An effort the model had never heard of

Reported from a live instance, on Bonsai:

  Jinja Exception: Unexpected reasoning effort high. Supported types are
  xhigh (default), medium, and low.

Effort goes out two ways because no single field works, and the second --
chat_template_kwargs -- is not a parameter the server interprets. It is
rendered into the model's own chat template, which does not ignore a value it
does not know: it calls raise_exception, and the request dies before a token.
So a perfectly ordinary option, drawn by this application in its own menu, took
the whole reply with it.

The vocabulary is per model and nobody agrees. gpt-oss takes low/medium/high.
Bonsai takes low/medium/xhigh and refuses high. OpenAI has added minimal, xhigh
and max at different points, and which of them a given model accepts varies
again. One global tuple was going to be wrong for somebody whatever it held.

A model carries its own list now, and the picker, the slash command and the
request builder all read it. A column rather than a key in capabilities_json,
for the reason context_length is one: that dict is rebuilt wholesale from the
submitted checkboxes on every save.

And it corrects itself. A refusal retries the reply once without the effort
rather than losing it -- safe only because the template renders before any
token, so nothing has been emitted, and there is a guard that keeps it that way
-- then narrows the model's list. Bonsai's error states what it does take, so
that is what gets stored.

Note the parser bug, because it is a good one: "high" is a substring of
"xhigh", so reading the advertised list by substring learned `high` from a
sentence explaining that `high` is the problem. Whole words now, with a test
named after it.

/effort reads its levels off the picker instead of a second copy of the list
kept in the browser.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

CHANGELOG.md

@@ -16,6 +16,30 @@ for 1.0.0 have something to be assembled from.
 
 ## Unreleased
 
+## 1.2.0
+
+- Fixed: **choosing a reasoning effort could kill the reply outright**, with a
+  Jinja traceback where the answer should have been. Reasoning effort is sent
+  two ways, and the second — `chat_template_kwargs` — is rendered into the
+  model's own chat template, which does not ignore a value it has never heard
+  of: it raises, and the whole request fails. The catch is that the vocabulary
+  is **not the same for every model**. gpt-oss takes `low/medium/high`; Bonsai
+  takes `low/medium/xhigh` and refuses `high`; OpenAI has added `minimal`,
+  `xhigh` and `max` at various points. This application offered the same three
+  to everything, so on some models the top setting was one the model would
+  throw for.
+- **A model now has its own list of the efforts it accepts**, on its page under
+  Models, and the composer's picker and `/effort` offer only those. Tick none
+  and the familiar three are used, which is right for nearly everything.
+- **And it corrects itself.** If an endpoint refuses an effort anyway — a model
+  swapped underneath a name, a runtime upgraded — that reply is retried once
+  without it instead of being lost, and the model's list is narrowed so the
+  menu stops offering something that does not work. Where the endpoint says
+  what it *does* take, that is what gets stored.
+- `/effort` now reads the levels from the picker rather than from a second copy
+  of the list kept in the browser, so the two can no longer disagree about what
+  a valid effort is.
+
 ## 1.1.2
 
 Two things a phone found that 1.1.0's phone pass had not.

src/lembas/__init__.py

@@ -1,3 +1,3 @@
 """LLeMbas - a Middle-earth themed web UI for OpenAI-compatible LLM endpoints."""
 
-__version__ = "1.1.2"
+__version__ = "1.2.0"

