feat(local-llm): B1b-Plumbing — tools/tool_calls durch Adapter/Bridge/Brain-Client

Traegt OpenAI-Tool-Definitionen (tools) durch den ganzen lokalen Pfad und gibt
tool_calls zurueck:
- adapter.py: tools -> llama.cpp /v1/chat/completions (tool_choice=auto),
  message.tool_calls zurueck in llm_response.
- aria_bridge.py: _local_llm + /internal/local-llm reichen tools durch, geben
  tool_calls zurueck.
- local_llm.py: local_llm_chat akzeptiert tools, result enthaelt tool_calls.

Inert bis der Brain-Tool-Loop (naechster Schritt) tools uebergibt — Verhalten
unveraendert. Tool-Set + lokale Tool-Loop + Router-Anpassung folgen.

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

bridge/aria_bridge.py

@@ -3367,9 +3367,10 @@ class ARIABridge:
     _LLM_TIMEOUT_S = 30.0
 
     async def _local_llm(self, messages: list, max_tokens: int = 512,
-                         temperature: float = 0.7, stop=None) -> dict:
+                         temperature: float = 0.7, stop=None, tools=None) -> dict:
         """Schickt einen llm_request an den llm-adapter (Gamebox), wartet auf
-        llm_response. Rueckgabe: {ok, content, model, elapsedMs} oder {ok:False, error}."""
+        llm_response. tools (B1b) werden durchgereicht; tool_calls kommen zurueck.
+        Rueckgabe: {ok, content, tool_calls, model, elapsedMs} oder {ok:False, error}."""
         if self.ws_rvs is None:
             return {"ok": False, "error": "RVS-Verbindung nicht aktiv"}
         if not isinstance(messages, list) or not messages:
@@ -3388,8 +3389,10 @@ class ARIABridge:
             }
             if stop:
                 req_payload["stop"] = stop
-            logger.info("[rvs] llm_request → llm-adapter (id=%s, msgs=%d, max_tokens=%d)",
-                        request_id[:8], len(messages), max_tokens)
+            if tools:
+                req_payload["tools"] = tools
+            logger.info("[rvs] llm_request → llm-adapter (id=%s, msgs=%d, max_tokens=%d, tools=%d)",
+                        request_id[:8], len(messages), max_tokens, len(tools) if tools else 0)
             ok = await self._send_to_rvs({
                 "type": "llm_request",
                 "payload": req_payload,
@@ -3407,6 +3410,7 @@ class ARIABridge:
             return {
                 "ok": True,
                 "content": result.get("content", ""),
+                "tool_calls": result.get("tool_calls"),
                 "model": result.get("model"),
                 "elapsedMs": result.get("elapsedMs"),
             }
@@ -3885,9 +3889,11 @@ class ARIABridge:
                         temperature = float(data.get("temperature"))
                     except (TypeError, ValueError):
                         temperature = 0.7
+                    _tools = data.get("tools") if isinstance(data.get("tools"), list) else None
                     result = await self._local_llm(
                         messages=messages, max_tokens=max_tokens,
                         temperature=temperature, stop=data.get("stop"),
+                        tools=_tools,
                     )
                     status = 200 if result.get("ok") else 502
                     await _send_response(writer, status, result)