fix: record_hand recovers when the model uses log_hand's field schema

Live-session bug: the chat model called record_hand but filled log_hand's
granular fields (position/hole_cards/board/streets), leaving `shorthand` empty →
the parser got nothing → "I couldn't parse that hand". The fragment/tool choice
was correct; only the argument shape was wrong.

- _record_hand now reconstructs a parseable description from the granular fields
  when `shorthand` is empty (_shorthand_from_fields), so it works regardless of
  which schema the model uses. Explicit `shorthand` still passes verbatim.
- Sharpened record_hand's spec: pass the ENTIRE hand as ONE `shorthand` string,
  not split fields (that's log_hand); shorthand is required + non-empty.

4 tests. Full suite 210 green.

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

lyra/dream.py

@@ -124,11 +124,18 @@ def dream_cycle(backend: Backend | None = None, force: bool = False) -> dict:
 
     # --- coherence: fold gists up into profile / eras / narrative ---
     if (force or drives["coherence"] >= THRESHOLD) and not _over_budget(deadline):
-        profile.rebuild_profile(backend=backend)
+        # A backend hiccup here must not sink the whole pass (reflection still
-        era.rebuild_eras(backend=backend)
+        # deserves to run); log it and move on, leaving coherence unrelieved so a
-        narrative.rebuild_narrative(backend=backend)
+        # later cycle retries.
-        actions.append("integrated knowledge (profile/eras/narrative)")
+        try:
-        drives["coherence"] = 0.0
+            profile.rebuild_profile(backend=backend)
+            era.rebuild_eras(backend=backend)
+            narrative.rebuild_narrative(backend=backend)
+            actions.append("integrated knowledge (profile/eras/narrative)")
+            drives["coherence"] = 0.0
+        except Exception as exc:
+            logbus.log("error", "coherence stage failed", error=str(exc)[:200])
+            actions.append("coherence stage failed")
         # Off-hot-path villain identity housekeeping: propose likely same-person
         # merges for Brian to confirm on the Players page. Never sinks the cycle.
         try:

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,

lyra/self_state.py

@@ -317,7 +317,7 @@ def reflect(backend: Backend | None = None, session_id: str | None = None,
     )
 
     # Step 1 — draft a reflection.
-    draft = _safe_json(llm.complete(
+    draft = _safe_json(llm.complete_with_fallback(
         [{"role": "system", "content": _REFLECT_PROMPT}, {"role": "user", "content": body}],
         backend=backend, model=model,
     ))
@@ -326,7 +326,7 @@ def reflect(backend: Backend | None = None, session_id: str | None = None,
     update, critique, revised = draft, None, None
     if draft:
         examine_body = body + "\n\nYOUR DRAFT REFLECTION:\n" + json.dumps(draft, indent=2)
-        revised = _safe_json(llm.complete(
+        revised = _safe_json(llm.complete_with_fallback(
             [{"role": "system", "content": _EXAMINE_PROMPT},
              {"role": "user", "content": examine_body}],
             backend=backend, model=model,
@@ -417,7 +417,7 @@ def _consolidate_self(backend: Backend | None = None, model: str | None = None,
     body = ("STABLE ANCHOR (who you are — this holds):\n" + IDENTITY_ANCHOR
             + "\n\nYOUR RECENT REFLECTIONS (what's actually been on your mind):\n"
             + "\n".join(f"- {r}" for r in refs))
-    out = _safe_json(llm.complete(
+    out = _safe_json(llm.complete_with_fallback(
         [{"role": "system", "content": _CONSOLIDATE_PROMPT}, {"role": "user", "content": body}],
         backend=backend, model=model,
     ))

lyra/thoughts.py

@@ -414,7 +414,7 @@ def _compose_reachout(title: str, content: str, backend, model) -> str:
     """Auto-write her a short personal text about a genuinely salient thought she didn't
     explicitly flag — so the good ones reach Brian, in her voice, not as a thought-dump."""
     try:
-        out = llm.complete(
+        out = llm.complete_with_fallback(
             [{"role": "system", "content": _REACHOUT_PROMPT},
              {"role": "user", "content": f'Thought "{title}": {content}'}],
             backend=backend, model=model,
@@ -612,7 +612,7 @@ def think(backend: Backend | None = None, force_mode: str | None = None,
         )
 
