feat: add viz_bundle support to report generation and enhance schema

- Introduced the `viz_bundle` block type to the report profile schema, allowing for the inclusion of bundled visualizations in PDF reports.
- Updated the `build_structured_report_pdf` function to handle `VizBundleBlock` and append its content to the report.
- Enhanced the report catalog API to include details for the new `viz_bundle` block type.
- Added configuration editors for various visualization bundles in the frontend settings page.
- Updated tests to validate the new `viz_bundle` functionality and ensure proper handling of report profiles.
- Bumped application version to reflect these enhancements.

backend/report_chart_plotting.py

@@ -0,0 +1,91 @@
+"""Chart.js-ähnliche Payloads → PNG (Matplotlib). Von PDF- und Bundle-Rendering gemeinsam genutzt."""
+from __future__ import annotations
+
+import io
+from typing import Any
+
+import matplotlib
+
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+
+
+def _color_to_rgb(hex_or_rgba: str) -> tuple[float, float, float]:
+    s = (hex_or_rgba or "#333333").strip()
+    if s.startswith("#") and len(s) >= 7:
+        try:
+            r = int(s[1:3], 16) / 255.0
+            g = int(s[3:5], 16) / 255.0
+            b = int(s[5:7], 16) / 255.0
+            return (r, g, b)
+        except ValueError:
+            pass
+    return (0.12, 0.62, 0.46)
+
+
+def chart_payload_to_png(payload: dict[str, Any], fig_width_in: float = 6.2, fig_height_in: float = 3.4) -> bytes:
+    chart_type = payload.get("chart_type") or "line"
+    data = payload.get("data") or {}
+    labels = data.get("labels") or []
+    datasets = data.get("datasets") or []
+
+    fig, ax = plt.subplots(figsize=(fig_width_in, fig_height_in), dpi=120)
+    ax.set_facecolor("#fafaf9")
+    fig.patch.set_facecolor("#ffffff")
+
+    if chart_type == "pie" and datasets:
+        ds0 = datasets[0]
+        values = ds0.get("data") or []
+        colors = ds0.get("backgroundColor") or ["#1D9E75", "#378ADD", "#D85A30"]
+        if labels and values and len(labels) == len(values):
+            ax.pie(values, labels=labels, autopct="%1.0f%%", colors=colors[: len(values)], startangle=90)
+            ax.axis("equal")
+        else:
+            ax.text(0.5, 0.5, "Keine Daten", ha="center", va="center", transform=ax.transAxes)
+
+    elif chart_type in ("line", "bar", "scatter") and datasets:
+        x = range(len(labels)) if labels else []
+        for i, ds in enumerate(datasets):
+            y = ds.get("data") or []
+            if not y:
+                continue
+            lab = ds.get("label") or f"Serie {i + 1}"
+            col = _color_to_rgb(str(ds.get("borderColor") or ds.get("backgroundColor") or "#1D9E75"))
+            if chart_type == "bar":
+                yv = y[: len(labels)] if labels else y
+                bg = ds.get("backgroundColor")
+                if isinstance(bg, list):
+                    cols = [_color_to_rgb(str(c)) for c in bg[: len(yv)]]
+                else:
+                    cols = [_color_to_rgb(str(bg or "#1D9E75"))] * len(yv)
+                ax.bar(list(range(len(yv))), yv, label=lab, color=cols[: len(yv)], alpha=0.88)
+            else:
+                ax.plot(
+                    list(x)[: len(y)],
+                    y,
+                    label=lab,
+                    color=col,
+                    linewidth=1.6,
+                    marker="o",
+                    markersize=2,
+                )
+        if labels and chart_type != "bar":
+            step = max(1, len(labels) // 8)
+            ax.set_xticks(list(x)[::step])
+            ax.set_xticklabels([labels[j] for j in range(0, len(labels), step)], rotation=25, fontsize=7)
+        elif labels and chart_type == "bar":
+            ax.set_xticks(list(x))
+            ax.set_xticklabels(labels, rotation=30, fontsize=7)
+        ax.legend(loc="upper right", fontsize=7)
+        ax.grid(True, alpha=0.25)
+        ax.set_xmargin(0.02)
+
+    else:
+        ax.text(0.5, 0.5, "Diagrammtyp nicht unterstützt oder leer", ha="center", va="center", transform=ax.transAxes)
+
+    fig.tight_layout()
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png", bbox_inches="tight", facecolor=fig.get_facecolor())
+    plt.close(fig)
+    buf.seek(0)
+    return buf.read()

backend/report_pdf_render.py

@@ -1,5 +1,5 @@
 """
-PDF-Bericht aus ReportProfilePayload: ReportLab für Text/Layout, Matplotlib für Chart.js-ähnliche Payloads.
+PDF-Bericht aus ReportProfilePayload: ReportLab für Text/Layout, Matplotlib für Chart-Payloads.
 """
 from __future__ import annotations
 
@@ -8,10 +8,6 @@ import logging
 from typing import Any
 from xml.sax.saxutils import escape
 
-import matplotlib
-
-matplotlib.use("Agg")
-import matplotlib.pyplot as plt
 from reportlab.lib.pagesizes import A4
 from reportlab.lib.styles import getSampleStyleSheet
 from reportlab.lib.units import mm
@@ -20,100 +16,21 @@ from reportlab.platypus import Paragraph, SimpleDocTemplate, Spacer
 
 from db import get_cursor, get_db
 from report_chart_fetch import fetch_chart_payload
+from report_chart_plotting import chart_payload_to_png
 from report_profile_schema import (
     AiInsightBlock,
     ChartBlock,
     ReportProfilePayload,
     SectionBlock,
+    VizBundleBlock,
 )
+from report_viz_bundle_pdf import append_viz_bundle_to_story
 
 logger = logging.getLogger(__name__)
 