src/lembas/api/admin_models.py

@@ -177,7 +177,11 @@ async def model_detail(
             "groups": list(db.scalars(select(Group).order_by(Group.name))),
             "capabilities": PROTOCOL_CAPABILITIES,
             "tool_capabilities": TOOL_CAPABILITIES,
+            # Every effort this application understands, so an administrator
+            # can tick the ones their model actually takes -- and the model's
+            # current answer, which is the common three until somebody says.
             "efforts": chat_service.EFFORTS,
+            "model_efforts": chat_service.efforts_for(model),
             # Rows predating the split have no tool_* keys at all. Showing them
             # unticked would be a lie: tools.enabled_tools treats absent as on
             # when `tools` is on, so that an upgrade does not silently take web
@@ -238,6 +242,7 @@ async def update_model(
     position: str = Form(""),
     context_length: str = Form(""),
     default_effort: str = Form(""),
+    reasoning_efforts: list[str] = Form(default=[]),
     group_ids: list[str] = Form(default=[]),
     capability: list[str] = Form(default=[]),
 ) -> Response:
@@ -260,9 +265,19 @@ async def update_model(
     # Merged rather than rebuilt, unlike the capabilities below: params_json
     # holds whatever sampling defaults an administrator has set and this form
     # only carries one of them.
+    # Which efforts this model takes at all. Submitted as a list of ticked
+    # values; empty means "nobody has said", and `chat.efforts_for` answers with
+    # the common three. Stored in the order `EFFORTS` declares rather than the
+    # order a browser happened to send.
+    chosen = [value for value in chat_service.EFFORTS if value in (reasoning_efforts or [])]
+    model.reasoning_efforts = chosen
+
     params = dict(model.params_json or {})
     wanted = default_effort.strip().lower()
-    if wanted in chat_service.EFFORTS:
+    # Checked against what this model takes, not against everything this
+    # application has heard of -- a default of `high` on a model whose template
+    # refuses it is a chat that fails on its first turn.
+    if wanted in chat_service.efforts_for(model):
         params["reasoning_effort"] = wanted
     else:
         params.pop("reasoning_effort", None)

src/lembas/api/pages.py

@@ -82,10 +82,12 @@ def _chat_context(db: DBSession, user: User, chat: Chat | None) -> dict:
             else []
         ),
         "attached_base_ids": [base.id for base in chat.knowledge_bases] if chat else [],
-        # The three a reasoning model understands. From the service so the
+        # What *this* model takes, not the three every model used to be assumed
-        # command, the control and the request builder cannot disagree about
+        # to take. The vocabulary is per model -- gpt-oss has no `xhigh` and
-        # what is a valid effort.
+        # Bonsai has no `high`, and sending the wrong one does not degrade, it
-        "efforts": chat_service.EFFORTS,
+        # raises inside the chat template and fails the reply. From the service
+        # so the command, the control and the request builder cannot disagree.
+        "efforts": chat_service.efforts_for(current) if current else chat_service.DEFAULT_EFFORTS,
         # What the picker shows, and what `build_request` will send. One
         # resolver so the two cannot disagree.
         "resolved_effort": chat_service.resolved_effort(chat) if chat else "",

src/lembas/db/models/connection.py

@@ -19,7 +19,7 @@ from sqlalchemy import (
 from sqlalchemy.orm import Mapped, mapped_column, relationship
 
 from lembas.db.base import Base, Timestamps, UUIDPrimaryKey
-from lembas.db.types import JSONDict
+from lembas.db.types import JSONDict, JSONList
 
 if TYPE_CHECKING:
     # Import only for the annotation; at runtime SQLAlchemy resolves the
@@ -137,6 +137,20 @@ class Model(UUIDPrimaryKey, Timestamps, Base):
     # ticked anything.
     context_length: Mapped[int] = mapped_column(Integer, default=0, nullable=False)
 
+    # Which reasoning efforts this model actually accepts. Empty means "nobody
+    # has said", and `services/chat.efforts_for` answers with the common set.
+    #
+    # It has to be per model, because the vocabulary is: gpt-oss takes
+    # low/medium/high, Bonsai takes low/medium/xhigh and *raises* on high, and
+    # OpenAI's own list has grown minimal, xhigh and max at different times. A
+    # single global tuple is a guess that is wrong for somebody.
+    #
+    # ⚠ A column and not a key in `capabilities_json`, for exactly the reason
+    # `context_length` is one: that dict is rebuilt wholesale from the submitted
+    # checkboxes on every save, so anything in it that is not a checkbox is
+    # destroyed the next time an administrator ticks anything.
+    reasoning_efforts: Mapped[list[str]] = mapped_column(JSONList, default=list)
+
     connection: Mapped[Connection] = relationship(back_populates="models")
     groups: Mapped[list[Group]] = relationship(
         "Group", secondary=model_groups, back_populates="models"

src/lembas/services/chat.py

@@ -387,7 +387,15 @@ def build_request(
         ):
             body["tool_choice"] = {"type": "function", "function": {"name": force_tool}}
 
