- Updated the tender service to include a new dependency for listing rejected tenders by company, allowing for more refined tender recommendations.
- Introduced a new field in the SearchForm to specify whether to exclude rejected tenders from the recommendation results.
- Enhanced the Recommend method to filter out rejected tenders based on the new exclusion logic, improving the relevance of AI-ranked tender recommendations.
- Added unit tests to verify the exclusion logic for rejected tenders, ensuring robust functionality.
This update improves the tender recommendation process by ensuring that company-rejected tenders are not included in the results, enhancing user experience and satisfaction.
- Added a new endpoint in the `tender` handler for retrieving AI-ranked tender recommendations for a company, improving the functionality of the admin panel.
- Updated the `SearchForm` to include a query parameter for `only_active_deadlines`, allowing for more flexible search options.
- Enhanced API documentation for the new endpoint to provide clear usage instructions and expected parameters.
This update improves the tender management system by providing administrators with better tools for accessing relevant tender information.
- Introduced `FormatAIProcedureRef` and `ParseAIProcedureRef` functions in the `tender` domain for handling AI service tender references.
- Added unit tests for these functions in `ai_reference_test.go` to ensure correct parsing and formatting behavior.
- Updated the `TenderResponse` struct to include a new `ProcedureRef` field for improved data representation.
- Enhanced the `GetByProcedureReference` method in the repository to retrieve tenders based on the new procedure reference format.
- Modified the `Recommend` method in the service layer to utilize the new procedure reference handling, improving the recommendation process.
This update enhances the handling of AI procedure references, ensuring better data integrity and usability in the tender management system.
- Changed the `Rank` field type from `string` to `int` in the `RecommendedTenderResponse` struct within the `company` domain for better data representation.
- Updated the `Rank` field type from `string` to `int` in the `TenderResponse` struct within the `tender` domain to ensure consistency in ranking data.
- Modified the `Rank` field type from `string` to `int` in the `RecommendedTender` struct within the AI summarizer package to align with the updated data structure.
This update enhances the data integrity and consistency across the tender management system by standardizing the rank representation as an integer.
- Added new fields `Rank` and `Analysis` to the `TenderResponse` struct for improved data representation.
- Updated the `RecommendTenders` handler to reflect changes in API documentation, including a new summary and description for AI-ranked tender recommendations.
- Improved error handling in the recommendation process, ensuring appropriate responses for missing company IDs and unavailable AI services.
This update enhances the tender response capabilities and improves the clarity of the recommendation API, aligning with the overall goal of providing better insights for users.
- Updated the `ResolvedEstimatedValueAndCurrency` method to aggregate procurement lot values when the tender-level estimated value is not set, improving accuracy in value retrieval.
- Introduced the `AggregateProcurementLotEstimatedValue` function to sum estimated values from procurement lots and return the first found currency.
- Modified the `ToResponseWithLanguage` method to utilize the new estimated value resolution logic.
- Added unit tests for the new functionality, ensuring correct behavior for various scenarios in the `entity_test.go` and `budget_test.go` files.
This update improves the handling of estimated values in tenders, enhancing the overall reliability of the tender management system.
- Added `NoticePublicationID` field to the `SearchForm` for filtering tenders by TED notice publication ID.
- Updated Swagger documentation in the handler methods to include the new `notice_publication_id` parameter for relevant endpoints.
- Modified the repository's search filter to incorporate the new `NoticePublicationID` field, allowing for more precise search queries.
This update improves the search capabilities within the tender management system, enhancing user experience and data retrieval accuracy.
- Updated the AI pipeline service to include a new `ScrapedDocumentMetadataSyncer` interface for persisting scraped document metadata onto tender records.
- Modified the `NewService` function to accept the new metadata syncer dependency.
- Implemented synchronization of scraped document metadata in the `ScrapeDocuments` and `Run` methods.
- Enhanced the tender service to enrich search filters based on scraped documents and added a new method for syncing scraped documents from storage.
- Updated the `SearchForm` to include `ContractFolderIDsWithDocuments` for better handling of scraped documents in queries.
This update improves the integration of scraped document handling within the AI pipeline, enhancing data consistency and operational efficiency in the tender management system.
- 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.
- Modified the ToResponse method in the Tender entity to create an OrganizationResponse instance for BuyerOrganization, ensuring safe access to its Name field.