 _CONTENT_TRUNCATE = 12000
 
 
-def _color_to_rgb(hex_or_rgba: str) -> tuple[float, float, float]:
-    s = (hex_or_rgba or "#333333").strip()
-    if s.startswith("#") and len(s) >= 7:
-        try:
-            r = int(s[1:3], 16) / 255.0
-            g = int(s[3:5], 16) / 255.0
-            b = int(s[5:7], 16) / 255.0
-            return (r, g, b)
-        except ValueError:
-            pass
-    return (0.12, 0.62, 0.46)
-
-
-def chart_payload_to_png(payload: dict[str, Any], fig_width_in: float = 6.2, fig_height_in: float = 3.4) -> bytes:
-    """Erzeugt PNG aus Chart.js-kompatiblem Payload (line, bar, pie)."""
-    chart_type = payload.get("chart_type") or "line"
-    data = payload.get("data") or {}
-    labels = data.get("labels") or []
-    datasets = data.get("datasets") or []
-
-    fig, ax = plt.subplots(figsize=(fig_width_in, fig_height_in), dpi=120)
-    ax.set_facecolor("#fafaf9")
-    fig.patch.set_facecolor("#ffffff")
-
-    if chart_type == "pie" and datasets:
-        ds0 = datasets[0]
-        values = ds0.get("data") or []
-        colors = ds0.get("backgroundColor") or ["#1D9E75", "#378ADD", "#D85A30"]
-        if labels and values and len(labels) == len(values):
-            ax.pie(values, labels=labels, autopct="%1.0f%%", colors=colors[: len(values)], startangle=90)
-            ax.axis("equal")
-        else:
-            ax.text(0.5, 0.5, "Keine Daten", ha="center", va="center", transform=ax.transAxes)
-
-    elif chart_type in ("line", "bar", "scatter") and datasets:
-        x = range(len(labels)) if labels else []
-        for i, ds in enumerate(datasets):
-            y = ds.get("data") or []
-            if not y:
-                continue
-            lab = ds.get("label") or f"Serie {i + 1}"
-            col = _color_to_rgb(str(ds.get("borderColor") or ds.get("backgroundColor") or "#1D9E75"))
-            if chart_type == "bar":
-                yv = y[: len(labels)] if labels else y
-                bg = ds.get("backgroundColor")
-                if isinstance(bg, list):
-                    cols = [_color_to_rgb(str(c)) for c in bg[: len(yv)]]
-                else:
-                    cols = [_color_to_rgb(str(bg or "#1D9E75"))] * len(yv)
-                ax.bar(list(range(len(yv))), yv, label=lab, color=cols[: len(yv)], alpha=0.88)
-            else:
-                ax.plot(
-                    list(x)[: len(y)],
-                    y,
-                    label=lab,
-                    color=col,
-                    linewidth=1.6,
-                    marker="o",
-                    markersize=2,
-                )
-        if labels and chart_type != "bar":
-            step = max(1, len(labels) // 8)
-            ax.set_xticks(list(x)[::step])
-            ax.set_xticklabels([labels[j] for j in range(0, len(labels), step)], rotation=25, fontsize=7)
-        elif labels and chart_type == "bar":
-            ax.set_xticks(list(x))
-            ax.set_xticklabels(labels, rotation=30, fontsize=7)
-        ax.legend(loc="upper right", fontsize=7)
-        ax.grid(True, alpha=0.25)
-        ax.set_xmargin(0.02)
-
-    else:
-        ax.text(0.5, 0.5, "Diagrammtyp nicht unterstützt oder leer", ha="center", va="center", transform=ax.transAxes)
-
-    fig.tight_layout()
-    buf = io.BytesIO()
-    fig.savefig(buf, format="png", bbox_inches="tight", facecolor=fig.get_facecolor())
-    plt.close(fig)
-    buf.seek(0)
-    return buf.read()
-
-
 def _insight_text(profile_id: str, insight_id: str | None) -> tuple[str, str]:
     """Returns (heading, body_text)."""
     if not insight_id:
@@ -172,6 +89,8 @@ def build_structured_report_pdf(
             story.append(Spacer(1, 4 * mm))
             story.append(Paragraph(escape(block.title), styles["Heading2"]))
             story.append(Spacer(1, 2 * mm))
+        elif isinstance(block, VizBundleBlock):
+            append_viz_bundle_to_story(story, styles, profile_id, block.bundle_id, block.config)
         elif isinstance(block, ChartBlock):
             try:
                 chart = fetch_chart_payload(block.chart_id, profile_id, block.window_days)
@@ -188,7 +107,6 @@ def build_structured_report_pdf(
             try:
                 png = chart_payload_to_png(chart)
                 img_buf = io.BytesIO(png)
-                # Breite ~ volle Textbreite (~180mm auf A4 mit Standardrändern Platypus)
                 iw = 170 * mm
                 ih = 85 * mm
                 story.append(RLImage(img_buf, width=iw, height=ih))

backend/report_profile_schema.py

@@ -3,15 +3,18 @@ Konfigurierbarer PDF-Bericht v1: Payload-Schema (unabhängig vom Dashboard-Layou
 
 Block-Typen:
 - section: Überschrift
+- viz_bundle: Layer-2b-Ver bundles (KPIs, Text, Charts) — gleiche Config wie Dashboard
 - chart: diagramm via report_chart_fetch (chart_id + window_days)
 - ai_insight: optional insight_id (UUID), sonst Platzhalter für spätere Auswahl
 """
 from __future__ import annotations
 