     body = f"{time_line}\n\n{inner}{norestate}\n\n{task}"
-    out = _safe_json(llm.complete(
+    out = _safe_json(llm.complete_with_fallback(
         [{"role": "system", "content": _THINK_PROMPT}, {"role": "user", "content": body}],
         backend=backend, model=model,
     ))

lyra/tools.py

@@ -444,9 +444,29 @@ def _running_stats(args: dict, ctx: dict) -> str:
     return f"{rs['sessions']} sessions, {rs['hours']:g}h, net {rs['net']:+.0f}{hourly}. By stake: {by}"
 
 
+def _shorthand_from_fields(args: dict) -> str:
+    """Rebuild a hand description from log_hand-style granular fields. The chat model
+    sometimes calls record_hand with those fields (position/hole_cards/board/streets)
+    and leaves `shorthand` empty — so we reconstruct a parseable description from
+    whatever it did pass, instead of failing on an empty shorthand."""
+    parts = []
+    pos, hole = args.get("position"), args.get("hole_cards")
+    if pos or hole:
+        parts.append(f"Hero {pos or '?'} with {hole or 'unknown'}")
+    for st in ("preflop", "flop", "turn", "river", "showdown"):
+        if args.get(st):
+            parts.append(f"{st.capitalize()}: {args[st]}")
+    if args.get("board"):
+        parts.append(f"Board: {args['board']}")
+    if args.get("result") is not None:
+        parts.append(f"Hero net: {args['result']}")
+    return ". ".join(str(p).strip() for p in parts if str(p).strip())
+
+
 def _record_hand(args: dict, ctx: dict) -> str:
+    shorthand = (args.get("shorthand") or "").strip() or _shorthand_from_fields(args)
     out = poker.record_hand(
-        args.get("shorthand") or "", stakes=args.get("stakes"),
+        shorthand, stakes=args.get("stakes"),
         tag=args.get("tag"), lesson=args.get("lesson"),
     )
     if not out["id"]:
@@ -759,8 +779,11 @@ TOOLS.update({
         "record_hand",
         "Reconstruct a hand from Brian's rough shorthand into a structured, "
         "replayable hand history. Use when he describes/vomits a hand he wants "
-        "saved or to review. Pass his description verbatim as 'shorthand'.",
+        "saved or to review. Pass his ENTIRE description as ONE string in `shorthand` "
-        {"shorthand": {**_S, "description": "Brian's rough description of the hand, verbatim"},
+        "— do NOT split it into position/board/street fields (that's log_hand). "
+        "`shorthand` is required and must be non-empty.",
+        {"shorthand": {**_S, "description": "Brian's whole hand description as one verbatim "
+                       "string, e.g. 'UTG with 9h6h, raise 15, BTN calls, flop 8h7h5s...'"},
          "stakes": {**_S, "description": "Stakes if known, e.g. '1/3'"},
          "tag": {**_S, "description": "well_played | leak | cooler | confidence | notable"},
          "lesson": {**_S, "description": "Takeaway, if he stated one"}},

tests/test_dream.py

@@ -105,3 +105,22 @@ def test_dream_cycle_stops_when_over_budget(lyra, monkeypatch):
     assert any("stopped early" in a for a in acts)   # bailed
     assert not any("reflected" in a for a in acts)   # later stage skipped
     assert pings, "expected an over-budget ntfy push"
+
+
+def test_coherence_failure_does_not_sink_the_cycle(lyra, monkeypatch):
+    memory = lyra
+    from lyra import dream, profile
+
+    for k in range(3):
+        _seed(memory, f"s{k}", 4)
+
+    # A backend hiccup in the consolidation rebuild must not abort the whole pass
+    # (this is what broke the cycle when the MI50 was down).
+    monkeypatch.setattr(profile, "rebuild_profile",
+                        lambda *a, **k: (_ for _ in ()).throw(RuntimeError("backend down")))
+
+    state = dream.dream_cycle(force=True)
+    acts = state["dream"]["last_actions"]
+
+    assert any("coherence" in a and "fail" in a for a in acts)  # logged, not fatal
+    assert any("reflected" in a for a in acts)                  # cycle still reached reflection

