A ceiling that was a schedule, and a reply that ended in silence

Reported: an ordinary chat with a small local model researching a question
well -- six searches, each one informed by the last -- stopped at the round
limit and produced no answer at all. Two separate faults, and the second is
the serious one.

The limit was 5 and it should not have been a working number. It was 1 once,
and the note beside it already said why that was wrong: a count low enough to
be reached by ordinary work is a schedule, not a ceiling, and it overrides the
model's judgement on every turn instead of catching a runaway. Five was the
same mistake with a larger number. It is 0 now -- no ceiling, falling back to
MAX_TOOL_ROUNDS as a runaway backstop, which is the shape `Limits.steps`
already had for an agent chat. What bounds an ordinary chat is the context
window, which is a real limit rather than a guess at how much looking-up a
question deserves. An administrator who wants a ceiling can still set one.

The worse fault: *every* budget ended the reply where it was noticed. That is
survivable for a model that narrates as it works and produces nothing at all
for one that goes straight to tool calls -- an empty bubble with a red line
under it, and everything it had gathered thrown away. `_wrap_up` withdraws the
tools and asks once more instead. What it found is in the transcript either
way; one request turns it into an answer. Same move `plan_submit` makes, and
the reason the loop now runs to `budget + 2`: the round at the budget notices,
the one after it answers. The event stays, because an answer the model chose to
give and one it gave because it ran out of room read identically otherwise.

`_too_big` is the one exception and stays a hard stop. It *is* the finding that
there is no room for another request, so a wrap-up round would be the same
overflow with an upstream error in place of an explanation.

`core.keep_working` was gated on the agent family and is now gated on
`unbounded`, the exact complement of `round_budget` -- so an ordinary chat with
no ceiling is told to work until the job is done rather than being told nothing,
and is never told it has a budget of two hundred, which it would ration.

The regression test asserts the reply is not empty, and fails with `'' ==
'Here is what I found.'` against the old code -- which is exactly what was seen.

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

src/lembas/services/generation.py

@@ -450,7 +450,14 @@ async def _run(generation: Generation) -> None:
         # tokens and the clock instead.
         budget = limits.steps if limits else (chat_rounds or MAX_TOOL_ROUNDS)
 
-        for round_number in range(budget + 1):
+        # Set once a budget has run out, holding the last round open with the
+        # tools withdrawn so the reply ends in an answer rather than in silence.
+        # See `_wrap_up`. `budget + 2` rather than `+ 1` is that extra round:
+        # the iteration at `budget` is where the overrun is noticed, and the one
+        # after it is where the model gets to say what it found.
+        wrapping_up = False
+
+        for round_number in range(budget + 2):
             generation.rounds = round_number + 1
 
             # Recomputed every round, against once before the loop. The request
@@ -467,6 +474,11 @@ async def _run(generation: Generation) -> None:
             # branch below on purpose: an ordinary chat with a round budget can
             # fill a small window too, and `context_limit` is what decides,
             # not what kind of chat it is.
+            # The one budget that still stops dead rather than asking for a final
+            # answer. Every other one can afford one more request; this one is
+            # the finding that there is no room for a request, and a wrap-up
+            # round would be the same overflow with an upstream error instead of
+            # an explanation.
             if round_number and _too_big(generation):
                 _gave_up(generation, "with no room left in the context window")
                 break
@@ -476,18 +488,20 @@ async def _run(generation: Generation) -> None:
             # Stop already covers the mid-stream case. Time spent waiting for a
             # person is subtracted -- somebody who thinks for ten minutes about
             # one command should not thereby spend the whole allowance.
-            if limits is not None and round_number:
+            if limits is not None and round_number and not wrapping_up:
                 spent = (time.monotonic() - started) - generation.waited
+                ran_out = ""
                 if spent > limits.wall_seconds:
-                    _gave_up(generation, f"after {spent / 60:.0f} minutes")
-                    break
-                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
+                    ran_out = f"after {spent / 60:.0f} minutes"
+                elif generation.output_bytes > limits.output_bytes:
+                    ran_out = "with too much output to read"
+                else:
+                    written = _written(generation)
+                    if limits.completion_tokens and written > limits.completion_tokens:
+                        ran_out = f"after writing about {written:,} tokens"
+                if ran_out:
+                    offered, payload = _wrap_up(generation, ran_out, payload)
+                    wrapping_up = True
             accumulator = tools_service.ToolCallAccumulator()
             # Text the model produced in *this* round, needed separately from
             # generation.content when echoing the assistant turn back.
@@ -582,29 +596,37 @@ async def _run(generation: Generation) -> None:
             # not. The count is of *consecutive* stops.
             generation.nudges = 0
 
