"""Renders a ReportContent (structured, from the LLM) into the Markdown
document the API/UI serve alongside the JSON - see spec section 6G for the
16-section layout this follows.
"""

from __future__ import annotations

from app.prompts.report_generation import Finding, InferredProject, ReportContent


def _render_findings(findings: list[Finding]) -> str:
    if not findings:
        return "_No findings for this section from the current evidence._\n"
    lines = []
    for f in findings:
        lines.append(f"- **{f.headline}** _(confidence: {f.confidence.value.replace('_', ' ')})_")
        lines.append(f"  {f.summary}")
        if f.date:
            lines.append(f"  _Date: {f.date}_")
    return "\n".join(lines) + "\n"


def _render_projects(projects: list[InferredProject]) -> str:
    if not projects:
        return "_No inferred strategic projects from the current evidence._\n"
    lines = []
    for p in projects:
        lines.append(
            f"- **{p.project_name}** _({p.status.value.replace('_', ' ')}, confidence {p.confidence:.0%})_"
        )
        lines.append(f"  {p.summary}")
        if p.alternative_explanations:
            lines.append(f"  Alternative explanations: {'; '.join(p.alternative_explanations)}")
    return "\n".join(lines) + "\n"


def _render_list(items: list[str]) -> str:
    if not items:
        return "_None noted._\n"
    return "\n".join(f"- {item}" for item in items) + "\n"


def render_report_markdown(
    content: ReportContent,
    *,
    company_name: str,
    generated_at: str,
    model_provider: str,
    model_name: str,
    sources: list[dict],
) -> str:
    parts = [
        f"# Competitive Intelligence Report: {company_name}",
        f"_Generated {generated_at} · {model_provider}/{model_name}_",
        "",
        "## 1. Executive Summary",
        content.executive_summary,
        "",
        "## 2. Company Overview",
        content.company_overview,
        "",
        "## 3. Products and Service Landscape",
        _render_findings(content.products_and_services),
        "## 4. Recent Developments",
        _render_findings(content.recent_developments),
        "## 5. Strategic Initiatives",
        _render_findings(content.strategic_initiatives),
        "## 6. Key Project Signals",
        _render_projects(content.key_inferred_projects),
        "## 7. Competitive Positioning",
        content.market_positioning,
        "",
        content.competitor_comparison,
        "",
        "## 8. SWOT Analysis",
        "**Strengths**",
        _render_list(content.swot.strengths),
        "**Weaknesses**",
        _render_list(content.swot.weaknesses),
        "**Opportunities**",
        _render_list(content.swot.opportunities),
        "**Threats**",
        _render_list(content.swot.threats),
        "## 9. Hiring Signals",
        _render_findings(content.hiring_signals),
        "## 10. Product and Technology Signals",
        _render_findings(content.technology_signals + content.patent_signals),
        "## 11. Customer Sentiment",
        content.customer_sentiment,
        "",
        "## 12. Financial and Regulatory Signals",
        _render_findings(content.financial_signals + content.regulatory_and_legal_signals),
        "## 13. Risks and Opportunities",
        "**Risks**",
        _render_list(content.risks),
        "**Opportunities**",
        _render_list(content.opportunities),
        "## 14. Important Unknowns",
        _render_list(content.unknowns_and_missing_data),
        "## 15. Sources",
        _render_sources(sources),
        "## 16. Methodology and Limitations",
        content.methodology,
        "",
        content.limitations,
    ]
    return "\n".join(str(p) for p in parts)


def _render_sources(sources: list[dict]) -> str:
    if not sources:
        return "_No sources recorded for this report._\n"
    lines = [
        f"- [{s.get('title') or s.get('url')}]({s.get('url')}) — retrieved {s.get('retrieved_date')}"
        for s in sources
    ]
    return "\n".join(lines) + "\n"