"""FLSA Compliance Audit handler (LLM-based).

Generates a Fair Labor Standards Act compliance audit report including
employee classification analysis, overtime review, recordkeeping assessment,
and a prioritized remediation plan.
"""

from __future__ import annotations

import os
from pathlib import Path

from .base_handler import BaseServiceHandler

SERVICE_SYSTEM_PROMPT = """You are a compliance analyst at Performance West Inc.
generating a Fair Labor Standards Act (FLSA) compliance audit report.

RULES:
- Write in professional, clear business English
- Cite specific FLSA regulations (29 CFR § 541, etc.)
- Never provide legal advice — use "we recommend" not "you must"
- For each finding: what was found, regulation, risk level (Low/Medium/High/Critical), remediation
- Structure with clear headings and bullet points
- Include specific section references from the Fair Labor Standards Act
- Reference DOL Fact Sheets where applicable
- Note state-specific requirements where the client operates
"""

SECTIONS = [
    {
        "name": "executive_summary",
        "prompt": (
            "Write a 200-word executive summary of the FLSA audit findings. "
            "Include the scope of the audit, number of positions reviewed, "
            "overall compliance posture, and highest-priority findings."
        ),
    },
    {
        "name": "classification_analysis",
        "prompt": (
            "Analyze each employee classification (exempt vs non-exempt) "
            "against the duties tests under 29 CFR § 541. For each role: "
            "state the current classification, whether it meets the salary "
            "basis test ($684/week), whether it passes the duties test for "
            "the claimed exemption (executive, administrative, professional, "
            "computer, outside sales), and the risk if misclassified."
        ),
    },
    {
        "name": "overtime_analysis",
        "prompt": (
            "Analyze overtime calculation methods and identify any violations. "
            "Review the regular rate of pay calculations, treatment of bonuses "
            "and commissions in overtime, comp time practices, fluctuating "
            "workweek usage, and any off-the-clock work risks."
        ),
    },
    {
        "name": "recordkeeping_review",
        "prompt": (
            "Review timekeeping and recordkeeping compliance under 29 CFR § 516. "
            "Assess: accuracy of time records, retention periods, required data "
            "fields, break/meal period documentation, and any gaps that could "
            "expose the organization in a wage-hour investigation."
        ),
    },
    {
        "name": "youth_employment",
        "prompt": (
            "Review compliance with child labor provisions under FLSA § 212-213. "
            "If the client employs any workers under 18: permitted occupations, "
            "hour restrictions, hazardous occupation orders, and required "
            "documentation. If not applicable, state so briefly."
        ),
    },
    {
        "name": "remediation_plan",
        "prompt": (
            "Provide a prioritized remediation plan for all findings. "
            "For each item: finding reference, risk level, recommended action, "
            "responsible party, and suggested timeline. Group by priority "
            "(Critical → High → Medium → Low)."
        ),
    },
]


class FLSAAuditHandler(BaseServiceHandler):
    SERVICE_SLUG = "flsa-audit"
    SERVICE_NAME = "FLSA Compliance Audit"
    TEMPLATE_NAME = "flsa_audit_template.docx"
    REQUIRES_LLM = True

    async def process(self, order_data: dict) -> list[str]:
        work_dir = self._make_work_dir()
        order_number = order_data["name"]
        context = self._extract_order_context(order_data)

        # 1. Load template and fill basic variables
        template_path = self._get_template_path()
        docx_filename = self._output_filename(order_number, "docx")
        docx_path = os.path.join(work_dir, docx_filename)

        variables = {
            "order_number": order_number,
            "customer_name": order_data.get("customer_name", ""),
            "date": __import__("datetime").datetime.now().strftime("%B %d, %Y"),
            "service_name": self.SERVICE_NAME,
            "company_size": order_data.get("custom_company_size", "N/A"),
            "industry": order_data.get("custom_industry", "N/A"),
            "state": order_data.get("custom_state", "N/A"),
        }
        self._fill_template(template_path, variables, docx_path)

        # 2. Generate LLM sections
        sections = await self._generate_sections(
            SERVICE_SYSTEM_PROMPT, SECTIONS, context
        )

        # 3. Append sections to the document
        self._add_sections_to_doc(docx_path, sections)

        # 4. Convert to PDF
        pdf_path = self._convert_to_pdf(docx_path)

        return [docx_path, pdf_path]