"""
Pydantic Models - GENERATED FILE

Do not edit directly. Regenerate using modelgen.
"""

from datetime import datetime
from enum import Enum
from typing import Any, Dict, List, Optional
from uuid import UUID

from pydantic import BaseModel, Field

class GraphNode(BaseModel):
    """A pipeline stage node."""
    id: str
    status: str = "idle"
    items_in: int = 0
    items_out: int = 0

class GraphEdge(BaseModel):
    """An edge between pipeline stages."""
    source: str
    target: str
    throughput: int = 0

class BoundingBoxEvent(BaseModel):
    """Bounding box in SSE event payloads."""
    x: int
    y: int
    w: int
    h: int
    confidence: float
    label: str
    resolved_brand: Optional[str] = None
    source: Optional[str] = None

class BrandSummary(BaseModel):
    """Per-brand stats in the final report."""
    brand: str
    total_appearances: int = 0
    total_screen_time: float = 0.0
    avg_confidence: float = 0.0
    first_seen: float = 0.0
    last_seen: float = 0.0

class GraphUpdate(BaseModel):
    """Pipeline node state transition. SSE event: graph_update"""
    nodes: List[GraphNode] = Field(default_factory=list)
    edges: List[GraphEdge] = Field(default_factory=list)
    active_path: List[str] = Field(default_factory=list)

class StatsUpdate(BaseModel):
    """Funnel statistics snapshot. SSE event: stats_update"""
    frames_extracted: int = 0
    frames_after_scene_filter: int = 0
    regions_detected: int = 0
    regions_resolved_by_ocr: int = 0
    regions_escalated_to_local_vlm: int = 0
    regions_escalated_to_cloud_llm: int = 0
    cloud_llm_calls: int = 0
    processing_time_seconds: float = 0.0
    estimated_cloud_cost_usd: float = 0.0

class FrameUpdate(BaseModel):
    """Current frame being processed. SSE event: frame_update"""
    frame_ref: int
    timestamp: float
    jpeg_b64: str
    boxes: List[BoundingBoxEvent] = Field(default_factory=list)

class Detection(BaseModel):
    """A confirmed brand detection. SSE event: detection"""
    brand: str
    timestamp: float
    duration: float
    confidence: float
    source: str
    content_type: str
    bbox: Optional[BoundingBoxEvent] = None
    frame_ref: Optional[int] = None

class LogEvent(BaseModel):
    """Pipeline log line. SSE event: log"""
    level: str
    stage: str
    msg: str
    ts: str
    trace_id: Optional[str] = None

class DetectionReportSummary(BaseModel):
    """Final detection report summary."""
    video_source: str
    content_type: str
    duration_seconds: float
    total_detections: int = 0
    brands: List[BrandSummary] = Field(default_factory=list)
    stats: Optional[StatsUpdate] = None

class JobComplete(BaseModel):
    """Final report when pipeline finishes. SSE event: job_complete"""
    job_id: str
    report: Optional[DetectionReportSummary] = None