feat: cloud-first consolidation routing + graceful backend fallback

Nail down which backend each LLM path uses, and make the dream cycle resilient to
a backend being down (the MI50 outage left profile/era/narrative — pinned to mi50
with no fallback — aborting every dream cycle).

- Consolidation (summaries + profile/era/narrative) -> cloud via SUMMARY_BACKEND=
  cloud (.env, not committed). Matches the documented lesson that the MI50 is too
  slow/hot for bulk consolidation; nothing background touches the card now.
- llm.complete_with_fallback(): try the primary backend, fall back to cloud on
  error (re-raise if already cloud / no key). Wired into reflect + think so the
  introspection voice (3090/dolphin) survives the gaming PC being powered off.
- dream coherence stage is now fault-isolated: a rebuild failure logs + continues
  instead of sinking the whole pass (reflection still runs).
- .env: removed stale INTROSPECTION_BACKEND=mi50 (live routing is the web-switchable
  introspection_mode DB setting = dolphin/3090; the var only fed a dead fallback).

Verified: forced cycle runs consolidation on cloud, introspection on the 3090,
completes with zero MI50 calls. 206 pass, ruff clean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015yrEb5qpPGv2FjyxrB7LLk

lyra/llm.py

@@ -92,6 +92,26 @@ def complete(messages: list[Message], backend: Backend = "local", model: str | N
     return out
 
 
+def complete_with_fallback(messages: list[Message], backend: Backend, model: str | None = None,
+                           *, fallback: Backend = "cloud",
+                           max_tokens: int | None = None, timeout: float | None = None) -> str:
+    """`complete()` but if the primary backend errors (e.g. a local GPU that's
+    powered off or down), retry once on `fallback` (cloud) instead of failing.
+    Lets local/GPU-routed work (introspection, consolidation) degrade gracefully.
+    Re-raises if the primary is already the fallback or no cloud key is configured."""
+    try:
+        return complete(messages, backend=backend, model=model,
+                        max_tokens=max_tokens, timeout=timeout)
+    except Exception as exc:
+        can_fallback = backend != fallback and (fallback != "cloud" or load().openai_api_key)
+        if not can_fallback:
+            raise
+        logbus.log("info", "llm fell back", primary=backend, to=fallback, error=str(exc)[:80])
+        # Drop the primary's model on fallback — let the fallback pick its own default.
+        return complete(messages, backend=fallback, model=None,
+                        max_tokens=max_tokens, timeout=timeout)
+
+
 def chat_call(
     messages: list, backend: Backend = "cloud", model: str | None = None,
     tools: list | None = None,