feat: complete production hardening implementation, specialty canonicalization, google-genai migration, voice reliability, sqlite concurrency, and test suite consolidation

ai-patient-onboarding/app/domain/models/__init__.py

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+"""
+Domain models package.
+"""
+
+from app.domain.models.patient_state import (
+    SymptomItem,
+    MedicationItem,
+    AllergyItem,
+    MedicalHistoryItem,
+    SurgicalHistoryItem,
+    PreviousEpisodeItem,
+    FamilyHistoryItem,
+    FieldContainer,
+    PatientState,
+)
+from app.domain.models.extraction import ExtractionResult, QuestionIntent
+from app.domain.models.contracts import ResponseContext, ResponseResult, ResponseType, FactConfidence
+
+__all__ = [
+    "SymptomItem",
+    "MedicationItem",
+    "AllergyItem",
+    "MedicalHistoryItem",
+    "SurgicalHistoryItem",
+    "PreviousEpisodeItem",
+    "FamilyHistoryItem",
+    "FieldContainer",
+    "PatientState",
+    "ExtractionResult",
+    "QuestionIntent",
+    "ResponseContext",
+    "ResponseResult",
+    "ResponseType",
+    "FactConfidence",
+]

ai-patient-onboarding/app/domain/models/contracts.py

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+"""
+Response contracts, enums, and data models (Rules 102, 103, 104, 105, 116):
+- ResponseType Enum
+- QuestionIntent Enum
+- ResponseContext Input Contract
+- ResponseResult Output Contract
+- FactConfidence Model
+"""
+
+from enum import Enum
+from typing import Optional, List, Dict, Any
+from pydantic import BaseModel, Field
+
+
+class ResponseType(str, Enum):
+    GREETING = "greeting"
+    ACKNOWLEDGEMENT = "acknowledgement"
+    FOLLOW_UP = "follow_up"
+    CLARIFICATION = "clarification"
+    REFUSAL = "refusal"
+    UNKNOWN = "unknown"
+    SAFETY = "safety"
+    CRISIS = "crisis"
+    COMPLETION = "completion"
+
+
+class QuestionIntent(str, Enum):
+    SYMPTOM_NAME = "symptom_name"
+    SYMPTOM_DURATION = "symptom_duration"
+    SYMPTOM_SEVERITY = "symptom_severity"
+    SYMPTOM_LOCATION = "symptom_location"
+    SYMPTOM_ONSET = "symptom_onset"
+    SYMPTOM_FREQUENCY = "symptom_frequency"
+    SYMPTOM_TRIGGER = "symptom_trigger"
+    ASSOCIATED_SYMPTOMS = "associated_symptoms"
+
+    MEDICAL_HISTORY = "medical_history"
+    MEDICATIONS = "medications"
+    ALLERGIES = "allergies"
+    FAMILY_HISTORY = "family_history"
+    SURGICAL_HISTORY = "surgical_history"
+
+
+class ResponseContext(BaseModel):
+    language: str = "en"
+    patient_message: str
+    intent: str = "fact_extraction"
+    primary_symptom: Optional[str] = None
+    missing_information: Optional[str] = None
+    selected_question: Optional[str] = None
+    question_intent: Optional[QuestionIntent] = None
+    safety_status: str = "normal"
+    onboarding_completed: bool = False
+    current_state: Optional[Dict[str, Any]] = None
+
+
+class ResponseResult(BaseModel):
+    response: str
+    language: str = "en"
+    question_intent: Optional[str] = None
+    response_type: ResponseType = ResponseType.FOLLOW_UP
+
+
+class FactConfidence(BaseModel):
+    source: str = "patient"
+    method: str = "explicit"
+    confidence: float = 1.0

