1052 lines
39 KiB
Python
1052 lines
39 KiB
Python
from collections.abc import Callable
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from typing import Any
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from unittest.mock import patch
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import pytest
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from nanoid import generate as generate_nanoid
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from sqlalchemy import select
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from sqlalchemy.ext.asyncio import AsyncSession
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from src import models
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from src.config import settings
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from src.deriver.queue_manager import QueueManager, WorkerOwnership
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from src.utils.work_unit import construct_work_unit_key
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@pytest.mark.asyncio
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class TestQueueProcessing:
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"""Test suite for queue processing functionality"""
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async def test_get_and_claim_work_units(
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self,
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sample_queue_items: list[models.QueueItem],
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sample_session_with_peers: tuple[models.Session, list[models.Peer]],
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) -> None:
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"""Test that get_and_claim_work_units correctly identifies unprocessed work"""
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session, _peers = sample_session_with_peers # pyright: ignore[reportUnusedVariable]
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# Verify we have queue items from our test setup
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assert len(sample_queue_items) == 9 # 6 representation + 3 summary
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# Create a queue manager instance
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queue_manager = QueueManager()
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# Get available work units
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work_units = await queue_manager.get_and_claim_work_units()
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# Should have some work units available (may include items from other tests)
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assert len(work_units) > 0
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# Check that all work units have the expected structure
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for work_unit in work_units:
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assert isinstance(work_unit, str)
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assert work_unit.split(":")[0] in ["representation", "summary"]
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# The test is mainly verifying that get_and_claim_work_units works without errors
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# and returns properly structured work unit key strings
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async def test_work_unit_claiming(
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self,
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db_session: AsyncSession,
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sample_queue_items: list[models.QueueItem], # noqa: ARG001 # pyright: ignore[reportUnusedParameter]
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sample_session_with_peers: tuple[models.Session, list[models.Peer]],
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) -> None:
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"""Test that work units can be claimed and are not available to other workers"""
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_session, _peers = sample_session_with_peers
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# Create a queue manager instance
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queue_manager = QueueManager()
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# Get available work units
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work_units = await queue_manager.get_and_claim_work_units()
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assert len(work_units) > 0
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# The API already claimed returned units; verify it's tracked and not returned again
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work_unit = next(iter(work_units.keys()))
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tracked = (
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await db_session.execute(
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select(models.ActiveQueueSession).where(
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models.ActiveQueueSession.work_unit_key == work_unit
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)
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)
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).scalar_one_or_none()
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assert tracked is not None
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# Get available work units again - the claimed one should not be available
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remaining_work_units = await queue_manager.get_and_claim_work_units()
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# The claimed work unit should not be in the remaining list
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assert work_unit not in remaining_work_units
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@pytest.mark.asyncio
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async def test_get_and_claim_excludes_already_claimed(
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self,
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sample_queue_items: list[models.QueueItem], # noqa: ARG001 # pyright: ignore[reportUnusedParameter]
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) -> None:
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queue_manager = QueueManager()
