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LLeMbas/tests/test_generation_tools.py
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Jaroslav Beneš bc141eae10 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>
2026-08-03 11:11:05 +02:00

384 lines
14 KiB
Python

"""The tool loop: one reply, several requests."""
from __future__ import annotations
from lembas.db.models import ROLE_ASSISTANT, Chat, Connection, Message, Model
from lembas.services import generation as generation_service
from lembas.services import settings_store
from lembas.services import tools as tools_service
from lembas.services.search.base import SearchResult
def _chat_with_tools(db, user_id):
connection = Connection(name="c", base_url="http://127.0.0.1:1", api_key_encrypted="")
db.add(connection)
db.commit()
db.add(Model(connection_id=connection.id, model_id="m", capabilities_json={"tools": True}))
db.commit()
chat = Chat(user_id=user_id, model_id="m", connection_id=connection.id)
db.add(chat)
db.commit()
db.add(Message(chat_id=chat.id, role="user", content="What is a mallorn?", complete=True))
db.commit()
assistant = Message(chat_id=chat.id, role=ROLE_ASSISTANT, content="", complete=False)
db.add(assistant)
db.commit()
return chat.id, assistant.id
def _tool_call_chunk(name: str, arguments: str) -> dict:
return {
"choices": [
{"delta": {"tool_calls": [{"index": 0, "id": "c1", "function": {
"name": name, "arguments": arguments}}]}}
]
}
def _text_chunk(text: str) -> dict:
return {"choices": [{"delta": {"content": text}}]}
def _stub_stream(rounds, seen_payloads):
"""A stream_chat that returns a different scripted round each time."""
async def stream_chat(_endpoint, payload):
seen_payloads.append(payload)
for chunk in rounds[min(len(seen_payloads) - 1, len(rounds) - 1)]:
yield chunk
return stream_chat
async def test_a_tool_call_produces_a_second_request(db, user_id, monkeypatch):
"""The whole point: one reply, two round trips, with the search result in
the second one's messages."""
settings_store.update(db, {"enabled": True}, key=settings_store.SEARCH)
chat_id, message_id = _chat_with_tools(db, user_id)
async def fake_search(_config, _query, *, limit=None):
return [SearchResult("Mallorn", "https://tolkien.test/mallorn", "A golden tree.")]
monkeypatch.setattr("lembas.services.search.run", fake_search)
payloads = []
monkeypatch.setattr(
generation_service,
"stream_chat",
_stub_stream(
[
[_tool_call_chunk("web_search", '{"query": "mallorn"}')],
[_text_chunk("A mallorn is a golden tree.")],
],
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 len(payloads) == 2, "the model asked for a tool, so it must be asked again"
assert generation.text == "A mallorn is a golden tree."
# The second request carries the assistant's own call back, then the result.
followups = payloads[1]["messages"][-2:]
assert followups[0]["tool_calls"][0]["function"]["name"] == "web_search"
assert followups[1]["role"] == "tool"
assert "https://tolkien.test/mallorn" in followups[1]["content"]
# And the reader gets to see what it looked up.
assert generation.tool_events[0]["query"] == "mallorn"
assert generation.tool_events[0]["results"][0]["url"] == "https://tolkien.test/mallorn"
async def test_the_tools_array_is_absent_without_the_capability(db, user_id, monkeypatch):
chat_id, message_id = _chat_with_tools(db, user_id)
# Search enabled, but the model is not marked as supporting tools.
settings_store.update(db, {"enabled": True}, key=settings_store.SEARCH)
model = db.query(Model).first()
model.capabilities_json = {}
db.commit()
payloads = []
monkeypatch.setattr(
generation_service, "stream_chat", _stub_stream([[_text_chunk("hi")]], payloads)
)
monkeypatch.setattr("lembas.services.chat.generate_title", _never_called_title)
await generation_service._run(
generation_service.Generation(chat_id=chat_id, message_id=message_id)
)
assert "tools" not in payloads[0]
async def test_text_before_a_tool_call_is_kept(db, user_id, monkeypatch):
"""A model that narrates what it is about to look up must not lose that
when the results come back."""
settings_store.update(db, {"enabled": True}, key=settings_store.SEARCH)
chat_id, message_id = _chat_with_tools(db, user_id)
monkeypatch.setattr(
"lembas.services.search.run", _empty_search
)
monkeypatch.setattr(
generation_service,
"stream_chat",
_stub_stream(
[
[
_text_chunk("Let me look that up. "),
_tool_call_chunk("web_search", '{"query": "mallorn"}'),
],
[_text_chunk("Nothing found.")],
],
[],
),
)
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 == "Let me look that up. Nothing found."
async def test_a_model_that_only_ever_calls_tools_is_stopped(db, user_id, monkeypatch):
"""Otherwise a small model that has decided searching is the answer keeps
searching until the context runs out, at a full request each time."""
settings_store.update(db, {"enabled": True}, key=settings_store.SEARCH)
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"}')]], 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)
# 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
# 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"]
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.
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
somebody changes the guard.
