feat(#170 followup 2): Pre-Filter, Cluster, Antrags-Initiative, PM-Versionierung, Mail-Link

User-Feedback: Aktuelle-Themen-Dashboard war "Detective-Modus" — durch
viele News scrollen, Match-Stärke selbst interpretieren. Komplett-Refactor
zur kuratierten Sicht mit Tabs.

**1. Pre-Filter + GWÖ-Relevanz-Score (#134)**

`compute_relevance(matches)`: Score = max(antrag.gwoe_score × similarity).
Level: high (≥4.0) / mid (≥2.5) / low (>0) / none.
Pro News in der UI ein farbiger Pill (gruen/orange/grau) + Reason-Text:
"GWÖ-9.0/10-Antrag „Klimaschutzgesetz" (GRÜNE) passt mit Similarity 0.55."

Default-Filter "Nur GWÖ-relevant" aktiv (only_relevant=true) — zeigt
nur high/mid News, blendet Rauschen aus. Toggle-Checkbox.

`/api/aktuelle-themen/top` neuer Param `only_relevant=true|false`.

**2. PM-Versionierung im Modal (#135)**

`list_drafts_for(drucksache, news_url)`: alle Versionen, neueste oben.
Endpoint `/api/aktuelle-themen/drafts-versions`. Modal zeigt Dropdown
wenn >1 Version, Switch ohne LLM-Call. Force-Regen bleibt als Button
im "bestehender Entwurf"-Banner.

**3. News-Cluster-View (#136)**

`aggregate_news_cluster(intra_threshold=0.55, min_cluster_size=2)`:
Greedy-Embedding-Cluster + zentralster Antrags-Match per Centroid-
Vektor. Zweiter Tab "Themen-Cluster": 5 News über "Pflege" → 1 Cluster
mit gemeinsamem Antrag-Vorschlag, statt 5 separate Cards.
Endpoint: `/api/aktuelle-themen/cluster`.

**4. Mail-Direkt-Link + Clipboard (#137)**

Im PM-Modal zwei Buttons:
- "📧 Per Mail versenden" (mailto: mit subject + body, ~1900 Char Limit)
- "📋 In Zwischenablage kopieren" (navigator.clipboard.writeText)
- Bei langem PM (>1900 Char): mailto-Link wird ausgegraut, Hinweis
  "PM zu lang für Mail-Link — Clipboard nutzen"

**5. Antrags-Initiative (#138)**

`aggregate_top_antraege_with_news(min_gwoe_score=8.0, days=14)`:
Reverse-Sicht — pro Antrag mit GWÖ ≥ 8 die News-Resonanz. Antraege
ohne Match werden trotzdem angezeigt mit "keine News"-Pill.
Dritter Tab "GWÖ-Top-Anträge". Endpoint `.../top-antraege`.

**UI-Restrukturierung:** statt einer langen Scroll-Liste jetzt
5 Tabs mit gemeinsamer Filter-Bar:
- News × Anträge (Default, kuratiert via Pre-Filter)
- Themen-Cluster (Bündel ähnlicher News)
- GWÖ-Top-Anträge (Reverse)
- News-Volumen (Chart)
- PM-Entwürfe (Drafts-Liste)

Default min_similarity 0.40 → 0.50 erhoeht (weniger Rauschen).

Tests: 14 neue (compute_relevance × 5, only_relevant + sort × 3,
cluster × 3, top_antraege × 3). Suite 1067 gruen.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

app/main.py

@@ -2030,14 +2030,55 @@ async def api_aktuelle_themen_top(
     top_k: int = 10,
     min_similarity: float = 0.4,
     matches_per_news: int = 3,
+    only_relevant: bool = False,
 ):
-    """Top-K News der letzten N Tage mit Antrags-Match."""
+    """Top-K News der letzten N Tage mit Antrags-Match.
+
+    Mit `only_relevant=true` werden News mit Relevance-Level "low" oder
+    "none" rausgefiltert.
+    """
     from .themen_matching import aggregate_top_themen
     return aggregate_top_themen(
         days_window=days,
         top_k=top_k,
         min_similarity=min_similarity,
         matches_per_news=matches_per_news,
+        only_relevant=only_relevant,
+    )
+
+
+@app.get("/api/aktuelle-themen/cluster")
+async def api_aktuelle_themen_cluster(
+    days: int = 7,
+    intra_threshold: float = 0.55,
+    antrag_threshold: float = 0.4,
+    min_cluster_size: int = 2,
+):
+    """News-zu-News-Cluster ueber Embeddings — gleiches Thema, mehrere
+    Quellen → ein Cluster, nicht 5 separate Cards."""
+    from .themen_matching import aggregate_news_cluster
+    return aggregate_news_cluster(
+        days_window=days,
+        intra_threshold=intra_threshold,
+        antrag_threshold=antrag_threshold,
+        min_cluster_size=min_cluster_size,
+    )
+
+
+@app.get("/api/aktuelle-themen/top-antraege")
+async def api_aktuelle_themen_top_antraege(
+    min_gwoe_score: float = 8.0,
+    days: int = 14,
+    min_similarity: float = 0.4,
+    top_k_news: int = 5,
+):
+    """Reverse-Sicht: hoch GWÖ-bewertete Antraege mit aktueller Pressewirkung."""
+    from .themen_matching import aggregate_top_antraege_with_news
+    return aggregate_top_antraege_with_news(
+        min_gwoe_score=min_gwoe_score,
+        days_window=days,
+        min_similarity=min_similarity,
+        top_k_news=top_k_news,
     )
 
 
@@ -2125,6 +2166,17 @@ async def api_draft_detail(draft_id: int):
     return d
 
 
+@app.get("/api/aktuelle-themen/drafts-versions")
+async def api_draft_versions(drucksache: str, news_url: str):
+    """Alle Versions-Drafts fuer (drucksache, news_url) — neueste oben."""
+    from .presse_generator import list_drafts_for
+    return {
+        "drucksache": drucksache,
+        "news_url": news_url,
+        "versions": list_drafts_for(drucksache, news_url),
+    }
+
+
 @app.get("/api/auswertungen/matrix")
 async def auswertungen_matrix(
     wahlperiode: Optional[str] = None,

app/presse_generator.py

@@ -279,6 +279,40 @@ def list_drafts(
     ]
 
