import aiohttp

from ...config.logfire_config import get_logger
from ..models import ModelSpec

logger = get_logger(__name__)


async def discover_google_models(api_key: str, session: aiohttp.ClientSession) -> list[ModelSpec]:
    """1:1 Physical Parity Implementation from ProviderDiscoveryService."""
    models = []
    try:
        model_specs = [
            ModelSpec(
                "gemini-1.5-pro",
                "google",
                2097152,
                True,
                True,
                False,
                None,
                1.25,
                5.00,
                "Advanced reasoning and multimodal capabilities",
            ),
            ModelSpec(
                "gemini-1.5-flash",
                "google",
                1048576,
                True,
                True,
                False,
                None,
                0.075,
                0.30,
                "Fast and versatile performance",
            ),
            ModelSpec(
                "gemini-3.1-pro",
                "google",
                2097152,
                True,
                True,
                False,
                None,
                1.25,
                5.00,
                "Latest advanced reasoning model",
            ),
            ModelSpec(
                "gemini-3.1-flash",
                "google",
                1048576,
                True,
                True,
                False,
                None,
                0.10,
                0.40,
                "Latest high-performance flash model",
            ),
            ModelSpec(
                "gemini-3.1-flash-lite", "google", 1048576, True, True, False, None, 0.05, 0.20, "Ultra-fast lite model"
            ),
            ModelSpec(
                "gemini-2.0-flash-lite-preview-02-05",
                "google",
                1048576,
                True,
                True,
                False,
                None,
                0.05,
                0.20,
                "Next-gen ultra-fast preview model",
            ),
            ModelSpec(
                "gemini-1.0-pro",
                "google",
                30720,
                True,
                False,
                False,
                None,
                0.50,
                1.50,
                "Efficient model for text tasks",
            ),
            ModelSpec(
                "text-embedding-004",
                "google",
                2048,
                False,
                False,
                True,
                768,
                0.00,
                0,
                "Google's latest embedding model",
            ),
        ]

        base_url = "https://generativelanguage.googleapis.com/v1beta/models"
        headers = {"x-goog-api-key": api_key}

        async with session.get(base_url, headers=headers) as response:
            if response.status == 200:
                models = model_specs
                logger.info(f"Discovered {len(models)} Google models")
            else:
                logger.warning(f"Google API returned status {response.status}")
    except Exception as e:
        logger.error(f"Error discovering Google models: {e}")
    return models