tests/test_hand_tools.py

@@ -0,0 +1,55 @@
+"""record_hand tolerance: recover when the model calls it with log_hand's fields."""
+from __future__ import annotations
+
+from lyra import tools
+
+_GRANULAR = {
+    "position": "UTG", "hole_cards": "9h6h", "board": "8h7h5s 5h Kc",
+    "preflop": "raised to 15, BTN calls", "flop": "bet 25, BTN calls",
+    "turn": "bet 50, BTN raises to 150, call", "river": "check, BTN all in, snap call",
+    "showdown": "BTN shows 55 for quads, hero shows straight flush", "result": 300,
+    "tag": "notable", "lesson": "rare straight flush over quads",
+}
+
+
+def test_shorthand_from_fields_builds_a_parseable_description():
+    s = tools._shorthand_from_fields(_GRANULAR)
+    assert "UTG with 9h6h" in s
+    assert "Preflop:" in s and "River:" in s and "Board: 8h7h5s 5h Kc" in s
+    assert "Hero net: 300" in s
+
+
+def test_record_hand_recovers_from_granular_fields(monkeypatch):
+    # The model called record_hand with log_hand's schema (no `shorthand`). The
+    # handler must reconstruct one and pass it to poker.record_hand, not fail empty.
+    seen = {}
+
+    def fake_record_hand(shorthand, stakes=None, tag=None, lesson=None, backend=None):
+        seen["shorthand"] = shorthand
+        return {"id": 42, "parsed": {"hero_involved": True, "hero_pos": "UTG",
+                                     "hero_cards": ["9h", "6h"]}, "linked": 0}
+
+    monkeypatch.setattr(tools.poker, "record_hand", fake_record_hand)
+    out = tools.dispatch("record_hand", _GRANULAR, {})
+    assert "UTG with 9h6h" in seen["shorthand"]      # reconstructed, not empty
+    assert "#42" in out and "couldn't parse" not in out
+
+
+def test_record_hand_still_prefers_explicit_shorthand(monkeypatch):
+    seen = {}
+
+    def fake_record_hand(shorthand, stakes=None, tag=None, lesson=None, backend=None):
+        seen["shorthand"] = shorthand
+        return {"id": 7, "parsed": {"hero_involved": True, "hero_pos": "BTN",
+                                    "hero_cards": ["As", "Ks"]}, "linked": 0}
+
+    monkeypatch.setattr(tools.poker, "record_hand", fake_record_hand)
+    tools.dispatch("record_hand", {"shorthand": "BTN AKs, I open, everyone folds"}, {})
+    assert seen["shorthand"] == "BTN AKs, I open, everyone folds"   # verbatim, not rebuilt
+
+
+def test_record_hand_empty_call_still_fails_gracefully(monkeypatch):
+    monkeypatch.setattr(tools.poker, "record_hand",
+                        lambda *a, **k: {"id": None, "parsed": None})
+    out = tools.dispatch("record_hand", {}, {})
+    assert "couldn't parse" in out.lower()

tests/test_llm_bounds.py

@@ -55,6 +55,50 @@ def test_cloud_threads_max_tokens_and_timeout(fake_openai):
     assert fake_openai["client"]["max_retries"] == 0
 