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first_batch = await queue_manager.get_and_claim_work_units()
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assert len(first_batch) > 0
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# Call again; previously claimed keys should not appear
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second_batch = await queue_manager.get_and_claim_work_units()
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assert all(k not in second_batch for k in first_batch)
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@pytest.mark.asyncio
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async def test_claim_work_unit_conflict_returns_false(
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self,
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db_session: AsyncSession,
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sample_queue_items: list[models.QueueItem], # noqa: ARG001 # pyright: ignore[reportUnusedParameter]
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) -> None:
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# Pre-create an active session for a key
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queue_manager = QueueManager()
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claimed = await queue_manager.get_and_claim_work_units()
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assert len(claimed) > 0
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key = list(claimed.keys())[0]
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# Trying to claim the same key again via the API should return empty dict
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claimed_again = await queue_manager.claim_work_units(db_session, [key])
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assert claimed_again == {}
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@pytest.mark.asyncio
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async def test_get_next_message_orders_and_filters_simple(
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self,
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db_session: AsyncSession,
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sample_session_with_peers: tuple[models.Session, list[models.Peer]],
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create_queue_payload: Callable[..., Any],
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add_queue_items: Callable[..., Any],
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) -> None:
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session, peers = sample_session_with_peers
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peer = peers[0]
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# Create and save messages to the database first
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messages: list[models.Message] = []
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for i in range(3):
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message = models.Message(
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session_name=session.name,
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workspace_name=session.workspace_name,
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peer_name=peer.name,
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content="hello",
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token_count=10,
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seq_in_session=i + 1,
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)
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db_session.add(message)
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messages.append(message)
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await db_session.commit()
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# Refresh to get the actual IDs
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for message in messages:
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await db_session.refresh(message)
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payloads: list[tuple[dict[str, Any], int]] = []
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for message in messages:
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payload = create_queue_payload( # type: ignore[reportUnknownArgumentType]
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message=message,
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task_type="representation",
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observed=peer.name,
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observer=peer.name,
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)
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payloads.append((payload, message.id))
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items = await add_queue_items(payloads, session.id, session.workspace_name)
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# Determine ascending order by DB id
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ordered = (
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(
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await db_session.execute(
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select(models.QueueItem)
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.where(models.QueueItem.work_unit_key == items[0].work_unit_key)
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.order_by(models.QueueItem.id)
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)
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)
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.scalars()
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.all()
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)
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first, second = ordered[0], ordered[1]
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qm = QueueManager()
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aqs = models.ActiveQueueSession(
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work_unit_key=first.work_unit_key,
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)
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db_session.add(aqs)
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await db_session.commit()
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await db_session.refresh(aqs)