-            if round_number == budget:
-                # Out of rounds with the model still asking for tools. Recorded
-                # rather than silently dropped: an answer that stops here needs
-                # to be explicable.
+            if round_number >= budget:
+                # Out of rounds with the model still asking for tools.
                 #
-                # `budget`, not `MAX_ROUNDS`. The loop is sized by the budget on
-                # the line above and the message below has always reported it,
-                # but the comparison was against the global 3 -- so an agent
-                # 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.
+                # The tools are withdrawn and it is asked once more, rather than
+                # the reply simply ending here. A model that goes straight to
+                # tool calls has written no prose at all by this point, so
+                # breaking produced an empty bubble with an error line under it
+                # -- somebody watching a good piece of research get to its sixth
+                # search saw the whole thing thrown away. What it has gathered is
+                # in the transcript either way; one more request turns it into an
+                # answer.
+                #
+                # `budget`, not `MAX_ROUNDS`. The loop is sized by the budget
+                # above and the message below has always reported it, but the
+                # comparison was against the global 3 -- so an agent 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 {howmany} of tool calls without an answer."
-                        ),
-                    }
+                offered, payload = _wrap_up(
+                    generation,
+                    f"after {howmany} of tool calls",
+                    payload,
+                    name=calls[0]["name"],
                 )
-                generation.touch()
-                break
+                if wrapping_up:
+                    # Already asked, and it called a tool anyway -- which it
+                    # cannot do, since none were offered. A backstop, not a path.
+                    break
+                wrapping_up = True
+                continue
 
             # Parsed once, here, and shared by everything below: the approval
             # card, `policy.decide`, and the runner. See `_arguments_for`.
@@ -930,6 +952,40 @@ def _gave_up(generation, why: str) -> None:
     generation.touch()
 
 
+def _wrap_up(generation, why: str, payload: dict, *, name: str = "budget") -> tuple[list, dict]:
+    """A budget has run out. Withdraw the tools and ask for an answer.
+
+    Returns the empty tool list and the payload without its `tools` array, so
+    the next request is one the model can only answer.
+
+    Every budget used to end the reply where it was noticed, which is fine for a
+    model that narrates as it works and produces nothing at all for one that goes
+    straight to tool calls: an empty bubble with a red line under it, and a good
+    piece of research thrown away at its sixth search. What it has gathered is
+    already in the transcript, so one more request without tools turns it into
+    an answer. That is the same move `plan_submit` makes -- a turn should not end
+    mid-sentence -- and it is why the loop runs to `budget + 2`.
+
+    The event still goes in the transcript. The reader has to be able to tell an
+    answer the model chose to give from one it gave because it ran out of room,
+    and those read identically otherwise.
+    """
+    generation.tool_events.append(
+        {
+            "name": name,
+            "kind": "agent",
+            "status": "error",
+            "results": [],
+            "error": (
+                f"Stopped {why}. What follows is an answer from what had been "
+                "gathered by then; ask again to carry on."
+            ),
+        }
+    )
+    generation.touch()
+    return [], {key: value for key, value in payload.items() if key != "tools"}
+
+
 def _nudge(
     generation: Generation,
     context,

src/lembas/services/harness.py

@@ -149,6 +149,11 @@ def context_variables(
         # same sentence with a different number in it. Blank when there is no
         # ceiling at all, so the fragment vanishes rather than promising zero.
         "round_budget": str(settings_store.chat_rounds(db) or ""),
+        # The complement, and the gate on `core.keep_working`. Exactly one of
+        # the two is ever set: a model told it has a budget rations it and stops
+        # early to report progress, and one told to keep going does the work.
+        # Not rendered anywhere either.
+        "unbounded": "" if settings_store.chat_rounds(db) else "yes",
         "memory_limit": str(memories_service.MAX_MEMORY_CHARS),
         "tool_names": _tool_names(offered),
         "memories": memories_service.block(db, user) if "memory" in families else "",
@@ -219,8 +224,11 @@ def _agent_values(db: DBSession, chat, user) -> dict[str, str]:
         "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.
+        # invites it to ration one. `unbounded` is its complement and is what
+        # `core.keep_working` is gated on, so an agent chat always gets the
+        # keep-going half whatever the instance setting says.
         "round_budget": "",
+        "unbounded": "yes",
         "project_files": _project_files(db, chat, context, settings_store, index_service),
         # Already resolved on the context, from one primary-key lookup in
         # `agent_session.resolve`. A plan the model cannot see is a plan it

