* feat: Enhance annotation module with template management and validation
- Added DatasetMappingCreateRequest and DatasetMappingUpdateRequest schemas to handle dataset mapping requests with camelCase and snake_case support.
- Introduced Annotation Template schemas including CreateAnnotationTemplateRequest, UpdateAnnotationTemplateRequest, and AnnotationTemplateResponse for managing annotation templates.
- Implemented AnnotationTemplateService for creating, updating, retrieving, and deleting annotation templates, including validation of configurations and XML generation.
- Added utility class LabelStudioConfigValidator for validating Label Studio configurations and XML formats.
- Updated database schema for annotation templates and labeling projects to include new fields and constraints.
- Seeded initial annotation templates for various use cases including image classification, object detection, and text classification.
* feat: Enhance TemplateForm with improved validation and dynamic field rendering; update LabelStudio config validation for camelCase support
* feat: Update docker-compose.yml to mark datamate dataset volume and network as external
* feat: Refactor configuration and sync logic for improved dataset handling and logging
* feat: Enhance annotation synchronization and dataset file management
- Added new fields `tags_updated_at` to `DatasetFiles` model for tracking the last update time of tags.
- Implemented new asynchronous methods in the Label Studio client for fetching, creating, updating, and deleting task annotations.
- Introduced bidirectional synchronization for annotations between DataMate and Label Studio, allowing for flexible data management.
- Updated sync service to handle annotation conflicts based on timestamps, ensuring data integrity during synchronization.
- Enhanced dataset file response model to include tags and their update timestamps.
- Modified database initialization script to create a new column for `tags_updated_at` in the dataset files table.
- Updated requirements to ensure compatibility with the latest dependencies.
* refactor: rename artifactId and application name to 'datamate'; add model configuration and related services
* refactor: simplify package scanning by using wildcard for mapper packages
* feat: add model health check functionality and improve model configuration
* feat: increase api_key length and enhance ModelConfig annotations
* refactor: rename artifactId and application name to 'datamate'; add model configuration and related services
* refactor: simplify package scanning by using wildcard for mapper packages
* feat: add model health check functionality and improve model configuration
* Enhance CleaningTaskService to track cleaning process progress and update ExecutorType to DATAMATE
* Refactor project to use 'datamate' naming convention for services and configurations
