One round for a chat, as many as it takes for an agent

Two different jobs were sharing one number. A plain conversation asking a
question is one round of looking things up and then an answer; the rounds after
that were a small model that had decided searching was the answer searching
until the context ran out, at a full request each. MAX_ROUNDS is 1 now. Several
tools can still be called within that round, which is the thing worth telling
the model.

The trade is real and worth naming: a plain chat can no longer search and then
read one of the results, because reading is a second round. That is what an
agent chat is for.

An agent chat is sized by Limits instead, where steps is now a runaway backstop
and not a working budget. It was 40 and it was reached -- a step count low
enough to be the thing that ends a reply is a count that ends it halfway. What
bounds one now is the wall clock and a new completion-token ceiling, with zero
meaning no ceiling, the same convention index_chars already uses.

That ceiling would have been decorative. generation.completion_tokens is only
populated when the endpoint sends a usage block, and llama.cpp, Ollama and
friends never do; the fallback estimate is computed once, in _run's finally,
long after the loop that needs it. So _written takes the larger of reported and
estimated, and there is a test that runs the whole thing against a stream
reporting no usage at all. A limit that works on OpenAI and silently does
nothing everywhere else is the worst kind: one that looks configured.

core.rounds could not stay one fragment. "You get at most N rounds" is not the
same sentence with a different number in it -- a model told it has a budget
rations it and stops early to report progress, which is exactly the behaviour
that strands a long piece of work. So it splits: core.rounds keeps the
one-round case and gates on a new round_budget variable that _agent_values
blanks, and core.keep_working says the other thing to an agent chat.

A queued message during a one-round reply is now never taken mid-reply -- there
is no work under way to steer -- and falls through to _drain, which gives it a
reply of its own. No code change went with that; it falls out of the guard, and
there is a test so that "it happens to work" and "it is meant to work" stop
looking the same.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

src/lembas/services/generation.py

@@ -379,6 +379,10 @@ async def _run(generation: Generation) -> None:
                 if generation.output_bytes > limits.output_bytes:
                     _gave_up(generation, "with too much output to read")
                     break
+                written = _written(generation)
+                if limits.completion_tokens and written > limits.completion_tokens:
+                    _gave_up(generation, f"after writing about {written:,} tokens")
+                    break
             accumulator = tools_service.ToolCallAccumulator()
             # Text the model produced in *this* round, needed separately from
             # generation.content when echoing the assistant turn back.
@@ -446,13 +450,13 @@ async def _run(generation: Generation) -> None:
                 # chat allowed forty steps stopped after three and said it had
                 # taken forty. Two numbers, one of them wrong, in code whose
                 # whole job is to say what happened.
+                howmany = "one round" if budget == 1 else f"{budget} rounds"
                 generation.tool_events.append(
                     {
                         "name": calls[0]["name"],
                         "status": "error",
                         "error": (
-                            f"Stopped after {budget} rounds of tool calls "
-                            f"without an answer."
+                            f"Stopped after {howmany} of tool calls without an answer."
                         ),
                     }
                 )