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A ceiling for a chat, and a nudge for an agent that stops early

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MAX_ROUNDS = 1 was wrong, and wrong in a way worth writing down. The loop
already ends the moment a round comes back with no tool calls -- that is the
model saying it has what it needs, and it is the termination condition every
agentic harness uses. A round limit was never a schedule; it exists to catch the
case where the model never says so. One is low enough to stop being a ceiling
and start being a schedule: it overrode the model's judgement on every single
turn.

And it broke something concrete. 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. That is not an edge
case, it is the library working at half depth, and I understated it as "cannot
search the web and then read a result" when the change went in.

It is a setting now, under General, default 5, with 0 meaning no ceiling. The
loop and the harness both read settings_store.chat_rounds, so the model is never
told a budget that is not its own; tools.MAX_ROUNDS is the fallback for callers
with no session and a test pins the two equal. core.rounds goes back to naming
the number, and vanishes entirely when there is no ceiling rather than promising
zero rounds.

The other half of "let it decide how long to go": an agent reply that ends while
its plan still has open tasks is asked once to carry on. Only against a plan,
because that is the one thing there is to be objectively wrong about -- a model
with no plan that says it has finished is believed, and arguing with it would be
guessing. At most twice in a row, with the count reset the moment it calls a
tool again, so the bound is on consecutive stops rather than on stops in total.
Never in Plan mode and never past plan_submit, which ends the turn on purpose.
Giving up is recorded as an event rather than left silent.

The model's own words go back with the nudge, which turned up a real bug on the
way: ReasoningSplitter holds back a few characters against a <think> tag split
across chunks, so round_text at the end of a round was missing its tail. That
text is echoed as an assistant turn for tool rounds too, so a model has been
occasionally asked to continue from a transcript where it trailed off
mid-sentence. Flushed per round now.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
This commit is contained in:
Jaroslav Beneš
2026-08-03 12:41:36 +02:00
parent 0452e742e8
commit bf9287493b
12 changed files with 491 additions and 45 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/lembas/api/admin.py
+4
View File
@@ -59,6 +59,7 @@ async def save_general(
allow_signup: bool = Form(False),
system_prompt: str = Form(""),
compact_threshold: int = Form(95),
max_chat_rounds: int = Form(5),
) -> Response:
"""Save instance settings.
@@ -77,6 +78,9 @@ async def save_general(
"compact_threshold": (
0 if compact_threshold <= 0 else min(max(compact_threshold, 50), 99)
),
# Floor of 0, not 1: zero is how "no ceiling" is said, and the loop
# falls back to a runaway backstop rather than to this number.
"max_chat_rounds": min(max(max_chat_rounds, 0), 100),
},
)
log.info("registration %s by %s", "opened" if allow_signup else "closed", user.email)
src/lembas/api/admin_agents.py
+2
View File
@@ -78,6 +78,7 @@ async def save_agents(
index_chars: int = Form(2000),
instructions_enabled: bool = Form(False),
instructions_chars: int = Form(4000),
nudge_unfinished: bool = Form(False),
) -> Response:
settings_store.update(
db,
@@ -110,6 +111,7 @@ async def save_agents(
"index_chars": min(max(index_chars, 0), 20_000),
"instructions_enabled": instructions_enabled,
"instructions_chars": min(max(instructions_chars, 0), 20_000),
"nudge_unfinished": nudge_unfinished,
},
key=settings_store.AGENTS,
)
src/lembas/services/generation.py
+146 -4
View File
@@ -30,7 +30,7 @@ from lembas.db.models import KIND_AGENT, ROLE_ASSISTANT, ROLE_USER, Chat, Messag
