Marko Djordjevic 847ff67986 feat(ml): add TA-Lib annotation generation and import workflow ... Add complete workflow for using TA-Lib to bootstrap training data: - generate_talib_annotations.py: Python script to run TA-Lib CDL* functions and output span annotations in UI-compatible format - import_talib_annotations.ts: TypeScript script to import generated annotations into the UI database with auto-label-type creation - npm script 'import-annotations' for easy execution - TALIB_WORKFLOW.md: Comprehensive guide covering the full cycle: * Generate patterns with TA-Lib * Import into UI * Review and edit in browser * Export and train model * Compare predictions with TA-Lib detections * Iterate for improvement This enables the intended workflow: use TA-Lib for initial annotations, manually refine them, then train a model that learns from corrections.		2026-02-15 19:18:28 +01:00
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__pycache__	feat(ml): add TA-Lib annotation generation and import workflow	2026-02-15 19:18:28 +01:00
__init__.py	feat(ml): add database schema, config parser, and DVC setup	2026-02-15 12:08:53 +01:00
annotation_ingestion.py	feat(ml): implement annotation ingestion with windowed/BIO encoding and TA-Lib patterns	2026-02-15 12:28:58 +01:00
config.py	feat(ml): add database schema, config parser, and DVC setup	2026-02-15 12:08:53 +01:00
db.py	feat(ml): add database schema, config parser, and DVC setup	2026-02-15 12:08:53 +01:00
main.py	feat(ml): implement FastAPI inference service with model loading, preprocessing, and prediction endpoints	2026-02-15 14:29:07 +01:00
preprocessing.py	feat(ml): implement FastAPI inference service with model loading, preprocessing, and prediction endpoints	2026-02-15 14:29:07 +01:00