-    apply_effort(body, (chat.params_json or {}).get("reasoning_effort"))
+    # The model's own vocabulary, looked up here rather than passed in: every
+    # caller of `build_request` would otherwise have to remember, which is the
+    # trap `audio_service.template_flags` fell into.
+    chat_model = model_for(db, chat)
+    apply_effort(
+        body,
+        (chat.params_json or {}).get("reasoning_effort"),
+        efforts_for(chat_model) if chat_model is not None else None,
+    )
     return body
 
 
@@ -405,7 +413,42 @@ def build_request(
 # an effort on sends neither field and is byte-for-byte what it was. An endpoint
 # strict about unknown parameters will refuse the extra one -- but on a chat
 # somebody deliberately set an effort on, not on every chat in the instance.
-EFFORTS = ("low", "medium", "high")
+# Every reasoning effort this application understands, and the subset a model
+# gets when nobody has said otherwise.
+#
+# 🚨 These are two different questions and conflating them is what broke a
+# chat on Bonsai: `EFFORTS` was `("low", "medium", "high")` and was used both to
+# validate what somebody chose *and* to decide what to offer, so a model whose
+# vocabulary is low/medium/**xhigh** could not be given its own top setting,
+# and the one it was given -- `high` -- made its chat template call
+# `raise_exception` and took the whole reply with it.
+#
+# The known list is the union across providers, which have not agreed: OpenAI
+# has added `minimal`, `xhigh` and `max` at different points; gpt-oss takes
+# low/medium/high; Bonsai takes low/medium/xhigh and refuses high. `none` is
+# deliberately absent -- this application already spells that `off`, and two
+# spellings of off is the failure this codebase keeps cataloguing.
+EFFORTS = ("minimal", "low", "medium", "high", "xhigh", "max")
+
+# What a model is offered when its own list is empty. The three every reasoning
+# model since the first one has understood.
+DEFAULT_EFFORTS = ("low", "medium", "high")
+
+
+def efforts_for(model) -> tuple[str, ...]:
+    """The efforts this model accepts, in the order they should be offered.
+
+    A model's own list when an administrator has set one or the endpoint has
+    taught us one (see `generation._narrow_efforts`), and the common three
+    otherwise. Filtered against `EFFORTS` on the way out, so a value stored by
+    an older release -- or learned from an endpoint that advertised something
+    this application has never heard of -- cannot reach a request body.
+    """
+    stored = list(getattr(model, "reasoning_efforts", None) or [])
+    chosen = [value for value in stored if value in EFFORTS]
+    if not chosen:
+        return DEFAULT_EFFORTS
+    return tuple(value for value in EFFORTS if value in chosen)
 
 
 def resolved_effort(chat) -> str:
@@ -427,9 +470,19 @@ def resolved_effort(chat) -> str:
     return value if value in EFFORTS else ""
 
 
-def apply_effort(body: dict[str, Any], effort: str | None) -> None:
+def apply_effort(
-    """Put a chosen reasoning effort into a request body, in both forms."""
+    body: dict[str, Any], effort: str | None, supported: tuple[str, ...] | None = None
-    if not effort or effort not in EFFORTS:
+) -> None:
+    """Put a chosen reasoning effort into a request body, in both forms.
+
+    `supported` is the model's own vocabulary. An effort outside it is dropped
+    rather than sent, because the second form below is not advisory: it reaches
+    the model's Jinja chat template, and a template that does not know the value
+    raises rather than ignoring it -- which fails the whole request, not the
+    parameter.
+    """
+    allowed = supported or DEFAULT_EFFORTS
+    if not effort or effort not in allowed:
         return
     body["reasoning_effort"] = effort
     kwargs = dict(body.get("chat_template_kwargs") or {})

src/lembas/services/generation.py

@@ -19,6 +19,7 @@ import asyncio
 import contextlib
 import json
 import logging
+import re
 import time
 import uuid
 from dataclasses import dataclass, field, replace
@@ -454,6 +455,122 @@ def _narrower(instance: float, quota: int) -> float:
     return float(min(instance, quota))
 
