Create models.py

models.py

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+from pydantic import BaseModel, Field
+from typing import Optional, Dict, List, Any
+from enum import Enum
+import datetime
+import hashlib
+
+class EventSeverity(Enum):
+    LOW = "low"
+    MEDIUM = "medium" 
+    HIGH = "high"
+    CRITICAL = "critical"
+
+class HealingAction(Enum):
+    RESTART_CONTAINER = "restart_container"
+    SCALE_OUT = "scale_out"
+    TRAFFIC_SHIFT = "traffic_shift"
+    CIRCUIT_BREAKER = "circuit_breaker"
+    ROLLBACK = "rollback"
+    ALERT_TEAM = "alert_team"
+    NO_ACTION = "no_action"
+
+class ReliabilityEvent(BaseModel):
+    timestamp: str = Field(default_factory=lambda: datetime.datetime.now().isoformat())
+    component: str
+    service_mesh: str = "default"
+    
+    # Core metrics
+    latency_p99: float = Field(ge=0)
+    error_rate: float = Field(ge=0, le=1)
+    throughput: float = Field(ge=0)
+    
+    # Resource metrics  
+    cpu_util: Optional[float] = Field(default=None, ge=0, le=1)
+    memory_util: Optional[float] = Field(default=None, ge=0, le=1)
+    
+    # Business metrics
+    revenue_impact: Optional[float] = Field(default=None, ge=0)
+    user_impact: Optional[int] = Field(default=None, ge=0)
+    
+    # Topology context
+    upstream_deps: List[str] = Field(default_factory=list)
+    downstream_deps: List[str] = Field(default_factory=list)
+    
+    severity: EventSeverity = EventSeverity.LOW
+    fingerprint: str = Field(default="")
+    
+    def __init__(self, **data):
+        super().__init__(**data)
+        # Generate fingerprint for deduplication
+        if not self.fingerprint:
+            fingerprint_str = f"{self.component}_{self.latency_p99}_{self.error_rate}_{self.timestamp}"
+            self.fingerprint = hashlib.md5(fingerprint_str.encode()).hexdigest()
+    
+    class Config:
+        use_enum_values = True
+
+class HealingPolicy(BaseModel):
+    name: str
+    conditions: Dict[str, Any]
+    actions: List[HealingAction]
+    priority: int = Field(ge=1, le=5)
+    cool_down_seconds: int = 300
+    enabled: bool = True
+
+class AnomalyResult(BaseModel):
+    is_anomaly: bool
+    confidence: float
+    predicted_cause: str
+    recommended_actions: List[HealingAction]
+    similar_incidents: List[str] = Field(default_factory=list)
+    business_impact: Optional[Dict[str, Any]] = None