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_, items_to_process = await qm.get_queue_item_batch(
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task_type="representation",
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work_unit_key=first.work_unit_key,
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aqs_id=aqs.id,
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)
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nxt = items_to_process[0] if items_to_process else None
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assert nxt is not None and nxt.id == first.id
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# Mark first processed, next should be the second
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first.processed = True
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await db_session.commit()
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_, items_to_process2 = await qm.get_queue_item_batch(
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task_type="representation",
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work_unit_key=first.work_unit_key,
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aqs_id=aqs.id,
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)
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nxt2 = items_to_process2[0] if items_to_process2 else None
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assert nxt2 is not None and nxt2.id == second.id
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@pytest.mark.asyncio
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async def test_cleanup_work_unit_removes_row(
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self,
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sample_queue_items: list[models.QueueItem], # noqa: ARG001 # pyright: ignore[reportUnusedParameter]
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db_session: AsyncSession,
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) -> None:
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qm = QueueManager()
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claimed = await qm.get_and_claim_work_units()
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assert len(claimed) > 0
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key = list(claimed.keys())[0]
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aqs_id = claimed[key]
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removed = await qm._cleanup_work_unit(aqs_id, key) # pyright: ignore[reportPrivateUsage]
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assert removed is True
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remaining = (
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await db_session.execute(
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select(models.ActiveQueueSession).where(
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models.ActiveQueueSession.work_unit_key == key
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)
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)
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).scalar_one_or_none()
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assert remaining is None
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async def test_stale_work_unit_cleanup(
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self,
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sample_session_with_peers: tuple[models.Session, list[models.Peer]],
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) -> None:
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"""Test that stale work units are cleaned up properly"""
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_session, _peers = sample_session_with_peers
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# Create an active queue session with an old timestamp
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# from datetime import datetime, timedelta, timezone
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# datetime.now(timezone.utc) - timedelta(minutes=10)
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# We'll test this by checking that the cleanup logic works in get_and_claim_work_units
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# which is called by the queue manager during normal operation
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queue_manager = QueueManager()
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# Get available work units - this should clean up stale entries
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work_units = await queue_manager.get_and_claim_work_units()
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# This test ensures the cleanup logic doesn't break, though we don't have stale entries yet
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assert isinstance(work_units, dict)
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async def test_work_unit_key_format(
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self, sample_session_with_peers: tuple[models.Session, list[models.Peer]]
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) -> None:
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"""Test that work unit keys have the correct format"""
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session, peers = sample_session_with_peers
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peer1, peer2, _ = peers
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# Create a representation work unit key
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# Format: task_type:workspace:session:sender:target
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work_unit_key = (
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f"representation:workspace1:{session.name}:{peer1.name}:{peer2.name}"
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)
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# Check that the key contains the expected information
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assert session.name in work_unit_key
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assert peer1.name in work_unit_key
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assert peer2.name in work_unit_key
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assert "representation" in work_unit_key
