feat(auto-annotation): add LLM-based annotation operators

Add three new LLM-powered auto-annotation operators:
- LLMTextClassification: Text classification using LLM
- LLMNamedEntityRecognition: Named entity recognition with type validation
- LLMRelationExtraction: Relation extraction with entity and relation type validation

Key features:
- Load LLM config from t_model_config table via modelId parameter
- Lazy loading of LLM configuration on first execute()
- Result validation with whitelist checking for entity/relation types
- Fault-tolerant: returns empty results on LLM failure instead of throwing
- Fully compatible with existing Worker pipeline

Files added:
- runtime/ops/annotation/_llm_utils.py: Shared LLM utilities
- runtime/ops/annotation/llm_text_classification/: Text classification operator
- runtime/ops/annotation/llm_named_entity_recognition/: NER operator
- runtime/ops/annotation/llm_relation_extraction/: Relation extraction operator

Files modified:
- runtime/ops/annotation/__init__.py: Register 3 new operators
- runtime/python-executor/datamate/auto_annotation_worker.py: Add to Worker whitelist
- frontend/src/pages/DataAnnotation/OperatorCreate/hooks/useOperatorOperations.ts: Add to frontend whitelist

frontend/src/pages/DataAnnotation/OperatorCreate/hooks/useOperatorOperations.ts

@@ -22,6 +22,9 @@ type CategoryGroup = {
 const ANNOTATION_OPERATOR_ID_WHITELIST = new Set([
   "ImageObjectDetectionBoundingBox",
   "test_annotation_marker",
+  "LLMTextClassification",
+  "LLMNamedEntityRecognition",
+  "LLMRelationExtraction",
 ]);
 
 const ensureArray = (value: unknown): string[] => {