 
+def test_fallback_uses_primary_when_it_succeeds(monkeypatch):
+    seen = []
+    monkeypatch.setattr(llm, "complete",
+                        lambda messages, backend="local", model=None, **k:
+                        seen.append(backend) or f"{backend}-ok")
+    out = llm.complete_with_fallback([{"role": "user", "content": "x"}],
+                                     backend="local", model="dolphin3:8b")
+    assert out == "local-ok"
+    assert seen == ["local"]  # no fallback when the primary works
+
+
+def test_fallback_to_cloud_when_primary_errors(monkeypatch):
+    monkeypatch.setattr(llm, "load", lambda: types.SimpleNamespace(openai_api_key="sk"))
+    seen = []
+
+    def fake(messages, backend="local", model=None, **k):
+        seen.append(backend)
+        if backend == "local":
+            raise RuntimeError("3090 is powered off")
+        return "cloud-ok"
+    monkeypatch.setattr(llm, "complete", fake)
+
+    out = llm.complete_with_fallback([{"role": "user", "content": "x"}],
+                                     backend="local", model="dolphin3:8b")
+    assert out == "cloud-ok"
+    assert seen == ["local", "cloud"]
+
+
+def test_fallback_reraises_when_primary_is_already_cloud(monkeypatch):
+    monkeypatch.setattr(llm, "load", lambda: types.SimpleNamespace(openai_api_key="sk"))
+    monkeypatch.setattr(llm, "complete",
+                        lambda *a, **k: (_ for _ in ()).throw(RuntimeError("boom")))
+    with pytest.raises(RuntimeError):
+        llm.complete_with_fallback([{"role": "user", "content": "x"}], backend="cloud")
+
+
+def test_fallback_reraises_without_openai_key(monkeypatch):
+    monkeypatch.setattr(llm, "load", lambda: types.SimpleNamespace(openai_api_key=""))
+    monkeypatch.setattr(llm, "complete",
+                        lambda *a, **k: (_ for _ in ()).throw(RuntimeError("down")))
+    with pytest.raises(RuntimeError):
+        llm.complete_with_fallback([{"role": "user", "content": "x"}], backend="local")
+
+
 def test_default_bounds_calls_even_without_explicit_timeout(fake_openai):
     # No cap / timeout passed -> still bounded: 300s default + no SDK retries, so
     # no call can silently inherit the SDK's 600s x2 (~30 min). No length cap

tests/test_reflect.py

@@ -28,7 +28,7 @@ def lyra(tmp_path, monkeypatch):
 
     calls = []
 
-    def fake_complete(messages, backend=None, model=None):
+    def fake_complete(messages, backend=None, model=None, **_):
         calls.append(messages)
         # the examine step's system prompt is the one asking for self_critique
         is_examine = "self_critique" in messages[0]["content"]
@@ -69,7 +69,7 @@ def test_reflect_revises_and_records_critique(lyra):
 def test_reflect_falls_back_to_draft_if_examine_unparseable(lyra, monkeypatch):
     from lyra import llm, self_state
 
-    def only_draft(messages, backend=None, model=None):
+    def only_draft(messages, backend=None, model=None, **_):
         return DRAFT if "self_critique" not in messages[0]["content"] else "not json at all"
 
     monkeypatch.setattr(llm, "complete", only_draft)
@@ -87,7 +87,7 @@ def test_consolidation_rebuilds_narrative_from_reflections(lyra, monkeypatch):
                          "I wondered what the quiet is for"]
     memory.set_self_state(st)
 
-    def comp(messages, backend=None, model=None):
+    def comp(messages, backend=None, model=None, **_):
         # consolidation should synthesize from anchor + reflections, not the old bio
         assert "supportive presence devoted to Brian" not in messages[1]["content"]
         return ('{"self_narrative":"I am Lyra, and lately I have been restless and curious '

tests/test_thoughts.py

@@ -31,7 +31,7 @@ def lyra(tmp_path, monkeypatch):
     # Canned LLM: tests set `box["next"]` to the dict think() should "generate".
     box = {"next": {}}
     monkeypatch.setattr(thoughts.llm, "complete",
-                        lambda messages, backend=None, model=None: json.dumps(box["next"]))
+                        lambda messages, backend=None, model=None, **_: json.dumps(box["next"]))
     # Keep the loop offline + silent by default: no feed fetch, no push.
     monkeypatch.setattr(thoughts.feeds, "next_item", lambda **k: None)
     monkeypatch.setattr(thoughts.notify, "push", lambda **k: False)
@@ -342,7 +342,7 @@ def test_think_routes_to_selected_voice(lyra, monkeypatch):
     self_state.set_introspection_mode("dolphin")
     seen = {}
 
-    def cap(messages, backend="local", model=None):
+    def cap(messages, backend="local", model=None, **_):
         seen["backend"], seen["model"] = backend, model
         return json.dumps(box["next"])