-from typing import Literal, Union
+from typing import Any, Literal, Union
 
 from pydantic import BaseModel, Field, model_validator
 
+from dashboard_widget_config import validate_widget_entry_config
+
 ALLOWED_CHART_IDS: frozenset[str] = frozenset(
     {
         "weight_trend",
@@ -22,7 +25,17 @@ ALLOWED_CHART_IDS: frozenset[str] = frozenset(
     }
 )
 
-_MAX_BLOCKS = 24
+_MAX_BLOCKS = 32
+
+ALLOWED_VIZ_BUNDLE_IDS: frozenset[str] = frozenset(
+    {
+        "body_history_viz",
+        "nutrition_history_viz",
+        "fitness_history_viz",
+        "recovery_history_viz",
+        "history_overview_viz",
+    }
+)
 
 
 class SectionBlock(BaseModel):
@@ -48,10 +61,27 @@ class AiInsightBlock(BaseModel):
     insight_id: str | None = Field(default=None, max_length=48)
 
 
+class VizBundleBlock(BaseModel):
+    """Gleiche Layer-2b-Bundles wie im Dashboard; config wie validate_widget_entry_config."""
+
+    type: Literal["viz_bundle"] = "viz_bundle"
+    bundle_id: str = Field(min_length=1, max_length=64)
+    config: dict[str, Any] = Field(default_factory=dict)
+
+    @model_validator(mode="after")
+    def _bundle_config(self) -> VizBundleBlock:
+        if self.bundle_id not in ALLOWED_VIZ_BUNDLE_IDS:
+            raise ValueError(
+                f"Unbekanntes bundle_id: {self.bundle_id!r} (erlaubt: {sorted(ALLOWED_VIZ_BUNDLE_IDS)})"
+            )
+        self.config = validate_widget_entry_config(self.bundle_id, self.config)
+        return self
+
+
 class ReportProfilePayload(BaseModel):
     version: Literal[1] = 1
     document_title: str = Field(default="", max_length=120)
-    blocks: list[Union[SectionBlock, ChartBlock, AiInsightBlock]]
+    blocks: list[Union[SectionBlock, ChartBlock, AiInsightBlock, VizBundleBlock]]
 
     @model_validator(mode="after")
     def _blocks_limit(self) -> ReportProfilePayload:
@@ -74,12 +104,16 @@ def default_report_profile_dict() -> dict:
     p = ReportProfilePayload(
         document_title="",
         blocks=[
-            SectionBlock(title="Körpergewicht"),
-            ChartBlock(chart_id="weight_trend", window_days=90),
-            SectionBlock(title="Energiebilanz"),
-            ChartBlock(chart_id="energy_balance", window_days=28),
-            SectionBlock(title="Trainingsvolumen"),
-            ChartBlock(chart_id="training_volume", window_days=84),
+            SectionBlock(title="Verlauf — Körper"),
+            VizBundleBlock(bundle_id="body_history_viz", config={"chart_days": 90}),
+            SectionBlock(title="Verlauf — Ernährung"),
+            VizBundleBlock(bundle_id="nutrition_history_viz", config={"chart_days": 90}),
+            SectionBlock(title="Verlauf — Fitness"),
+            VizBundleBlock(bundle_id="fitness_history_viz", config={"chart_days": 90}),
+            SectionBlock(title="Verlauf — Erholung"),
+            VizBundleBlock(bundle_id="recovery_history_viz", config={"chart_days": 90}),
+            SectionBlock(title="Gesamtübersicht"),
+            VizBundleBlock(bundle_id="history_overview_viz", config={"chart_days": 90}),
         ],
     )
     return p.to_stored_dict()

