847ff67986
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.
9 lines
239 B
Bash
9 lines
239 B
Bash
NODE_ENV=production
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PORT=3000
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DATABASE_PATH=/app/data/candles.db
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# ML Inference Service Configuration
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INFERENCE_API_URL=http://localhost:8001
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INFERENCE_API_TIMEOUT=30000
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INFERENCE_BATCH_TIMEOUT=120000
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NEXT_PUBLIC_PREDICTIONS_ENABLED=true
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