from lembas.db.session import session_scope
from lembas.services import chat as chat_service
from lembas.services import compaction as compaction_service
from lembas.services import interaction, tokens, tool_labels
from lembas.services import interaction, settings_store, tokens, tool_labels
from lembas.services import metrics as metrics_service
from lembas.services import prompts as prompts_service
from lembas.services import tools as tools_service
@@ -58,6 +58,17 @@ RENDER_INTERVAL = 0.1
# gets the final frames, then are pruned.
KEEP_FINISHED = timedelta(minutes=5)
# What "no ceiling" resolves to. A setting of 0 means an administrator does not
# want a round limit, but a loop needs *some* stop or a model stuck calling one
# cheap tool runs until the process does. This is high enough never to be
# reached by anything but that.
MAX_TOOL_ROUNDS = 200
# How many times in a row a reply that stopped with plan tasks outstanding may
# be told to carry on. Two, so a model that genuinely has nothing left to do can
# say so and be believed rather than argued with indefinitely.
MAX_NUDGES = 2
@dataclass
class Generation:
@@ -142,6 +153,10 @@ class Generation:
# -- the one frame that reaches a browser after a reply is over.
drained: bool = False
injected_ids: list[str] = field(default_factory=list)
# How many times *in a row* this reply has ended with plan tasks still open
# and been told to carry on. Reset the moment it calls a tool again, so the
# count is of consecutive stops rather than of stops in total.
nudges: int = 0
def touch(self) -> None:
self.version += 1
@@ -363,11 +378,18 @@ async def _run(generation: Generation) -> None:
# vision model, a plain string to anything else, or the endpoint
# rejects the whole request.
vision = chat_service.model_supports(db, chat, "vision")
chat_rounds = settings_store.chat_rounds(db)
nudge_enabled = bool(settings_store.agents(db).get("nudge_unfinished"))
generation.prompt_estimate = tokens.estimate_request(payload)
limits = tool_context.agent.limits if tool_context.agent else None
budget = limits.steps if limits else tools_service.MAX_ROUNDS
# A ceiling, not a schedule -- the loop below ends the moment a round
# produces no tool calls, which is the model saying it is done. Zero
# means an ordinary chat has no ceiling either; `steps` is already a
# runaway backstop rather than a budget, so an agent chat is bounded by
# tokens and the clock instead.
budget = limits.steps if limits else (chat_rounds or MAX_TOOL_ROUNDS)
for round_number in range(budget + 1):
generation.rounds = round_number + 1
@@ -441,9 +463,47 @@ async def _run(generation: Generation) -> None:
# Let followers and other tasks run between chunks.
await asyncio.sleep(0)
# The round is over, so anything the splitter is still holding back
# against a `<think>` tag split across chunks is not a tag. Flushed
# here rather than only after the loop, because `round_text` is
# echoed back as an assistant turn -- for a tool round and for a
# nudge alike -- and a turn missing its last few words is a turn the
# model is asked to continue from having apparently trailed off.
for kind, piece in splitter.flush():
if kind == REASONING:
generation.reasoning.append(piece)
else:
generation.content.append(piece)
round_text.append(piece)
calls = accumulator.calls
if generation.stopped or not calls:
break
# The model says it is done. Believe it -- unless this is an
# agent chat whose plan still has work in it, in which case ask
# once. `_nudge` returns the turn to send, or None.
added = _nudge(
generation,
tool_context,
enabled=nudge_enabled,
stopped=generation.stopped,
round_number=round_number,
budget=budget,
)
if added is None:
break
# Its own words go back with the nudge. Without the assistant
# turn the model is asked to carry on from a transcript in which
# it never spoke, and repeats itself.
said = "".join(round_text).strip()
messages = [*payload["messages"]]
if said:
messages.append({"role": "assistant", "content": said})
payload = {**payload, "messages": [*messages, added]}
continue
# Something was called, so whatever it said it had finished, it had
# 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
@@ -631,7 +691,6 @@ async def _warm_project(generation: Generation) -> None:
the new one was silently never warmed on any chat that had a listing --
which is to say, on every chat after the first reply.
"""
from lembas.services import settings_store
from lembas.services.agent import index as index_service
from lembas.services.agent import instructions as instructions_service
from lembas.services.agent import session as agent_session
@@ -758,6 +817,89 @@ def _gave_up(generation, why: str) -> None:
generation.touch()
def _nudge(
generation: Generation,
context,
*,
enabled: bool,
stopped: bool,
round_number: int,
budget: int,
) -> dict | None:
"""The turn telling an agent to carry on, or None to let the reply end.
A model that stops with work outstanding is the failure `core.keep_working`
is worded against, and prompting is the cheaper half of the fix. This is the
other half, and it only fires where there is something objective to check
against: an open task on the chat's own plan. Without a plan there is
nothing to be wrong about, so nothing happens -- a model that has genuinely
finished must be able to say so and be believed.