backend/report_viz_bundle_pdf.py

@@ -0,0 +1,386 @@
+"""
+Layer-2b Verlauf-Bundles → PDF-Abschnitte (KPIs + eingebettete Chart-Payloads).
+
+Gleiche Datenquellen und Config-Validierung wie Dashboard-Widgets (dashboard_widget_config).
+"""
+from __future__ import annotations
+
+import io
+import logging
+from typing import Any
+
+from reportlab.lib.units import mm
+from reportlab.platypus import Image as RLImage
+from reportlab.platypus import Paragraph, Spacer
+from xml.sax.saxutils import escape
+
+from dashboard_widget_config import validate_widget_entry_config
+from data_layer.body_viz import get_body_history_viz_bundle
+from data_layer.fitness_viz import get_fitness_dashboard_viz_bundle
+from data_layer.history_overview_viz import get_history_overview_viz_bundle
+from data_layer.nutrition_viz import get_nutrition_history_viz_bundle
+from data_layer.recovery_viz import get_recovery_dashboard_viz_bundle
+from data_layer.utils import safe_float
+from report_chart_plotting import chart_payload_to_png
+
+logger = logging.getLogger(__name__)
+
+BUNDLE_HEADINGS: dict[str, str] = {
+    "body_history_viz": "Körper — Kennwerte & Verlauf",
+    "nutrition_history_viz": "Ernährung — Kennwerte & Charts",
+    "fitness_history_viz": "Fitness / Training",
+    "recovery_history_viz": "Erholung & Vitalwerte",
+    "history_overview_viz": "Gesamtübersicht & Korrelationen",
+}
+
+
+def _add_chart_to_story(story: list, styles: dict, payload: dict[str, Any], caption: str | None = None) -> None:
+    meta = payload.get("metadata") or {}
+    if meta.get("confidence") == "insufficient":
+        msg = escape(meta.get("message") or "Keine Daten")
+        story.append(Paragraph(f"<i>{msg}</i>", styles["Normal"]))
+        story.append(Spacer(1, 2 * mm))
+        return
+    if caption:
+        story.append(Paragraph(f"<b>{escape(caption)}</b>", styles["Normal"]))
+    try:
+        png = chart_payload_to_png(payload)
+        story.append(RLImage(io.BytesIO(png), width=170 * mm, height=85 * mm))
+    except Exception as e:
+        logger.warning("bundle chart png: %s", e)
+        story.append(Paragraph("Diagramm konnte nicht gerendert werden.", styles["Normal"]))
+    story.append(Spacer(1, 4 * mm))
+
+
+def _append_interpretation_tiles(story: list, styles: dict, tiles: list[dict[str, Any]]) -> None:
+    if not tiles:
+        return
+    story.append(Paragraph("<b>Einschätzungen</b>", styles["Heading4"]))
+    for t in tiles:
+        cat = escape(str(t.get("category") or t.get("title") or "—"))
+        title = t.get("title")
+        detail = t.get("detail")
+        val = t.get("value")
+        parts = [f"<b>{cat}</b>"]
+        if title and str(title) != str(cat):
+            parts.append(escape(str(title)))
+        if val is not None and val != "":
+            parts.append(f"({escape(str(val))})")
+        story.append(Paragraph(" — ".join(parts), styles["Normal"]))
+        if detail:
+            story.append(Paragraph(escape(str(detail)[:500]), styles["BodyText"]))
+    story.append(Spacer(1, 3 * mm))
+
+
+def _append_kpi_tiles_fitness_nutreco(story: list, styles: dict, tiles: list[dict[str, Any]], compact: bool) -> None:
+    if not tiles:
+        return
+    use = tiles[:4] if compact else tiles
+    story.append(Paragraph("<b>KPI-Kacheln</b>", styles["Heading4"]))
+    for t in use:
+        cat = escape(str(t.get("category") or t.get("title") or "—"))
+        val = escape(str(t.get("value") or "—"))
+        sub = t.get("sublabel") or t.get("body")
+        line = f"• <b>{cat}</b>: {val}"
+        if sub:
+            line += f" — {escape(str(sub)[:180])}"
+        story.append(Paragraph(line, styles["Normal"]))
+    story.append(Spacer(1, 3 * mm))
+
+
+def _append_insights_lines(story: list, styles: dict, insights: list[dict[str, Any]], label: str) -> None:
+    if not insights:
+        return
+    story.append(Paragraph(f"<b>{escape(label)}</b>", styles["Heading4"]))
+    for item in insights:
+        title = item.get("title") or item.get("heading")
+        body = item.get("body") or item.get("text")
+        if title:
+            story.append(Paragraph(escape(str(title)), styles["Normal"]))
+        if body:
+            story.append(Paragraph(escape(str(body)[:600]), styles["BodyText"]))
+    story.append(Spacer(1, 2 * mm))
+
+
+def _weight_series_payload(bundle_weight: dict[str, Any]) -> dict[str, Any] | None:
+    series = bundle_weight.get("series") or []
+    if len(series) < 2:
+        return None
+    labels = [str(p.get("date") or "") for p in series]
+    datasets: list[dict[str, Any]] = [
+        {
+            "label": "Gewicht (kg)",
+            "data": [safe_float(p.get("weight")) for p in series],
+            "borderColor": "#1D9E75",
+        }
+    ]
+    if any(p.get("avg7") is not None for p in series):
+        datasets.append(
+            {
+                "label": "Ø 7T",
+                "data": [safe_float(p.get("avg7")) for p in series],
+                "borderColor": "#378ADD",
+            }
+        )
+    return {"chart_type": "line", "data": {"labels": labels, "datasets": datasets}, "metadata": {"confidence": "high"}}
+
+
+def _line_payload_from_points(
+    points: list[dict[str, Any]],
+    x_key: str,
+    y_key: str,
+    label: str,
+) -> dict[str, Any] | None:
+    if len(points) < 2:
+        return None
+    labels = [str(p.get(x_key) or "") for p in points]
+    ys = [safe_float(p.get(y_key)) for p in points]
+    return {
+        "chart_type": "line",
+        "data": {
+            "labels": labels,
+            "datasets": [{"label": label, "data": ys, "borderColor": "#1D9E75"}],
+        },
+        "metadata": {"confidence": "high"},
+    }
+
+
+def _append_body_bundle(story: list, styles: dict, profile_id: str, cfg: dict[str, Any]) -> None:
+    days = int(cfg.get("chart_days") or 30)
+    bundle = get_body_history_viz_bundle(profile_id, days)
+    story.append(Paragraph(escape(BUNDLE_HEADINGS["body_history_viz"]), styles["Heading2"]))
+    if bundle.get("confidence") == "insufficient":
+        story.append(Paragraph(escape(bundle.get("message") or "Keine Körperdaten"), styles["Normal"]))
+        story.append(Spacer(1, 4 * mm))
+        return