ai-patient-onboarding/app/domain/models/extraction.py

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+"""
+Extraction result and question intent domain models.
+"""
+
+from typing import Any, Dict, List, Optional
+from pydantic import BaseModel, Field
+
+
+class ExtractedFact(BaseModel):
+    category: str  # 'symptom', 'medication', 'allergy', 'medical_history', 'family_history', etc.
+    data: Dict[str, Any]
+
+
+class ExtractionResult(BaseModel):
+    raw_message: str
+    normalized_message: str
+    detected_language: str = "en"
+    updates: Dict[str, Any] = Field(default_factory=dict)
+    is_emergency: bool = False
+    is_crisis: bool = False
+    emergency_reason: Optional[str] = None
+
+
+class QuestionIntent(BaseModel):
+    intent_code: str  # e.g., 'reason_for_visit', 'symptom_duration', 'medical_history'
+    field: str
+    attribute: Optional[str] = None
+    target_symptom: Optional[str] = None

ai-patient-onboarding/app/domain/models/patient_state.py

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+"""
+Strongly typed domain models for Patient Onboarding state management.
+"""
+
+from typing import Any, Dict, List, Optional, Union
+from pydantic import BaseModel, Field
+
+
+class SymptomItem(BaseModel):
+    name: str
+    canonical_name: Optional[str] = None
+    duration: Optional[str] = None
+    severity: Optional[str] = None
+    location: Optional[str] = None
+    frequency: Optional[str] = None
+    onset: Optional[str] = None
+    pattern: Optional[str] = None
+    trigger: Optional[str] = None
+    relieving_factor: Optional[str] = None
+    associated_findings: Optional[str] = None
+
+
+class MedicationItem(BaseModel):
+    name: str
+    canonical_name: Optional[str] = None
+    dosage: Optional[str] = None
+    frequency: Optional[str] = None
+    duration: Optional[str] = None
+    purpose: Optional[str] = None
+
+
+class AllergyItem(BaseModel):
+    name: str
+    canonical_name: Optional[str] = None
+    type: Optional[str] = None  # e.g., 'drug', 'food', 'environment'
+    reaction: Optional[str] = None  # e.g., 'rash', 'swelling'
+
+
+class MedicalHistoryItem(BaseModel):
+    condition: str
+    canonical_name: Optional[str] = None
+    duration: Optional[str] = None
+    status: Optional[str] = "active"
+    details: Optional[str] = None
+
+
+class SurgicalHistoryItem(BaseModel):
+    procedure: str
+    body_site: Optional[str] = None
+    approximate_date: Optional[str] = None
+    reason: Optional[str] = None
+
+
+class PreviousEpisodeItem(BaseModel):
+    description: str
+    time: Optional[str] = None
+    outcome: Optional[str] = None
+
+
+class FamilyHistoryItem(BaseModel):
+    relation: str  # e.g., 'father', 'mother', 'sibling'
+    condition: str
+    canonical_name: Optional[str] = None
+
+
+class FieldContainer(BaseModel):
+    status: str = "not_collected"  # 'not_collected' | 'reported' | 'confirmed_none' | 'unknown' | 'declined'
+    items: List[Dict[str, Any]] = Field(default_factory=list)
+
+
+class SpecialtyConfidence(BaseModel):
+    code: str
+    name: str
+    confidence: float = 1.0
+    evidence: List[str] = Field(default_factory=list)
+
+
+class PatientState(BaseModel):
+    reason_for_visit: Optional[str] = None
+    symptoms: List[SymptomItem] = Field(default_factory=list)
+    medical_history: Union[FieldContainer, List[MedicalHistoryItem], Dict[str, Any]] = Field(default_factory=list)
+    medications: Union[FieldContainer, List[MedicationItem], Dict[str, Any]] = Field(default_factory=list)
+    allergies: Union[FieldContainer, List[AllergyItem], Dict[str, Any]] = Field(default_factory=list)
+    surgical_history: List[SurgicalHistoryItem] = Field(default_factory=list)
+    previous_episodes: List[PreviousEpisodeItem] = Field(default_factory=list)
+    family_history: List[FamilyHistoryItem] = Field(default_factory=list)
+    additional_information: List[Dict[str, Any]] = Field(default_factory=list)