f8cd37ac8c
Includes: API (Express/TypeScript), Astro site, Python workers, document generators, FCC compliance tools, Canada CRTC formation, Ansible infrastructure, and deployment scripts. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
126 lines
4.8 KiB
Python
126 lines
4.8 KiB
Python
"""FLSA Compliance Audit handler (LLM-based).
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Generates a Fair Labor Standards Act compliance audit report including
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employee classification analysis, overtime review, recordkeeping assessment,
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and a prioritized remediation plan.
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"""
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from __future__ import annotations
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import os
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from pathlib import Path
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from .base_handler import BaseServiceHandler
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SERVICE_SYSTEM_PROMPT = """You are a compliance analyst at Performance West Inc.
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generating a Fair Labor Standards Act (FLSA) compliance audit report.
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RULES:
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- Write in professional, clear business English
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- Cite specific FLSA regulations (29 CFR § 541, etc.)
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- Never provide legal advice — use "we recommend" not "you must"
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- For each finding: what was found, regulation, risk level (Low/Medium/High/Critical), remediation
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- Structure with clear headings and bullet points
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- Include specific section references from the Fair Labor Standards Act
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- Reference DOL Fact Sheets where applicable
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- Note state-specific requirements where the client operates
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"""
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SECTIONS = [
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{
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"name": "executive_summary",
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"prompt": (
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"Write a 200-word executive summary of the FLSA audit findings. "
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"Include the scope of the audit, number of positions reviewed, "
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"overall compliance posture, and highest-priority findings."
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),
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},
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{
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"name": "classification_analysis",
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"prompt": (
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"Analyze each employee classification (exempt vs non-exempt) "
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"against the duties tests under 29 CFR § 541. For each role: "
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"state the current classification, whether it meets the salary "
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"basis test ($684/week), whether it passes the duties test for "
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"the claimed exemption (executive, administrative, professional, "
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"computer, outside sales), and the risk if misclassified."
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),
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},
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{
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"name": "overtime_analysis",
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"prompt": (
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"Analyze overtime calculation methods and identify any violations. "
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"Review the regular rate of pay calculations, treatment of bonuses "
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"and commissions in overtime, comp time practices, fluctuating "
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"workweek usage, and any off-the-clock work risks."
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),
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},
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{
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"name": "recordkeeping_review",
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"prompt": (
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"Review timekeeping and recordkeeping compliance under 29 CFR § 516. "
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"Assess: accuracy of time records, retention periods, required data "
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"fields, break/meal period documentation, and any gaps that could "
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"expose the organization in a wage-hour investigation."
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),
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},
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{
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"name": "youth_employment",
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"prompt": (
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"Review compliance with child labor provisions under FLSA § 212-213. "
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"If the client employs any workers under 18: permitted occupations, "
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"hour restrictions, hazardous occupation orders, and required "
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"documentation. If not applicable, state so briefly."
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),
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},
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{
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"name": "remediation_plan",
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"prompt": (
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"Provide a prioritized remediation plan for all findings. "
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"For each item: finding reference, risk level, recommended action, "
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"responsible party, and suggested timeline. Group by priority "
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"(Critical → High → Medium → Low)."
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),
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},
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]
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class FLSAAuditHandler(BaseServiceHandler):
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SERVICE_SLUG = "flsa-audit"
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SERVICE_NAME = "FLSA Compliance Audit"
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TEMPLATE_NAME = "flsa_audit_template.docx"
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REQUIRES_LLM = True
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async def process(self, order_data: dict) -> list[str]:
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work_dir = self._make_work_dir()
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order_number = order_data["name"]
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context = self._extract_order_context(order_data)
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# 1. Load template and fill basic variables
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template_path = self._get_template_path()
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docx_filename = self._output_filename(order_number, "docx")
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docx_path = os.path.join(work_dir, docx_filename)
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variables = {
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"order_number": order_number,
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"customer_name": order_data.get("customer_name", ""),
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"date": __import__("datetime").datetime.now().strftime("%B %d, %Y"),
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"service_name": self.SERVICE_NAME,
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"company_size": order_data.get("custom_company_size", "N/A"),
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"industry": order_data.get("custom_industry", "N/A"),
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"state": order_data.get("custom_state", "N/A"),
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}
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self._fill_template(template_path, variables, docx_path)
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# 2. Generate LLM sections
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sections = await self._generate_sections(
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SERVICE_SYSTEM_PROMPT, SECTIONS, context
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)
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# 3. Append sections to the document
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self._add_sections_to_doc(docx_path, sections)
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# 4. Convert to PDF
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pdf_path = self._convert_to_pdf(docx_path)
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return [docx_path, pdf_path]
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