+    summ = bundle.get("summary") or {}
+    if summ:
+        w = summ.get("weight_kg")
+        bf = summ.get("body_fat_pct")
+        parts = []
+        if w is not None:
+            parts.append(f"Gewicht: {w} kg")
+        if bf is not None:
+            parts.append(f"KF%: {bf}")
+        if parts:
+            story.append(Paragraph(escape(" · ".join(parts)), styles["Normal"]))
+            story.append(Spacer(1, 2 * mm))
+    if cfg.get("show_kpis", True):
+        _append_interpretation_tiles(story, styles, bundle.get("interpretation_tiles") or [])
+    w = bundle.get("weight") or {}
+    if cfg.get("show_weight_chart", True):
+        pl = _weight_series_payload(w)
+        if pl:
+            _add_chart_to_story(story, styles, pl, "Gewicht")
+    cal = bundle.get("caliper") or {}
+    if cfg.get("show_body_fat_chart", False):
+        ser = cal.get("series") or []
+        pts = [{"date": p.get("date"), "y": p.get("body_fat_pct")} for p in ser if p.get("body_fat_pct") is not None]
+        pl = _line_payload_from_points(pts, "date", "y", "KF %")
+        if pl:
+            _add_chart_to_story(story, styles, pl, "Körperfett (Caliper)")
+    circ = bundle.get("circumference") or {}
+    if cfg.get("show_proportion_chart", False):
+        prop = circ.get("proportion_series") or []
+        pts = [{"date": p.get("date"), "y": p.get("v_taper_cm")} for p in prop if p.get("v_taper_cm") is not None]
+        pl = _line_payload_from_points(pts, "date", "y", "V-Taper (cm)")
+        if pl:
+            _add_chart_to_story(story, styles, pl, "Proportion (Brust–Taille)")
+    if cfg.get("show_circumference_index_chart", False):
+        idx = circ.get("index_series") or []
+        if len(idx) >= 2:
+            labels = [str(p.get("date") or "") for p in idx]
+            ds: list[dict[str, Any]] = []
+            for key, lab, col in (
+                ("waist_idx", "Taille-Index", "#D85A30"),
+                ("chest_idx", "Brust-Index", "#1D9E75"),
+                ("belly_idx", "Bauch-Index", "#378ADD"),
+            ):
+                ys = [safe_float(p.get(key)) for p in idx]
+                if any(v is not None for v in ys):
+                    ds.append({"label": lab, "data": ys, "borderColor": col})
+            if ds:
+                pl = {"chart_type": "line", "data": {"labels": labels, "datasets": ds}, "metadata": {"confidence": "high"}}
+                _add_chart_to_story(story, styles, pl, "Umfang-Indizes")
+    story.append(Spacer(1, 2 * mm))
+
+
+def _append_nutrition_bundle(story: list, styles: dict, profile_id: str, cfg: dict[str, Any]) -> None:
+    days = int(cfg.get("chart_days") or 30)
+    bundle = get_nutrition_history_viz_bundle(profile_id, days)
+    story.append(Paragraph(escape(BUNDLE_HEADINGS["nutrition_history_viz"]), styles["Heading2"]))
+    if not bundle.get("has_nutrition_entries"):
+        story.append(Paragraph(escape(bundle.get("message") or "Keine Ernährungsdaten"), styles["Normal"]))
+        story.append(Spacer(1, 4 * mm))
+        return
+    compact = cfg.get("kpi_detail") == "compact"
+    if cfg.get("show_kpis", True):
+        _append_kpi_tiles_fitness_nutreco(story, styles, bundle.get("kpi_tiles") or [], compact)
+    if cfg.get("show_heuristics", False):
+        h = bundle.get("nutrition_correlation_heuristics") or []
+        for item in h:
+            t = item.get("text") or item.get("title")
+            if t:
+                story.append(Paragraph(f"• {escape(str(t))}", styles["Normal"]))
+        story.append(Spacer(1, 2 * mm))
+    charts = bundle.get("chart_payloads") or {}
+    if cfg.get("show_calorie_balance_chart", False) or cfg.get("show_energy_protein_charts", False):
+        pl = charts.get("energy_balance")
+        if pl:
+            _add_chart_to_story(story, styles, pl, "Energiebilanz")
+    if cfg.get("show_energy_protein_charts", False) or cfg.get("show_protein_lean_chart", False):
+        pl = charts.get("protein_adequacy")
+        if pl:
+            _add_chart_to_story(story, styles, pl, "Protein-Adäquanz")
+        pl2 = charts.get("nutrition_adherence")
+        if pl2:
+            _add_chart_to_story(story, styles, pl2, "Ernährungs-Adherence")
+    if cfg.get("show_macro_distribution_pair", False) or cfg.get("show_macro_daily_bars", False):
+        wm = bundle.get("weekly_macro_chart")
+        if isinstance(wm, dict) and wm.get("chart_type"):
+            _add_chart_to_story(story, styles, wm, "Makros (wöchentlich)")
+    kw = bundle.get("kcal_vs_weight") or {}
+    if cfg.get("show_kcal_vs_weight", False) and kw.get("points"):
+        pts = kw["points"]
+        if pts:
+            pl = _line_payload_from_points(pts, "date", "kcal", "kcal")
+            if pl:
+                _add_chart_to_story(story, styles, pl, "Kalorien vs. Zeit")
+    story.append(Spacer(1, 2 * mm))
+
+
+def _append_fitness_bundle(story: list, styles: dict, profile_id: str, cfg: dict[str, Any]) -> None:
+    days = int(cfg.get("chart_days") or 30)
+    bundle = get_fitness_dashboard_viz_bundle(profile_id, days)
+    story.append(Paragraph(escape(BUNDLE_HEADINGS["fitness_history_viz"]), styles["Heading2"]))
+    if not bundle.get("has_activity_entries"):
+        story.append(Paragraph(escape(bundle.get("message") or "Keine Aktivitätsdaten"), styles["Normal"]))
+        story.append(Spacer(1, 4 * mm))
+        return
+    compact = cfg.get("kpi_detail") == "compact"
+    if cfg.get("show_kpis", True):
+        _append_kpi_tiles_fitness_nutreco(story, styles, bundle.get("kpi_tiles") or [], compact)
+    if cfg.get("show_progress_insights", False):
+        _append_insights_lines(story, styles, bundle.get("progress_insights") or [], "Einschätzungen")
+    charts = bundle.get("charts") or {}
+    if cfg.get("show_chart_training_volume", True) and charts.get("training_volume"):
+        _add_chart_to_story(story, styles, charts["training_volume"], "Trainingsvolumen")
+    if cfg.get("show_chart_training_type_distribution", True) and charts.get("training_type_distribution"):
+        _add_chart_to_story(story, styles, charts["training_type_distribution"], "Trainingsarten")
+    if cfg.get("show_chart_quality_sessions", False) and charts.get("quality_sessions"):
