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/harness.py

@@ -125,6 +125,11 @@ def context_variables(
         "user_name": (user.name or "") if user is not None else "",
         "model_name": "",
         "max_rounds": str(tools_service.MAX_ROUNDS),
+        # Not rendered anywhere. It is the gate on `core.rounds`: an ordinary
+        # chat gets one round and is told to ask for everything at once, an
+        # agent chat is told to keep going, and those are different sentences
+        # rather than the same sentence with a different number in it.
+        "round_budget": str(tools_service.MAX_ROUNDS),
         "memory_limit": str(memories_service.MAX_MEMORY_CHARS),
         "tool_names": _tool_names(offered),
         "memories": memories_service.block(db, user) if "memory" in families else "",
@@ -181,6 +186,10 @@ def _agent_values(db: DBSession, chat, user) -> dict[str, str]:
         "agent_mode": policy.MODE_GUIDANCE.get(context.mode, ""),
         "agent_rewound": rewound,
         "max_rounds": str(context.limits.steps),
+        # Blanked, which is what makes `core.rounds` vanish here: `steps` is a
+        # runaway backstop and telling a model it has a budget of two hundred
+        # invites it to ration one.
+        "round_budget": "",
         "project_files": _project_files(db, chat, context, settings_store, index_service),
     }