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assert "workspace1" in work_unit_key
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# Create a summary work unit key
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# Summary work units use None for sender/target
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summary_work_unit_key = f"summary:workspace1:{session.name}:None:None"
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assert session.name in summary_work_unit_key
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assert "None" in summary_work_unit_key
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assert "summary" in summary_work_unit_key
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assert "workspace1" in summary_work_unit_key
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@pytest.mark.asyncio
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async def test_representation_batching_respects_token_limits(
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self,
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db_session: AsyncSession,
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sample_session_with_peers: tuple[models.Session, list[models.Peer]],
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create_queue_payload: Callable[..., Any],
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) -> None:
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"""Test that representation tasks are batched based on token limits"""
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session, peers = sample_session_with_peers
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peer = peers[0]
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# Create messages with token counts that exceed batch limit
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limit = settings.DERIVER.REPRESENTATION_BATCH_MAX_TOKENS
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token_counts = [limit // 2, limit // 2, limit // 2]
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# Create and save messages to the database first
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messages: list[models.Message] = []
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for i, token_count in enumerate(token_counts):
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message = models.Message(
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session_name=session.name,
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workspace_name=session.workspace_name,
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peer_name=peer.name,
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content=f"Test message {i}",
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token_count=token_count,
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seq_in_session=i + 1,
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)
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db_session.add(message)
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messages.append(message)
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await db_session.commit()
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# Refresh to get the actual IDs
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for message in messages:
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await db_session.refresh(message)
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# Create queue items with token counts
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payload_entries = [
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(
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create_queue_payload( # type: ignore[reportUnknownArgumentType]
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message=msg,
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task_type="representation",
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observed=peer.name,
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observer=peer.name,
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),
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msg,
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)
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for msg in messages
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]
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queue_items: list[models.QueueItem] = []
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for payload, message in payload_entries:
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task_type = payload.get("task_type", "unknown")
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work_unit_key = construct_work_unit_key(session.workspace_name, payload)
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queue_item = models.QueueItem(
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session_id=session.id,
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task_type=task_type,
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work_unit_key=work_unit_key,
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payload=payload,
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processed=False,
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workspace_name=session.workspace_name,
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message_id=message.id,
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)
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db_session.add(queue_item)
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queue_items.append(queue_item)
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await db_session.commit()
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for item in queue_items:
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await db_session.refresh(item)
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# Mock process_items to capture batches
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processed_batches: list[dict[str, Any]] = []
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async def mock_process_representation_batch(
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messages: list[models.Message],
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observed: str | None = None, # pyright: ignore[reportUnusedParameter]
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observer: str | None = None, # pyright: ignore[reportUnusedParameter]
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) -> None:
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processed_batches.append(
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{
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"task_type": "representation",
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"payload_count": len(messages),
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}
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)
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# Process work unit and verify batching
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qm = QueueManager()
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work_unit_key = queue_items[0].work_unit_key
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worker_id = "test_worker"
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# Manually claim and assign ownership
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claimed_units = await qm.claim_work_units(db_session, [work_unit_key])
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aqs_id = claimed_units[work_unit_key]
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qm.worker_ownership[worker_id] = WorkerOwnership(
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work_unit_key=work_unit_key, aqs_id=aqs_id
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)
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with patch(
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"src.deriver.queue_manager.process_representation_batch",
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side_effect=mock_process_representation_batch,
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):
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await qm.process_work_unit(work_unit_key, worker_id)
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# Should create 2 batches due to token limits
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assert len(processed_batches) == 2
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assert processed_batches[0]["payload_count"] == 2
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assert processed_batches[1]["payload_count"] == 1
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assert all(b["task_type"] == "representation" for b in processed_batches)
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@pytest.mark.asyncio
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async def test_token_batching_filters_by_work_unit(
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self,
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db_session: AsyncSession,
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sample_session_with_peers: tuple[models.Session, list[models.Peer]],
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create_queue_payload: Callable[..., Any],
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) -> None:
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"""Test that messages are batched chronologically across all peers, then filtered by work unit"""
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session, peers = sample_session_with_peers
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alice, bob, steve = peers[0], peers[1], peers[2]
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# Create messages from different peers with specific token counts
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# Message sequence: alice(250), bob(400), steve(300), alice(500), bob(500), alice(40), steve(100)
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# Token limit: 2000 - should batch messages 1-6 (1990 tokens)
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messages_data = [
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(alice, 250),
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(bob, 400),
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(steve, 300),
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(alice, 500),
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(bob, 500),
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(alice, 40),
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(steve, 100),
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]
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messages: list[models.Message] = []
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for i, (peer, token_count) in enumerate(messages_data):
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message = models.Message(
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session_name=session.name,
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workspace_name=session.workspace_name,
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peer_name=peer.name,
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content=f"Message from {peer.name}",
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token_count=token_count,
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seq_in_session=i + 1,
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)
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db_session.add(message)
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messages.append(message)
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await db_session.commit()
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for message in messages:
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await db_session.refresh(message)
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# Create queue items for alice's work unit (representation)
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alice_queue_items: list[models.QueueItem] = []
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bob_queue_items: list[models.QueueItem] = []
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steve_queue_items: list[models.QueueItem] = []
|
|
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for i, message in enumerate(messages):
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peer = messages_data[i][0]
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target = alice # All observing alice for simplicity
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payload = create_queue_payload( # type: ignore[reportUnknownArgumentType]
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message=message,
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task_type="representation",
