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ai-training/_docs/02_document/state.json
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Oleksandr Bezdieniezhnykh 142c6c4de8 Refactor constants management to use Pydantic BaseModel for configuration
- Replaced module-level path variables in constants.py with a structured Pydantic Config class.
- Updated all relevant modules (train.py, augmentation.py, exports.py, dataset-visualiser.py, manual_run.py) to access paths through the new config structure.
- Fixed bugs related to image processing and model saving.
- Enhanced test infrastructure to accommodate the new configuration approach.

This refactor improves code maintainability and clarity by centralizing configuration management.
2026-03-27 18:18:30 +02:00

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{
"current_step": "complete",
"completed_steps": ["discovery", "module-analysis", "component-assembly", "system-synthesis", "verification", "solution-extraction", "problem-extraction", "final-report"],
"focus_dir": null,
"modules_total": 21,
"modules_documented": [
"constants", "utils", "security", "hardware_service", "cdn_manager",
"dto/annotationClass", "dto/imageLabel", "inference/dto", "inference/onnx_engine",
"api_client", "augmentation", "inference/tensorrt_engine", "inference/inference",
"exports", "convert-annotations", "dataset-visualiser",
"train", "start_inference",
"manual_run",
"annotation-queue/annotation_queue_dto", "annotation-queue/annotation_queue_handler"
],
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"components_written": [
"01_core", "02_security", "03_api_cdn", "04_data_models",
"05_data_pipeline", "06_training", "07_inference", "08_annotation_queue"
],
"last_updated": "2026-03-26T00:00:00Z"
}