feat: separate CHAT_MODEL (gpt-4o) for persona fidelity

Mid-size models (gpt-4o-mini, qwen2.5-14b) resist persona instructions —
help-desk closers and feelings-disclaimers leak through regardless. Route live
chat to a stronger model while keeping bulk consolidation cheap:

- config: CHAT_MODEL (default gpt-4o), distinct from CLOUD_MODEL (gpt-4o-mini)
- llm.complete gains a `model` override; chat.respond uses chat_model on cloud,
  consolidation paths keep cloud_model
- persona: reword the "no sign-off" rule so genuine questions are welcome and
  only reflexive customer-service closers are discouraged

Verified: on gpt-4o she owns her mood without disclaimers and drops most
help-desk tails — clearly more in-character than mini/qwen.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

lyra/chat.py

@@ -92,7 +92,9 @@ def build_messages(session_id: str, user_msg: str) -> list[Message]:
 def respond(session_id: str, user_msg: str, backend: Backend = "cloud") -> str:
     """Produce Lyra's reply to a single user message and persist the exchange."""
     cfg = config.load()
-    model = {"local": cfg.local_model, "cloud": cfg.cloud_model, "mi50": cfg.mi50_model}.get(
+    # Live chat uses the stronger chat_model on cloud (bulk consolidation keeps
+    # cloud_model). local/mi50 use their own configured model.
+    model = {"local": cfg.local_model, "cloud": cfg.chat_model, "mi50": cfg.mi50_model}.get(
         backend, backend
     )
     logbus.log(
@@ -101,7 +103,7 @@ def respond(session_id: str, user_msg: str, backend: Backend = "cloud") -> str:
     )
 
     messages = build_messages(session_id, user_msg)
-    reply = llm.complete(messages, backend=backend)
+    reply = llm.complete(messages, backend=backend, model=model)
     logbus.log("info", "reply", session=session_id, chars=len(reply))
 
     memory.remember(session_id, "user", user_msg)