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/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)