src/lembas/services/prompts.py

@@ -131,9 +131,20 @@ VARIABLES: tuple[Variable, ...] = (
     Variable(
         "round_budget",
         "Round budget applies",
-        "Set in an ordinary chat and blank in an agent chat. Nothing renders it; "
-        "it exists so a fragment can say `requires=('round_budget',)` and appear "
-        "for one and not the other.",
+        "Set when an administrator has put a ceiling on an ordinary chat's tool "
+        "rounds, and blank otherwise — including in every agent chat. Nothing "
+        "renders it; it exists so a fragment can say "
+        "`requires=('round_budget',)` and appear only where there is a budget "
+        "worth planning within.",
+    ),
+    Variable(
+        "unbounded",
+        "No round budget",
+        "The exact complement of the one above: set whenever `round_budget` is "
+        "blank. Nothing renders this either. Two gates rather than one because "
+        "what is worth telling a model with a budget and what is worth telling "
+        "one that should work until the job is done are different sentences, "
+        "not the same sentence with a different number in it.",
     ),
     Variable(
         "memory_limit",
@@ -656,18 +667,22 @@ BUILTIN: tuple[Fragment, ...] = (
         label="Working until it is done",
         group=GROUP_CORE,
         order=111,
-        families=("agent",),
-        hint="An agent chat only, and the counterpart to the round budget above. "
-        "A model told it has a budget rations it and stops early to report "
-        "progress; the step count here is a runaway backstop, not an "
-        "allowance, and saying so is what makes a long piece of work run.",
+        when_tools=True,
+        requires=("unbounded",),
+        hint="The counterpart to the round budget above, and exactly one of the "
+        "two ever appears: `unbounded` is set precisely when `round_budget` is "
+        "not. A model told it has a budget rations it and stops early to report "
+        "progress; where the number is a runaway backstop rather than an "
+        "allowance, saying so is what makes a long piece of work run. An agent "
+        "chat always gets this one; an ordinary chat gets it whenever an "
+        "administrator has set no ceiling, which is now the default.",
         default=(
             "Keep working until the task is actually done. You are not rationing a "
             "round budget: call tools as many times as the work needs, one step "
             "informing the next. What ends a reply is finishing it, being stopped, or "
-            "running past the time and output an administrator allowed — and if that "
-            "happens you are told so and can be asked to carry on. Do not stop halfway "
-            "to report progress and wait to be told to continue."
+            "running out of room — and if you run out you are told so, asked for an "
+            "answer from what you have, and can be asked to carry on afterwards. Do "
+            "not stop halfway to report progress and wait to be told to continue."
         ),
     ),
     Fragment(

src/lembas/services/settings_store.py

@@ -25,7 +25,7 @@ AUDIO = "audio"
 # Used when nothing is stored. `services/tools.py:MAX_ROUNDS` is the same number
 # and exists for callers with no session -- this module is where the setting is
 # read, and the two are asserted equal by a test so they cannot drift.
-DEFAULT_CHAT_ROUNDS = 5
+DEFAULT_CHAT_ROUNDS = 0
 SEARCH = "search"
 PROMPTS = "prompts"
 AGENTS = "agents"
@@ -53,11 +53,21 @@ def _general_defaults() -> dict[str, Any]:
         # model saying it has what it needs. This only catches the case where it
         # never says so.
         #
-        # Five rather than one because several built-in tools are two-step pairs
-        # -- knowledge_get and notes_get read a document "by the id a search
-        # returned" -- so a ceiling of one makes the second half unreachable and
-        # the library searchable but not readable. Zero means no ceiling.
-        "max_chat_rounds": 5,
+        # Zero, meaning no ceiling, and the loop falls back to MAX_TOOL_ROUNDS
+        # as a runaway backstop -- the same shape `Limits.steps` has for an agent
+        # chat. It was 1, then 5, and both were the same mistake at different
+        # scales: a number low enough to be reached by ordinary work is not a
+        # ceiling, it is a schedule, and it overrides the model's judgement on
+        # every turn rather than catching a runaway. Five was reached by a small
+        # local model doing a genuinely good piece of research -- six searches,
+        # each one informed by the last -- and the reply ended there.
+        #
+        # What actually bounds an ordinary chat is the context window
+        # (`CONTEXT_HEADROOM`), which is a real limit rather than a guess at how
+        # much looking-up a question deserves. An administrator who wants a
+        # ceiling can still set one, and `core.rounds` then tells the model it
+        # has one; with none, `core.keep_working` tells it to work until done.
+        "max_chat_rounds": 0,
     }
 
 

src/lembas/services/tools.py

@@ -58,15 +58,21 @@ log = logging.getLogger(__name__)
 # searching is the answer, searching until the context runs out at a full
 # request each.
 #
-# It was briefly 1, which is low enough to stop being a ceiling and start being
-# a schedule: it overrode the model's judgement on every turn rather than
-# catching a runaway. Worse, several built-ins are two-step pairs --
-# `knowledge_get` and `notes_get` read a document "by the id a search returned"
-# -- so one round left the library searchable and not readable.
+# It was 1, then 5, and now 0 meaning no ceiling at all. Both numbers were the
+# same mistake at different scales: low enough to be reached by ordinary work is
+# low enough to be a schedule rather than a ceiling, overriding the model's
+# judgement on every turn instead of catching a runaway. One left the library
+# searchable and not readable, since `knowledge_get` and `notes_get` read a
+# document "by the id a search returned". Five ended a piece of research at its
+# sixth search.
+#
+# What bounds an ordinary chat now is the context window, and the loop falls
+# back to `generation.MAX_TOOL_ROUNDS` as a runaway backstop -- the shape
+# `Limits.steps` already had for an agent chat.
 #
 # `settings_store.chat_rounds()` is what the loop and the harness read; this is
 # the fallback for callers with no session, and a test pins the two together.
-MAX_ROUNDS = 5
+MAX_ROUNDS = 0
 
 # Tool families, matching the per-model capability flags and the permission
 # keys. The three names differ by prefix only, which is deliberate: adding a