Lars
645967a2ab
Part A Implementation (Nutrition Basis Metrics): - Registry-based metadata system (flexible, not hardcoded) - 4 placeholders registered: kcal_avg, protein_avg, carb_avg, fat_avg - Evidence-based tagging (code-derived, draft-derived, unresolved, to_verify) - Single source of truth for all consumers (Prompt, GUI, Export, Validation) Technical: - backend/placeholder_registry.py: Core registry framework - backend/placeholder_registrations/nutrition_part_a.py: Part A registrations - backend/placeholder_registry_export.py: Export integration - backend/routers/prompts.py: /placeholders/export-values-extended integration Metadata completeness: - 22 metadata fields per placeholder - Evidence tracking for all fields - Architecture alignment (Layer 1/2a/2b) NO LOGIC CHANGE: - Data Layer unchanged (nutrition_metrics.py) - Resolver unchanged (placeholder_resolver.py) - Values identical (only metadata/export enhanced) Breaking Change Risk: NONE Deploy Risk: VERY LOW (only export enhancement) Plan: .claude/task/rework_0b_placeholder/NUTRITION_PART_A_CHANGE_PLAN.md Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
137 lines
4.0 KiB
Python
137 lines
4.0 KiB
Python
"""
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Placeholder Registry Export Integration
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Integrates the new placeholder registry with the existing export system.
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Provides backward-compatible export with enhanced metadata from registry.
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"""
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from typing import Dict, List
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from placeholder_registry import get_registry, EvidenceType
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def get_registry_metadata_for_export(profile_id: str) -> Dict:
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"""
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Get metadata from registry formatted for export.
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Returns:
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Dict with:
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- flat: List of all metadata dicts
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- by_category: Dict mapping category to list of metadata
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- evidence_report: Statistics about evidence types
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- validation_report: Validation issues
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"""
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registry = get_registry()
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# Get all metadata
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all_metadata = registry.get_all()
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# Build flat export
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flat = []
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for key, metadata in sorted(all_metadata.items()):
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meta_dict = metadata.to_dict()
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flat.append(meta_dict)
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# Build by_category
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by_category = {}
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for metadata in all_metadata.values():
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cat = metadata.category
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if cat not in by_category:
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by_category[cat] = []
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by_category[cat].append(metadata.to_dict())
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# Evidence report
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evidence_stats = {
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"code_derived": len(registry.get_by_evidence_type(EvidenceType.CODE_DERIVED)),
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"draft_derived": len(registry.get_by_evidence_type(EvidenceType.DRAFT_DERIVED)),
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"mixed": len(registry.get_by_evidence_type(EvidenceType.MIXED)),
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"unresolved": len(registry.get_by_evidence_type(EvidenceType.UNRESOLVED)),
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"to_verify": len(registry.get_by_evidence_type(EvidenceType.TO_VERIFY))
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}
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evidence_detail = {
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etype.value: registry.get_by_evidence_type(etype)
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for etype in EvidenceType
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}
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# Validation report
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validation_issues = registry.validate_all()
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return {
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"flat": flat,
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"by_category": by_category,
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"evidence_report": {
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"statistics": evidence_stats,
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"detail": evidence_detail
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},
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"validation_report": validation_issues
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}
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def merge_registry_with_legacy_export(
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registry_data: Dict,
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legacy_data: Dict,
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resolved_values: Dict[str, str]
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) -> Dict:
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"""
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Merge registry metadata with legacy export data.
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Args:
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registry_data: Data from get_registry_metadata_for_export()
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legacy_data: Existing legacy export structure
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resolved_values: Resolved placeholder values (key -> value)
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Returns:
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Merged export with registry enhancements
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"""
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# Start with legacy structure
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merged = legacy_data.copy()
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# Add registry metadata section
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merged["registry_metadata"] = {
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"flat": registry_data["flat"],
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"by_category": registry_data["by_category"],
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"evidence_report": registry_data["evidence_report"],
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"validation_report": registry_data["validation_report"]
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}
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# Populate runtime values in registry metadata
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for meta_dict in merged["registry_metadata"]["flat"]:
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key = meta_dict["key"]
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if key in resolved_values:
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meta_dict["value_display"] = resolved_values[key]
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# Note: value_raw extraction can be added here if needed
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return merged
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def get_enhanced_export_with_registry(profile_id: str, legacy_export: Dict) -> Dict:
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"""
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Enhance legacy export with registry metadata.
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Args:
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profile_id: User profile ID
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legacy_export: Existing legacy export structure
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Returns:
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Enhanced export with registry metadata section
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"""
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# Get registry data
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registry_data = get_registry_metadata_for_export(profile_id)
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# Get resolved values (for value_display population)
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from placeholder_resolver import get_placeholder_example_values
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resolved_values = get_placeholder_example_values(profile_id)
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cleaned_values = {
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key.replace('{{', '').replace('}}', ''): value
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for key, value in resolved_values.items()
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}
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# Merge
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enhanced = merge_registry_with_legacy_export(
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registry_data,
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legacy_export,
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cleaned_values
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)
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return enhanced
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