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ai_intelligence_layer/models/input_models.py

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+"""
+Input data models for the AI Intelligence Layer.
+Defines schemas for enriched telemetry, race context, and request payloads.
+"""
+from pydantic import BaseModel, Field
+from typing import List, Literal, Optional
+
+
+class EnrichedTelemetryWebhook(BaseModel):
+    """Single lap of enriched telemetry data from HPC enrichment module."""
+    lap: int = Field(..., description="Lap number")
+    aero_efficiency: float = Field(..., ge=0.0, le=1.0, description="Aerodynamic efficiency (0..1, higher is better)")
+    tire_degradation_index: float = Field(..., ge=0.0, le=1.0, description="Tire wear (0..1, higher is worse)")
+    ers_charge: float = Field(..., ge=0.0, le=1.0, description="Energy recovery system charge level")
+    fuel_optimization_score: float = Field(..., ge=0.0, le=1.0, description="Fuel efficiency score")
+    driver_consistency: float = Field(..., ge=0.0, le=1.0, description="Lap-to-lap consistency")
+    weather_impact: Literal["low", "medium", "high"] = Field(..., description="Weather effect severity")
+
+
+class RaceInfo(BaseModel):
+    """Current race information."""
+    track_name: str = Field(..., description="Name of the circuit")
+    total_laps: int = Field(..., gt=0, description="Total race laps")
+    current_lap: int = Field(..., ge=0, description="Current lap number")
+    weather_condition: str = Field(..., description="Current weather (e.g., Dry, Wet, Mixed)")
+    track_temp_celsius: float = Field(..., description="Track temperature in Celsius")
+
+
+class DriverState(BaseModel):
+    """Current driver state."""
+    driver_name: str = Field(..., description="Driver name")
+    current_position: int = Field(..., gt=0, description="Current race position")
+    current_tire_compound: Literal["soft", "medium", "hard", "intermediate", "wet"] = Field(..., description="Current tire compound")
+    tire_age_laps: int = Field(..., ge=0, description="Laps on current tires")
+    fuel_remaining_percent: float = Field(..., ge=0.0, le=100.0, description="Remaining fuel percentage")
+
+
+class Competitor(BaseModel):
+    """Competitor information."""
+    position: int = Field(..., gt=0, description="Race position")
+    driver: str = Field(..., description="Driver name")
+    tire_compound: Literal["soft", "medium", "hard", "intermediate", "wet"] = Field(..., description="Tire compound")
+    tire_age_laps: int = Field(..., ge=0, description="Laps on current tires")
+    gap_seconds: float = Field(..., description="Gap in seconds (negative if ahead)")
+
+
+class RaceContext(BaseModel):
+    """Complete race context."""
+    race_info: RaceInfo
+    driver_state: DriverState
+    competitors: List[Competitor] = Field(default_factory=list)
+
+
+class Strategy(BaseModel):
+    """A single race strategy option."""
+    strategy_id: int = Field(..., description="Unique strategy identifier (1-20)")
+    strategy_name: str = Field(..., description="Short descriptive name")
+    stop_count: int = Field(..., ge=1, le=3, description="Number of pit stops")
+    pit_laps: List[int] = Field(..., description="Lap numbers for pit stops")
+    tire_sequence: List[Literal["soft", "medium", "hard", "intermediate", "wet"]] = Field(..., description="Tire compounds in order")
+    brief_description: str = Field(..., description="One sentence rationale")
+    risk_level: Literal["low", "medium", "high", "critical"] = Field(..., description="Risk assessment")
+    key_assumption: str = Field(..., description="Main assumption this strategy relies on")
+
+
+class BrainstormRequest(BaseModel):
+    """Request for strategy brainstorming."""
+    enriched_telemetry: Optional[List[EnrichedTelemetryWebhook]] = Field(None, description="Enriched telemetry data")
+    race_context: RaceContext = Field(..., description="Current race context")
+
+
+class AnalyzeRequest(BaseModel):
+    """Request for strategy analysis."""
+    enriched_telemetry: Optional[List[EnrichedTelemetryWebhook]] = Field(None, description="Enriched telemetry data")
+    race_context: RaceContext = Field(..., description="Current race context")
+    strategies: List[Strategy] = Field(..., description="Strategies to analyze (typically 20)")

ai_intelligence_layer/models/internal_models.py

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+"""
+Internal data models for processing.
+"""
+from pydantic import BaseModel
+from typing import Dict, Any
+
+
+class TelemetryTrends(BaseModel):
+    """Calculated trends from enriched telemetry."""
+    tire_deg_rate: float  # Per lap rate of change
+    aero_efficiency_avg: float  # Moving average
+    ers_pattern: str  # "charging", "stable", "depleting"
+    fuel_critical: bool  # Whether fuel is a concern
+    driver_form: str  # "excellent", "good", "inconsistent"