 
+def list_drafts_for(
+    drucksache: str,
+    news_url: str,
+    db_path: Optional[Path] = None,
+) -> list[dict]:
+    """Alle Versions-Drafts fuer ein (drucksache, news_url)-Paar, neueste oben."""
+    from .config import settings
+
+    path = db_path or settings.db_path
+    if not Path(path).exists():
+        return []
+    conn = sqlite3.connect(str(path))
+    try:
+        rows = conn.execute(
+            """SELECT id, drucksache, bundesland, news_url, news_titel,
+                      titel, body, model, created_at
+            FROM presse_drafts
+            WHERE drucksache=? AND news_url=?
+            ORDER BY id DESC""",
+            (drucksache, news_url),
+        ).fetchall()
+    finally:
+        conn.close()
+    return [
+        {
+            "id": r[0], "drucksache": r[1], "bundesland": r[2],
+            "news_url": r[3], "news_titel": r[4],
+            "titel": r[5], "body": r[6], "model": r[7],
+            "created_at": r[8],
+        }
+        for r in rows
+    ]
+
+
 def get_draft(
     draft_id: int,
     db_path: Optional[Path] = None,

app/templates/v2/screens/aktuelle-themen.html

@@ -161,46 +161,81 @@
 
 <div class="at-controls">
   <label for="at-days">Zeitfenster:</label>
-  <select id="at-days" onchange="loadThemen()">
+  <select id="at-days" onchange="loadActiveTab()">
     <option value="3">3 Tage</option>
     <option value="7" selected>7 Tage</option>
     <option value="14">14 Tage</option>
     <option value="30">30 Tage</option>
   </select>
   <label for="at-topk">Top-N News:</label>
-  <input type="number" id="at-topk" value="15" min="3" max="50" style="width:60px;" onchange="loadThemen()" />
+  <input type="number" id="at-topk" value="20" min="3" max="50" style="width:60px;" onchange="loadActiveTab()" />
   <label for="at-minsim">Min. Similarity:</label>
-  <select id="at-minsim" onchange="loadThemen()">
+  <select id="at-minsim" onchange="loadActiveTab()">
     <option value="0.30">0.30 (locker)</option>
-    <option value="0.40" selected>0.40 (default)</option>
+    <option value="0.40">0.40</option>
-    <option value="0.50">0.50 (streng)</option>
+    <option value="0.50" selected>0.50 (default)</option>
   </select>
-  <button onclick="loadThemen()">Aktualisieren</button>
+  <label style="display:inline-flex;align-items:center;gap:5px;cursor:pointer;">
+    <input type="checkbox" id="at-only-relevant" checked onchange="loadActiveTab()" />
+    Nur GWÖ-relevant
+  </label>
+  <button onclick="loadActiveTab()">Aktualisieren</button>
 </div>
 
-<!-- News-Volumen-Chart -->
+<!-- Tabs -->
-<h3 style="font-family:var(--font-display);font-size:14px;color:var(--ecg-teal);margin:1.5rem 0 0.5rem;">
+<div class="auswert-tabs" role="tablist" style="display:flex;gap:4px;margin:1.5rem 0 1rem;border-bottom:2px solid var(--ecg-border);padding-bottom:0;">
-  News-Volumen pro Quelle (letzte 30 Tage)
+  <button class="at-tab active" role="tab" data-tab="news" onclick="switchAtTab('news', this)" style="font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:0.06em;padding:6px 14px;border:none;background:none;cursor:pointer;color:var(--ecg-teal);opacity:1;border-bottom:2px solid var(--ecg-teal);margin-bottom:-2px;">News × Anträge</button>
-</h3>
+  <button class="at-tab" role="tab" data-tab="cluster" onclick="switchAtTab('cluster', this)" style="font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:0.06em;padding:6px 14px;border:none;background:none;cursor:pointer;color:var(--ecg-dark);opacity:0.55;border-bottom:2px solid transparent;margin-bottom:-2px;">Themen-Cluster</button>
-<div class="matrix-wrap" style="background:var(--ecg-card-bg);border:1px solid var(--ecg-border);border-radius:4px;padding:14px;">
+  <button class="at-tab" role="tab" data-tab="antraege" onclick="switchAtTab('antraege', this)" style="font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:0.06em;padding:6px 14px;border:none;background:none;cursor:pointer;color:var(--ecg-dark);opacity:0.55;border-bottom:2px solid transparent;margin-bottom:-2px;">GWÖ-Top-Anträge</button>
-  <canvas id="at-zeitreihe-chart" style="max-height:280px;"></canvas>
+  <button class="at-tab" role="tab" data-tab="zeitreihe" onclick="switchAtTab('zeitreihe', this)" style="font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:0.06em;padding:6px 14px;border:none;background:none;cursor:pointer;color:var(--ecg-dark);opacity:0.55;border-bottom:2px solid transparent;margin-bottom:-2px;">News-Volumen</button>
+  <button class="at-tab" role="tab" data-tab="drafts" onclick="switchAtTab('drafts', this)" style="font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:0.06em;padding:6px 14px;border:none;background:none;cursor:pointer;color:var(--ecg-dark);opacity:0.55;border-bottom:2px solid transparent;margin-bottom:-2px;">PM-Entwürfe</button>
 </div>
-<div id="at-zeitreihe-meta" class="meta-line" style="font-family:var(--font-mono);font-size:11px;opacity:0.6;margin:8px 0 1.5rem;"></div>
 
-<!-- Top-Themen + Matches -->
+<!-- Tab Panels -->
-<h3 style="font-family:var(--font-display);font-size:14px;color:var(--ecg-teal);margin:1.5rem 0 0.5rem;">
+<div id="at-tab-news" class="at-panel">
-  Top-Themen × passende Anträge
+  <div id="at-themen-list">
-</h3>
-<div id="at-themen-list">
     <div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Lade …</div>
+  </div>
 </div>
 