+        _add_chart_to_story(story, styles, charts["quality_sessions"], "Qualitätssessions")
+    if cfg.get("show_chart_load_monitoring", False) and charts.get("load_monitoring"):
+        _add_chart_to_story(story, styles, charts["load_monitoring"], "Last / ACWR")
+    story.append(Spacer(1, 2 * mm))
+
+
+def _append_recovery_bundle(story: list, styles: dict, profile_id: str, cfg: dict[str, Any]) -> None:
+    days = int(cfg.get("chart_days") or 30)
+    bundle = get_recovery_dashboard_viz_bundle(profile_id, days)
+    story.append(Paragraph(escape(BUNDLE_HEADINGS["recovery_history_viz"]), styles["Heading2"]))
+    if not bundle.get("has_recovery_data"):
+        story.append(Paragraph(escape(bundle.get("message") or "Keine Erholungsdaten"), styles["Normal"]))
+        story.append(Spacer(1, 4 * mm))
+        return
+    compact = cfg.get("kpi_detail") == "compact"
+    if cfg.get("show_kpis", True):
+        _append_kpi_tiles_fitness_nutreco(story, styles, bundle.get("kpi_tiles") or [], compact)
+    if cfg.get("show_progress_insights", False):
+        _append_insights_lines(story, styles, bundle.get("progress_insights") or [], "Einschätzungen")
+    charts = bundle.get("charts") or {}
+    if cfg.get("show_chart_recovery_score", True) and charts.get("recovery_score"):
+        _add_chart_to_story(story, styles, charts["recovery_score"], "Recovery-Score")
+    if cfg.get("show_chart_hrv_rhr", True) and charts.get("hrv_rhr"):
+        _add_chart_to_story(story, styles, charts["hrv_rhr"], "HRV / RHR")
+    if cfg.get("show_chart_sleep_quality", True) and charts.get("sleep_duration_quality"):
+        _add_chart_to_story(story, styles, charts["sleep_duration_quality"], "Schlaf Dauer & Qualität")
+    if cfg.get("show_chart_sleep_debt", False) and charts.get("sleep_debt"):
+        _add_chart_to_story(story, styles, charts["sleep_debt"], "Schlafschuld")
+    if cfg.get("show_vitals_extra_trends", False):
+        if charts.get("vital_signs_matrix"):
+            _add_chart_to_story(story, styles, charts["vital_signs_matrix"], "Vital-Matrix")
+        if charts.get("vitals_history"):
+            _add_chart_to_story(story, styles, charts["vitals_history"], "Vital-Trends")
+    story.append(Spacer(1, 2 * mm))
+
+
+def _append_history_overview_bundle(story: list, styles: dict, profile_id: str, cfg: dict[str, Any]) -> None:
+    days = int(cfg.get("chart_days") or 30)
+    bundle = get_history_overview_viz_bundle(profile_id, days)
+    story.append(Paragraph(escape(BUNDLE_HEADINGS["history_overview_viz"]), styles["Heading2"]))
+    sect_keys = {
+        "body": cfg.get("show_section_body", True),
+        "nutrition": cfg.get("show_section_nutrition", True),
+        "fitness": cfg.get("show_section_fitness", True),
+        "recovery": cfg.get("show_section_recovery", True),
+    }
+    for sec in bundle.get("sections") or []:
+        sid = sec.get("id")
+        if not sect_keys.get(str(sid), True):
+            continue
+        title = escape(str(sec.get("title") or sid))
+        line = escape(str(sec.get("summary_line") or ""))
+        story.append(Paragraph(f"<b>{title}</b>: {line}", styles["Normal"]))
+        for it in sec.get("interpretation_short") or []:
+            t = it.get("title") if isinstance(it, dict) else None
+            if t:
+                story.append(Paragraph(f"• {escape(str(t))}", styles["BodyText"]))
+        for k in sec.get("kpi_short") or []:
+            if isinstance(k, dict):
+                cat = k.get("category") or k.get("title")
+                val = k.get("value")
+                if cat:
+                    story.append(Paragraph(f"• {escape(str(cat))}: {escape(str(val or ''))}", styles["BodyText"]))
+        story.append(Spacer(1, 2 * mm))
+    if cfg.get("show_correlation_c1_c3", True) or cfg.get("show_drivers_c4", True):
+        lag = bundle.get("lag_correlations") or {}
+        we = lag.get("weight_energy") or {}
+        if we.get("available") and (we.get("interpretation") or we.get("label")):
+            lab = escape(str(we.get("label") or "C1"))
+            interp = escape(str(we.get("interpretation") or "").strip())
+            if interp:
+                story.append(Paragraph(f"{lab}: {interp}", styles["Normal"]))
+    charts = bundle.get("chart_payloads") or {}
+    if cfg.get("show_correlation_c1_c3", True):
+        for key, cap in (
+            ("c1_weight_energy", "Korrelation Gewicht / Energie"),
+            ("c2_protein_lbm", "Protein / Magermasse"),
+            ("c3_load_vitals", "Last / Vitalwerte"),
+        ):
+            pl = charts.get(key)
+            if pl:
+                _add_chart_to_story(story, styles, pl, cap)
+    if cfg.get("show_drivers_c4", True):
+        pl = charts.get("c4_recovery_performance")
+        if pl:
+            _add_chart_to_story(story, styles, pl, "Top-Treiber")
+        drv = (bundle.get("lag_correlations") or {}).get("recovery_performance") or {}
+        for d in (drv.get("drivers") or [])[:12]:
+            if isinstance(d, dict):
+                lab = d.get("label") or d.get("factor")
+                val = d.get("impact") or d.get("score")
+                if lab:
+                    story.append(Paragraph(f"• {escape(str(lab))}: {escape(str(val or ''))}", styles["Normal"]))
+    story.append(Spacer(1, 2 * mm))
+
+
+def append_viz_bundle_to_story(
+    story: list,
+    styles: dict,
+    profile_id: str,
+    bundle_id: str,
+    raw_config: dict[str, Any],
+) -> None:
+    cfg = validate_widget_entry_config(bundle_id, raw_config)
+    if bundle_id == "body_history_viz":
+        _append_body_bundle(story, styles, profile_id, cfg)
+    elif bundle_id == "nutrition_history_viz":
+        _append_nutrition_bundle(story, styles, profile_id, cfg)
+    elif bundle_id == "fitness_history_viz":
+        _append_fitness_bundle(story, styles, profile_id, cfg)
+    elif bundle_id == "recovery_history_viz":
+        _append_recovery_bundle(story, styles, profile_id, cfg)
+    elif bundle_id == "history_overview_viz":
+        _append_history_overview_bundle(story, styles, profile_id, cfg)
+    else:
+        story.append(Paragraph(escape(f"Unbekanntes Bundle: {bundle_id}"), styles["Normal"]))

