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* 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: Add tag configuration management and related components - Introduced new components for tag selection and browsing in the frontend. - Added API endpoint to fetch tag configuration from the backend. - Implemented tag configuration management in the backend, including loading from YAML. - Enhanced template service to support dynamic tag rendering based on configuration. - Updated validation utilities to incorporate tag configuration checks. - Refactored existing code to utilize the new tag configuration structure. * feat: Refactor LabelStudioTagConfig for improved configuration loading and validation * feat: Update Makefile to include backend-python-docker-build in the build process * feat: Migrate to poetry for better deps management * Add pyyaml dependency and update Dockerfile to use Poetry for dependency management - Added pyyaml (>=6.0.3,<7.0.0) to pyproject.toml dependencies. - Updated Dockerfile to install Poetry and manage dependencies using it. - Improved layer caching by copying only dependency files before the application code. - Removed unnecessary installation of build dependencies to keep the final image size small. * feat: Remove duplicated backend-python-docker-build target from Makefile * fix: airflow is not ready for adding yet * feat: update Python version to 3.12 and remove project installation step in Dockerfile
51 lines
1.1 KiB
Python
51 lines
1.1 KiB
Python
from .config import (
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ConfigResponse,
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TagConfigResponse
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)
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from .mapping import (
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DatasetMappingCreateRequest,
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DatasetMappingCreateResponse,
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DatasetMappingUpdateRequest,
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DatasetMappingResponse,
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DeleteDatasetResponse,
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)
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from .sync import (
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SyncDatasetRequest,
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SyncDatasetResponse,
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SyncAnnotationsRequest,
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SyncAnnotationsResponse,
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)
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from .tag import (
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UpdateFileTagsRequest,
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UpdateFileTagsResponse,
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)
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from .template import (
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CreateAnnotationTemplateRequest,
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UpdateAnnotationTemplateRequest,
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AnnotationTemplateResponse,
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AnnotationTemplateListResponse
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)
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__all__ = [
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"ConfigResponse",
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"TagConfigResponse",
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"DatasetMappingCreateRequest",
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"DatasetMappingCreateResponse",
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"DatasetMappingUpdateRequest",
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"DatasetMappingResponse",
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"SyncDatasetRequest",
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"SyncDatasetResponse",
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"SyncAnnotationsRequest",
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"SyncAnnotationsResponse",
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"DeleteDatasetResponse",
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"UpdateFileTagsRequest",
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"UpdateFileTagsResponse",
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"CreateAnnotationTemplateRequest",
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"UpdateAnnotationTemplateRequest",
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"AnnotationTemplateResponse",
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"AnnotationTemplateListResponse",
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] |