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.

package.json

@@ -7,7 +7,8 @@
     "dev": "next dev",
     "build": "next build",
     "start": "next start",
-    "lint": "next lint"
+    "lint": "next lint",
+    "import-annotations": "tsx scripts/import_talib_annotations.ts"
   },
   "keywords": [],
   "author": "",
@@ -42,6 +43,7 @@
   },
   "devDependencies": {
     "drizzle-kit": "^0.31.9",
-    "tailwindcss": "^3.4.19"
+    "tailwindcss": "^3.4.19",
+    "tsx": "^4.21.0"
   }
 }