backend/routers/reports.py

@@ -19,6 +19,7 @@ from feature_logger import log_feature_usage
 from report_chart_fetch import CHART_CATALOG_FOR_API
 from report_pdf_render import build_structured_report_pdf
 from report_profile_schema import (
+    ALLOWED_VIZ_BUNDLE_IDS,
     ReportProfilePayload,
     default_report_profile_dict,
     parse_report_profile,
@@ -31,12 +32,21 @@ logger = logging.getLogger(__name__)
 @router.get("/catalog")
 def get_reports_catalog(session: dict = Depends(require_auth)):
     """Metadaten für UI: verfügbare Diagramme und Blocktypen."""
+    viz_titles = {
+        "body_history_viz": "Körper (Verlauf-Bundle)",
+        "nutrition_history_viz": "Ernährung (Verlauf-Bundle)",
+        "fitness_history_viz": "Fitness (Verlauf-Bundle)",
+        "recovery_history_viz": "Erholung (Verlauf-Bundle)",
+        "history_overview_viz": "Gesamtübersicht (Korrelationen)",
+    }
     return {
-        "catalog_version": 1,
+        "catalog_version": 2,
         "charts": CHART_CATALOG_FOR_API,
+        "viz_bundles": [{"id": bid, "title": viz_titles.get(bid, bid)} for bid in sorted(ALLOWED_VIZ_BUNDLE_IDS)],
         "block_types": [
             {"id": "section", "title": "Überschrift"},
-            {"id": "chart", "title": "Diagramm"},
+            {"id": "viz_bundle", "title": "Verlauf-Bundle (KPIs & Charts)"},
+            {"id": "chart", "title": "Einzel-Diagramm (Legacy)"},
             {"id": "ai_insight", "title": "KI-Auswertung"},
         ],
     }

backend/tests/test_report_profile_schema.py

@@ -29,3 +29,28 @@ def test_chart_block_unknown_id_raises():
     }
     with pytest.raises(Exception):
         ReportProfilePayload.model_validate(raw)
+
+
+def test_viz_bundle_roundtrip():
+    raw = {
+        "version": 1,
+        "document_title": "",
+        "blocks": [
+            {"type": "viz_bundle", "bundle_id": "body_history_viz", "config": {"chart_days": 14}},
+        ],
+    }
+    p = ReportProfilePayload.model_validate(raw)
+    assert p.blocks[0].type == "viz_bundle"
+    assert p.blocks[0].config.get("chart_days") == 14
+
+
+def test_viz_bundle_unknown_raises():
+    import pytest
+
+    raw = {
+        "version": 1,
+        "document_title": "",
+        "blocks": [{"type": "viz_bundle", "bundle_id": "not_a_bundle", "config": {}}],
+    }
+    with pytest.raises(Exception):
+        ReportProfilePayload.model_validate(raw)

frontend/src/pages/SettingsPage.jsx

@@ -5,6 +5,11 @@ import { useProfile } from '../context/ProfileContext'
 import { useAuth } from '../context/AuthContext'
 import { Avatar } from './ProfileSelect'
 import { api } from '../utils/api'
+import BodyHistoryVizConfigEditor from '../widgetSystem/BodyHistoryVizConfigEditor'
+import NutritionHistoryVizConfigEditor from '../widgetSystem/NutritionHistoryVizConfigEditor'
+import FitnessHistoryVizConfigEditor from '../widgetSystem/FitnessHistoryVizConfigEditor'
+import RecoveryHistoryVizConfigEditor from '../widgetSystem/RecoveryHistoryVizConfigEditor'
+import HistoryOverviewVizConfigEditor from '../widgetSystem/HistoryOverviewVizConfigEditor'
 import FeatureUsageOverview from '../components/FeatureUsageOverview'
 import UsageBadge from '../components/UsageBadge'
 
