from typing import Any

from pydantic import BaseModel, Field, create_model


class SubQuestions(BaseModel):
    """Structured output model for query decomposition — static fallback.

    When ``decompose_format`` is available from PromptService, a dynamic
    model with DB-configured description and max_length is used instead.
    See ``create_subquestions_model()``.
    """

    questions: list[str] = Field(
        description="請將問題/任務拆解成 1-3 個簡化子問題，標籤式主題必須清楚、簡潔、具體，一看就明白（建議 3-8 個字），若涉及地點、地區、人物、時間、金額/財政 等關鍵資訊，必須包含在標籤中 。具體提問/要求要精準、完整 並全部轉換成以下固定格式：\n「標籤式主題：具體提問/要求」",
        min_length=1,
        max_length=3,
    )


def create_subquestions_model(description: str, max_length: int) -> type[BaseModel]:
    """Create a dynamic SubQuestions model with configurable field constraints.

    Args:
        description: Field description text injected into the JSON format
            instruction sent to the LLM.
        max_length: Maximum number of sub-questions (1-5).

    Returns:
        A Pydantic BaseModel subclass with the configured constraints.
    """
    return create_model(
        "SubQuestions",
        questions=(
            list[str],
            Field(
                description=description,
                min_length=1,
                max_length=max_length,
            ),
        ),
    )


def parse_decompose_format(raw: str) -> dict[str, Any]:
    """Parse the decompose_format JSON string into a validated config dict.

    Returns a dict with ``description`` (str) and ``max_length`` (int).
    Raises ``ValueError`` if the JSON is invalid or fields are missing/malformed.
    """
    import json

    try:
        config = json.loads(raw)
    except json.JSONDecodeError as exc:
        raise ValueError(f"decompose_format is not valid JSON: {exc}") from exc

    if not isinstance(config, dict):
        raise ValueError("decompose_format must be a JSON object")

    description = config.get("description")
    if not isinstance(description, str) or not description.strip():
        raise ValueError("decompose_format.description must be a non-empty string")

    max_length = config.get("max_length")
    if not isinstance(max_length, int) or max_length < 1 or max_length > 5:
        raise ValueError("decompose_format.max_length must be an integer between 1 and 5")

    return {"description": description.strip(), "max_length": max_length}