feat(ml): add TA-Lib annotation generation and import workflow

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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.

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This commit is contained in:

Marko Djordjevic 2026-02-15 19:18:28 +01:00

parent 228f70daf3

commit 847ff67986

18 changed files with 5416 additions and 7 deletions

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