@@ -57,7 +62,10 @@ export default function SettingsPage() {
   const reportNewBlock = (kind) => {
     const charts = reportCatalog?.charts || []
     const first = charts[0]
+    const bundles = reportCatalog?.viz_bundles || []
+    const firstBundleId = bundles[0]?.id || 'body_history_viz'
     if (kind === 'section') return { type: 'section', title: 'Neue Überschrift' }
+    if (kind === 'viz_bundle') return { type: 'viz_bundle', bundle_id: firstBundleId, config: {} }
     if (kind === 'chart')
       return {
         type: 'chart',
@@ -586,10 +594,13 @@ export default function SettingsPage() {
           PDF-Bericht (strukturiert)
         </div>
         <p style={{ fontSize: 13, color: 'var(--text2)', marginBottom: 12, lineHeight: 1.65 }}>
-          <strong>Eigenes Berichtsprofil:</strong> Reihenfolge, Überschriften und Diagramme — unabhängig von der
-          Startübersicht. Die PDF-Datei wird <strong>serverseitig</strong> aus denselben Datenquellen wie die
-          Chart-API erzeugt (kein Screenshot). Das unterscheidet sich vom optionalen Widget „Übersicht als
-          Bild-PDF“ auf der Startseite.
+          <strong>Eigenes Berichtsprofil:</strong> Überschriften, <strong>Verlauf-Bundles</strong> (KPIs,
+          Einschätzungen und Diagramme wie im Bereich Verlauf) und optional einzelne Legacy-Diagramme. Gleiche
+          Schalter wie unter{' '}
+          <Link to="/settings/dashboard-layout" style={{ color: 'var(--accent)' }}>
+            Übersicht anpassen
+          </Link>
+          . PDF wird serverseitig aus dem Datenlayer erzeugt — kein Screenshot der Widgets.
         </p>
         {!canExport && (
           <div
@@ -755,6 +766,108 @@ export default function SettingsPage() {
                       />
                     </div>
                   )}
+                  {b.type === 'viz_bundle' && (
+                    <div style={{ marginTop: 8, display: 'flex', flexDirection: 'column', gap: 10 }}>
+                      <div>
+                        <label style={{ fontSize: 11, color: 'var(--text3)', display: 'block', marginBottom: 4 }}>
+                          Verlauf-Bundle
+                        </label>
+                        <select
+                          className="form-input"
+                          value={b.bundle_id}
+                          onChange={(e) =>
+                            setReportDraft((d) => {
+                              const blocks = d.blocks.map((x, j) =>
+                                j === idx ? { ...x, bundle_id: e.target.value, config: {} } : x
+                              )
+                              return { ...d, blocks }
+                            })
+                          }
+                        >
+                          {(reportCatalog.viz_bundles || []).map((vb) => (
+                            <option key={vb.id} value={vb.id}>
+                              {vb.title}
+                            </option>
+                          ))}
+                        </select>
+                      </div>
+                      {b.bundle_id === 'body_history_viz' && (
+                        <BodyHistoryVizConfigEditor
+                          config={b.config || {}}
+                          onChange={(next) =>
+                            setReportDraft((d) => {
+                              const blocks = d.blocks.map((x, j) => {
+                                if (j !== idx) return x
+                                if (Object.keys(next).length === 0) return { ...x, config: {} }
+                                return { ...x, config: { ...(x.config || {}), ...next } }
+                              })
+                              return { ...d, blocks }
+                            })
+                          }
+                        />
+                      )}
+                      {b.bundle_id === 'nutrition_history_viz' && (
+                        <NutritionHistoryVizConfigEditor
+                          config={b.config || {}}
+                          onChange={(next) =>
+                            setReportDraft((d) => {
+                              const blocks = d.blocks.map((x, j) => {
+                                if (j !== idx) return x
+                                if (Object.keys(next).length === 0) return { ...x, config: {} }
+                                return { ...x, config: { ...(x.config || {}), ...next } }
+                              })
+                              return { ...d, blocks }
+                            })
+                          }
+                        />
+                      )}
+                      {b.bundle_id === 'fitness_history_viz' && (
+                        <FitnessHistoryVizConfigEditor
+                          config={b.config || {}}
+                          onChange={(next) =>
+                            setReportDraft((d) => {
+                              const blocks = d.blocks.map((x, j) => {
+                                if (j !== idx) return x
+                                if (Object.keys(next).length === 0) return { ...x, config: {} }
+                                return { ...x, config: { ...(x.config || {}), ...next } }
+                              })
+                              return { ...d, blocks }
+                            })
+                          }
+                        />
+                      )}
+                      {b.bundle_id === 'recovery_history_viz' && (
+                        <RecoveryHistoryVizConfigEditor
+                          config={b.config || {}}
+                          onChange={(next) =>
+                            setReportDraft((d) => {
+                              const blocks = d.blocks.map((x, j) => {
+                                if (j !== idx) return x
+                                if (Object.keys(next).length === 0) return { ...x, config: {} }
+                                return { ...x, config: { ...(x.config || {}), ...next } }
+                              })
+                              return { ...d, blocks }
+                            })
+                          }
+                        />
+                      )}
+                      {b.bundle_id === 'history_overview_viz' && (
+                        <HistoryOverviewVizConfigEditor
+                          config={b.config || {}}
+                          onChange={(next) =>
+                            setReportDraft((d) => {
+                              const blocks = d.blocks.map((x, j) => {
+                                if (j !== idx) return x
+                                if (Object.keys(next).length === 0) return { ...x, config: {} }
+                                return { ...x, config: { ...(x.config || {}), ...next } }
+                              })
+                              return { ...d, blocks }
+                            })
+                          }
+                        />
+                      )}
+                    </div>
+                  )}
                 </li>
               ))}
             </ul>
@@ -772,7 +885,8 @@ export default function SettingsPage() {
               >
                 <option value="">+ Block hinzufügen…</option>
                 <option value="section">Überschrift</option>
-                <option value="chart">Diagramm</option>
+                <option value="viz_bundle">Verlauf-Bundle (KPIs &amp; Diagramme)</option>
+                <option value="chart">Einzel-Diagramm (Legacy)</option>
                 <option value="ai_insight">KI-Auswertung</option>
               </select>
             </div>