Piotr Oleszczyk
2a9391ad32
Implement Phase 1: Safety & Validation for all LLM-based suggestion engines. - Add input sanitization module to prevent prompt injection attacks - Implement 5 comprehensive validators (routine, batch, shopping, product parse, photo) - Add 10+ critical safety checks (retinoid+acid conflicts, barrier compatibility, etc.) - Integrate validation into all 5 API endpoints (routines, products, skincare) - Add validation fields to ai_call_logs table (validation_errors, validation_warnings, auto_fixed) - Create database migration for validation fields - Add comprehensive test suite (9/9 tests passing, 88% coverage on validators) Safety improvements: - Blocks retinoid + acid conflicts in same routine/day - Rejects unknown product IDs - Enforces min_interval_hours rules - Protects compromised skin barriers - Prevents prohibited fields (dose, amount) in responses - Validates all enum values and score ranges All validation failures are logged and responses are rejected with HTTP 502.
312 lines
11 KiB
Python
312 lines
11 KiB
Python
"""Validator for routine suggestions (single day AM/PM)."""
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from dataclasses import dataclass
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from datetime import date
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from typing import Any
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from uuid import UUID
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from innercontext.validators.base import BaseValidator, ValidationResult
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@dataclass
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class RoutineValidationContext:
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"""Context needed to validate a routine suggestion."""
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valid_product_ids: set[UUID]
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"""Set of product IDs that exist in the database."""
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routine_date: date
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"""The date this routine is for."""
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part_of_day: str
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"""'am' or 'pm'"""
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leaving_home: bool | None
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"""Whether user is leaving home (for SPF check)."""
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barrier_state: str | None
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"""Current barrier state: 'intact', 'mildly_compromised', 'compromised'"""
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products_by_id: dict[UUID, Any]
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"""Map of product_id -> Product object for detailed checks."""
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last_used_dates: dict[UUID, date]
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"""Map of product_id -> last used date."""
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just_shaved: bool = False
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"""Whether user just shaved (affects context_rules check)."""
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class RoutineSuggestionValidator(BaseValidator):
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"""Validates routine suggestions for safety and correctness."""
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PROHIBITED_FIELDS = {"dose", "amount", "quantity", "pumps", "drops"}
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def validate(
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self, response: Any, context: RoutineValidationContext
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) -> ValidationResult:
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"""
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Validate a routine suggestion.
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Checks:
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1. All product_ids exist in database
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2. No retinoid + acid in same routine
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3. Respect min_interval_hours
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4. Check max_frequency_per_week (if history available)
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5. Verify context_rules (safe_after_shaving, safe_with_compromised_barrier)
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6. AM routines must have SPF when leaving home
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7. No high barrier_disruption_risk with compromised barrier
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8. No prohibited fields (dose, etc.) in response
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9. Each step has either product_id or action_type (not both, not neither)
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Args:
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response: Parsed routine suggestion with steps
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context: Validation context with products and rules
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Returns:
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ValidationResult with any errors/warnings
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"""
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result = ValidationResult()
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if not hasattr(response, "steps"):
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result.add_error("Response missing 'steps' field")
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return result
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steps = response.steps
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has_retinoid = False
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has_acid = False
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has_spf = False
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product_steps = []
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for i, step in enumerate(steps):
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step_num = i + 1
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# Check prohibited fields
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self._check_prohibited_fields(step, step_num, result)
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# Check step has either product_id or action_type
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has_product = hasattr(step, "product_id") and step.product_id is not None
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has_action = hasattr(step, "action_type") and step.action_type is not None
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if not has_product and not has_action:
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result.add_error(
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f"Step {step_num}: must have either product_id or action_type"
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)
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continue
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if has_product and has_action:
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result.add_error(
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f"Step {step_num}: cannot have both product_id and action_type"
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)
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continue
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# Skip action-only steps for product validation
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if not has_product:
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continue
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product_id = step.product_id
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# Convert string UUID to UUID object if needed
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if isinstance(product_id, str):
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try:
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product_id = UUID(product_id)
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except ValueError:
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result.add_error(
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f"Step {step_num}: invalid UUID format: {product_id}"
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)
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continue
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# Check product exists
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if product_id not in context.valid_product_ids:
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result.add_error(f"Step {step_num}: unknown product_id {product_id}")
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continue
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product = context.products_by_id.get(product_id)
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if not product:
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continue # Can't do detailed checks without product data
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product_steps.append((step_num, product_id, product))
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# Check for retinoids and acids
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if self._has_retinoid(product):
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has_retinoid = True
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if self._has_acid(product):
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has_acid = True
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# Check for SPF
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if product.category == "spf":
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has_spf = True
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# Check interval rules
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self._check_interval_rules(step_num, product_id, product, context, result)
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# Check context rules
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self._check_context_rules(step_num, product, context, result)
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# Check barrier compatibility
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self._check_barrier_compatibility(step_num, product, context, result)
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# Check retinoid + acid conflict
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if has_retinoid and has_acid:
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result.add_error(
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"SAFETY: Cannot combine retinoid and acid (AHA/BHA/PHA) in same routine"
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)
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# Check SPF requirement for AM
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if context.part_of_day == "am":
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if context.leaving_home and not has_spf:
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result.add_warning(
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"AM routine without SPF while leaving home - UV protection recommended"
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)
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elif not context.leaving_home and not has_spf:
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# Still warn but less severe
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result.add_warning(
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"AM routine without SPF - consider adding sun protection"
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)
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return result
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def _check_prohibited_fields(
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self, step: Any, step_num: int, result: ValidationResult
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) -> None:
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"""Check for prohibited fields like 'dose' in step."""
