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>

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"