 
+# --- A reasoning effort the model will not take ------------------------------
+#
+# `chat_template_kwargs.reasoning_effort` is not advisory. It reaches the
+# model's Jinja chat template, and a template that does not know the value does
+# not ignore it -- gpt-oss and Bonsai both call `raise_exception`, which fails
+# the whole request. The reader sees their reply die with a Jinja traceback in
+# it, having chosen a perfectly ordinary-looking option from a menu this
+# application drew.
+#
+# So the value is checked against the model's own vocabulary before it is sent
+# (`chat.apply_effort`), and this is the second line: when it is refused anyway
+# -- an endpoint upgraded underneath us, a model whose list nobody has set --
+# the reply is retried once without it rather than lost, and the model's list is
+# narrowed so the menu stops offering something that does not work.
+
+
+def _effort_was_refused(message: str) -> bool:
+    """Whether this error is the chat template refusing the effort we sent.
+
+    Deliberately narrow. Anything that merely mentions reasoning would also
+    match a model politely declining to think, and retrying *that* silently
+    would hide a real failure behind a second request.
+    """
+    lowered = message.lower()
+    return "effort" in lowered and ("unexpected" in lowered or "supported" in lowered)
+
+
+def _advertised_efforts(message: str) -> list[str]:
+    """The efforts an error message says it will take, if it says.
+
+    Bonsai's is "Unexpected reasoning effort high. Supported types are xhigh
+    (default), medium, and low." -- which is the answer, written out, in the
+    failure. Read only from the part after "supported", so the *rejected* value
+    named in the first sentence is not collected as a supported one.
+
+    Best-effort by design: it only ever narrows what is offered, an
+    administrator can set the list by hand, and anything unrecognised is
+    dropped by `efforts_for` on the way out.
+    """
+    lowered = message.lower()
+    if "supported" not in lowered:
+        return []
+    tail = lowered.split("supported", 1)[1]
+    # Whole words. `"high" in "xhigh"` is true, so a substring test reads
+    # Bonsai's "Supported types are xhigh (default), medium, and low" as
+    # advertising `high` -- the very value it has just refused -- and the list
+    # would learn the opposite of what the endpoint said.
+    words = set(re.findall(r"[a-z]+", tail))
+    return [effort for effort in chat_service.EFFORTS if effort in words]
+
+
+def _learn_refused_effort(model_id: str, refused: str, message: str) -> None:
+    """Write what the endpoint just taught us onto the model.
+
+    Its own session: this runs from inside a generation, which outlives the
+    request's session, and the whole point is that it survives to the next turn.
+    """
+    from lembas.db.models import Model
+
+    if not model_id:
+        return
+    try:
+        with session_scope() as db:
+            models = list(db.scalars(select(Model).where(Model.model_id == model_id)))
+            for model in models:
+                advertised = _advertised_efforts(message)
+                current = list(model.reasoning_efforts or chat_service.DEFAULT_EFFORTS)
+                # What the endpoint advertised, when it did; otherwise simply
+                # the list it had, minus the one it has just refused.
+                wanted = advertised or [e for e in current if e != refused]
+                wanted = [e for e in wanted if e in chat_service.EFFORTS and e != refused]
+                if wanted and wanted != list(model.reasoning_efforts or []):
+                    model.reasoning_efforts = wanted
+                    log.info(
+                        "model %s refused reasoning effort %r; efforts narrowed to %s",
+                        model_id, refused, wanted,
+                    )
+    except Exception:  # noqa: BLE001 - never let bookkeeping fail a reply
+        log.exception("could not record the refused effort for model %s", model_id)
+
+
+async def _stream_once(endpoint, payload, generation, model_id: str):
+    """`stream_chat`, retried once without the reasoning effort if that is what
+    the endpoint objected to.
+
+    ⚠ The retry is only safe because the template is rendered *before* any token
+    is produced, so a refusal arrives with nothing yet emitted. `sent` is the
+    guard that keeps it that way: once a single chunk has reached the caller,
+    the reply is under way and a second request would duplicate it.
+    """
+    sent = False
+    try:
+        async for chunk in stream_chat(endpoint, payload):
+            sent = True
+            yield chunk
+        return
+    except LLMError as exc:
+        refused = str((payload.get("chat_template_kwargs") or {}).get("reasoning_effort") or "")
+        if sent or not refused or not _effort_was_refused(exc.message):
+            raise
+        log.info("retrying without reasoning effort %r: %s", refused, exc.message)
+        _learn_refused_effort(model_id, refused, exc.message)
+
+    retry = dict(payload)
+    retry.pop("reasoning_effort", None)
+    kwargs = dict(retry.get("chat_template_kwargs") or {})
+    kwargs.pop("reasoning_effort", None)
+    if kwargs:
+        retry["chat_template_kwargs"] = kwargs
+    else:
+        retry.pop("chat_template_kwargs", None)
+
+    async for chunk in stream_chat(endpoint, retry):
+        yield chunk
+
+
 async def _run(generation: Generation) -> None:
     """Produce one reply, then persist it. Never raises into the task.
 
