at `/admin/execution-analytics` - [x] Form validation works correctly (requires graph ID, validates inputs) - [x] API endpoint `/api/executions/admin/execution_analytics` responds correctly - [x] Authentication works properly through generated API client - [x] Analytics generation works with different LLM models (gpt-4o-mini, gpt-4o, etc.) - [x] Results display correctly with appropriate status badges (success/failed/skipped) - [x] CSV export functionality downloads correct data - [x] Error handling displays appropriate toast messages - [x] Feature flag bypass works for admin users (generates analytics regardless of user flags) - [x] Batch processing handles multiple executions correctly - [x] Loading states show proper feedback during processing #### For configuration changes: - [x] `.env.default` is updated or already compatible with my changes - [x] `docker-compose.yml` is updated or already compatible with my changes - [x] No configuration changes required for this feature **Related to:** PR #11325 (base correctness score functionality) 🤖 Generated with [Claude Code](https://claude.ai/code) --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com> Co-authored-by: Zamil Majdy <majdyz@users.noreply.github.com>