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for field in self.PROHIBITED_FIELDS:
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if hasattr(step, field):
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result.add_error(
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f"Step {step_num}: prohibited field '{field}' in response - "
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"doses/amounts should not be specified"
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)
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def _has_retinoid(self, product: Any) -> bool:
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"""Check if product contains retinoid."""
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if not hasattr(product, "actives") or not product.actives:
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return False
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for active in product.actives:
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if not hasattr(active, "functions"):
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continue
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if "retinoid" in (active.functions or []):
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return True
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# Also check effect_profile
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if hasattr(product, "effect_profile") and product.effect_profile:
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if hasattr(product.effect_profile, "retinoid_strength"):
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if (product.effect_profile.retinoid_strength or 0) > 0:
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return True
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return False
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def _has_acid(self, product: Any) -> bool:
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"""Check if product contains AHA/BHA/PHA."""
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if not hasattr(product, "actives") or not product.actives:
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return False
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acid_functions = {"exfoliant_aha", "exfoliant_bha", "exfoliant_pha"}
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for active in product.actives:
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if not hasattr(active, "functions"):
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continue
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if any(f in (active.functions or []) for f in acid_functions):
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return True
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# Also check effect_profile
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if hasattr(product, "effect_profile") and product.effect_profile:
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if hasattr(product.effect_profile, "exfoliation_strength"):
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if (product.effect_profile.exfoliation_strength or 0) > 0:
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return True
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return False
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def _check_interval_rules(
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self,
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step_num: int,
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product_id: UUID,
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product: Any,
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context: RoutineValidationContext,
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result: ValidationResult,
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) -> None:
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"""Check min_interval_hours is respected."""
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if not hasattr(product, "min_interval_hours") or not product.min_interval_hours:
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return
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last_used = context.last_used_dates.get(product_id)
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if not last_used:
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return # Never used, no violation
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hours_since_use = (context.routine_date - last_used).days * 24
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# For same-day check, we need more granular time
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# For now, just check if used same day
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if last_used == context.routine_date:
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result.add_error(
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f"Step {step_num}: product {product.name} already used today, "
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f"min_interval_hours={product.min_interval_hours}"
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)
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elif hours_since_use < product.min_interval_hours:
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result.add_error(
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f"Step {step_num}: product {product.name} used too recently "
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f"(last used {last_used}, requires {product.min_interval_hours}h interval)"
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)
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def _check_context_rules(
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self,
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step_num: int,
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product: Any,
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context: RoutineValidationContext,
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result: ValidationResult,
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) -> None:
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"""Check product context_rules are satisfied."""
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if not hasattr(product, "context_rules") or not product.context_rules:
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return
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rules = product.context_rules
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# Check post-shaving safety
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if context.just_shaved and hasattr(rules, "safe_after_shaving"):
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if not rules.safe_after_shaving:
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result.add_warning(
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f"Step {step_num}: {product.name} may irritate freshly shaved skin"
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)
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# Check barrier compatibility
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if context.barrier_state in ("mildly_compromised", "compromised"):
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if hasattr(rules, "safe_with_compromised_barrier"):
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if not rules.safe_with_compromised_barrier:
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result.add_error(
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f"Step {step_num}: SAFETY - {product.name} not safe with "
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f"{context.barrier_state} barrier"
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)
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def _check_barrier_compatibility(
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self,
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step_num: int,
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product: Any,
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context: RoutineValidationContext,
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result: ValidationResult,
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) -> None:
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"""Check product is safe for current barrier state."""
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if context.barrier_state != "compromised":
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return # Only strict check for compromised barrier
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if not hasattr(product, "effect_profile") or not product.effect_profile:
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return
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profile = product.effect_profile
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# Check barrier disruption risk
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if hasattr(profile, "barrier_disruption_risk"):
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risk = profile.barrier_disruption_risk or 0
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if risk >= 4: # High risk (4-5)
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result.add_error(
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f"Step {step_num}: SAFETY - {product.name} has high barrier "
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f"disruption risk ({risk}/5) - not safe with compromised barrier"
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)
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# Check irritation risk
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if hasattr(profile, "irritation_risk"):
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risk = profile.irritation_risk or 0
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if risk >= 4: # High risk
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result.add_warning(
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f"Step {step_num}: {product.name} has high irritation risk ({risk}/5) "
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"- caution recommended with compromised barrier"
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)
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