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/config.py

@@ -17,7 +17,8 @@ class Config:
     mi50_base_url: str  # OpenAI-compatible llama.cpp server on the MI50 box
     mi50_model: str
     openai_api_key: str
-    cloud_model: str
+    cloud_model: str  # cloud model for bulk/consolidation work (cheap)
+    chat_model: str  # cloud model for live chat (stronger; persona fidelity)
     embed_backend: str  # "cloud" (OpenAI) or "local" (Ollama)
     embed_model: str  # OpenAI embedding model
     local_embed_model: str  # Ollama embedding model
@@ -33,6 +34,7 @@ def load() -> Config:
         mi50_model=os.getenv("MI50_MODEL", "local-gpu"),
         openai_api_key=os.getenv("OPENAI_API_KEY", ""),
         cloud_model=os.getenv("CLOUD_MODEL", "gpt-4o-mini"),
+        chat_model=os.getenv("CHAT_MODEL", "gpt-4o"),
         embed_backend=os.getenv("EMBED_BACKEND", "cloud").lower(),
         embed_model=os.getenv("EMBED_MODEL", "text-embedding-3-small"),
         local_embed_model=os.getenv("LOCAL_EMBED_MODEL", "nomic-embed-text"),