feat(brain+ui+app): Triggers — passive Aufweck-Quellen fuer ARIA

ARIA hatte bisher nur ein "User fragt → Brain antwortet"-Modell. Neu:
Trigger laufen passiv im Hintergrund (kein LLM-Call) und wecken ARIA
nur dann auf wenn ein Event tatsaechlich passiert.

Drei Typen, zwei aktuell implementiert:
  timer   — einmalig zu festem ISO-Timestamp ("erinner mich in 10min")
  watcher — Polling alle N Sek einer Condition, feuert bei True mit Throttle
            (z.B. "disk_free_gb < 5", max 1x/h)
  cron    — Platzhalter fuer spaeter

aria-brain/triggers.py
  CRUD auf /data/triggers/<name>.json + /data/triggers/logs/<name>.jsonl.
  create_timer, create_watcher, mark_fired, list_logs, etc.

aria-brain/watcher.py
  Built-in Condition-Variablen: disk_free_gb, disk_free_pct, uptime_sec,
  hour_of_day, day_of_week, rvs_connected, memory_count.
  Sicherer Condition-Parser via ast — Whitelist auf Vergleich + BoolOp +
  Name + Const. Kein eval, kein exec, keine Builtins.

aria-brain/background.py
  Async Loop laeuft alle 30s, sammelt einmalig Variables, geht durch
  Trigger-Liste, _should_fire-Check (Timer: fires_at vergangen / Watcher:
  check_interval + throttle respektiert + condition true). Fire ruft
  agent.chat(prompt, source="trigger") — ARIA bekommt das wie eine
  Push-Nachricht und antwortet via Bridge → RVS → App.

aria-brain/main.py
  /triggers/list, /{name}, /{name}/logs, /timer, /watcher, PATCH, DELETE,
  /triggers/conditions (Variablen + aktuelle Werte). Lifespan-Handler
  startet den Background-Loop beim Container-Start, stoppt beim Shutdown.

aria-brain/agent.py
  Meta-Tools fuer ARIA: trigger_timer, trigger_watcher, trigger_cancel,
  trigger_list. ARIA legt Trigger via Tool-Call selbst an wenn Stefan das
  wuenscht. Side-Channel-Event 'trigger_created' wird in chat-Response
  mitgeschickt damit App + Diagnostic eine Bubble zeigen.

aria-brain/prompts.py
  Neue System-Prompt-Section: Liste aktiver Triggers + verfuegbare
  Condition-Variablen mit aktuellen Werten + Operatoren-Erklaerung.
  ARIA weiss damit immer was es schon gibt und welche Vars sie nutzen kann.

bridge/aria_bridge.py + rvs/server.js
  trigger_created als neuer RVS-Message-Type, Bridge forwarded das aus
  data.events analog zu skill_created.

diagnostic/index.html
  Neuer Top-Tab "Trigger". Liste mit Type-Badges (⏱ TIMER / 👁 WATCHER),
  Status, Fire-Count, last_fired. Aktivieren/Deaktivieren + Löschen pro
  Trigger. "+ Neu"-Modal mit Type-Dropdown, Timer-Minuten oder
  Watcher-Condition + Vars-Anzeige + Throttle. Info-Modal-Eintrag mit
  Erklaerung. Live-Bubble im Chat wenn ARIA selbst einen anlegt.

android/src/screens/ChatScreen.tsx
  trigger_created RVS-Handler → eigene Bubble (gelber Border, "⏰ ARIA
  hat einen Trigger angelegt", Type/Detail/Message/Zeit). ChatMessage
  bekam triggerCreated-Feld. Lokal-only-Schutz beim Server-Sync analog
  zu skill_created.

