1c61b80731
- Add rules_engine.py with quantitative rules for all 8 workout types - Add quality gate retry loop in generate_single_workout() - Expand calibrate_structure_rules to all 120 combinations (8 types × 5 goals × 3 sections) - Wire WeeklySplitPattern DB records into _pick_weekly_split() - Enforce movement patterns from WorkoutStructureRule in exercise selection - Add straight-set strength support (single main lift, 4-6 rounds) - Add modality consistency check for duration-dominant workout types - Add InjuryStep component to onboarding and preferences - Add sibling exercise exclusion in regenerate and preview_day endpoints - Display generator warnings on dashboard - Expand fix_rep_durations, fix_exercise_flags, fix_movement_pattern_typo - Add audit_exercise_data and check_rules_drift management commands - Add Next.js frontend with dashboard, onboarding, preferences, history pages - Add generator app with ML-powered workout generation pipeline - 96 new tests across 7 test modules Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
35 lines
1.0 KiB
Python
35 lines
1.0 KiB
Python
from rest_framework import serializers
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from .models import *
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from exercise.models import Exercise
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from exercise.serializers import ExerciseSerializer
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import uuid
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class SupersetExerciseSerializer(serializers.ModelSerializer):
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exercise = serializers.SerializerMethodField()
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unique_id = serializers.SerializerMethodField()
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class Meta:
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model = SupersetExercise
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fields = '__all__'
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def get_exercise(self, obj):
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data = ExerciseSerializer(obj.exercise, many=False).data
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return data
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def get_unique_id(self, obj):
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return str(uuid.uuid4())
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class SupersetSerializer(serializers.ModelSerializer):
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exercises = serializers.SerializerMethodField()
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class Meta:
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model = Superset
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fields = '__all__'
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def get_exercises(self, obj):
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if obj.pk is None:
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return []
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objs = SupersetExercise.objects.filter(superset=obj).order_by('order')
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data = SupersetExerciseSerializer(objs, many=True).data
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return data
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