Every "no" is a plain None:
* the setting is off, or the reply was stopped, or it errored;
* this is not an agent chat, or is one in Plan mode -- `plan_submit` ends
the turn deliberately and nudging past it would be arguing with the whole
point of the mode;
* there is no plan, or every task on it is done or dropped;
* there is no round left to carry on in, or it has already been asked
MAX_NUDGES times in a row.
The last one is recorded rather than silent. A reply that stopped twice with
work outstanding is worth being able to see afterwards.
"""
agent = getattr(context, "agent", None)
if not enabled or stopped or generation.error or agent is None:
return None
if agent.mode == agent_policy.MODE_PLAN or generation.plan_final:
return None
plan = generation.plan if generation.plan is not None else agent.plan
open_tasks = [
task
for phase in (plan or {}).get("phases", [])
for task in phase.get("tasks", [])
if task.get("status") not in ("done", "dropped")
]
if not open_tasks:
return None
if round_number >= budget:
return None
if generation.nudges >= MAX_NUDGES:
generation.tool_events.append(
{
"name": "plan_update",
"kind": "plan",
"status": "error",
"error": (
f"Stopped with {len(open_tasks)} task(s) still open on the "
f"plan, after being asked twice to carry on."
),
"results": [],
}
)
generation.touch()
return None
generation.nudges += 1
remaining = "\n".join(f"- {task['id']} {task['text']}" for task in open_tasks[:8])
# A user turn, and phrased as the reader would phrase it. Everything else
# this codebase injects is quoted and attributed because it came out of a
# file or a machine; this is the application speaking on the reader's behalf
# about the reader's own plan, which is the one case where that is honest.
return {
"role": "user",
"content": (
"The plan still has work in it:\n"
f"{remaining}\n\n"
"Carry on with the next one. If something here cannot be done, or is "
"no longer worth doing, mark it dropped with plan_update and say why "
"— do not leave it open and stop."
),
}
def _written(generation: Generation) -> int:
"""How much this reply has written so far, in tokens, reported or estimated.
src/lembas/services/harness.py
+9 -5
View File
@@ -124,12 +124,16 @@ def context_variables(
"instance_name": str(settings_store.get(db, "instance_name") or "LLeMbas"),
"user_name": (user.name or "") if user is not None else "",
"model_name": "",
"max_rounds": str(tools_service.MAX_ROUNDS),
# What this request will actually allow, so the model is not told a
# number that is not its own. `tools_service.MAX_ROUNDS` is only the
# fallback for callers with no session.
"max_rounds": str(settings_store.chat_rounds(db) or 0),
# 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),
# chat has a ceiling worth planning within, an agent chat is told to
# keep going instead, and those are different sentences rather than the
# 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 ""),
"memory_limit": str(memories_service.MAX_MEMORY_CHARS),
"tool_names": _tool_names(offered),
"memories": memories_service.block(db, user) if "memory" in families else "",
src/lembas/services/prompts.py
+14 -10
View File
@@ -628,17 +628,21 @@ BUILTIN: tuple[Fragment, ...] = (
order=110,
when_tools=True,
requires=("round_budget",),
hint="An ordinary chat only. It gets ONE round of tool calls, and the "
"thing worth saying about one round is 'ask for everything at once' — "
"which is different in kind from what is true of an agent chat's two "
"hundred, not a different number in the same sentence. So this is "
"gated on `round_budget`, which `_agent_values` blanks, and the agent "
"case is its own fragment below.",
variables=("max_rounds",),
hint="An ordinary chat only, and only when it has a ceiling at all. "
"What is worth telling a model with a budget is different in kind "
"from what is worth telling one that should keep going until the work "
"is done — not the same sentence with a different number in it — so "
"this is gated on `round_budget`, which `_agent_values` blanks and "
"which is also blank when an administrator has set no ceiling. The "
"agent case is its own fragment below.",
default=(
"You get one round of tool calls, and then you have to answer with what "
"came back. Ask for everything you need at once — several tools can be "
"called in the same round. If what comes back is not enough, say what you "
"would look up next rather than answering as though it were."