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

aria-brain/main.py

@@ -20,6 +20,9 @@ import logging
 import os
 from typing import List, Optional
 
+import asyncio
+from contextlib import asynccontextmanager
+
 from fastapi import FastAPI, HTTPException, BackgroundTasks, Request
 from fastapi.responses import Response
 from pydantic import BaseModel, Field
@@ -30,6 +33,9 @@ from proxy_client import ProxyClient
 from agent import Agent
 import skills as skills_mod
 import metrics as metrics_mod
+import triggers as triggers_mod
+import watcher as watcher_mod
+import background as background_mod
 
 logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(name)s: %(message)s")
 logger = logging.getLogger("aria-brain")
@@ -37,7 +43,23 @@ logger = logging.getLogger("aria-brain")
 QDRANT_HOST = os.environ.get("QDRANT_HOST", "aria-qdrant")
 QDRANT_PORT = int(os.environ.get("QDRANT_PORT", "6333"))
 
-app = FastAPI(title="ARIA Brain", version="0.1.0")
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """Beim Brain-Start: Trigger-Background-Loop anwerfen. Beim Shutdown: stoppen."""
+    task = asyncio.create_task(background_mod.run_loop(agent))
+    logger.info("Lifespan: Trigger-Loop gestartet")
+    try:
+        yield
+    finally:
+        task.cancel()
+        try:
+            await task
+        except asyncio.CancelledError:
+            pass
+        logger.info("Lifespan: Trigger-Loop gestoppt")
+
+
+app = FastAPI(title="ARIA Brain", version="0.1.0", lifespan=lifespan)
 
 _embedder: Optional[Embedder] = None
 _store: Optional[VectorStore] = None
@@ -414,6 +436,103 @@ def metrics_calls():
     return metrics_mod.stats()
 
 
+# ─── Triggers (passive Aufweck-Quellen) ─────────────────────────────
+
+class TriggerTimerBody(BaseModel):
+    name: str
+    fires_at: str  # ISO timestamp
+    message: str
+    author: str = "stefan"
+
+
+class TriggerWatcherBody(BaseModel):
+    name: str
+    condition: str
+    message: str
+    check_interval_sec: int = 300
+    throttle_sec: int = 3600
+    author: str = "stefan"
+
+
+class TriggerPatch(BaseModel):
+    active: bool | None = None
+    message: str | None = None
+    condition: str | None = None
+    throttle_sec: int | None = None
+    check_interval_sec: int | None = None
+    fires_at: str | None = None
+
+
+@app.get("/triggers/list")
+def triggers_list(active_only: bool = False):
+    return {"triggers": triggers_mod.list_triggers(active_only=active_only)}
+
+
+@app.get("/triggers/conditions")
+def triggers_conditions():
+    """Verfuegbare Variablen fuer Watcher-Conditions (mit aktuellen Werten)."""
+    return {
+        "variables": watcher_mod.describe_variables(),
+        "current": watcher_mod.collect_variables(),
+    }
+
+
+@app.get("/triggers/{name}")
+def triggers_get(name: str):
+    t = triggers_mod.read(name)
+    if t is None:
+        raise HTTPException(404, f"Trigger '{name}' nicht gefunden")
+    return t
+
+
+@app.get("/triggers/{name}/logs")
+def triggers_get_logs(name: str, limit: int = 50):
+    return {"logs": triggers_mod.list_logs(name, limit=limit)}
+
+
+@app.post("/triggers/timer")
+def triggers_create_timer(body: TriggerTimerBody):
+    try:
+        return triggers_mod.create_timer(
+            name=body.name, fires_at_iso=body.fires_at,
+            message=body.message, author=body.author,
+        )
+    except ValueError as exc:
+        raise HTTPException(400, str(exc))
+
+
+@app.post("/triggers/watcher")
+def triggers_create_watcher(body: TriggerWatcherBody):
+    try:
+        return triggers_mod.create_watcher(
+            name=body.name, condition=body.condition,
+            message=body.message,
+            check_interval_sec=body.check_interval_sec,
+            throttle_sec=body.throttle_sec,
+            author=body.author,
+        )
+    except ValueError as exc:
+        raise HTTPException(400, str(exc))
+
+
+@app.patch("/triggers/{name}")
+def triggers_patch(name: str, body: TriggerPatch):
+    patch = {k: v for k, v in body.model_dump().items() if v is not None}
+    try:
+        return triggers_mod.update(name, patch)
+    except ValueError as exc:
+        raise HTTPException(404, str(exc))
+
+
+@app.delete("/triggers/{name}")
+def triggers_delete(name: str):
+    try:
+        triggers_mod.delete(name)
+    except ValueError as exc:
+        raise HTTPException(404, str(exc))
+    return {"deleted": name}
+
+
 # ─── Skills ─────────────────────────────────────────────────────────
 
 class SkillCreate(BaseModel):