Analysepipeline: Visualisierung der Refresh-Schritte

Neuer Tab "Analysepipeline" zwischen Faktencheck und Quellenuebersicht.
Zeigt 9 Verarbeitungsschritte als n8n-artige Blockkette: Quellen sichten,
Nachrichten sammeln, Doppeltes filtern, Relevanz bewerten, Orte erkennen,
Lagebild verfassen, Fakten pruefen, Qualitaetscheck, Benachrichtigen.

- Backend: refresh_pipeline_steps-Tabelle persistiert pro Refresh+Pass die
  Status- und Zahlen-Werte. pipeline_tracker.py kapselt Start/Done/Skip/Error
  inkl. WebSocket-Broadcast (Event-Typ pipeline_step). 9 Hooks im Orchestrator
  speisen die Anzeige.
- API: GET /api/incidents/{id}/pipeline liefert Definition + letzten Stand
  (Zahlen aus letztem Refresh, Multi-Pass-Konsolidierung).
- Frontend: pipeline.js rendert Vollbild-Blockkette mit pulsierendem Glow am
  aktiven Block, animierten Pfeilen bei Datenfluss, Haekchen am fertigen Block.
  Hover-Tooltip mit Erklaerung in Nutzersprache, Klick oeffnet Detail-Popup.
  Bei Research-Lagen leuchtet ein Schleifen-Pfeil pro Mehrfach-Durchlauf auf.
  Mini-Variante (nur Icons) im Refresh-Progress-Popup.
- CSS: Light/Dark-Theme-fest, dezenter Circuit-Hintergrund (5% Opacity),
  Mobile-vertikale Stapelung unter 900px, prefers-reduced-motion respektiert.
- Uebersprungene Schritte (z.B. Geoparsing ohne neue Artikel) werden
  ausgeblendet, brandneue Lagen ohne Refresh zeigen Hinweis.

Tooltips bewusst in normaler Sprache ohne Internas (keine Modellnamen,
keine Toolnamen, keine Phasen-Labels).

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

src/routers/incidents.py

@@ -613,6 +613,98 @@ async def get_factchecks(
     return [dict(row) for row in rows]
 
 
+@router.get("/{incident_id}/pipeline")
+async def get_pipeline(
+    incident_id: int,
+    current_user: dict = Depends(get_current_user),
+    db: aiosqlite.Connection = Depends(db_dependency),
+):
+    """Analysepipeline-Status der Lage: Definition aller Schritte + Stand des
+    letzten (oder gerade laufenden) Refreshs.
+
+    Antwort:
+        {
+          "is_research": bool,
+          "is_running": bool,
+          "last_refresh": {started_at, completed_at, duration_sec, status, pass_total} | null,
+          "steps_definition": [{key, label, icon, tooltip}, ...],
+          "steps": [{step_key, status, count_value, count_secondary, pass_number}, ...]
+        }
+    """
+    from services.pipeline_tracker import PIPELINE_STEPS
+
+    tenant_id = current_user.get("tenant_id")
+    incident_row = await _check_incident_access(db, incident_id, current_user["id"], tenant_id)
+    is_research = (incident_row["type"] or "adhoc") == "research"
+
+    # Juengsten Refresh-Log waehlen: bevorzugt running, sonst der letzte completed
+    cursor = await db.execute(
+        """SELECT id, started_at, completed_at, status, retry_count
+           FROM refresh_log
+           WHERE incident_id = ? AND status = 'running'
+           ORDER BY started_at DESC LIMIT 1""",
+        (incident_id,),
+    )
+    row = await cursor.fetchone()
+    if not row:
+        cursor = await db.execute(
+            """SELECT id, started_at, completed_at, status, retry_count
+               FROM refresh_log
+               WHERE incident_id = ?
+               ORDER BY started_at DESC LIMIT 1""",
+            (incident_id,),
+        )
+        row = await cursor.fetchone()
+
+    last_refresh = None
+    steps = []
+    is_running = False
+    if row:
+        is_running = row["status"] == "running"
+        # Pipeline-Steps zu diesem Refresh laden
+        sc = await db.execute(
+            """SELECT step_key, pass_number, status, count_value, count_secondary,
+                      started_at, completed_at
+               FROM refresh_pipeline_steps
+               WHERE refresh_log_id = ?
+               ORDER BY pass_number ASC, id ASC""",
+            (row["id"],),
+        )
+        steps = [dict(r) for r in await sc.fetchall()]
+
+        # Pass-Total: bei Research-Lagen mit Multi-Pass-Daten ermitteln
+        max_pass = 1
+        for s in steps:
+            if s["pass_number"] and s["pass_number"] > max_pass:
+                max_pass = s["pass_number"]
+
+        # Dauer berechnen (nur wenn completed)
+        duration_sec = None
+        try:
+            if row["started_at"] and row["completed_at"]:
+                t0 = datetime.strptime(row["started_at"], "%Y-%m-%d %H:%M:%S")
+                t1 = datetime.strptime(row["completed_at"], "%Y-%m-%d %H:%M:%S")
+                duration_sec = max(0, int((t1 - t0).total_seconds()))
+        except Exception:
+            duration_sec = None
+
+        last_refresh = {
+            "started_at": row["started_at"],
+            "completed_at": row["completed_at"],
+            "status": row["status"],
+            "duration_sec": duration_sec,
+            "pass_total": max_pass,
+        }
+
+    return {
+        "is_research": is_research,
+        "is_running": is_running,
+        "last_refresh": last_refresh,
+        "steps_definition": PIPELINE_STEPS,
+        "steps": steps,
+    }
+
+
 @router.get("/{incident_id}/locations")
 async def get_locations(
     incident_id: int,