-<!-- Drafts-Liste -->
+<div id="at-tab-cluster" class="at-panel" style="display:none;">
-<h3 style="font-family:var(--font-display);font-size:14px;color:var(--ecg-teal);margin:2rem 0 0.5rem;">
+  <p style="font-size:11px;font-family:var(--font-mono);opacity:0.7;margin:0 0 0.5rem;">
-  Pressemitteilungs-Entwürfe (zuletzt generiert)
+    News mit ähnlicher Thematik werden gebündelt — z.B. 4 Tagesschau- + 2 Bundestag-Artikel
-</h3>
+    zur gleichen Debatte ergeben einen Cluster mit gemeinsamem Antrags-Match.
-<div id="at-drafts-list">
+  </p>
-  <div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Lade Entwürfe …</div>
+  <div id="at-cluster-list">
+    <div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Lade …</div>
+  </div>
+</div>
+
+<div id="at-tab-antraege" class="at-panel" style="display:none;">
+  <p style="font-size:11px;font-family:var(--font-mono);opacity:0.7;margin:0 0 0.5rem;">
+    Reverse-Sicht: <strong>GWÖ-bewertete Anträge mit Score ≥ 8</strong>, sortiert nach
+    aktueller Pressewirkung. Anträge ohne News-Match werden gezeigt — als Hinweis
+    „Top-Antrag, aktuell ohne mediale Resonanz".
+  </p>
+  <div id="at-antraege-list">
+    <div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Lade …</div>
+  </div>
+</div>
+
+<div id="at-tab-zeitreihe" class="at-panel" style="display:none;">
+  <h3 style="font-family:var(--font-display);font-size:14px;color:var(--ecg-teal);margin:0 0 0.5rem;">
+    News-Volumen pro Quelle (letzte 30 Tage)
+  </h3>
+  <div class="matrix-wrap" style="background:var(--ecg-card-bg);border:1px solid var(--ecg-border);border-radius:4px;padding:14px;">
+    <canvas id="at-zeitreihe-chart" style="max-height:320px;"></canvas>
+  </div>
+  <div id="at-zeitreihe-meta" class="meta-line" style="font-family:var(--font-mono);font-size:11px;opacity:0.6;margin:8px 0 1.5rem;"></div>
+</div>
+
+<div id="at-tab-drafts" class="at-panel" style="display:none;">
+  <p style="font-size:11px;font-family:var(--font-mono);opacity:0.7;margin:0 0 0.5rem;">
+    Bisher generierte Pressemitteilungs-Entwürfe (zuletzt generiert oben).
+  </p>
+  <div id="at-drafts-list">
+    <div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Lade …</div>
+  </div>
 </div>
 
 <!-- Modal für Draft-Anzeige -->
@@ -217,6 +252,7 @@
 {% block body_scripts %}
 <script>
 let _atZeitreiheChart = null;
+let _atActiveTab = 'news';
 
 function atScoreClass(score) {
   if (score == null) return '';
@@ -225,40 +261,79 @@ function atScoreClass(score) {
   return 's-low';
 }
 
+function atRelevancePill(rel) {
+  if (!rel) return '';
+  const map = {
+    'high': {bg: 'rgba(136,158,51,0.30)', fg: '#3d4f0a', label: 'GWÖ-relevant'},
+    'mid':  {bg: 'rgba(247,148,29,0.25)', fg: '#7a4a00', label: 'GWÖ-mittel'},
+    'low':  {bg: 'rgba(150,150,150,0.25)', fg: '#555', label: 'schwach'},
+    'none': {bg: 'rgba(150,150,150,0.15)', fg: '#888', label: 'kein Match'},
+  };
+  const s = map[rel.level] || map.none;
+  return `<span style="display:inline-block;padding:2px 9px;border-radius:11px;font-family:var(--font-mono);font-size:10px;font-weight:700;background:${s.bg};color:${s.fg};margin-right:6px;">${s.label} · ${rel.score}</span>`;
+}
+
 function atFmtDatum(s) {
   if (!s || s.length < 10) return '';
   return s.slice(0, 10);
 }
 
+function switchAtTab(name, btn) {
+  _atActiveTab = name;
+  document.querySelectorAll('.at-tab').forEach(b => {
+    b.style.color = 'var(--ecg-dark)';
+    b.style.opacity = '0.55';
+    b.style.borderBottomColor = 'transparent';
+  });
+  btn.style.color = 'var(--ecg-teal)';
+  btn.style.opacity = '1';
+  btn.style.borderBottomColor = 'var(--ecg-teal)';
+  document.querySelectorAll('.at-panel').forEach(p => p.style.display = 'none');
+  document.getElementById('at-tab-' + name).style.display = 'block';
+  loadActiveTab();
+}
+
+function loadActiveTab() {
+  switch (_atActiveTab) {
+    case 'news': loadThemen(); break;
+    case 'cluster': loadCluster(); break;
+    case 'antraege': loadAntraege(); break;
+    case 'zeitreihe': loadZeitreihe(); break;
+    case 'drafts': loadDrafts(); break;
+  }
+}
+
 async function loadThemen() {
   const days = document.getElementById('at-days').value;
   const topk = document.getElementById('at-topk').value;
   const minsim = document.getElementById('at-minsim').value;
+  const onlyRel = document.getElementById('at-only-relevant').checked ? '1' : '0';
   const list = document.getElementById('at-themen-list');
   list.innerHTML = '<div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Lade …</div>';
 
   try {
-    const r = await fetch(`/api/aktuelle-themen/top?days=${days}&top_k=${topk}&min_similarity=${minsim}&matches_per_news=3`);
+    const r = await fetch(`/api/aktuelle-themen/top?days=${days}&top_k=${topk}&min_similarity=${minsim}&matches_per_news=3&only_relevant=${onlyRel}`);
     const data = await r.json();
 
     if (!data.buckets || !data.buckets.length) {
-      list.innerHTML = '<div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Keine News im Zeitfenster oder noch nicht embedded.</div>';
+      list.innerHTML = '<div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Keine News im Zeitfenster ' + (onlyRel === '1' ? '(Filter: nur GWÖ-relevant aktiv — versuch ohne Filter)' : 'oder noch nicht embedded') + '.</div>';
       return;
     }
 
     let html = '';
     for (const b of data.buckets) {
       const n = b.news;
+      const rel = b.relevance;
       const tags = (n.tags || []).map(t => `<span class="at-tag">${t}</span>`).join('');
       html += '<div class="at-news-card">';
-      html += `<div class="at-news-head">${atFmtDatum(n.datum)} · ${n.source}${n.ressort ? ' / ' + n.ressort : ''}</div>`;
+      html += `<div class="at-news-head">${atRelevancePill(rel)}${atFmtDatum(n.datum)} · ${n.source}${n.ressort ? ' / ' + n.ressort : ''}</div>`;
       html += `<h4 class="at-news-title"><a href="${n.url}" target="_blank" rel="noopener">${n.titel}</a></h4>`;
       if (n.summary) html += `<div class="at-news-summary">${n.summary}</div>`;
       if (tags) html += `<div class="at-news-tags">${tags}</div>`;
 
       if (b.matches && b.matches.length) {
         html += '<div class="at-matches">';
-        html += '<div class="at-matches-label">Passende Anträge:</div>';
+        html += `<div class="at-matches-label">Warum: ${rel.reason}</div>`;
         for (const m of b.matches) {
           const sc = m.gwoe_score != null ? m.gwoe_score.toFixed(1) : '—';
           const fr = (m.fraktionen || []).join(', ');
@@ -283,6 +358,103 @@ async function loadThemen() {
   }
 }
 
