"""Pydantic request and response models for the RT-OSS HTTP server."""

from __future__ import annotations

from pathlib import Path

from pydantic import BaseModel, field_validator

# ---------------------------------------------------------------------------
# Conductor
# ---------------------------------------------------------------------------


class DeployRequest(BaseModel):
    config: dict


class DeployResponse(BaseModel):
    campaign_id: str


class CampaignStatusResponse(BaseModel):
    campaign_id: str
    status: str
    config_name: str
    progress: int
    total_steps: int
    started_at: float
    ended_at: float | None = None
    result: dict | None = None
    error: str | None = None


class CancelResponse(BaseModel):
    campaign_id: str
    cancelled: bool


# ---------------------------------------------------------------------------
# Inference
# ---------------------------------------------------------------------------


class SdrConfig(BaseModel):
    device: str
    center_freq: float
    sample_rate: float
    gain: float | str = "auto"


class LoadModelRequest(BaseModel):
    model_path: str
    label_map: dict[str, int]  # class_name -> class_index

    @field_validator("model_path")
    @classmethod
    def validate_model_path(cls, v: str) -> str:
        p = Path(v)
        if ".." in p.parts:
            raise ValueError("model_path must not contain path traversal components")
        if p.suffix.lower() != ".onnx":
            raise ValueError("model_path must point to an .onnx file")
        # Resolve to catch symlink-based traversal; return the resolved absolute path
        # so callers always work with the real filesystem location.
        resolved = p.resolve()
        if resolved.suffix.lower() != ".onnx":
            raise ValueError("Resolved model_path must point to an .onnx file")
        return str(resolved)


class LoadModelResponse(BaseModel):
    loaded: bool
    model_path: str
    num_classes: int


class StartInferenceRequest(BaseModel):
    sdr_config: SdrConfig


class StartInferenceResponse(BaseModel):
    running: bool


class StopInferenceResponse(BaseModel):
    stopped: bool


class ConfigureRequest(BaseModel):
    """Partial SDR reconfiguration — only supplied fields are updated."""

    center_freq: float | None = None
    sample_rate: float | None = None
    gain: float | str | None = None


class ConfigureResponse(BaseModel):
    configured: bool


class InferenceStatusResponse(BaseModel):
    """Latest inference result as returned by GET /inference/status.

    When ``idle`` is True the radio is scanning but no signal was detected.
    ``device_id`` is the raw prediction label from the model's label map.
    The frontend is responsible for mapping device_id to a human name and
    determining whether the device is authorized.
    """

    timestamp: float
    idle: bool = False
    device_id: str | None = None  # prediction label; None when idle
    confidence: float = 0.0
    snr_db: float = 0.0