"""LLM prompt for AI report commentary.

Provider-agnostic system + user prompt builder. Output contract:
JSON with keys summary, highlights, concerns, next_actions."""


SYSTEM_PROMPT = """You are an experienced CFO providing executive-level commentary
on a financial report. Your output MUST be valid JSON of this exact shape:

{
  "summary": "<2-3 sentence executive summary of the report period>",
  "highlights": ["<observation 1>", "<observation 2>", ...],
  "concerns": ["<thing to investigate 1>", ...],
  "next_actions": ["<suggested action 1>", ...]
}

Rules:
- Use the data provided. Do not invent numbers.
- Tone: professional, concise, factual.
- Currency formatting: always include the $ symbol and 2 decimal places.
- For anomalies: explicitly mention the variance percentage AND the dollar amount.
- Do NOT include markdown code fences. Do NOT include any prose outside the JSON.
"""


def build_prompt(report_result: dict, anomalies: list) -> tuple[str, str]:
    """Build (system_prompt, user_prompt) tuple."""
    parts = []

    # Report context
    parts.append(f"REPORT: {report_result.get('report_name', 'Untitled')}")
    period = report_result.get('period', {})
    parts.append(f"PERIOD: {period.get('label', '')} "
                 f"({period.get('date_from', '')} to {period.get('date_to', '')})")
    comp_period = report_result.get('comparison_period')
    if comp_period:
        parts.append(f"COMPARED TO: {comp_period.get('label', '')} "
                     f"({comp_period.get('date_from', '')} to {comp_period.get('date_to', '')})")
    parts.append("")

    # Rows (the actual numbers)
    parts.append("REPORT LINES:")
    for row in report_result.get('rows', []):
        line = f"  - {row.get('label', '?')}: ${row.get('amount', 0):,.2f}"
        if row.get('amount_comparison') is not None:
            line += f" (comparison: ${row['amount_comparison']:,.2f}"
            if row.get('variance_pct') is not None:
                line += f", {row['variance_pct']:+.1f}%"
            line += ")"
        if row.get('is_subtotal'):
            line += " [SUBTOTAL]"
        parts.append(line)
    parts.append("")

    # Anomalies
    if anomalies:
        parts.append("ANOMALIES (variances exceeding threshold):")
        for a in anomalies[:10]:
            parts.append(
                f"  - {a['label']}: {a['direction']}d {a['variance_pct']:.1f}% "
                f"(${a['variance_amount']:+,.2f}, severity: {a['severity']})"
            )
        parts.append("")

    parts.append("Generate the JSON commentary per the system prompt.")

    return (SYSTEM_PROMPT, "\n".join(parts))