# backend/models.py

from dataclasses import dataclass
from typing import Any, Optional

# Model name mapping for anonymization
# Maps internal model names to display labels
MODEL_NAME_MAP = {
    "xtts": "Model A",     # Coqui XTTS -> Model A
    "csm": "Model B",      # Sesame CSM -> Model B
    "orpheus": "Model C",  # Orpheus -> Model C
}


def get_display_model_name(internal_name: str) -> str:
    """Convert internal model name to display label."""
    return MODEL_NAME_MAP.get(internal_name, internal_name.upper())


def audio_to_base64_url(audio_data):
    """Return the audio data URL string as-is (no-op since audio_url is already a base64 data URL)."""
    return audio_data if isinstance(audio_data, str) else None


# Data models
@dataclass
class Clip:
    id: str
    model: str
    speaker: str  # male/female
    exercise: str
    exercise_id: str
    transcript: str
    audio_url: Any  # Can be string URL or tuple (array, sample_rate)
    duration_s: Optional[float] = None


@dataclass
class MOSResponse:
    session_id: str
    clip_id: str
    clarity: int
    pronunciation: int
    prosody: int
    naturalness: int
    overall: int
    comment: str = ""
    gender_mismatch: bool = False  # Flag for wrong gender voice


@dataclass
class ABResponse:
    session_id: str
    clip_a_id: str
    clip_b_id: str
    comparison_type: str  # "model_vs_model" or "gender_vs_gender"
    choice: str  # "A", "B", "tie"
    comment: str = ""
    gender_mismatch_a: bool = False  # Flag for wrong gender voice in clip A
    gender_mismatch_b: bool = False  # Flag for wrong gender voice in clip B