feat(diagnostic): Quell-Badge an ARIA-Bubbles (local / claude / fast-path)

Zeigt pro Antwort, welcher Backend sie erzeugt hat — farbcodiert (lokal=gruen,
Claude=blau, Fast-Path=lila). Nur in Diagnostic (App bleibt Mama-tauglich).

- agent.chat() gibt jetzt (reply, answered_by) zurueck; an jedem Return-Punkt
  gesetzt (fast-path/local/claude). Beide Aufrufer (main.py, background.py)
  angepasst. main.py: ChatOut.answered_by.
- bridge: liest answered_by aus /chat, reicht es an _process_core_response,
  broadcastet es im chat-Payload UND persistiert es in chat_backup (answeredBy)
  → bleibt nach Reload.
- diagnostic: srcBadgeHtml() rendert den Badge in Live-Chat + History;
  server.js liefert answeredBy in der chat_history.

Erweiterbar: spaeter kann ein Bild-Backend (FLUX/Modellname) denselben Kanal
nutzen. Modellwechsel-fuer-Antworten (groessere Modelle bei mehr GPUs) bleibt
B0.5/Skalierungs-Thema im Plan.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

aria-brain/agent.py

@@ -1263,7 +1263,7 @@ class Agent:
 
     def chat(self, user_message: str, source: str = "",
              project_id: Optional[str] = None,
-             pending_queue: Optional[list[str]] = None) -> str:
+             pending_queue: Optional[list[str]] = None) -> tuple:
         """Verarbeitet eine User-Nachricht — pro Request project_id explizit
         angegeben (leer = Hauptchat). Kein globaler active_project-State mehr —
         so laufen parallele /chat-Requests fuer verschiedene Projekte echt
@@ -1297,7 +1297,7 @@ class Agent:
             self.conversation.add("assistant", fast_reply, project_id=active_project_id)
             if active_project_id:
                 projects_mod.touch_project(active_project_id)
-            return fast_reply
+            return fast_reply, "fast-path"
 
         # 1. User-Turn an die Konversation
         self.conversation.add("user", user_message, source=source,
@@ -1311,7 +1311,7 @@ class Agent:
         # teure Claude-Aufbau + Tool-Loop wird uebersprungen. Sonst None → Claude.
         local_reply = self._try_local_fast_lane(user_message, active_project_id)
         if local_reply is not None:
-            return local_reply
+            return local_reply, "local"
 
         # 2. Hot Memory (alle pinned Punkte)
         hot = self.store.list_pinned()
@@ -1512,7 +1512,7 @@ class Agent:
         # 7. Assistant-Turn (final reply) in die Conversation
         self.conversation.add("assistant", final_reply,
                               project_id=active_project_id)
-        return final_reply
+        return final_reply, "claude"
 
     # ── Tool-Dispatcher ───────────────────────────────────────
 

aria-brain/background.py

@@ -150,7 +150,7 @@ async def _fire(trigger: dict, agent_factory) -> None:
 
     try:
         agent = agent_factory()
-        reply = agent.chat(prompt, source="trigger")
+        reply, _ = agent.chat(prompt, source="trigger")
         events = agent.pop_events()
         logger.info("[trigger] %s gefeuert → ARIA-Reply: %s", name, reply[:80])
         triggers_mod.append_log(name, {"event": "reply", "text": reply[:500]})

aria-brain/main.py

@@ -630,6 +630,9 @@ class ChatOut(BaseModel):
     turns: int
     distilling: bool
     events: list = Field(default_factory=list)
+    # Welcher Backend die Antwort erzeugt hat: "local" (Qwen), "claude",
+    # "fast-path" (Skill/Regex). Fuer den Quell-Badge in Diagnostic.
+    answered_by: str = "claude"
     # Echo der project_id die dieser Turn hatte. Bridge nutzt sie damit die
     # ausgehende Chat-Bubble sauber getaggt in der richtigen Thread-Bahn der
     # UI landet.
@@ -713,7 +716,7 @@ async def chat(body: ChatIn, background: BackgroundTasks):
                 # Sync-Aufruf im Executor damit wir den Event-Loop nicht blocken —
                 # chat() macht HTTP-Calls (Proxy) die 30-60s dauern koennen.
                 loop = asyncio.get_running_loop()
-                reply = await loop.run_in_executor(
+                reply, answered_by = await loop.run_in_executor(
                     None,
                     lambda: a.chat(
                         body.message, source=body.source, project_id=pid,
@@ -735,6 +738,7 @@ async def chat(body: ChatIn, background: BackgroundTasks):
                 distilling=needs_distill,
                 events=a.pop_events(),
                 project_id=pid,
+                answered_by=answered_by,
             )
     finally:
         _project_pending[pid] = [