"You get at most {{max_rounds}} rounds of tool calls before you have to "
"answer with what you have. Several tools can be called in one round, so "
"ask for everything you need at once rather than one thing at a time. "
"Plan within that: two careful searches beat six that run out halfway. If "
"what comes back is not enough, say what you would look up next rather "
"than answering as though it were."
),
),
Fragment(
src/lembas/services/settings_store.py
+35
View File
@@ -21,6 +21,11 @@ from lembas.db.models import Setting
GENERAL = "general"
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
SEARCH = "search"
PROMPTS = "prompts"
AGENTS = "agents"
@@ -42,6 +47,17 @@ def _general_defaults() -> dict[str, Any]:
# Never fires for a model whose context_length is 0, since that is
# "unknown" rather than "small". See services/compaction.py.
"compact_threshold": 95,
# How many rounds of tool calls an ordinary chat may take before it has
# to answer with words. A **ceiling**, not a schedule: the loop already
# ends the moment a round comes back with no tool calls, which is the
# 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,
}
@@ -116,6 +132,11 @@ def _agents_defaults() -> dict[str, Any]:
# untrusted, and the fragment carrying it is where that is dealt with.
"instructions_enabled": True,
"instructions_chars": 4000,
# Whether a reply that ends while its plan still has open tasks is told
# once to carry on. Only ever fires against a plan, because that is the
# one thing there is to be objectively wrong about -- a model with no
# plan that says it has finished is believed.
"nudge_unfinished": True,
}
@@ -214,6 +235,20 @@ def get(db: DBSession, name: str, *, key: str = GENERAL) -> Any:
return get_group(db, key).get(name)
def chat_rounds(db: DBSession) -> int:
"""The ceiling on an ordinary chat's rounds of tool calls, clamped.
Zero is meaningful and is not clamped away: it means "no ceiling", the same
convention `index_chars` and `max_completion_tokens` use. Read through here
rather than from the group directly so the loop and the harness cannot
disagree about the number the model is told.
"""
stored = get_group(db, GENERAL).get("max_chat_rounds")
if stored is None:
return DEFAULT_CHAT_ROUNDS
return min(max(int(stored), 0), 100)
def update(db: DBSession, changes: dict[str, Any], *, key: str = GENERAL) -> dict[str, Any]:
"""Merge changes into a settings group and persist them."""
row = db.get(Setting, key)
src/lembas/services/tools.py
+15 -9
View File
@@ -50,16 +50,22 @@ log = logging.getLogger(__name__)
# instead, which is two orders of magnitude larger, because an agent reply is
# meant to run until the work is done.
#
# One, deliberately. 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. Several tools can still be called *within* that round,
# which is the thing worth telling the model -- see `core.rounds`.
# A **ceiling, not a schedule.** The loop ends the moment a round comes back
# with no tool calls -- that is the model saying it has what it needs, and it is
# the same termination condition every agentic harness uses. This number only
# catches the case where it never says so: a small model that has decided
# searching is the answer, searching until the context runs out at a full
# request each.
#
# The trade is real and worth naming: a 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.
MAX_ROUNDS = 1
# 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.
#
# `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
# Tool families, matching the per-model capability flags and the permission
# keys. The three names differ by prefix only, which is deliberate: adding a
src/lembas/web/templates/admin/agents.html
+15
View File
@@ -155,6 +155,21 @@
<input class="input" id="max_total_output_bytes" name="max_total_output_bytes"
value="{{ values.max_total_output_bytes }}" inputmode="numeric">
</div>
<div class="field">
<label class="checkbox">
<input type="checkbox" name="nudge_unfinished"
{{ 'checked' if values.nudge_unfinished }}>
<span>Ask it to carry on when it stops with tasks outstanding</span>
</label>
<p class="field__hint">
Only ever against a plan, and only while tasks on it are still open —
that is the one thing there is to be objectively wrong about. A reply
with no plan that says it has finished is believed. It is asked at most
twice in a row, and if it stops a third time that is recorded in the
transcript rather than argued with.
</p>
</div>
<div class="field">
<label class="field__label" for="max_steps">Most rounds of tool calls</label>
<input class="input" id="max_steps" name="max_steps"
src/lembas/web/templates/admin/general.html
+23
View File
@@ -64,6 +64,29 @@
</div>
</section>
<section class="card">
<h2 class="card__title">Tool calls in an ordinary chat</h2>
<p class="card__lede">
A model ends its own turn the moment it stops asking for tools — that is
it saying it has what it needs, and nothing here overrides it. This is a
ceiling for the case where it never says so.