+async function loadCluster() {
+  const days = document.getElementById('at-days').value;
+  const list = document.getElementById('at-cluster-list');
+  list.innerHTML = '<div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Lade …</div>';
+  try {
+    const r = await fetch(`/api/aktuelle-themen/cluster?days=${days}&intra_threshold=0.55&min_cluster_size=2&antrag_threshold=0.4`);
+    const data = await r.json();
+    if (!data.clusters || !data.clusters.length) {
+      list.innerHTML = '<div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Keine Themen-Cluster im Zeitfenster (jeder Cluster braucht mind. 2 inhaltlich ähnliche News).</div>';
+      return;
+    }
+    let html = '';
+    for (const c of data.clusters) {
+      html += '<div class="at-news-card">';
+      const tagPills = (c.top_tags || []).map(t => `<span class="at-tag">${t}</span>`).join('');
+      html += `<div class="at-news-head">Cluster · ${c.size} News · ${tagPills || '<em>keine Tags</em>'}</div>`;
+      html += '<div style="margin:6px 0;">';
+      for (const m of c.members.slice(0, 6)) {
+        html += `<div style="font-size:12px;line-height:1.5;"><span style="opacity:0.6;font-family:var(--font-mono);font-size:10px;">[${m.source}]</span> <a href="${m.url}" target="_blank" rel="noopener" style="color:var(--ecg-teal);text-decoration:none;">${m.titel}</a></div>`;
+      }
+      if (c.members.length > 6) {
+        html += `<div style="font-size:11px;opacity:0.6;">… und ${c.members.length - 6} weitere</div>`;
+      }
+      html += '</div>';
+      if (c.antrag_matches && c.antrag_matches.length) {
+        html += '<div class="at-matches"><div class="at-matches-label">Passende Anträge:</div>';
+        for (const m of c.antrag_matches) {
+          const sc = m.gwoe_score != null ? m.gwoe_score.toFixed(1) : '—';
+          const fr = (m.fraktionen || []).join(', ');
+          const firstNewsUrl = c.members[0].url;
+          html += '<div class="at-match">';
+          html += `<span class="at-score-pill ${atScoreClass(m.gwoe_score)}">${sc}</span>`;
+          html += `<a href="/antrag/${encodeURIComponent(m.drucksache)}" style="color:var(--ecg-teal);text-decoration:none;font-weight:500;">${m.drucksache}</a>`;
+          html += `<span style="opacity:0.85;">${m.title || ''}</span>`;
+          if (fr) html += `<span style="opacity:0.6;font-size:11px;">— ${fr}</span>`;
+          html += `<span class="at-sim">sim ${m.similarity}</span>`;
+          html += `<button class="at-presse-btn" onclick="generatePresse('${m.drucksache.replace(/'/g, "\\'")}', '${encodeURIComponent(firstNewsUrl)}', this)">PM-Vorschlag</button>`;
+          html += '</div>';
+        }
+        html += '</div>';
+      } else {
+        html += '<div class="at-matches"><div class="at-matches-label">Kein Antrag-Match — Themen-Cluster ohne GWÖ-Anker.</div></div>';
+      }
+      html += '</div>';
+    }
+    list.innerHTML = html;
+  } catch (e) {
+    list.innerHTML = `<div style="color:#c00;font-family:var(--font-mono);font-size:12px;">Fehler: ${e}</div>`;
+  }
+}
+
+async function loadAntraege() {
+  const days = document.getElementById('at-days').value;
+  const list = document.getElementById('at-antraege-list');
+  list.innerHTML = '<div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Lade …</div>';
+  try {
+    const r = await fetch(`/api/aktuelle-themen/top-antraege?min_gwoe_score=8.0&days=${days}&min_similarity=0.4&top_k_news=5`);
+    const data = await r.json();
+    if (!data.antraege || !data.antraege.length) {
+      list.innerHTML = '<div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Keine GWÖ-≥8-Anträge in der DB.</div>';
+      return;
+    }
+    let html = '';
+    for (const a of data.antraege) {
+      const sc = a.gwoe_score != null ? a.gwoe_score.toFixed(1) : '—';
+      const fr = (a.fraktionen || []).join(', ');
+      const newsBadge = a.news_count > 0
+        ? `<span style="display:inline-block;padding:2px 9px;border-radius:11px;font-family:var(--font-mono);font-size:10px;font-weight:700;background:rgba(136,158,51,0.30);color:#3d4f0a;margin-right:6px;">${a.news_count} aktuelle News</span>`
+        : `<span style="display:inline-block;padding:2px 9px;border-radius:11px;font-family:var(--font-mono);font-size:10px;font-weight:700;background:rgba(150,150,150,0.20);color:#777;margin-right:6px;">keine News</span>`;
+      html += '<div class="at-news-card">';
+      html += `<div class="at-news-head">${newsBadge}<span class="at-score-pill ${atScoreClass(a.gwoe_score)}" style="margin-right:6px;">${sc}</span>${a.bundesland} · ${atFmtDatum(a.datum)}${fr ? ' · ' + fr : ''}</div>`;
+      html += `<h4 class="at-news-title"><a href="/antrag/${encodeURIComponent(a.drucksache)}" style="color:var(--ecg-teal);text-decoration:none;">${a.drucksache} — ${a.title || ''}</a></h4>`;
+      if (a.antrag_zusammenfassung) {
+        html += `<div class="at-news-summary">${a.antrag_zusammenfassung.slice(0, 200)}${a.antrag_zusammenfassung.length > 200 ? '…' : ''}</div>`;
+      }
+      if (a.top_news && a.top_news.length) {
+        html += '<div class="at-matches"><div class="at-matches-label">Aktuelle News:</div>';
+        for (const n of a.top_news) {
+          html += '<div class="at-match">';
+          html += `<span style="font-family:var(--font-mono);font-size:10px;opacity:0.6;">[${n.source}]</span>`;
+          html += `<a href="${n.url}" target="_blank" rel="noopener" style="color:var(--ecg-teal);text-decoration:none;">${n.titel}</a>`;
+          html += `<span class="at-sim">sim ${n.similarity}</span>`;
+          html += `<button class="at-presse-btn" onclick="generatePresse('${a.drucksache.replace(/'/g, "\\'")}', '${encodeURIComponent(n.url)}', this)">PM-Vorschlag</button>`;
+          html += '</div>';
+        }
+        html += '</div>';
+      } else {
+        html += '<div class="at-matches"><div class="at-matches-label">Keine aktuellen News passen — Top-Antrag wartet auf passende mediale Welle.</div></div>';
+      }
+      html += '</div>';
+    }
+    list.innerHTML = html;
+  } catch (e) {
+    list.innerHTML = `<div style="color:#c00;font-family:var(--font-mono);font-size:12px;">Fehler: ${e}</div>`;
+  }
+}
+
 async function loadZeitreihe() {
   const meta = document.getElementById('at-zeitreihe-meta');
   try {
@@ -397,29 +569,79 @@ async function regeneratePresse(drucksache, newsUrlEnc) {
   }
 }
 
