feat(tts): System-Flag speak (ja/nein) pro Antwort statt <voice>-Tag-Hack
Stefans Idee: die QUELLE entscheidet ueber Vorlesen, nicht der Reply-Inhalt. Fast-Path (reiner Steuerbefehl) = speak=False (stumm); ARIA-Antworten (local/claude) = speak=True (vorlesen ok — eine Ansage ist sogar nett). - agent.chat() gibt jetzt (reply, answered_by, speak) zurueck; main.py ChatOut.speak; background.py-Aufrufer angepasst. - bridge: liest speak aus /chat, reicht es an _process_core_response; bei speak=False wird TTS uebersprungen — VOR jeder <voice>-Logik. Robust: unabhaengig davon, ob die Skill-fast_pattern-Reply ein <voice></voice> enthaelt (das verlor ARIA beim semantischen Skill-Rebuild — genau der Bug). App braucht keinen Change: kein xtts_request -> kein Audio -> stumm. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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@@ -1299,7 +1299,9 @@ class Agent:
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self.conversation.add("assistant", fast_reply, project_id=active_project_id)
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if active_project_id:
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projects_mod.touch_project(active_project_id)
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return fast_reply, "fast-path"
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# Fast-Path = reiner Steuerbefehl → NICHT vorlesen (speak=False).
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# System-Flag statt <voice>-Tag: robust, unabhaengig vom Skill-Inhalt.
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return fast_reply, "fast-path", False
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# 1. User-Turn an die Konversation
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self.conversation.add("user", user_message, source=source,
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@@ -1313,7 +1315,7 @@ class Agent:
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# teure Claude-Aufbau + Tool-Loop wird uebersprungen. Sonst None → Claude.
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local_reply = self._try_local_fast_lane(user_message, active_project_id)
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if local_reply is not None:
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return local_reply, "local"
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return local_reply, "local", True # ARIA-Antwort → vorlesen ok
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# 2. Hot Memory (alle pinned Punkte)
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hot = self.store.list_pinned()
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@@ -1514,7 +1516,7 @@ class Agent:
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# 7. Assistant-Turn (final reply) in die Conversation
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self.conversation.add("assistant", final_reply,
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project_id=active_project_id)
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return final_reply, "claude"
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return final_reply, "claude", True # ARIA-Antwort → vorlesen ok
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# ── Tool-Dispatcher ───────────────────────────────────────
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@@ -150,7 +150,7 @@ async def _fire(trigger: dict, agent_factory) -> None:
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try:
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agent = agent_factory()
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reply, _ = agent.chat(prompt, source="trigger")
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reply, _, _ = agent.chat(prompt, source="trigger")
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events = agent.pop_events()
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logger.info("[trigger] %s gefeuert → ARIA-Reply: %s", name, reply[:80])
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triggers_mod.append_log(name, {"event": "reply", "text": reply[:500]})
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+5
-1
@@ -633,6 +633,9 @@ class ChatOut(BaseModel):
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# Welcher Backend die Antwort erzeugt hat: "local" (Qwen), "claude",
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# "fast-path" (Skill/Regex). Fuer den Quell-Badge in Diagnostic.
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answered_by: str = "claude"
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# Soll die Antwort vorgelesen werden? Fast-Path (reiner Steuerbefehl) = False;
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# ARIA-Antworten (local/claude) = True. System-Flag statt <voice>-Tag.
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speak: bool = True
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# Echo der project_id die dieser Turn hatte. Bridge nutzt sie damit die
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# ausgehende Chat-Bubble sauber getaggt in der richtigen Thread-Bahn der
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# UI landet.
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@@ -716,7 +719,7 @@ async def chat(body: ChatIn, background: BackgroundTasks):
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# Sync-Aufruf im Executor damit wir den Event-Loop nicht blocken —
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# chat() macht HTTP-Calls (Proxy) die 30-60s dauern koennen.
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loop = asyncio.get_running_loop()
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reply, answered_by = await loop.run_in_executor(
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reply, answered_by, speak = await loop.run_in_executor(
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None,
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lambda: a.chat(
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body.message, source=body.source, project_id=pid,
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@@ -739,6 +742,7 @@ async def chat(body: ChatIn, background: BackgroundTasks):
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events=a.pop_events(),
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project_id=pid,
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answered_by=answered_by,
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speak=speak,
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)
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finally:
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_project_pending[pid] = [
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