</p>
<div class="field">
<label class="field__label" for="max-chat-rounds">Most rounds of tool calls</label>
<input class="input" id="max-chat-rounds" name="max_chat_rounds" type="number"
min="0" max="100" value="{{ values.max_chat_rounds }}">
<p class="field__hint">
Several tools can be called in one round, so this is not a count of
tools. Leave room for at least two: <code>knowledge_get</code> and
<code>notes_get</code> read a document by an id a <em>search</em>
returned, so a ceiling of one leaves the library searchable and not
readable. <code>0</code> means no ceiling, which is how an agent chat
already works — those are bounded under
<a href="/admin/agents">Agents</a> by time and tokens instead.
</p>
</div>
</section>
<section class="card">
<h2 class="card__title">
Registration
tests/test_agent_plan.py
+157
View File
@@ -351,3 +351,160 @@ def test_a_plan_pointer_at_another_chats_message_is_ignored(db, owner):
db.commit()
assert session.resolve(db, chat, owner).plan == {}
# --- Being asked to carry on ------------------------------------------------------
def _stub(rounds, seen):
async def stream_chat(_endpoint, payload):
seen.append(payload)
for chunk in rounds[min(len(seen) - 1, len(rounds) - 1)]:
yield chunk
return stream_chat
def _text(text):
return {"choices": [{"delta": {"content": text}}]}
def _call(name, arguments):
return {"choices": [{"delta": {"tool_calls": [
{"index": 0, "id": "c1", "function": {"name": name, "arguments": arguments}}]}}]}
def _reply(db, chat):
from lembas.services import generation as generation_service
db.add(Message(chat_id=chat.id, role="user", content="do it", complete=True))
db.commit()
assistant = Message(chat_id=chat.id, role=ROLE_ASSISTANT, content="", complete=False)
db.add(assistant)
db.commit()
return generation_service.Generation(chat_id=chat.id, message_id=assistant.id)
async def _run(monkeypatch, generation, rounds, seen):
from lembas.services import generation as generation_service
monkeypatch.setattr(generation_service, "stream_chat", _stub(rounds, seen))
async def _no_title(*_a, **_k):
return ""
monkeypatch.setattr("lembas.services.chat.generate_title", _no_title)
await generation_service._run(generation)
async def test_stopping_with_open_tasks_is_answered_with_carry_on(db, owner, monkeypatch):
"""The half prompting cannot do. core.keep_working tells it not to stop
halfway; this is what happens when it does anyway."""
chat = _agent_chat(db, owner, mode=policy.MODE_AUTO)
_with_plan(db, chat, V1)
generation = _reply(db, chat)
seen: list[dict] = []
await _run(monkeypatch, generation, [[_text("I have done the first bit.")],
[_text("All finished.")]], seen)
# Three requests: the reply, then a nudge, then a second nudge -- this
# model never marks anything done, so the plan stays open and it is asked
# until MAX_NUDGES runs out. That it gives up is the next test.
assert len(seen) == 3, "it was asked again"
nudge = seen[1]["messages"][-1]
assert nudge["role"] == "user"
assert "still has work in it" in nudge["content"]
assert "Rotate it" in nudge["content"], "and says which tasks"
# Its own words go back with it, or it is asked to carry on from a
# transcript in which it never spoke.
assert seen[1]["messages"][-2]["content"] == "I have done the first bit."
async def test_a_finished_plan_is_believed(db, owner, monkeypatch):
chat = _agent_chat(db, owner, mode=policy.MODE_AUTO)
done = plans.build(title="x", phases=[{"title": "P", "tasks": ["a"]}])
done["phases"][0]["tasks"][0]["status"] = "done"
_with_plan(db, chat, done)
generation = _reply(db, chat)
seen: list[dict] = []
await _run(monkeypatch, generation, [[_text("All done.")]], seen)
assert len(seen) == 1
async def test_a_chat_with_no_plan_is_never_nudged(db, owner, monkeypatch):
"""There is nothing to be objectively wrong about, so a model that says it
has finished is believed."""
