- Rename workflow from "Release Notify (Ali AI Final)" to "Release Notify Workflow" for clarity
- Replace jq multi-line argument construction with printf for better readability
- Simplify payload generation by building content string separately before passing to jq
- Reduce complexity of nested jq arguments while maintaining identical output format
- Add new GitHub Actions workflow to notify WeChat on release branch merges
- Implement HEAD sync check to prevent race conditions with GitHub API
- Add commit validation to ensure PR is the latest merge to release branch
- Fetch PR commits and generate AI summary using Alibaba Qwen API
- Send formatted Markdown notification to WeChat webhook with release details
- Include branch, author, PR title, and AI-generated change summary in notification
- Add GitHub Actions workflow to notify on merged release branch PRs
- Implement HEAD sync check to ensure branch is up-to-date before notification
- Fetch commit messages from merged PR for AI summarization
- Integrate Alibaba Qwen AI to generate Chinese release summaries for QA team
- Send formatted Markdown notifications to WeChat webhook with PR details and AI summary
- Workflow triggers only on final PR merge to release branches to avoid duplicate notifications
Multiple services were performing individual database queries for FileMetadata when resolving missing file names/sizes. This change batches the queries using `in_()` to reduce database round trips and improve performance.
feat(app): support file metadata in chat messages and DSL app overwrite
- Extended chat message file objects with `name`, `size`, and `file_type` fields across app_chat_service and workflow_service
- Added ability to overwrite existing app configurations via DSL import in app_dsl_service, including type validation and config update logic for AgentConfig, MultiAgentConfig, and WorkflowConfig
- Replace Statement-based implicit memory count (count/3) with actual
MemorySummary node count filtered by DERIVED_FROM_STATEMENT relationship
- Add minimum threshold of 5 MemorySummary nodes before reporting data
- Add _build_empty_profile() to return structured empty profile when
insufficient data exists, skipping unnecessary LLM calls
Added `get_user_by_id_regardless_active` in user repository to support activation/deactivation workflows, updated `user_service` to use it, and refactored `_enrich_release_config` in `app_dsl_service` to accept `default_model_config_id` as a parameter instead of reading from config dict.
Align update response with get_end_user_info by extracting profile,
knowledge_tags, and behavioral_hints to top-level keys instead of
returning raw meta_data dict.