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observed=peer.name,
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observer=target.name,
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)
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work_unit_key = construct_work_unit_key(session.workspace_name, payload)
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queue_item = models.QueueItem(
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session_id=session.id,
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task_type="representation",
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work_unit_key=work_unit_key,
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payload=payload,
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processed=False,
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workspace_name=session.workspace_name,
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message_id=message.id,
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)
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db_session.add(queue_item)
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# Track items by peer
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if peer == alice:
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alice_queue_items.append(queue_item)
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elif peer == bob:
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bob_queue_items.append(queue_item)
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else:
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steve_queue_items.append(queue_item)
|
|
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await db_session.commit()
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for item in alice_queue_items + bob_queue_items + steve_queue_items:
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await db_session.refresh(item)
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|
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qm = QueueManager()
|
|
|
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# Mock the token limit to 2000 for this test
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with patch.object(settings.DERIVER, "REPRESENTATION_BATCH_MAX_TOKENS", 2000):
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# Test alice's work unit
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alice_work_unit_key = alice_queue_items[0].work_unit_key
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alice_aqs = models.ActiveQueueSession(work_unit_key=alice_work_unit_key)
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db_session.add(alice_aqs)
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await db_session.commit()
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await db_session.refresh(alice_aqs)
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alice_messages, alice_items = await qm.get_queue_item_batch(
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task_type="representation",
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work_unit_key=alice_work_unit_key,
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aqs_id=alice_aqs.id,
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)
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assert len(alice_messages) == 6
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alice_message_ids: set[int] = {m.id for m in alice_messages}
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expected_batch_ids = {
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messages[0].id, # alice(250)
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messages[1].id, # bob(400)
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messages[2].id, # steve(300)
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messages[3].id, # alice(500)
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messages[4].id, # bob(500)
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messages[5].id, # alice(40)
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}
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assert alice_message_ids == expected_batch_ids
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# Ensure items are only for alice
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assert all(qi.payload.get("observed") == alice.name for qi in alice_items)
|
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|
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# Test bob's work unit - starts at message 2 for per-work-unit anchoring
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bob_work_unit_key = bob_queue_items[0].work_unit_key
|
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bob_aqs = models.ActiveQueueSession(work_unit_key=bob_work_unit_key)
|
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db_session.add(bob_aqs)
|
|
await db_session.commit()
|
|
await db_session.refresh(bob_aqs)
|
|
|
|
bob_messages, bob_items = await qm.get_queue_item_batch(
|
|
task_type="representation",
|
|
work_unit_key=bob_work_unit_key,
|
|
aqs_id=bob_aqs.id,
|
|
)
|
|
|
|
# Bob should get 4 messages (2..5)
|
|
assert len(bob_messages) == 4
|
|
bob_message_ids: set[int] = {m.id for m in bob_messages}
|
|
expected_bob_ids = {
|
|
messages[1].id, # bob(400)
|
|
messages[2].id, # steve(300)
|
|
messages[3].id, # alice(500)
|
|
messages[4].id, # bob(500)
|
|
}
|
|
assert bob_message_ids == expected_bob_ids
|
|
# Ensure items are only for bob
|
|
assert all(qi.payload.get("observed") == bob.name for qi in bob_items)
|
|
|
|
# Test steve's work unit - starts at message 3 for per-work-unit anchoring
|
|
steve_work_unit_key = steve_queue_items[0].work_unit_key
|
|
steve_aqs = models.ActiveQueueSession(work_unit_key=steve_work_unit_key)
|
|
db_session.add(steve_aqs)
|
|
await db_session.commit()
|
|
await db_session.refresh(steve_aqs)
|
|
|
|
steve_messages, steve_items = await qm.get_queue_item_batch(
|
|
task_type="representation",
|
|
work_unit_key=steve_work_unit_key,
|
|
aqs_id=steve_aqs.id,
|
|
)
|
|
|
|
# Steve should get 5 messages (3..7)
|
|
assert len(steve_messages) == 5
|
|
steve_message_ids: set[int] = {m.id for m in steve_messages}
|
|
expected_steve_ids = {
|
|
messages[2].id, # steve(300)
|
|
messages[3].id, # alice(500)
|
|
messages[4].id, # bob(500)
|
|
messages[5].id, # alice(40)
|
|
messages[6].id, # steve(100)
|
|
}
|
|
assert steve_message_ids == expected_steve_ids
|
|