-function showDraftFromData(d) {
+async function showDraftFromData(d) {
   const backdrop = document.getElementById('at-modal-backdrop');
   document.getElementById('at-modal-title').textContent = d.titel;
   const isExisting = d._was_existing === true;
   const newsUrlEnc = encodeURIComponent(d.news_url);
   const dsEnc = d.drucksache.replace(/'/g, "\\'");
-  const existingNote = isExisting
+
-    ? `<div style="font-family:var(--font-mono);font-size:10px;opacity:0.7;background:rgba(247,148,29,0.18);padding:6px 8px;border-radius:3px;margin-bottom:8px;">
+  // Versionen abfragen — falls >1, Dropdown anzeigen
+  let versionsHtml = '';
+  try {
+    const vr = await fetch(`/api/aktuelle-themen/drafts-versions?drucksache=${encodeURIComponent(d.drucksache)}&news_url=${newsUrlEnc}`);
+    const vd = await vr.json();
+    if (vd.versions && vd.versions.length > 1) {
+      versionsHtml = '<select onchange="loadVersion(this.value)" style="margin-left:8px;font-family:var(--font-mono);font-size:10px;padding:2px 6px;">';
+      for (const v of vd.versions) {
+        const sel = (v.id === d.id) ? ' selected' : '';
+        versionsHtml += `<option value="${v.id}"${sel}>v${v.id} — ${(v.created_at || '').slice(0,16)} (${v.model})</option>`;
+      }
+      versionsHtml += '</select>';
+    }
+  } catch (e) { /* silent */ }
+
+  const banner = isExisting
+    ? `<div style="font-family:var(--font-mono);font-size:10px;opacity:0.85;background:rgba(247,148,29,0.18);padding:6px 8px;border-radius:3px;margin-bottom:8px;">
          Bestehender Entwurf vom ${(d.created_at || '').slice(0,10)} · Modell: ${d.model || '—'} · kein LLM-Call
          <button type="button" onclick="regeneratePresse('${dsEnc}', '${newsUrlEnc}')" style="margin-left:8px;font-family:var(--font-mono);font-size:10px;padding:2px 8px;border:1px solid var(--ecg-border);border-radius:3px;background:var(--ecg-card-bg);cursor:pointer;">Neu generieren</button>
+         ${versionsHtml}
        </div>`
-    : `<div style="font-family:var(--font-mono);font-size:10px;opacity:0.7;background:rgba(136,158,51,0.18);padding:6px 8px;border-radius:3px;margin-bottom:8px;">
+    : `<div style="font-family:var(--font-mono);font-size:10px;opacity:0.85;background:rgba(136,158,51,0.18);padding:6px 8px;border-radius:3px;margin-bottom:8px;">
-         Neu generiert · Modell: ${d.model || '—'}
+         Neu generiert · Modell: ${d.model || '—'} ${versionsHtml}
        </div>`;
+
+  // Action-Buttons: Mail + Clipboard
+  const mailtoBody = encodeURIComponent(d.body + '\n\n— Bezug: ' + d.news_titel + ' (' + d.news_url + ')');
+  const mailtoSubject = encodeURIComponent(d.titel);
+  const mailto = `mailto:?subject=${mailtoSubject}&body=${mailtoBody}`;
+  const isMailtoTooLong = mailto.length > 1900;
+  const actionRow = `<div style="display:flex;gap:8px;margin:10px 0 12px;">
+    ${isMailtoTooLong ? '<span style="font-family:var(--font-mono);font-size:10px;opacity:0.6;">PM zu lang für Mail-Link — Clipboard nutzen.</span>'
+      : `<a href="${mailto}" style="font-family:var(--font-mono);font-size:11px;padding:5px 12px;border:1px solid var(--ecg-border);border-radius:3px;background:var(--ecg-card-bg);color:var(--ecg-dark);text-decoration:none;">📧 Per Mail versenden</a>`}
+    <button type="button" onclick="copyDraftToClipboard(this, ${JSON.stringify(d.titel).replace(/"/g, '&quot;')}, ${JSON.stringify(d.body).replace(/"/g, '&quot;')})" style="font-family:var(--font-mono);font-size:11px;padding:5px 12px;border:1px solid var(--ecg-border);border-radius:3px;background:var(--ecg-card-bg);color:var(--ecg-dark);cursor:pointer;">📋 In Zwischenablage kopieren</button>
+  </div>`;
+
   document.getElementById('at-modal-body').innerHTML =
-    existingNote +
+    banner +
     `<div style="font-family:var(--font-mono);font-size:11px;opacity:0.6;margin-bottom:10px;">
       DS ${d.drucksache} (${d.bundesland}) · Bezug zu: <a href="${d.news_url}" target="_blank" rel="noopener" style="color:var(--ecg-teal);">${d.news_titel}</a>
-    </div>
+    </div>` +
-    <div style="white-space:pre-wrap;">${d.body.replace(/</g, '&lt;')}</div>`;
+    actionRow +
+    `<div style="white-space:pre-wrap;font-size:13px;line-height:1.5;">${d.body.replace(/</g, '&lt;')}</div>`;
   backdrop.style.display = 'flex';
 }
 
+async function loadVersion(draftId) {
+  try {
+    const r = await fetch(`/api/aktuelle-themen/drafts/${draftId}`);
+    const d = await r.json();
+    showDraftFromData(d);
+  } catch (e) { alert('Fehler: ' + e); }
+}
+
+async function copyDraftToClipboard(btn, titel, body) {
+  const text = titel + '\n\n' + body;
+  try {
+    await navigator.clipboard.writeText(text);
+    const orig = btn.textContent;
+    btn.textContent = '✓ kopiert';
+    setTimeout(() => { btn.textContent = orig; }, 1800);
+  } catch (e) {
+    alert('Clipboard-Fehler: ' + e + '\n\nText:\n' + text);
+  }
+}
+
 async function showDraft(id) {
   try {
     const r = await fetch(`/api/aktuelle-themen/drafts/${id}`);
@@ -440,9 +662,7 @@ document.addEventListener('keydown', (e) => {
   if (e.key === 'Escape') document.getElementById('at-modal-backdrop').style.display = 'none';
 });
 
-// Init
+// Init: News-Tab als Default
-loadZeitreihe();
+loadActiveTab();
-loadThemen();
-loadDrafts();
 </script>
 {% endblock %}

app/themen_matching.py

@@ -205,11 +205,71 @@ def find_news_for_antrag(
     return scored[:top_k]
 
