- Revised the Gap Analysis Report to provide detailed counts of implemented, partial, and not implemented controls, enhancing clarity on compliance status.
- Updated the ISO27001 Roadmap to include a status column for deliverables, improving tracking of progress towards certification.
- Adjusted the Statement of Applicability to reconcile summary counts with control rows and clarify the applicability of outsourced development.
These updates strengthen the documentation framework, ensuring it accurately reflects the current state of security controls and compliance efforts within the Tender Management System.
- Introduced a comprehensive suite of security documents to support ISO/IEC 27001 certification, including the ISMS Foundation, Risk Assessment Matrix, Gap Analysis Report, Statement of Applicability, and ISO27001 Roadmap.
- Updated the README to include links to the new security documentation, enhancing the project's compliance framework and providing clear guidance on security policies and procedures.
This addition strengthens the overall security posture of the Tender Management System and aligns with industry standards for information security management.
- Added `search` and `q` query parameters to the `SearchForm` for improved notification searching capabilities.
- Implemented `ResolvedSearch` method to prioritize search term resolution from the new parameters.
- Updated `GetByUserID` repository method to support searching notifications by title and message using regex.
- Enhanced logging in the `GetNotifications` service method to include search parameters.
- Updated Swagger documentation to reflect the new search parameters for the notification API.
This update improves the user experience by allowing more flexible and efficient searching of notifications.
- Added new AI onboarding and recommendation endpoints in the company handler for starting onboarding and retrieving ranked tender recommendations.
- Introduced `StartAIOnboarding` and `GetAIRecommendations` methods in the company service to handle AI interactions.
- Updated the company service constructor to include the AI recommendation client.
- Enhanced the AI summarizer client with methods for onboarding and fetching recommendations.
- Added response structures for onboarding and recommended tenders in the company form.
This update enhances the tender management system by integrating AI capabilities for onboarding and tender recommendations, improving user experience and operational efficiency.
- Updated `.drone.yml` to remove lingering legacy worker source files after git deletion, ensuring a clean build environment.
- Modified `Makefile` to include a new `build-worker` target that removes deprecated scraper and queue source files, streamlining the worker build process.
This change enhances the build process by eliminating outdated components and ensuring that the worker is built without legacy dependencies.
- Removed the QueueConfig structure and related queue management files as they are no longer in use.
- Updated the worker initialization to reflect the removal of queue-related configurations.
- Cleaned up the bootstrap process by eliminating deprecated logging related to the queue system.
This update streamlines the worker's configuration and prepares the codebase for future enhancements without the legacy queue management components.
Paginate un-summarized tenders and mark rows missing notice/folder IDs as handled so the worker cannot spin forever. Return 400/404 for validation and not-found cases on AI summarize/analyze triggers instead of leaking internal errors as 500.
- Added a new endpoint to trigger on-demand agentic analysis for tenders via the AI service.
- Introduced `TriggerAIAnalyze` method in the `TenderHandler` to handle requests and responses for AI analysis.
- Updated the `tenderService` to include `TriggerAIAnalyze` method, which validates input and interacts with the AI summarizer client.
- Enhanced the `AIAnalyzeResponse` and `AIAnalyzeDocument` structures to support the new analysis feature.
- Refactored the `DocumentSummarizationWorker` and `TranslationWorker` to remove deprecated MinIO dependencies, streamlining the AI service interactions.
This update improves the functionality of the tender management system by allowing users to trigger AI analysis on-demand, enhancing the overall user experience and system capabilities.
- Improved the `IsDuplicateKeyError` function to utilize structured error messages for better accuracy in identifying duplicate key errors.
- Introduced `duplicateKeyMessages` and `hasStructuredWriteException` functions to parse and extract relevant information from MongoDB error messages.
- Updated `DuplicateKeyMatchesField` to match duplicate key errors against specific fields by analyzing error messages rather than relying on substring matching.
This refactor enhances the clarity and reliability of duplicate key error handling, ensuring more precise identification of conflicts in MongoDB operations.
- Updated `InitAISummarizerClient` to accept `mongoManager` for tracking translation success.
- Introduced new `Statistics` endpoint in the dashboard to fetch scraping and translation statistics.
- Enhanced `TranslationWorker` to utilize the new success counter for tracking successful translations.
- Added necessary data structures and query forms for statistics reporting.
This refactor improves the tracking of AI translation success and provides new insights through the dashboard statistics.
Map E11000 from the per-collection phone index to friendly conflict
errors and skip redundant GetByPhone when the phone is unchanged.
Not blocking: IAT test DB may need a one-off dedupe for index build;
phone uniqueness is per collection (users vs customers), not global.
Added functionality to check for existing customers and users by phone number during registration and updates. Updated the handler, service, and repository layers to include phone number checks, ensuring unique phone numbers across customers and users.
Frontend sends nested address field names for sorting; accept them alongside the existing country and state aliases.
Co-authored-by: Cursor <cursoragent@cursor.com>
Mazyar