# Ensure items are only for steve
|
|
assert all(qi.payload.get("observed") == steve.name for qi in steve_items)
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_per_work_unit_anchoring_with_token_limits(
|
|
self,
|
|
db_session: AsyncSession,
|
|
sample_session_with_peers: tuple[models.Session, list[models.Peer]],
|
|
create_queue_payload: Callable[..., Any],
|
|
) -> None:
|
|
"""Test that per-work-unit anchoring processes each sender's messages independently within token limits"""
|
|
|
|
session, peers = sample_session_with_peers
|
|
bob, steve, alice = peers[0], peers[1], peers[2]
|
|
|
|
# Create messages: bob(800), steve(800), alice(100), alice(200)
|
|
# Token limit: 1500
|
|
# With per-work-unit anchoring:
|
|
# - Bob's work unit: starts at message 1, includes only bob(800)
|
|
# - Steve's work unit: starts at message 2, includes only steve(800)
|
|
# - Alice's work unit: starts at message 3, includes alice(100) + alice(200)
|
|
messages_data = [
|
|
(bob, 800),
|
|
(steve, 800),
|
|
(alice, 100),
|
|
(alice, 200),
|
|
]
|
|
|
|
messages: list[models.Message] = []
|
|
for i, (peer, token_count) in enumerate(messages_data):
|
|
message = models.Message(
|
|
session_name=session.name,
|
|
workspace_name=session.workspace_name,
|
|
peer_name=peer.name,
|
|
content=f"Message from {peer.name}",
|
|
token_count=token_count,
|
|
seq_in_session=i + 1,
|
|
)
|
|
db_session.add(message)
|
|
messages.append(message)
|
|
|
|
await db_session.commit()
|
|
for message in messages:
|
|
await db_session.refresh(message)
|
|
|
|
# Create queue items
|
|
|
|
alice_queue_items: list[models.QueueItem] = []
|
|
bob_queue_items: list[models.QueueItem] = []
|
|
steve_queue_items: list[models.QueueItem] = []
|
|
|
|
for i, message in enumerate(messages):
|
|
peer = messages_data[i][0]
|
|
target = alice # All observing alice
|
|
|
|
payload = create_queue_payload( # type: ignore[reportUnknownArgumentType]
|
|
message=message,
|
|
task_type="representation",
|
|
observed=peer.name,
|
|
observer=target.name,
|
|
)
|
|
work_unit_key = construct_work_unit_key(session.workspace_name, payload)
|
|
|
|
queue_item = models.QueueItem(
|
|
session_id=session.id,
|
|
task_type="representation",
|
|
work_unit_key=work_unit_key,
|
|
payload=payload,
|
|
processed=False,
|
|
workspace_name=session.workspace_name,
|
|
message_id=message.id,
|
|
)
|
|
db_session.add(queue_item)
|
|
|
|
if peer == alice:
|
|
alice_queue_items.append(queue_item)
|
|
elif peer == bob:
|
|
bob_queue_items.append(queue_item)
|
|
elif peer == steve:
|
|
steve_queue_items.append(queue_item)
|
|
|
|
await db_session.commit()
|
|
for item in alice_queue_items + bob_queue_items + steve_queue_items:
|
|
await db_session.refresh(item)
|
|
|
|
qm = QueueManager()
|
|
|
|
# Mock the token limit to 1500 for this test
|
|
with patch.object(settings.DERIVER, "REPRESENTATION_BATCH_MAX_TOKENS", 1500):
|
|
# Test alice's work unit
|
|
# With per-work-unit anchoring, Alice starts at her own first message (message 3)
|
|
# Alice's batch: alice(100) + alice(200) = 300 tokens, well under 1500 limit
|
|
if alice_queue_items:
|
|
alice_work_unit_key = alice_queue_items[0].work_unit_key
|
|
alice_aqs = models.ActiveQueueSession(work_unit_key=alice_work_unit_key)
|
|
db_session.add(alice_aqs)
|
|
await db_session.commit()
|
|
await db_session.refresh(alice_aqs)
|
|
|
|
alice_messages2, _ = await qm.get_queue_item_batch(
|
|
task_type="representation",
|
|
work_unit_key=alice_work_unit_key,
|
|
aqs_id=alice_aqs.id,
|
|
)
|
|
|
|
# Per-work-unit anchoring: Alice starts at message 3 -> [3,4]
|
|
assert len(alice_messages2) == 2
|
|
assert [m.id for m in alice_messages2] == [
|
|
messages[2].id,
|
|
messages[3].id,
|
|
]
|
|
|
|
# Test bob's work unit
|
|
# With per-work-unit anchoring, Bob starts at his own first message (message 1)
|
|
# Bob's batch: bob(800) only, under 1500 limit
|
|
if bob_queue_items:
|
|
bob_work_unit_key = bob_queue_items[0].work_unit_key
|
|
bob_aqs = models.ActiveQueueSession(work_unit_key=bob_work_unit_key)
|
|
db_session.add(bob_aqs)
|
|
await db_session.commit()
|
|
await db_session.refresh(bob_aqs)
|
|
|
|
bob_messages2, _ = await qm.get_queue_item_batch(
|
|
task_type="representation",
|
|
work_unit_key=bob_work_unit_key,
|
|
aqs_id=bob_aqs.id,
|
|
)
|
|
|
|
assert len(bob_messages2) == 1
|
|
assert bob_messages2[0].id == messages[0].id # bob only
|
|
|
|
# Test steve's work unit
|
|
# With per-work-unit anchoring, Steve starts at his own first message (message 2)
|
|
# Steve's batch: steve(800) only, under 1500 limit
|
|
if steve_queue_items:
|
|
steve_work_unit_key = steve_queue_items[0].work_unit_key
|
|
steve_aqs = models.ActiveQueueSession(work_unit_key=steve_work_unit_key)
|
|
db_session.add(steve_aqs)
|
|
await db_session.commit()
|
|
await db_session.refresh(steve_aqs)
|
|
|
|
steve_messages2, _ = await qm.get_queue_item_batch(
|
|
task_type="representation",
|
|
work_unit_key=steve_work_unit_key,
|
|
aqs_id=steve_aqs.id,
|
|
)
|
|
|
|
# Per-work-unit anchoring: Steve starts at message 2 -> [2]
|
|
assert len(steve_messages2) == 1
|
|
assert [m.id for m in steve_messages2] == [
|
|
messages[1].id,
|
|
]
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_single_message_processing(
|
|
self,
|
|
db_session: AsyncSession,
|
|
sample_session_with_peers: tuple[models.Session, list[models.Peer]],
|
|
create_queue_payload: Callable[..., Any],
|
|
) -> None:
|
|
"""Test that multiple summary messages in same work unit are processed separately"""
|
|
|
|
session, peers = sample_session_with_peers
|
|
peer = peers[0]
|
|
|
|
# Create two summary messages
|
|
token_counts = [500, 600]
|
|
messages = [
|
|
models.Message(
|
|
session_name=session.name,
|
|
workspace_name=session.workspace_name,
|
|
peer_name=peer.name,
|
|
content="First summary message",
|
|
public_id=generate_nanoid(),
|
|
seq_in_session=1,
|
|
),
|
|
models.Message(
|
|
session_name=session.name,
|
|
workspace_name=session.workspace_name,
|
|
peer_name=peer.name,
|
|
content="Second summary message",
|
|
public_id=generate_nanoid(),
|
|
seq_in_session=2,
|
|
),
|
|
]
|
|
|
|
# Save messages to database first
|
|
for message in messages:
|
|
db_session.add(message)
|
|
await db_session.commit()
|
|
|
|
# Refresh to get the actual IDs
|
|
for message in messages:
|
|
await db_session.refresh(message)
|
|
|
|
# Create payloads and queue items
|
|
queue_items: list[models.QueueItem] = []
|
|