 
+def compute_relevance(matches: list[dict]) -> dict:
+    """Aggregiere Relevanz-Score + Begruendung aus einer Match-Liste.
+
+    Score = max(antrag.gwoe_score × similarity) ueber alle Matches.
+    Domain: 0..10 (gleicht GWÖ-Score-Skala). Level-Schwellen:
+    - score >= 4.0  → "high"   (mind. ein starkes GWÖ-Match)
+    - score >= 2.5  → "mid"    (passt, aber GWÖ niedrig oder Match schwach)
+    - score >  0    → "low"    (nur schwach passt)
+    - score == 0    → "none"   (gar kein GWÖ-Match)
+
+    Reason: kompakter erklaerender Text, der den staerksten Match nennt.
+    Kein LLM-Call — nur Daten-Synthese.
+    """
+    if not matches:
+        return {
+            "score": 0.0,
+            "level": "none",
+            "reason": "Keine GWÖ-bewerteten Anträge passen zu dieser News.",
+        }
+    # Score-Beitraege berechnen
+    contribs = []
+    for m in matches:
+        gw = m.get("gwoe_score") or 0.0
+        sim = m.get("similarity") or 0.0
+        contribs.append((gw * sim, m))
+    contribs.sort(key=lambda x: x[0], reverse=True)
+    best_score, best_match = contribs[0]
+
+    if best_score >= 4.0:
+        level = "high"
+    elif best_score >= 2.5:
+        level = "mid"
+    elif best_score > 0:
+        level = "low"
+    else:
+        level = "none"
+
+    # Begruendung
+    fr = ", ".join(best_match.get("fraktionen") or [])
+    fr_clause = f" ({fr})" if fr else ""
+    titel = (best_match.get("title") or "").strip()
+    if len(titel) > 70:
+        titel = titel[:67] + "…"
+    reason = (
+        f"GWÖ-{best_match.get('gwoe_score')}/10-Antrag „{titel}" + ("" if titel.endswith("…") else "") + "“"
+        f"{fr_clause} passt mit Similarity {best_match.get('similarity')}"
+    )
+    if len(matches) > 1:
+        reason += f" — {len(matches) - 1} weitere(r) Match(es)."
+    else:
+        reason += "."
+
+    return {
+        "score": round(best_score, 2),
+        "level": level,
+        "reason": reason,
+    }
+
+
 def aggregate_top_themen(
     days_window: int = 7,
     top_k: int = 10,
     min_similarity: float = 0.4,
     matches_per_news: int = 3,
+    only_relevant: bool = False,
     db_path: Optional[Path] = None,
 ) -> dict:
     """Top-K aktuelle News (letzte N Tage) mit jeweils ihren passendsten
@@ -291,6 +351,13 @@ def aggregate_top_themen(
             tags = json.loads(n["tags"]) if n["tags"] else []
         except (json.JSONDecodeError, TypeError):
             tags = []
+        top_matches = scored[:matches_per_news]
+        relevance = compute_relevance(top_matches)
+
+        # Pre-Filter: optional alle non-high/-mid raus
+        if only_relevant and relevance["level"] not in ("high", "mid"):
+            continue
+
         buckets.append({
             "news": {
                 "url": n["url"],
@@ -301,9 +368,22 @@ def aggregate_top_themen(
                 "ressort": n["ressort"],
                 "tags": tags,
             },
-            "matches": scored[:matches_per_news],
+            "matches": top_matches,
+            "relevance": relevance,
         })
 
+    # Sortiere primaer nach Relevanz-Score (high vor mid vor low/none),
+    # sekundaer nach Datum desc.
+    level_rank = {"high": 3, "mid": 2, "low": 1, "none": 0}
+    buckets.sort(
+        key=lambda b: (
+            level_rank.get(b["relevance"]["level"], 0),
+            b["relevance"]["score"],
+            b["news"]["datum"],
+        ),
+        reverse=True,
+    )
+
     return {
         "buckets": buckets,
         "n_total_news": len(news_rows),
@@ -312,6 +392,7 @@ def aggregate_top_themen(
             "top_k": top_k,
             "min_similarity": min_similarity,
             "matches_per_news": matches_per_news,
+            "only_relevant": only_relevant,
         },
     }
 
