- Introduced the GetScrapePortals method in the AI pipeline handler to list document scraping portals supported by the Opplens AI service.
- Updated the service layer to include GetScrapePortals, which retrieves the portals from the client and handles errors appropriately.
- Enhanced the routes to register the new endpoint for retrieving scrape portals.
- Added a new error type for invalid date ranges in the document scraper, improving validation and error handling.
This update expands the AI pipeline capabilities, allowing for better management of document scraping portals within the tender management system.
- Added `TranslationEnabled` and `TranslationInterval` fields to the worker configuration to manage automatic translation scheduling.
- Updated the worker initialization to log when the translation worker is disabled.
- Improved error handling in the AI summarizer client by introducing `APIStatusError` for better context on API failures, replacing direct error messages with structured error responses.
This update enhances the configurability of the worker and improves error reporting for AI service interactions, contributing to better maintainability and user experience.
- Added new routes and handlers for AI pipeline operations, including scraping documents, batch summarization, translation, and syncing with the Opplens AI service.
- Introduced request forms for handling tender references and batch operations.
- Enhanced the AI service with methods for triggering batch operations and managing pipeline runs.
- Updated Swagger documentation to reflect the new AI pipeline endpoints and their functionalities.
This update integrates comprehensive AI pipeline capabilities into the tender management system, improving operational efficiency and user experience.
- 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.
- 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.
- 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.
- 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.
Mazyar