ai_intelligence_layer/models/output_models.py

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+"""
+Output data models for the AI Intelligence Layer.
+Defines schemas for strategy generation and analysis results.
+"""
+from pydantic import BaseModel, Field
+from typing import List, Literal
+from models.input_models import Strategy
+
+
+class BrainstormResponse(BaseModel):
+    """Response from strategy brainstorming."""
+    strategies: List[Strategy] = Field(..., description="20 diverse strategy options")
+
+
+class PredictedOutcome(BaseModel):
+    """Predicted race outcome for a strategy."""
+    finish_position_most_likely: int = Field(..., gt=0, description="Most likely finishing position")
+    p1_probability: int = Field(..., ge=0, le=100, description="Probability of P1 (%)")
+    p2_probability: int = Field(..., ge=0, le=100, description="Probability of P2 (%)")
+    p3_probability: int = Field(..., ge=0, le=100, description="Probability of P3 (%)")
+    p4_or_worse_probability: int = Field(..., ge=0, le=100, description="Probability of P4 or worse (%)")
+    confidence_score: int = Field(..., ge=0, le=100, description="Overall confidence in prediction (%)")
+
+
+class RiskAssessment(BaseModel):
+    """Risk assessment for a strategy."""
+    risk_level: Literal["low", "medium", "high", "critical"] = Field(..., description="Overall risk level")
+    key_risks: List[str] = Field(..., description="Primary risks")
+    success_factors: List[str] = Field(..., description="Factors that enable success")
+
+
+class TelemetryInsights(BaseModel):
+    """Insights derived from enriched telemetry."""
+    tire_wear_projection: str = Field(..., description="Tire degradation projection")
+    aero_status: str = Field(..., description="Aerodynamic performance status")
+    fuel_margin: str = Field(..., description="Fuel situation assessment")
+    driver_form: str = Field(..., description="Driver consistency assessment")
+
+
+class EngineerBrief(BaseModel):
+    """Detailed brief for race engineer."""
+    title: str = Field(..., description="Brief title")
+    summary: str = Field(..., description="Executive summary")
+    key_points: List[str] = Field(..., description="Key decision points")
+    execution_steps: List[str] = Field(..., description="Step-by-step execution plan")
+
+
+class ECUCommands(BaseModel):
+    """Electronic Control Unit commands for car setup."""
+    fuel_mode: Literal["LEAN", "STANDARD", "RICH"] = Field(..., description="Fuel consumption mode")
+    ers_strategy: Literal["CONSERVATIVE", "BALANCED", "AGGRESSIVE_DEPLOY"] = Field(..., description="ERS deployment strategy")
+    engine_mode: Literal["SAVE", "STANDARD", "PUSH", "OVERTAKE"] = Field(..., description="Engine power mode")
+    brake_balance_adjustment: int = Field(..., ge=-5, le=5, description="Brake balance adjustment")
+    differential_setting: Literal["CONSERVATIVE", "BALANCED", "AGGRESSIVE"] = Field(..., description="Differential setting")
+
+
+class AnalyzedStrategy(BaseModel):
+    """A single analyzed strategy with full details."""
+    rank: int = Field(..., ge=1, le=3, description="Strategy rank (1-3)")
+    strategy_id: int = Field(..., description="Reference to original strategy")
+    strategy_name: str = Field(..., description="Strategy name")
+    classification: Literal["RECOMMENDED", "ALTERNATIVE", "CONSERVATIVE"] = Field(..., description="Strategy classification")
+    predicted_outcome: PredictedOutcome
+    risk_assessment: RiskAssessment
+    telemetry_insights: TelemetryInsights
+    engineer_brief: EngineerBrief
+    driver_audio_script: str = Field(..., description="Radio message to driver")
+    ecu_commands: ECUCommands
+
+
+class SituationalContext(BaseModel):
+    """Current situational context and alerts."""
+    critical_decision_point: str = Field(..., description="Current critical decision point")
+    telemetry_alert: str = Field(..., description="Important telemetry alerts")
+    key_assumption: str = Field(..., description="Key assumption for analysis")
+    time_sensitivity: str = Field(..., description="Time-sensitive factors")
+
+
+class AnalyzeResponse(BaseModel):
+    """Response from strategy analysis."""
+    top_strategies: List[AnalyzedStrategy] = Field(..., min_length=3, max_length=3, description="Top 3 strategies")
+    situational_context: SituationalContext
+
+
+class HealthResponse(BaseModel):
+    """Health check response."""
+    status: str = Field(..., description="Service status")
+    service: str = Field(..., description="Service name")
+    version: str = Field(..., description="Service version")
+    demo_mode: bool = Field(..., description="Whether demo mode is enabled")
+    enrichment_service_url: str = Field(..., description="URL of enrichment service")