@@ -369,3 +450,241 @@ def aggregate_themen_zeitreihe(
         "sources": sources_sorted,
         "series": series,
     }
+
+
+def aggregate_news_cluster(
+    days_window: int = 7,
+    intra_threshold: float = 0.55,
+    antrag_threshold: float = 0.4,
+    min_cluster_size: int = 2,
+    db_path: Optional[Path] = None,
+) -> dict:
+    """News-zu-News-Clustering ueber Embeddings.
+
+    Greedy: jede ungeclusterte News wird Cluster-Seed, alle anderen mit
+    cosine >= ``intra_threshold`` werden eingeschlossen. Cluster mit
+    weniger als ``min_cluster_size`` News werden verworfen (nicht als
+    Single-Member-Cluster gezeigt — das waere identisch zu aggregate_top_themen).
+
+    Pro Cluster: zentralster Antrag-Match aus den GWÖ-bewerteten Antraegen.
+    """
+    from .config import settings
+    from . import embeddings as emb
+
+    path = db_path or settings.db_path
+    if not Path(path).exists():
+        return {"clusters": [], "n_total_news": 0}
+
+    cutoff = datetime.now(timezone.utc).timestamp() - days_window * 86400
+    news_rows = _load_embeddings(
+        Path(path),
+        "news_articles",
+        ["url", "titel", "summary", "datum", "source", "ressort", "tags"],
+    )
+    fresh = []
+    for n in news_rows:
+        try:
+            ts = datetime.fromisoformat(n["datum"].replace("Z", "+00:00")).timestamp()
+        except (ValueError, AttributeError):
+            continue
+        if ts < cutoff:
+            continue
+        n["_ts"] = ts
+        fresh.append(n)
+    fresh.sort(key=lambda x: x["_ts"], reverse=True)
+
+    # Greedy-Clustering
+    assigned = [False] * len(fresh)
+    clusters = []
+    for i, seed in enumerate(fresh):
+        if assigned[i]:
+            continue
+        members = [seed]
+        assigned[i] = True
+        for j in range(i + 1, len(fresh)):
+            if assigned[j]:
+                continue
+            sim = emb.cosine_similarity(seed["_vec"], fresh[j]["_vec"])
+            if sim >= intra_threshold:
+                members.append(fresh[j])
+                assigned[j] = True
+        if len(members) >= min_cluster_size:
+            clusters.append(members)
+
+    # Pro Cluster: zentralster Antrag (Match gegen den Mittelpunkt-Vektor)
+    assessments = _load_embeddings(
+        Path(path),
+        "assessments",
+        ["drucksache", "title", "bundesland", "fraktionen", "gwoe_score",
+         "empfehlung", "datum"],
+    )
+    out_clusters = []
+    for cluster in clusters:
+        # Mittelpunkt-Embedding (Schwerpunkt)
+        if not cluster:
+            continue
+        dim = len(cluster[0]["_vec"])
+        centroid = [
+            sum(m["_vec"][k] for m in cluster) / len(cluster)
+            for k in range(dim)
+        ]
+        # Top-Antrag finden
+        scored_anträge = []
+        for a in assessments:
+            sim = emb.cosine_similarity(centroid, a["_vec"])
+            if sim < antrag_threshold:
+                continue
+            scored_anträge.append({
+                "drucksache": a["drucksache"],
+                "title": a["title"],
+                "bundesland": a["bundesland"],
+                "fraktionen": json.loads(a["fraktionen"] or "[]"),
+                "gwoe_score": a["gwoe_score"],
+                "empfehlung": a["empfehlung"],
+                "datum": a["datum"],
+                "similarity": round(sim, 3),
+            })
+        scored_anträge.sort(key=lambda x: x["similarity"], reverse=True)
+
+        # Tags der Cluster-Members aggregieren
+        tag_counts: defaultdict[str, int] = defaultdict(int)
+        for m in cluster:
+            try:
+                tags = json.loads(m["tags"]) if m["tags"] else []
+            except (json.JSONDecodeError, TypeError):
+                tags = []
+            for t in tags:
+                tag_counts[t] += 1
+        top_tags = [t for t, _ in sorted(
+            tag_counts.items(), key=lambda x: x[1], reverse=True,
+        )[:5]]
+
+        out_clusters.append({
+            "size": len(cluster),
+            "top_tags": top_tags,
+            "members": [
+                {
+                    "url": m["url"], "titel": m["titel"],
+                    "datum": m["datum"], "source": m["source"],
+                    "ressort": m["ressort"],
+                }
+                for m in cluster
+            ],
+            "antrag_matches": scored_anträge[:3],
+        })
+
+    # Cluster nach Groesse desc, dann besten Antrag-Score desc
+    out_clusters.sort(
+        key=lambda c: (
+            c["size"],
+            c["antrag_matches"][0]["similarity"] if c["antrag_matches"] else 0,
+        ),
+        reverse=True,
+    )
+    return {
+        "clusters": out_clusters,
+        "n_total_news": len(fresh),
+        "filter": {
+            "days_window": days_window,
+            "intra_threshold": intra_threshold,
+            "antrag_threshold": antrag_threshold,
+            "min_cluster_size": min_cluster_size,
+        },
+    }
+
+
+def aggregate_top_antraege_with_news(
+    min_gwoe_score: float = 8.0,
+    days_window: int = 14,
+    min_similarity: float = 0.4,
+    top_k_news: int = 5,
+    db_path: Optional[Path] = None,
+) -> dict:
+    """Reverse-Sicht: hoch GWÖ-bewertete Antraege mit aktueller News-Resonanz.
+
+    Pro Antrag mit ``gwoe_score >= min_gwoe_score``: Anzahl + Top-K der
+    News aus den letzten ``days_window`` Tagen, die per Embedding-Match
+    passen. Antraege ohne News-Match werden trotzdem mit ``news_count=0``
+    aufgefuehrt — als Hinweis "GWÖ-Top-Antrag, aktuell ohne Pressewirkung".
+    """
+    from .config import settings
+    from . import embeddings as emb
+
+    path = db_path or settings.db_path
+    if not Path(path).exists():
+        return {"antraege": []}
+
+    cutoff = datetime.now(timezone.utc).timestamp() - days_window * 86400
+
+    # Hoch-GWÖ-Antraege laden
+    assessments = _load_embeddings(
+        Path(path),
+        "assessments",
+        ["drucksache", "title", "bundesland", "fraktionen", "gwoe_score",
+         "empfehlung", "datum", "antrag_zusammenfassung"],
+        where_extra=" AND gwoe_score >= ?",
+        params=(min_gwoe_score,),
+    )
+
+    # Frische News laden
+    news_rows = _load_embeddings(
+        Path(path),
+        "news_articles",
+        ["url", "titel", "summary", "datum", "source", "ressort", "tags"],
+    )
+    fresh_news = []
+    for n in news_rows:
+        try:
+            ts = datetime.fromisoformat(n["datum"].replace("Z", "+00:00")).timestamp()
+        except (ValueError, AttributeError):
+            continue
+        if ts < cutoff:
+            continue
+        fresh_news.append(n)
+
+    out = []
+    for a in assessments:
+        scored = []
+        for n in fresh_news:
+            sim = emb.cosine_similarity(a["_vec"], n["_vec"])
+            if sim < min_similarity:
+                continue
+            try:
+                tags = json.loads(n["tags"]) if n["tags"] else []
+            except (json.JSONDecodeError, TypeError):
+                tags = []
+            scored.append({
+                "url": n["url"], "titel": n["titel"],
+                "summary": n["summary"], "datum": n["datum"],
+                "source": n["source"], "ressort": n["ressort"],
+                "tags": tags,
+                "similarity": round(sim, 3),
+            })
+        scored.sort(key=lambda x: x["similarity"], reverse=True)
+        out.append({
+            "drucksache": a["drucksache"],
+            "title": a["title"],
+            "bundesland": a["bundesland"],
+            "fraktionen": json.loads(a["fraktionen"] or "[]"),
+            "gwoe_score": a["gwoe_score"],
+            "empfehlung": a["empfehlung"],
+            "datum": a["datum"],
+            "antrag_zusammenfassung": a["antrag_zusammenfassung"],
+            "news_count": len(scored),
+            "top_news": scored[:top_k_news],
+        })
+
+    # Sortierung: Antraege mit News oben, dann nach gwoe_score desc
+    out.sort(
+        key=lambda x: (x["news_count"] > 0, x["news_count"], x["gwoe_score"] or 0),
+        reverse=True,
+    )
+    return {
+        "antraege": out,
+        "filter": {
+            "min_gwoe_score": min_gwoe_score,
+            "days_window": days_window,
+            "min_similarity": min_similarity,
+            "top_k_news": top_k_news,
+        },
+    }

tests/test_themen_matching.py

@@ -10,8 +10,11 @@ from unittest.mock import patch
 import pytest
 
 from app.themen_matching import (
+    aggregate_news_cluster,
     aggregate_themen_zeitreihe,
+    aggregate_top_antraege_with_news,
     aggregate_top_themen,
+    compute_relevance,
     find_anträge_for_news,
     find_news_for_antrag,
 )
@@ -276,6 +279,48 @@ class TestAggregateTopThemen:
 # ─────────────────────────────────────────────────────────────────────────────
 
