api/reports.py

"""
api/reports.py — PDF report generation for a given case.
"""

import io
import logging
from datetime import datetime

from fastapi import APIRouter, HTTPException, Request
from fastapi.responses import StreamingResponse

logger = logging.getLogger(__name__)
router = APIRouter()

DISCLAIMER_TEXT = (
    "RESEARCH & SCREENING DEMONSTRATION ONLY — NOT A MEDICAL DIAGNOSIS. "
    "This report is generated by an AI research system and must not be used "
    "for clinical decision-making. Results should not replace consultation with "
    "a qualified neurologist or healthcare professional."
)


def _generate_pdf(case: dict) -> bytes:
    """Generate a PDF report for a case using ReportLab."""
    from reportlab.lib import colors
    from reportlab.lib.pagesizes import A4
    from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
    from reportlab.lib.units import cm
    from reportlab.platypus import (
        HRFlowable, Paragraph, SimpleDocTemplate, Spacer, Table, TableStyle,
    )

    buf = io.BytesIO()
    doc = SimpleDocTemplate(
        buf,
        pagesize=A4,
        rightMargin=2.5 * cm,
        leftMargin=2.5 * cm,
        topMargin=2.5 * cm,
        bottomMargin=2.5 * cm,
    )

    styles = getSampleStyleSheet()
    teal = colors.HexColor("#0D7377")
    ink = colors.HexColor("#1A1A1A")
    muted = colors.HexColor("#6B6B6B")

    title_style = ParagraphStyle(
        "Title", parent=styles["Heading1"],
        fontSize=22, textColor=teal, spaceAfter=4,
    )
    subtitle_style = ParagraphStyle(
        "Subtitle", parent=styles["Normal"],
        fontSize=10, textColor=muted, spaceAfter=12,
    )
    section_style = ParagraphStyle(
        "Section", parent=styles["Heading2"],
        fontSize=12, textColor=ink, spaceBefore=16, spaceAfter=6,
    )
    body_style = ParagraphStyle(
        "Body", parent=styles["Normal"],
        fontSize=9, textColor=ink, leading=14, spaceAfter=8,
    )
    disclaimer_style = ParagraphStyle(
        "Disclaimer", parent=styles["Normal"],
        fontSize=8, textColor=colors.HexColor("#92400E"),
        backColor=colors.HexColor("#FEF3C7"),
        leading=12, spaceAfter=8, spaceBefore=8,
        leftIndent=8, rightIndent=8,
    )

    story = []

    # Header
    story.append(Paragraph("NeuroDraw", title_style))
    story.append(Paragraph("Parkinson's Handwriting Analysis — Research Report", subtitle_style))
    story.append(HRFlowable(width="100%", thickness=1, color=teal))
    story.append(Spacer(1, 0.4 * cm))

    # Case metadata
    case_id = case.get("case_id", "N/A")
    timestamp = case.get("timestamp", "N/A")
    mode = case.get("mode", "auto").replace("_", " ").title()
    try:
        dt = datetime.fromisoformat(timestamp.replace("Z", "+00:00"))
        formatted_time = dt.strftime("%d %B %Y, %H:%M UTC")
    except Exception:
        formatted_time = timestamp

    meta_data = [
        ["Case ID", case_id],
        ["Generated", formatted_time],
        ["Analysis Mode", mode],
        ["Mock Results", "Yes — model files not loaded" if case.get("is_mock") else "No — real inference"],
    ]
    meta_table = Table(meta_data, colWidths=[4 * cm, 13 * cm])
    meta_table.setStyle(TableStyle([
        ("FONTSIZE", (0, 0), (-1, -1), 9),
        ("TEXTCOLOR", (0, 0), (0, -1), muted),
        ("TEXTCOLOR", (1, 0), (1, -1), ink),
        ("TOPPADDING", (0, 0), (-1, -1), 3),
        ("BOTTOMPADDING", (0, 0), (-1, -1), 3),
    ]))
    story.append(meta_table)
    story.append(Spacer(1, 0.4 * cm))

    # Routing result
    story.append(Paragraph("Drawing Classification", section_style))
    routing = case.get("routing_result") or {}
    routing_data = [
        ["Detected Type", routing.get("label", "N/A")],
        ["Router Confidence", f"{routing.get('confidence', 0):.1%}"],
        ["Borderline", "Yes" if routing.get("is_borderline") else "No"],
    ]
    if case.get("type_agnostic_mode"):
        routing_data.append(["Mode", "Type-agnostic demo (Garbage gate bypassed)"])
    routing_table = Table(routing_data, colWidths=[4 * cm, 13 * cm])
    routing_table.setStyle(TableStyle([
        ("FONTSIZE", (0, 0), (-1, -1), 9),
        ("TEXTCOLOR", (0, 0), (0, -1), muted),
        ("TEXTCOLOR", (1, 0), (1, -1), ink),
        ("TOPPADDING", (0, 0), (-1, -1), 3),
        ("BOTTOMPADDING", (0, 0), (-1, -1), 3),
    ]))
    story.append(routing_table)