"""
from lembas.db.models import Message
from lembas.services import chat as chat_service
settings_store.update(db, {"enabled": True}, key=settings_store.SEARCH)
chat_id, message_id = _chat_with_tools(db, user_id)
chat = db.get(Chat, chat_id)
queued = chat_service.create_message(db, chat, "user", "actually, do it the other way",
queued=True)
queued_id = queued.id
monkeypatch.setattr("lembas.services.search.run", _empty_search)
monkeypatch.setattr(
generation_service,
"stream_chat",
_stub_stream(
[[_tool_call_chunk("web_search", '{"query": "x"}')], [_text_chunk("Done.")]],
[],
),
)
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)
# The row, not the payload: it was handed to a fresh reply by `_drain`,
# which is what clears `queued`.
db.expire_all()
assert db.get(Message, queued_id).queued is False
assert generation.drained is True
async def test_tool_activity_is_stored_with_the_message(db, user_id, monkeypatch):
settings_store.update(db, {"enabled": True}, key=settings_store.SEARCH)
chat_id, message_id = _chat_with_tools(db, user_id)
async def fake_search(_config, _query, *, limit=None):
return [SearchResult("Mallorn", "https://tolkien.test/m", "A tree.")]
monkeypatch.setattr("lembas.services.search.run", fake_search)
monkeypatch.setattr(
generation_service,
"stream_chat",
_stub_stream(
[
[_tool_call_chunk("web_search", '{"query": "mallorn"}')],
[_text_chunk("Done.")],
],
[],
),
)
monkeypatch.setattr("lembas.services.chat.generate_title", _never_called_title)
await generation_service._run(
generation_service.Generation(chat_id=chat_id, message_id=message_id)
)
stored = db.get(Message, message_id)
db.refresh(stored)
assert stored.tool_calls_json[0]["query"] == "mallorn"
assert stored.complete is True
async def _empty_search(_config, _query, *, limit=None):
return []
async def _never_called_title(*_args, **_kwargs):
"""Auto-titling makes its own request; these tests are about the tool loop."""
return "A title"
# --- Progress and concurrency ------------------------------------------------
async def test_the_status_names_the_running_tool_and_is_cleared(db, user_id, monkeypatch):
"""A remote tool can take seconds with nothing streaming, and a silent
pause is exactly what a hang looks like."""
settings_store.update(db, {"enabled": True}, key=settings_store.SEARCH)
chat_id, message_id = _chat_with_tools(db, user_id)
seen: list[str] = []
async def fake_search(_config, _query, *, limit=None):
seen.append(generation.status)
return []
monkeypatch.setattr("lembas.services.search.run", fake_search)
monkeypatch.setattr(
generation_service,
"stream_chat",
_stub_stream(
[[_tool_call_chunk("web_search", '{"query": "mallorn"}')], [_text_chunk("Done.")]],
[],
),
)
generation = generation_service.Generation(chat_id=chat_id, message_id=message_id)
await generation_service._run(generation)
# In words, from services/tool_labels.py -- the same table the transcript
# and the approval card read. It used to say "Running web_search…".
assert seen == ["Running Web search…"]
assert generation.status == "", "and it is cleared once they are done"
async def test_results_stay_paired_with_their_calls_when_run_together(db, user_id, monkeypatch):
"""Indexed rather than appended as they finish: an endpoint matching on
tool_call_id would otherwise pair the right id with the wrong content."""
import asyncio
settings_store.update(db, {"enabled": True}, key=settings_store.SEARCH)
chat_id, message_id = _chat_with_tools(db, user_id)
async def slow_first(_config, query, *, limit=None):
# The first call finishes last, which is the whole point of the test.
await asyncio.sleep(0.02 if query == "first" else 0)
return [SearchResult(f"result for {query}", f"https://t.test/{query}", "")]
monkeypatch.setattr("lembas.services.search.run", slow_first)
two_calls = {
"choices": [
{"delta": {"tool_calls": [
{"index": 0, "id": "a", "function": {
"name": "web_search", "arguments": '{"query": "first"}'}},
{"index": 1, "id": "b", "function": {
"name": "web_search", "arguments": '{"query": "second"}'}},
]}}
]
}
payloads: list[dict] = []
monkeypatch.setattr(
generation_service,
"stream_chat",
_stub_stream([[two_calls], [_text_chunk("Done.")]], payloads),
)
generation = generation_service.Generation(chat_id=chat_id, message_id=message_id)
await generation_service._run(generation)
turns = [m for m in payloads[1]["messages"] if m.get("role") == "tool"]
assert [turn["tool_call_id"] for turn in turns] == ["a", "b"]
assert "first" in turns[0]["content"] and "second" in turns[1]["content"]
# And the transcript keeps the same order.
assert [event["query"] for event in generation.tool_events] == ["first", "second"]
async def test_a_custom_tool_runs_inside_the_loop(db, user_id, monkeypatch, mock_http):
"""End to end: a row becomes an offered schema, the model calls it, and the
result comes back in the next request's messages."""
import httpx
from lembas.db.models import CustomTool
monkeypatch.setattr(
"socket.getaddrinfo", lambda *a, **k: [(2, 1, 6, "", ("93.184.216.34", 80))]
)
mock_http(lambda _r: httpx.Response(200, json={"summary": "Sunny in Minas Tirith."}))
db.add(
CustomTool(
slug="weather",
name="Weather",
description="Look up the weather.",
url_template="https://api.test/{{city}}",
parameters_json={"type": "object", "properties": {"city": {"type": "string"}}},
response_mode="json",
response_path="summary",
)
)
db.commit()
chat_id, message_id = _chat_with_tools(db, user_id)
payloads: list[dict] = []
monkeypatch.setattr(
generation_service,
"stream_chat",
_stub_stream(
[
[_tool_call_chunk("weather", '{"city": "Minas Tirith"}')],
[_text_chunk("It is sunny.")],
],
payloads,
),
)
generation = generation_service.Generation(chat_id=chat_id, message_id=message_id)
await generation_service._run(generation)
offered = {tool["function"]["name"] for tool in payloads[0]["tools"]}
assert "weather" in offered
tool_turns = [m for m in payloads[1]["messages"] if m.get("role") == "tool"]
assert tool_turns[0]["content"] == "Sunny in Minas Tirith."
assert generation.tool_events[0]["kind"] == "custom"
assert generation.tool_events[0]["label"] == "Weather"