"""Per-column system prompts: one focused LLM call per Classification field.

Each prompt is built from the column's coding rule (Vorlage
`Variables_Coding_Rules` sheet) plus the small targeted instructions it
needs (ISIC list for industry fields, currency hint for the `currency_*`
fields, the "nonpecuniary" exception for `dispute_value_nominal`).

The LLM is told to return JSON `{"<column>": <value>}` so the response
can be validated by the same `Classification` model used in v1 — we just
look at the one field we asked for.
"""

from legex.models.classification import Classification

MODE = "per_column"

_PREAMBLE = (
    "You extract a single variable from a court judgment. Read the "
    "judgment text the user provides and return a JSON object with "
    "exactly one key: the variable name below. The value must be the "
    "typed answer or JSON null. Do not invent information that is not "
    "in the text. Use native JSON types — a number is a number, not a "
    "string. Money amounts are JSON numbers; dates are JSON strings in "
    "YYYY-MM-DD format; counts are JSON integers."
)

_DISPUTE_TAIL = 'The value may also be the literal string "nonpecuniary" for non-monetary disputes.'

_ISIC_TAIL = (
    "The value must be one of the coded values listed below.\n\n"
    "## Allowed ISIC industry categories\n\n{isic_block}"
)

_CURRENCY_TAIL = (
    "Return the ISO-4217 currency code of the local currency of the "
    "proceedings (e.g. CHF for Switzerland, EUR for France/Germany/"
    "Belgium, GBP for the UK, AUD for Australia, NZD for New Zealand). "
    "Return null if the corresponding amount in the judgment is null."
)

_ISIC_COLUMNS = {
    "plaintiff_no1_ISIC1_industry_category",
    "defendant_no1_ISIC1_industry_category",
}

_CURRENCY_COLUMNS = {
    "Currency_dispute_value_nominal",
    "Currency_court_cost_awarded_nominal",
    "Currency_party_compensation_awarded_nominal",
}


def build_columns(
    rules: list[tuple[str, str]],
    isic: list[tuple[str, str, str]],
) -> dict[str, str]:
    """Returns {csv_column_name: system_prompt}.

    Keys use the field's alias when set (e.g. `Currency_*` capital C) so
    they line up with the GOLDENSET header. Python attribute names stay
    lowercase on the `Classification` model.
    """
    rules_by_name = {name: explanation for name, explanation in rules}
    isic_block = "\n".join(
        f"- {coded_value} — {category}: {description}"
        for coded_value, category, description in isic
    )

    out: dict[str, str] = {}
    for field, info in Classification.model_fields.items():
        col = info.alias or field
        rule = rules_by_name.get(col) or rules_by_name.get(field, "")
        body = (
            f"{_PREAMBLE}\n\n"
            f"## Variable: {col}\n\n"
            f"{rule}\n\n"
            f'Return JSON in the form: {{"{col}": <value>}}'
        )
        if col == "dispute_value_nominal":
            body += f"\n\n{_DISPUTE_TAIL}"
        if col in _ISIC_COLUMNS:
            body += "\n\n" + _ISIC_TAIL.format(isic_block=isic_block)
        if col in _CURRENCY_COLUMNS:
            body += f"\n\n{_CURRENCY_TAIL}"
        out[col] = body
    return out