    # Quality check
    story.append(Paragraph("Image Quality Assessment", section_style))
    quality = case.get("quality_check") or {}
    checks = quality.get("checks") or []
    if checks:
        check_data = [["Check", "Status", "Detail"]]
        for c in checks:
            check_data.append([
                c.get("name", ""),
                c.get("status", "").upper(),
                c.get("message", ""),
            ])
        check_table = Table(check_data, colWidths=[3.5 * cm, 2 * cm, 11.5 * cm])
        check_table.setStyle(TableStyle([
            ("FONTSIZE", (0, 0), (-1, -1), 8),
            ("BACKGROUND", (0, 0), (-1, 0), colors.HexColor("#E4E4E0")),
            ("FONTNAME", (0, 0), (-1, 0), "Helvetica-Bold"),
            ("TOPPADDING", (0, 0), (-1, -1), 3),
            ("BOTTOMPADDING", (0, 0), (-1, -1), 3),
            ("GRID", (0, 0), (-1, -1), 0.5, colors.HexColor("#E4E4E0")),
        ]))
        story.append(check_table)

    # Model results
    story.append(Paragraph("Model Analysis Results", section_style))

    def result_rows(result_dict: dict) -> list:
        if not result_dict:
            return []
        return [
            ["Model", result_dict.get("model_name", "N/A")],
            ["Assessment", result_dict.get("label", "N/A") + "-consistent"],
            ["Raw Probability", f"{result_dict.get('prob', 0):.4f}"],
            ["Inference Time", f"{result_dict.get('inference_time_ms', 0):.0f} ms"],
            ["Mock Result", "Yes" if result_dict.get("is_mock") else "No"],
        ]

    all_results = case.get("all_results")
    if all_results:
        for key, res in all_results.items():
            if res:
                rows = result_rows(res)
                t = Table(rows, colWidths=[4 * cm, 13 * cm])
                t.setStyle(TableStyle([
                    ("FONTSIZE", (0, 0), (-1, -1), 9),
                    ("TEXTCOLOR", (0, 0), (0, -1), muted),
                    ("TOPPADDING", (0, 0), (-1, -1), 2),
                    ("BOTTOMPADDING", (0, 0), (-1, -1), 2),
                ]))
                story.append(t)
                story.append(Spacer(1, 0.2 * cm))
    else:
        for res in [case.get("specialist_result"), case.get("unified_result")]:
            if res:
                rows = result_rows(res)
                t = Table(rows, colWidths=[4 * cm, 13 * cm])
                t.setStyle(TableStyle([
                    ("FONTSIZE", (0, 0), (-1, -1), 9),
                    ("TEXTCOLOR", (0, 0), (0, -1), muted),
                    ("TOPPADDING", (0, 0), (-1, -1), 2),
                    ("BOTTOMPADDING", (0, 0), (-1, -1), 2),
                ]))
                story.append(t)
                story.append(Spacer(1, 0.2 * cm))

    # Explanation
    explanation = case.get("explanation", "")
    if explanation:
        story.append(Paragraph("Interpretation", section_style))
        story.append(Paragraph(explanation, body_style))

    # Disclaimer
    story.append(Spacer(1, 0.6 * cm))
    story.append(HRFlowable(width="100%", thickness=1, color=colors.HexColor("#E4E4E0")))
    story.append(Spacer(1, 0.3 * cm))
    story.append(Paragraph(DISCLAIMER_TEXT, disclaimer_style))

    doc.build(story)
    buf.seek(0)
    return buf.read()


@router.post("/reports/{case_id}")
async def generate_report(case_id: str, request: Request):
    """Generate and stream a PDF report for the given case."""
    case = request.app.state.cases.get(case_id)
    if not case:
        raise HTTPException(status_code=404, detail=f"Case '{case_id}' not found")

    try:
        pdf_bytes = _generate_pdf(case)
    except Exception as exc:
        logger.error("PDF generation failed for case %s: %s", case_id, exc)
        raise HTTPException(status_code=500, detail="PDF generation failed")

    filename = f"neurodraw_report_{case_id[:8]}.pdf"
    return StreamingResponse(
        io.BytesIO(pdf_bytes),
        media_type="application/pdf",
        headers={"Content-Disposition": f'attachment; filename="{filename}"'},
    )