chat = _agent_chat(db, owner, mode=policy.MODE_AUTO)
generation = _reply(db, chat)
seen: list[dict] = []
await _run(monkeypatch, generation, [[_text("All done.")]], seen)
assert len(seen) == 1
async def test_plan_mode_is_never_nudged(db, owner, monkeypatch):
"""plan_submit ends the turn deliberately. Nudging past it would argue with
the whole point of the mode."""
chat = _agent_chat(db, owner, mode=policy.MODE_PLAN)
_with_plan(db, chat, V1)
generation = _reply(db, chat)
seen: list[dict] = []
await _run(monkeypatch, generation, [[_text("Here is what I would do.")]], seen)
assert len(seen) == 1
async def test_it_gives_up_after_two_and_says_so(db, owner, monkeypatch):
"""A model that has nothing left to do must be able to say so and be
believed rather than argued with indefinitely -- and a reply that stopped
twice with work outstanding is worth being able to see afterwards."""
chat = _agent_chat(db, owner, mode=policy.MODE_AUTO)
_with_plan(db, chat, V1)
generation = _reply(db, chat)
seen: list[dict] = []
await _run(monkeypatch, generation, [[_text("Nothing more from me.")]], seen)
from lembas.services import generation as generation_service
assert len(seen) == generation_service.MAX_NUDGES + 1
assert generation.tool_events[-1]["status"] == "error"
assert "asked twice" in generation.tool_events[-1]["error"]
async def test_calling_a_tool_again_resets_the_count(db, owner, monkeypatch):
"""The count is of consecutive stops. A model that stops, is nudged, does
some work and stops again has not run out of patience."""
chat = _agent_chat(db, owner, mode=policy.MODE_AUTO)
_with_plan(db, chat, V1)
generation = _reply(db, chat)
seen: list[dict] = []
await _run(
monkeypatch,
generation,
[[_text("Pausing.")], [_call("file_list", '{"path": "."}')], [_text("Pausing again.")]],
seen,
)
# Without the reset this run would end after two nudges, at three requests.
# The tool call in the middle clears the count, so it gets more than that --
# which is the property, and does not depend on where the stub stops.
assert len(seen) > 3
async def test_the_switch_turns_it_off(db, owner, monkeypatch):
from lembas.services import settings_store
settings_store.update(db, {"nudge_unfinished": False}, key=settings_store.AGENTS)
chat = _agent_chat(db, owner, mode=policy.MODE_AUTO)
_with_plan(db, chat, V1)
generation = _reply(db, chat)
seen: list[dict] = []
await _run(monkeypatch, generation, [[_text("All done.")]], seen)
assert len(seen) == 1
tests/test_generation_tools.py
+55 -13
View File
@@ -151,6 +151,10 @@ async def test_a_model_that_only_ever_calls_tools_is_stopped(db, user_id, monkey
chat_id, message_id = _chat_with_tools(db, user_id)
monkeypatch.setattr("lembas.services.search.run", _empty_search)
# Set explicitly rather than read from the constant: a test that reads the
# number under test passes whatever the number becomes, which is the
# assertion nobody wanted.
settings_store.update(db, {"max_chat_rounds": 3})
payloads = []
monkeypatch.setattr(
@@ -163,30 +167,27 @@ async def test_a_model_that_only_ever_calls_tools_is_stopped(db, user_id, monkey
generation = generation_service.Generation(chat_id=chat_id, message_id=message_id)
await generation_service._run(generation)
# One round that may call tools, then one that has to answer with words.
# Spelled out rather than derived from the constant: a test that reads
# MAX_ROUNDS passes whatever MAX_ROUNDS becomes, which is exactly the
# assertion nobody wanted.
assert tools_service.MAX_ROUNDS == 1
assert len(payloads) == 2
# The ceiling, plus the round that has to answer with words.
assert len(payloads) == 4
# Recorded rather than silently dropped: an answer that stops here has to
# be explicable.
assert generation.tool_events[-1]["status"] == "error"
assert "one round" in generation.tool_events[-1]["error"]
assert "3 rounds" in generation.tool_events[-1]["error"]
async def test_a_prompt_queued_during_a_one_round_reply_waits_for_its_own(
db, user_id, monkeypatch
):
"""`_inject` only takes a prompt in while there is a round left to answer in,
and with one round there never is -- so a queued message is not swallowed
into a reply that then has no chance to address it. It waits for `_drain`,
which always gives it a reply of its own.