@@ -643,7 +760,7 @@ async def _run(generation: Generation) -> None:
             # round thinks at all -- plenty of rounds do not.
             round_thinking: tuple[float, float] | None = None
 
-            async for chunk in stream_chat(endpoint, payload):
+            async for chunk in _stream_once(endpoint, payload, generation, model_id):
                 counts = chunk_usage(chunk)
                 if counts is not None:
                     generation.reported_usage = True

src/lembas/web/static/js/commands.js

@@ -271,8 +271,21 @@
 
   /* --- Reasoning effort ---------------------------------------------------
      The command drives the same select the composer shows, so there is one
-     piece of state and the control updates itself when the command is used. */
+     piece of state and the control updates itself when the command is used.
-  var EFFORTS = ["low", "medium", "high"];
+
+     Which efforts exist is read off that select's own options rather than
+     kept here. It used to be a second copy of `["low","medium","high"]`, which
+     was wrong the moment the vocabulary became per model: a Bonsai takes
+     `xhigh` and no `high`, so the list the server rendered and the list this
+     file believed in disagreed -- and the one that decides what `/effort xhigh`
+     does was this one. The select is the table; nothing else should hold it. */
+  function efforts() {
+    var select = el("[data-effort]");
+    if (!select) return [];
+    return Array.prototype.map
+      .call(select.options, function (option) { return option.value; })
+      .filter(function (value) { return value !== "off"; });
+  }
 
   function setEffort(rest) {
     var select = el("[data-effort]");
@@ -283,12 +296,14 @@
         "error"
       );
     }
+    var available = efforts();
+    var listed = available.join(", ");
     var wanted = (rest || "").trim().toLowerCase();
     if (!wanted) {
       return note(
-        EFFORTS.indexOf(select.value) === -1
+        available.indexOf(select.value) === -1
-          ? "No effort is being sent. Try low, medium or high."
+          ? "No effort is being sent. Try " + listed + "."
-          : "Effort is " + select.value + ". /effort low, medium, high, or off."
+          : "Effort is " + select.value + ". /effort " + listed + ", or off."
       );
     }
     /* "off" is the option's real value, not an empty string: the new-chat form
@@ -296,8 +311,11 @@
        sentinel and this has to match it. "default" and "none" still work,
        because somebody's fingers will type them. */
     if (wanted === "default" || wanted === "none") wanted = "off";
-    else if (wanted !== "off" && EFFORTS.indexOf(wanted) === -1) {
+    else if (wanted !== "off" && available.indexOf(wanted) === -1) {
-      return note("“" + wanted + "” is not an effort. Try low, medium, high or off.", "error");
+      return note(
+        "“" + wanted + "” is not an effort this model takes. Try " + listed + " or off.",
+        "error"
+      );
     }
     select.value = wanted;
     select.dispatchEvent(new Event("change", { bubbles: true }));

src/lembas/web/templates/admin/model_detail.html

@@ -104,11 +104,39 @@
       </p>
     </div>
 
+    <div class="field">
+      <span class="field__label">Reasoning efforts this model accepts</span>
+      <div class="btn-row">
+        {% for value in efforts %}
+        <label class="checkbox">
+          <input type="checkbox" name="reasoning_efforts" value="{{ value }}"
+                 {{ 'checked' if value in model_efforts }}>
+          <span class="mono">{{ value }}</span>
+        </label>
+        {% endfor %}
+      </div>
+      <p class="field__hint">
+        The vocabulary is <strong>not the same for every model</strong>, and
+        sending one a model does not know is not ignored — it is rendered into
+        the model's chat template, which raises and fails the whole reply.
+        gpt-oss takes <span class="mono">low/medium/high</span>; Bonsai takes
+        <span class="mono">low/medium/xhigh</span> and refuses
+        <span class="mono">high</span>; OpenAI has added
+        <span class="mono">minimal</span>, <span class="mono">xhigh</span> and
+        <span class="mono">max</span> at various points.
+        <br>
+        Tick none and the common three are offered, which is right for almost
+        everything. If an endpoint ever refuses one anyway, that reply is
+        retried without it and this list corrects itself — so this is worth
+        setting by hand only to save that one round trip.
+      </p>
+    </div>
+
     <div class="field">
       <label class="field__label" for="default-effort">Default reasoning effort</label>
       <select class="select" id="default-effort" name="default_effort">
         <option value="">None — send nothing</option>
-        {% for value in efforts %}
+        {% for value in model_efforts %}
         <option value="{{ value }}"
                 {{ 'selected' if model.params_json.get('reasoning_effort') == value }}>
           {{ value }}