- This change improves the robustness of the response structure by preventing potential nil dereference errors when BuyerOrganization is not set.
- Renamed and restructured tender-related API endpoints for improved clarity and consistency, including changing the route from `/admin/tenders` to `/admin/v1/companies` and updating the associated methods.
- Introduced a new SearchForm structure for listing tenders with advanced filtering capabilities, enhancing the API's search functionality.
- Updated the service and repository layers to align with the new endpoint structure, ensuring proper handling of tender data.
- Enhanced Swagger and YAML documentation to reflect the changes in endpoint structure, including detailed descriptions and examples for the new search functionality.
- Improved error handling and response structures to provide clearer feedback to API consumers, ensuring a more robust and user-friendly experience.
- Changed references in API documentation from `main.HealthResponse` to `bootstrap.HealthResponse` for consistency.
- Added new query parameters `publication_from` and `publication_to` to the tender listing and recommendation endpoints to allow filtering by publication date.
- Updated the `ListTendersRequest` struct to include optional fields for `from` and `to` timestamps.
- Modified the `TenderRepository` and `TenderService` interfaces to support the new filtering parameters in the tender listing functionality.
- Enhanced the service and handler layers to process the new query parameters, improving the flexibility of tender retrieval.
- Added a new field 'TenderID' to the TenderResponse structure, improving the data model for tender management.
- Updated the ToTenderResponse method to include the TenderID in the response, ensuring consistency in API outputs.
- This enhancement aligns with the ongoing improvements to the tender management system's data handling capabilities.
- Added 'ted_samples/' to .gitignore to exclude TED sample files from version control.
- Updated the TED scraper configuration to extend the cleanup duration from 24 hours to 72 hours, allowing for better resource management.
- Enhanced the Tender entity by adding new fields: TenderDeadline, SubmissionDeadline, ApplicationDeadline, and SubmissionURL, improving the data model for tender management.
- Updated the TenderResponse structure to include the new fields, ensuring consistency in API responses.
- Implemented logic in the TED scraper to calculate submission and application deadlines based on tender deadlines, enhancing the scraping functionality.
- Introduced a new tender approval management system, including the creation of tender approval entities, services, and repositories.
- Implemented CRUD operations for tender approvals, allowing companies to approve or reject tenders.
- Developed administrative and public API endpoints for listing, retrieving, and updating tender approvals with comprehensive filtering options.
- Enhanced Swagger documentation to accurately reflect the new endpoints, including detailed descriptions, parameters, and response formats.
- Updated existing routes to include tender approval management, ensuring adherence to Clean Architecture principles and maintaining a clear separation of concerns in the handler layer.
- Updated the tender API to include a new endpoint for recommending public tenders based on company profiles, enhancing user experience for mobile application users.
- Modified existing routes to reflect the new structure, changing the tender details route and adding a dedicated recommendation route.
- Improved Swagger documentation to accurately represent the new endpoint, including detailed descriptions, parameters, and response formats.
- Ensured adherence to Clean Architecture principles by maintaining clear separation of concerns in the service and handler layers.
- Removed all scraping-related functionality, including routes, handlers, services, and repository methods, to streamline the tender management system.
- Updated the tender API to focus solely on tender management, enhancing endpoints for listing, retrieving, and updating tenders.
- Improved Swagger documentation to reflect the removal of scraping endpoints and the addition of new tender-related features.
- Ensured adherence to Clean Architecture principles throughout the refactoring process, maintaining a clear separation of concerns.
- Updated the tender service to include company-based matching for tenders, allowing for more relevant results based on company CPV codes.
- Modified the ListTenders endpoint to accept a company ID parameter for calculating match percentages and sorting tenders accordingly.
- Refactored the tender response structure to include match percentage and days until deadline for better client-side handling.
- Updated API documentation to reflect changes in the tender listing functionality and added new endpoints for public tender access.
- Removed deprecated customer-related methods and streamlined customer listing functionality for improved clarity and performance.
- Introduced a new TED scraper in `cmd/scraper` to handle downloading and parsing TED XML files.
- Added configuration management for the scraper, including a new `Config` struct and YAML configuration file.
- Created necessary handler, service, and repository layers for tender management, adhering to Clean Architecture principles.
- Implemented comprehensive logging and error handling throughout the scraper functionality.
- Updated API routes to include tender management operations, enhancing the overall system capabilities.
Mazyar