from __future__ import annotations

from pathlib import Path

from bulkgen.config import (
    IMAGE_EXTENSIONS,
    TEXT_EXTENSIONS,
    Defaults,
    TargetConfig,
    TargetType,
    target_type_from_capabilities,
)
from bulkgen.providers.models import Capability, ModelInfo


def infer_required_capabilities(
    target_name: str, target: TargetConfig
) -> frozenset[Capability]:
    """Infer the capabilities a model must have based on filename and config.

    Raises :class:`ValueError` for unsupported file extensions.
    """
    suffix = Path(target_name).suffix.lower()
    caps: set[Capability] = set()

    if suffix in IMAGE_EXTENSIONS:
        caps.add(Capability.TEXT_TO_IMAGE)
        if target.reference_images:
            caps.add(Capability.REFERENCE_IMAGES)
        if target.control_images:
            caps.add(Capability.CONTROL_IMAGES)
    elif suffix in TEXT_EXTENSIONS:
        caps.add(Capability.TEXT_GENERATION)
        all_input_names = list(target.inputs) + list(target.reference_images)
        if any(Path(n).suffix.lower() in IMAGE_EXTENSIONS for n in all_input_names):
            caps.add(Capability.VISION)
    else:
        msg = f"Cannot infer target type for '{target_name}': unsupported extension '{suffix}'"
        raise ValueError(msg)

    return frozenset(caps)


def resolve_model(
    target_name: str, target: TargetConfig, defaults: Defaults
) -> ModelInfo:
    """Return the effective model for a target, validated against required capabilities.

    If the target specifies an explicit model, it is validated to have all
    required capabilities.  Otherwise the type-appropriate default is tried
    first; if it lacks a required capability the first capable model of the
    same type is selected.

    Raises :class:`ValueError` if no suitable model can be found.
    """
    from bulkgen.providers.registry import get_all_models

    all_models = get_all_models()
    required = infer_required_capabilities(target_name, target)
    target_type = target_type_from_capabilities(required)

    if target.model is not None:
        # Explicit model — look up and validate.
        for model in all_models:
            if model.name == target.model:
                missing = required - frozenset(model.capabilities)
                if missing:
                    names = ", ".join(sorted(missing))
                    msg = f"Model '{target.model}' for target '{target_name}' lacks required capabilities: {names}"
                    raise ValueError(msg)
                return model
        msg = f"Unknown model '{target.model}' for target '{target_name}'"
        raise ValueError(msg)

    # No explicit model — try the default first, then fall back.
    default_name = (
        defaults.image_model if target_type is TargetType.IMAGE else defaults.text_model
    )
    for model in all_models:
        if model.name == default_name:
            if required <= frozenset(model.capabilities):
                return model
            break

    # Default lacks capabilities — find the first capable model of the same type.
    model_type = "image" if target_type is TargetType.IMAGE else "text"
    for model in all_models:
        if model.type == model_type and required <= frozenset(model.capabilities):
            return model

    names = ", ".join(sorted(required))
    msg = (
        f"No model found for target '{target_name}' with required capabilities: {names}"
    )
    raise ValueError(msg)