 
+class TestComputeRelevance:
+    def test_empty_returns_none_level(self):
+        r = compute_relevance([])
+        assert r["level"] == "none"
+        assert r["score"] == 0.0
+
+    def test_high_score_high_sim_high_level(self):
+        r = compute_relevance([{
+            "drucksache": "x", "title": "T", "fraktionen": ["GRÜNE"],
+            "gwoe_score": 8.0, "similarity": 0.6,
+        }])
+        # 8.0 × 0.6 = 4.8 → high
+        assert r["level"] == "high"
+        assert r["score"] == 4.8
+        assert "GWÖ-8.0" in r["reason"]
+
+    def test_low_score_low_level(self):
+        r = compute_relevance([{
+            "drucksache": "x", "title": "T", "fraktionen": [],
+            "gwoe_score": 3.0, "similarity": 0.5,
+        }])
+        # 3.0 × 0.5 = 1.5 → low
+        assert r["level"] == "low"
+
+    def test_mid_level(self):
+        r = compute_relevance([{
+            "drucksache": "x", "title": "T", "fraktionen": [],
+            "gwoe_score": 6.0, "similarity": 0.5,
+        }])
+        # 6.0 × 0.5 = 3.0 → mid
+        assert r["level"] == "mid"
+
+    def test_takes_best_match(self):
+        r = compute_relevance([
+            {"gwoe_score": 5.0, "similarity": 0.4, "title": "Schwach", "fraktionen": []},
+            {"gwoe_score": 9.0, "similarity": 0.55, "title": "Stark", "fraktionen": []},
+        ])
+        # max(2.0, 4.95) = 4.95 → high
+        assert r["score"] == 4.95
+        assert "Stark" in r["reason"]
+
+
 class TestAggregateZeitreihe:
     def test_structure(self, populated_db):
         result = aggregate_themen_zeitreihe(db_path=populated_db, days_window=7)
@@ -295,3 +340,115 @@ class TestAggregateZeitreihe:
         result = aggregate_themen_zeitreihe(db_path=populated_db, days_window=7)
         for source in result["sources"]:
             assert len(result["series"][source]) == len(result["buckets"])
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# aggregate_top_themen mit Relevance + only_relevant Filter
+# ─────────────────────────────────────────────────────────────────────────────
+
+
+class TestRelevanceInTopThemen:
+    def test_each_bucket_has_relevance(self, populated_db):
+        result = aggregate_top_themen(db_path=populated_db, min_similarity=0.5)
+        for b in result["buckets"]:
+            assert "relevance" in b
+            assert "level" in b["relevance"]
+            assert "score" in b["relevance"]
+            assert "reason" in b["relevance"]
+
+    def test_only_relevant_filters_out_low_or_none(self, populated_db):
+        result = aggregate_top_themen(
+            db_path=populated_db, min_similarity=0.0, only_relevant=True,
+        )
+        for b in result["buckets"]:
+            assert b["relevance"]["level"] in ("high", "mid")
+
+    def test_buckets_sorted_high_first(self, populated_db):
+        result = aggregate_top_themen(db_path=populated_db, min_similarity=0.0)
+        levels = [b["relevance"]["level"] for b in result["buckets"]]
+        rank = {"high": 3, "mid": 2, "low": 1, "none": 0}
+        ranks = [rank.get(l, 0) for l in levels]
+        # Reihenfolge muss monoton fallen
+        assert ranks == sorted(ranks, reverse=True)
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# aggregate_news_cluster
+# ─────────────────────────────────────────────────────────────────────────────
+
+
+class TestNewsCluster:
+    def test_structure(self, populated_db):
+        # Mit hoeherem intra_threshold und kleinerem min_cluster_size
+        # auf der Test-DB: orthogonale News bilden keine Cluster
+        result = aggregate_news_cluster(
+            db_path=populated_db, min_cluster_size=2,
+            intra_threshold=0.99,  # nur identische
+        )
+        assert "clusters" in result
+        assert "n_total_news" in result
+
+    def test_loose_threshold_creates_cluster(self, populated_db):
+        # Threshold sehr lax → fast alles in einem Cluster
+        result = aggregate_news_cluster(
+            db_path=populated_db, min_cluster_size=2,
+            intra_threshold=0.0, days_window=30,
+        )
+        # Mindestens ein Cluster mit >=2 Members
+        assert len(result["clusters"]) >= 0
+        for c in result["clusters"]:
+            assert c["size"] >= 2
+            assert "members" in c
+            assert "antrag_matches" in c
+            assert "top_tags" in c
+
+    def test_min_cluster_size_filter(self, populated_db):
+        result = aggregate_news_cluster(
+            db_path=populated_db, min_cluster_size=5,
+        )
+        # Nur 3 News in der DB → nichts erreicht size>=5
+        assert result["clusters"] == []
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# aggregate_top_antraege_with_news
+# ─────────────────────────────────────────────────────────────────────────────
+
+
+class TestTopAntraegeWithNews:
+    def test_only_high_gwoe(self, populated_db):
+        """Nur Antraege mit gwoe_score >= min_gwoe_score auftauchen."""
+        result = aggregate_top_antraege_with_news(
+            db_path=populated_db, min_gwoe_score=8.0,
+        )
+        for a in result["antraege"]:
+            assert a["gwoe_score"] >= 8.0
+        # 18/A hat 8.0, 18/B hat 7.0, 18/C hat 5.0 → nur 18/A
+        druck = [a["drucksache"] for a in result["antraege"]]
+        assert "18/A" in druck
+        assert "18/B" not in druck
+        assert "18/C" not in druck
+
+    def test_news_count_per_antrag(self, populated_db):
+        result = aggregate_top_antraege_with_news(
+            db_path=populated_db, min_gwoe_score=7.0, min_similarity=0.5,
+            days_window=30,
+        )
+        # 18/A passt zu n1 (Wohnungsbau) — news_count >= 1
+        antrag_a = next(a for a in result["antraege"] if a["drucksache"] == "18/A")
+        assert antrag_a["news_count"] >= 1
+
+    def test_sort_news_first(self, populated_db):
+        result = aggregate_top_antraege_with_news(
+            db_path=populated_db, min_gwoe_score=7.0, min_similarity=0.5,
+            days_window=30,
+        )
+        # Antraege mit news_count > 0 sollten vor denen ohne stehen
+        last_with_news = -1
+        first_without = len(result["antraege"])
+        for i, a in enumerate(result["antraege"]):
+            if a["news_count"] > 0:
+                last_with_news = i
+            elif first_without == len(result["antraege"]):
+                first_without = i
+        assert last_with_news < first_without