"""
docs_export.py — La Suite Docs integration for CQAI Nursing Case Studies Tool

Converts care plans and case study responses to Markdown for La Suite Docs.
No API credentials needed.
"""

from __future__ import annotations

from datetime import date

import streamlit as st

DOCS_PUBLIC_INSTANCE = "https://notes.liiib.re"
DOCS_SIGNUP_URL = "https://notes.liiib.re"
DOCS_IMPORT_GUIDE = """
**How to use La Suite Docs (free, no credit card):**

1. **Sign up** → go to [notes.liiib.re ↗](https://notes.liiib.re) and click **Start Writing**
2. Click **Créer un nouveau compte** (Create a new account) — enter username, email, password
3. Once logged in, click **+ New document**
4. Click the **⋯ menu → Import** → select your downloaded `.md` file
5. Your document is live — share, annotate, collaborate in real time

> 💡 Accounts are free. Content resets monthly on this public demo instance.
> For a permanent instance, consider self-hosting on Railway (see CQAI docs).
""".format()


def render_save_to_docs(
    title: str,
    markdown_content: str,
    filename: str,
    description: str = "",
    instance_url: str = DOCS_PUBLIC_INSTANCE,
) -> None:
    """Render a 'Save to Docs' panel with .md download + Open Docs link."""
    st.markdown("---")
    st.markdown("#### 📄 Save to La Suite Docs")
    if description:
        st.caption(description)

    col_dl, col_open = st.columns(2)
    with col_dl:
        st.download_button(
            label="⬇️ Download as .md",
            data=markdown_content,
            file_name=f"{filename}.md",
            mime="text/markdown",
            use_container_width=True,
            key=f"docs_dl_{filename}",
        )
    with col_open:
        st.link_button(
            "🌐 Sign up / Open Docs",
            url="https://notes.liiib.re",
            use_container_width=True,
        )

    with st.expander("📋 How to import into Docs", expanded=False):
        st.markdown(DOCS_IMPORT_GUIDE)
        st.info(
            "💡 La Suite Docs is an open-source, GDPR-compliant alternative to Notion "
            "and Google Docs — built by the French and German governments. Free to use.",
            icon="ℹ️",
        )


# ---------------------------------------------------------------------------
# Case Studies — Markdown generators
# ---------------------------------------------------------------------------

def care_plan_to_markdown(
    case_title: str,
    patient_summary: str,
    adpie: dict,
    nanda_diagnoses: list,
    mcq_answers: dict | None = None,
) -> str:
    """
    Convert a NANDA/ADPIE care plan to Docs-ready Markdown.

    Args:
        case_title: e.g. "STEMI — Mr Ahmed, 58"
        patient_summary: brief case overview
        adpie: dict with keys Assessment, Diagnosis, Planning, Implementation, Evaluation
        nanda_diagnoses: list of NANDA diagnosis strings
        mcq_answers: optional dict of {question: answer} for NCLEX questions
    """
    lines = [
        f"# Care Plan — {case_title}",
        "",
        f"> Generated: {date.today().strftime('%d %B %Y')}  ",
        "> Tool: CQAI Nursing Case Studies  ",
        "> Framework: NANDA / ADPIE  ",
        "> *This document supports but does not replace clinical judgment.*",
        "",
        "---",
        "",
    ]

    if patient_summary:
        lines += [
            "## Patient Summary",
            "",
            patient_summary.strip(),
            "",
            "---",
            "",
        ]

    if nanda_diagnoses:
        lines += [
            "## NANDA Nursing Diagnoses",
            "",
        ]
        for dx in nanda_diagnoses:
            lines.append(f"- {dx}")
        lines.append("")
        lines.append("---")
        lines.append("")

    adpie_icons = {
        "Assessment": "🔍",
        "Diagnosis": "📋",
        "Planning": "🎯",
        "Implementation": "⚙️",
        "Evaluation": "✅",
    }

    if adpie:
        lines += [
            "## ADPIE Nursing Process",
            "",
        ]
        for step in ["Assessment", "Diagnosis", "Planning", "Implementation", "Evaluation"]:
            content = adpie.get(step, "")
            if content:
                icon = adpie_icons.get(step, "")
                lines += [
                    f"### {icon} {step}",
                    "",
                    content.strip() if isinstance(content, str) else "\n".join(f"- {c}" for c in content),
                    "",
                ]
        lines += ["---", ""]

    if mcq_answers:
        lines += [
            "## NCLEX Practice Questions — My Answers",
            "",
        ]
        for q, a in mcq_answers.items():
            lines.append(f"**Q:** {q}")
            lines.append(f"**A:** {a}")
            lines.append("")
        lines += ["---", ""]

    lines += [
        "## Reflection",
        "",
        "*Use these prompts for NMC revalidation portfolio:*",
        "",
        "- What assessment findings were most significant and why?",
        "- How did you prioritise nursing diagnoses in this case?",
        "- What would you do differently in clinical practice?",
        "- Which NMC Standards of Proficiency did this case address?",
        "",
        "---",
        "",
        "## NMC Revalidation — CPD Record",
        "",
        "| Field | Value |",
        "|-------|-------|",
        f"| **Case** | {case_title} |",
        "| **Date** | [DATE] |",
        "| **CPD method** | Case-based learning |",
        "| **NMC Standards** | [e.g. Platform 3.4, 4.2] |",
        "| **Hours** | [X] |",
        "",
        "---",
        "",
        "*Generated by CQAI Nursing Case Studies. "
        "This tool supports but does not replace clinical judgment.*",
    ]

    return "\n".join(lines)


def case_summary_to_markdown(
    case_title: str,
    presentation: str,
    key_learning: list,
    model_answers: dict,
) -> str:
    """Format a full case study summary for Docs."""
    lines = [
        f"# Case Study — {case_title}",
        "",
        f"> Generated: {date.today().strftime('%d %B %Y')}",
        "",
        "---",
        "",
        "## Clinical Presentation",
        "",
        presentation.strip(),
        "",
        "---",
        "",
    ]

    if model_answers:
        lines += ["## Model Answers (ADPIE)", ""]
        for step, answer in model_answers.items():
            lines += [f"### {step}", "", answer.strip() if answer else "*See textbook.*", ""]
        lines += ["---", ""]

    if key_learning:
        lines += ["## Key Learning Points", ""]
        for point in key_learning:
            lines.append(f"- {point}")
        lines += ["", "---", ""]

    lines += [
        "*Generated by CQAI Nursing Case Studies. "
        "This tool supports but does not replace clinical judgment.*",
    ]

    return "\n".join(lines)