tests/test_effort.py

@@ -366,3 +366,93 @@ def test_the_picker_never_says_default(client: TestClient, db, registered):
     assert "Effort: default" not in html
     assert "Effort: off" in html
     assert '<option value="medium" selected>' in html.replace("\n", "").replace("  ", "")
+
+
+# --- A vocabulary that is not the same for every model -----------------------
+#
+# Reported from a real instance, on a model called Bonsai:
+#
+#   Jinja Exception: Unexpected reasoning effort high. Supported types are
+#   xhigh (default), medium, and low.
+#
+# `chat_template_kwargs.reasoning_effort` is rendered into the model's own chat
+# template, and a template that does not know the value calls `raise_exception`
+# rather than ignoring it -- so the whole reply died, from an option this
+# application had drawn in a menu.
+BONSAI_ERROR = (
+    "Jinja Exception: Unexpected reasoning effort high. "
+    "Supported types are xhigh (default), medium, and low."
+)
+
+
+class _FakeModel:
+    def __init__(self, efforts=None):
+        self.reasoning_efforts = efforts or []
+
+
+def test_a_model_that_has_said_nothing_gets_the_common_three():
+    from lembas.services import chat as chat_service
+
+    assert chat_service.efforts_for(_FakeModel()) == ("low", "medium", "high")
+
+
+def test_a_model_can_take_xhigh_and_not_high():
+    from lembas.services import chat as chat_service
+
+    bonsai = _FakeModel(["xhigh", "medium", "low"])
+    assert chat_service.efforts_for(bonsai) == ("low", "medium", "xhigh")
+    assert "high" not in chat_service.efforts_for(bonsai)
+
+
+def test_an_effort_the_model_refuses_is_never_sent():
+    """The check that stops the crash happening at all."""
+    from lembas.services import chat as chat_service
+
+    supported = chat_service.efforts_for(_FakeModel(["xhigh", "medium", "low"]))
+    body: dict = {}
+    chat_service.apply_effort(body, "high", supported)
+    assert body == {}
+
+    chat_service.apply_effort(body, "xhigh", supported)
+    assert body["reasoning_effort"] == "xhigh"
+    assert body["chat_template_kwargs"]["reasoning_effort"] == "xhigh"
+
+
+def test_a_value_this_application_never_heard_of_cannot_reach_a_request():
+    from lembas.services import chat as chat_service
+
+    assert chat_service.efforts_for(_FakeModel(["ludicrous"])) == ("low", "medium", "high")
+
+
+def test_the_refusal_is_recognised_and_the_supported_list_read_out_of_it():
+    from lembas.services import generation
+
+    assert generation._effort_was_refused(BONSAI_ERROR)
+    assert generation._advertised_efforts(BONSAI_ERROR) == ["low", "medium", "xhigh"]
+
+
+def test_the_rejected_value_is_not_collected_as_a_supported_one():
+    """The message names the refused effort first and the supported ones after,
+    so anything reading the whole string would learn `high` from a sentence
+    saying `high` is the problem."""
+    from lembas.services import generation
+
+    assert "high" not in generation._advertised_efforts(BONSAI_ERROR)
+
+
+def test_an_ordinary_failure_is_not_retried_as_an_effort_problem():
+    """Retrying a genuine failure would hide it behind a second request."""
+    from lembas.services import generation
+
+    for message in (
+        "Connection refused.",
+        "The model is still loading.",
+        "context length exceeded",
+    ):
+        assert not generation._effort_was_refused(message)
+
+
+def test_a_model_with_no_advertisement_simply_loses_the_refused_value():
+    from lembas.services import generation
+
+    assert generation._advertised_efforts("Unexpected reasoning effort high.") == []