"""
Inference response types.

These are the shapes returned by the inference server.
Kept separate from detect.models to avoid coupling the
inference protocol to pipeline internals.
"""

from __future__ import annotations

from dataclasses import dataclass, field


@dataclass
class DetectResult:
    """Single object detection from YOLO or similar."""
    x: int
    y: int
    w: int
    h: int
    confidence: float
    label: str


@dataclass
class OCRResult:
    """Text extracted from a region."""
    text: str
    confidence: float
    bbox: tuple[int, int, int, int]  # x, y, w, h


@dataclass
class VLMResult:
    """Visual language model response for a crop."""
    brand: str
    confidence: float
    reasoning: str


@dataclass
class RegionResult:
    """A candidate region from CV analysis."""
    x: int
    y: int
    w: int
    h: int
    confidence: float
    label: str


@dataclass
class RegionDebugResult:
    """CV region analysis with debug overlays."""
    regions: list[RegionResult] = field(default_factory=list)
    edge_overlay_b64: str = ""
    lines_overlay_b64: str = ""
    horizontal_count: int = 0
    pair_count: int = 0


@dataclass
class ModelInfo:
    """Info about a loaded model."""
    name: str
    vram_mb: float
    quantization: str  # fp32, fp16, int8, int4


@dataclass
class ServerStatus:
    """Inference server health response."""
    loaded_models: list[ModelInfo] = field(default_factory=list)
    vram_used_mb: float = 0.0
    vram_budget_mb: float = 0.0
    strategy: str = "sequential"  # sequential, concurrent, auto