"""`_inject` only takes a prompt in while there is a round left to answer
in. With a ceiling of one there never is, so a queued message is not
swallowed into a reply that then has no chance to address it -- it waits for
`_drain`, which always gives it a reply of its own.
No code change went with this; it falls out of the guard. The test is here
because "it happens to work" and "it is meant to work" look the same until
One is no longer the default, but it is still a setting somebody can choose,
and "it happens to work" and "it is meant to work" look the same until
somebody changes the guard.
"""
settings_store.update(db, {"max_chat_rounds": 1})
from lembas.db.models import Message
from lembas.services import chat as chat_service
@@ -381,3 +382,44 @@ async def test_a_custom_tool_runs_inside_the_loop(db, user_id, monkeypatch, mock
assert tool_turns[0]["content"] == "Sunny in Minas Tirith."
assert generation.tool_events[0]["kind"] == "custom"
assert generation.tool_events[0]["label"] == "Weather"
def test_the_default_and_the_fallback_cannot_drift(db):
"""`tools.MAX_ROUNDS` exists for callers with no session; the setting is
what the loop and the harness read. Two numbers meaning one thing is how
a model gets told a budget it does not have."""
assert tools_service.MAX_ROUNDS == settings_store.DEFAULT_CHAT_ROUNDS
assert settings_store.chat_rounds(db) == tools_service.MAX_ROUNDS
async def test_a_ceiling_of_zero_does_not_mean_zero_rounds(db, user_id, monkeypatch):
"""It means no ceiling. Read carelessly it would mean the model never gets
to call anything, which is the opposite."""
settings_store.update(db, {"enabled": True}, key=settings_store.SEARCH)
settings_store.update(db, {"max_chat_rounds": 0})
chat_id, message_id = _chat_with_tools(db, user_id)
monkeypatch.setattr("lembas.services.search.run", _empty_search)
payloads = []
monkeypatch.setattr(
generation_service,
"stream_chat",
_stub_stream(
[[_tool_call_chunk("web_search", '{"query": "x"}')], [_text_chunk("Done.")]],
payloads,
),
)
monkeypatch.setattr("lembas.services.chat.generate_title", _never_called_title)
generation = generation_service.Generation(chat_id=chat_id, message_id=message_id)
await generation_service._run(generation)
assert generation.text == "Done."
assert len(payloads) == 2, "it called a tool and then answered, uninterrupted"
def test_the_ceiling_is_clamped(db):
settings_store.update(db, {"max_chat_rounds": 9999})
assert settings_store.chat_rounds(db) == 100
settings_store.update(db, {"max_chat_rounds": -5})
assert settings_store.chat_rounds(db) == 0
tests/test_harness.py
+16 -4
View File
@@ -360,15 +360,27 @@ def test_a_plain_chat_is_told_nothing_about_files(db, owner):
# --- One round, or as many as it takes ----------------------------------------
def test_a_plain_chat_is_told_it_has_one_round(db, owner):
"""And is told to ask for everything at once, which is the advice that
matters when there is only one."""
def test_a_plain_chat_is_told_its_real_ceiling(db, owner):
"""The number it is actually given, not a constant -- a model told it has
five rounds and cut off after three has been lied to about its own budget."""
settings_store.update(db, {"max_chat_rounds": 3})
text = harness.compose(db, owner, _tools("web_search"))
assert "one round of tool calls" in text
assert "at most 3 rounds" in text
assert "Keep working until the task is actually done" not in text
def test_no_ceiling_means_no_round_budget_is_claimed(db, owner):
"""Zero is "no ceiling", and a fragment promising zero rounds would be worse
than none at all."""
settings_store.update(db, {"max_chat_rounds": 0})
text = harness.compose(db, owner, _tools("web_search"))
# `core.interjection` also mentions rounds, so this asserts on the budget
# sentence rather than on the word.
assert "at most" not in text
def test_an_agent_chat_is_told_to_keep_going_instead(db, owner):
"""The two cannot be one fragment with a number in it. A model told it has
a budget rations it; the step count is a runaway backstop, and rationing