for i, message in enumerate(messages):
|
|
payload = create_queue_payload(
|
|
message, "summary", message_seq_in_session=i + 1
|
|
)
|
|
payload["token_count"] = token_counts[i]
|
|
|
|
work_unit_key = construct_work_unit_key(session.workspace_name, payload)
|
|
|
|
queue_item = models.QueueItem(
|
|
session_id=session.id,
|
|
task_type="summary",
|
|
work_unit_key=work_unit_key,
|
|
payload=payload,
|
|
processed=False,
|
|
workspace_name=session.workspace_name,
|
|
message_id=message.id,
|
|
)
|
|
db_session.add(queue_item)
|
|
queue_items.append(queue_item)
|
|
|
|
await db_session.commit()
|
|
|
|
# Mock and process work unit
|
|
processed_batches: list[dict[str, Any]] = []
|
|
|
|
async def mock_process_item(
|
|
queue_item: models.QueueItem,
|
|
) -> None:
|
|
processed_batches.append(
|
|
{"task_type": queue_item.task_type, "payload_count": 1}
|
|
)
|
|
|
|
qm = QueueManager()
|
|
work_unit_key = queue_items[0].work_unit_key
|
|
worker_id = "test_worker"
|
|
|
|
# Manually claim and assign ownership
|
|
claimed_units = await qm.claim_work_units(db_session, [work_unit_key])
|
|
aqs_id = claimed_units[work_unit_key]
|
|
qm.worker_ownership[worker_id] = WorkerOwnership(
|
|
work_unit_key=work_unit_key, aqs_id=aqs_id
|
|
)
|
|
|
|
with patch(
|
|
"src.deriver.queue_manager.process_item",
|
|
side_effect=mock_process_item,
|
|
):
|
|
await qm.process_work_unit(work_unit_key, worker_id)
|
|
|
|
# Verify both messages were processed in separate batches
|
|
assert len(processed_batches) == 2
|
|
assert all(batch["task_type"] == "summary" for batch in processed_batches)
|
|
assert all(batch["payload_count"] == 1 for batch in processed_batches)
|
|
|
|
# Query for the summary queue items that were processed
|
|
processed_items = (
|
|
(
|
|
await db_session.execute(
|
|
select(models.QueueItem)
|
|
.where(models.QueueItem.work_unit_key == work_unit_key)
|
|
.where(models.QueueItem.task_type == "summary")
|
|
.order_by(models.QueueItem.id)
|
|
)
|
|
)
|
|
.scalars()
|
|
.all()
|
|
)
|
|
|
|
# Assert we found both summary items
|
|
assert len(processed_items) == 2
|
|
|
|
# Assert both items are marked as processed
|
|
assert all(item.processed is True for item in processed_items)
|
|
|
|
# Optionally verify the items have the expected token counts from the messages
|
|
expected_token_counts = [500, 600] # From the test messages
|
|
actual_token_counts = [
|
|
item.payload.get("token_count") or 0 for item in processed_items
|
|
]
|
|
assert sorted(actual_token_counts) == sorted(expected_token_counts)
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_first_message_exceeds_token_limit_still_included(
|
|
self,
|
|
db_session: AsyncSession,
|
|
sample_session_with_peers: tuple[models.Session, list[models.Peer]],
|
|
create_queue_payload: Callable[..., Any],
|
|
) -> None:
|
|
"""Test that if the first message exceeds BATCH_MAX_TOKENS, it's still included alone"""
|
|
|
|
session, peers = sample_session_with_peers
|
|
peer = peers[0]
|
|
|
|
# Create messages where first message exceeds the batch limit
|
|
limit = settings.DERIVER.REPRESENTATION_BATCH_MAX_TOKENS
|
|
token_counts = [limit + 1000, 100, 200] # First message way over limit
|
|
|
|
# Create and save messages to the database first
|
|
messages: list[models.Message] = []
|
|
for i, token_count in enumerate(token_counts):
|
|
message = models.Message(
|
|
session_name=session.name,
|
|
workspace_name=session.workspace_name,
|
|
peer_name=peer.name,
|
|
content=f"Test message {i}",
|
|
token_count=token_count,
|
|
seq_in_session=i + 1,
|
|
)
|
|
db_session.add(message)
|
|
messages.append(message)
|
|
|
|
await db_session.commit()
|
|
|
|
# Refresh to get the actual IDs
|
|
for message in messages:
|
|
await db_session.refresh(message)
|
|
|
|
# Create queue items
|
|
payload_entries = [
|
|
(
|
|
create_queue_payload( # type: ignore[reportUnknownArgumentType]
|
|
message=msg,
|
|
task_type="representation",
|
|
observed=peer.name,
|
|
observer=peer.name,
|
|
),
|
|
msg,
|
|
)
|
|
for msg in messages
|
|
]
|
|
|
|
# Add items to queue
|
|
queue_items: list[models.QueueItem] = []
|
|
for payload, message in payload_entries:
|
|
task_type = payload.get("task_type", "unknown")
|
|
work_unit_key = construct_work_unit_key(session.workspace_name, payload)
|
|
|
|
queue_item = models.QueueItem(
|
|
session_id=session.id,
|
|
task_type=task_type,
|
|
work_unit_key=work_unit_key,
|
|
payload=payload,
|
|
processed=False,
|
|
workspace_name=session.workspace_name,
|
|
message_id=message.id,
|
|
)
|
|
db_session.add(queue_item)
|
|
queue_items.append(queue_item)
|
|
|
|
await db_session.commit()
|
|
for item in queue_items:
|
|
await db_session.refresh(item)
|
|
|
|
# Mock process_items to capture batches
|
|
processed_batches: list[dict[str, Any]] = []
|
|
|
|
async def mock_process_representation_batch(
|
|
messages: list[models.Message],
|
|
observed: str | None = None, # pyright: ignore[reportUnusedParameter]
|
|
observer: str | None = None, # pyright: ignore[reportUnusedParameter]
|
|
) -> None:
|
|
processed_batches.append(
|
|
{
|
|
"task_type": "representation",
|
|
"payload_count": len(messages),
|
|
}
|
|
)
|
|
|
|
qm = QueueManager()
|
|
work_unit_key = queue_items[0].work_unit_key
|
|
worker_id = "test_worker"
|
|
|
|
# Manually claim and assign ownership
|
|
claimed_units = await qm.claim_work_units(db_session, [work_unit_key])
|
|
aqs_id = claimed_units[work_unit_key]
|
|
qm.worker_ownership[worker_id] = WorkerOwnership(
|
|
work_unit_key=work_unit_key, aqs_id=aqs_id
|
|
)
|
|
|
|
with patch(
|
|
"src.deriver.queue_manager.process_representation_batch",
|
|
side_effect=mock_process_representation_batch,
|
|
):
|
|
await qm.process_work_unit(work_unit_key, worker_id)
|
|
|
|
# Should create 2 batches: first large message alone, then second and third together
|
|
assert len(processed_batches) == 2
|
|
assert (
|
|
processed_batches[0]["payload_count"] == 1
|
|
) # First message (over limit) alone
|
|
assert processed_batches[1]["payload_count"] == 2 # Second and third messages
|
|
assert all(b["task_type"] == "representation" for b in processed_batches)
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_message_exactly_at_token_limit(
|
|
self,
|
|
db_session: AsyncSession,
|
|
sample_session_with_peers: tuple[models.Session, list[models.Peer]],
|
|
create_queue_payload: Callable[..., Any],
|
|
) -> None:
|
|
"""Test boundary condition when cumulative sum exactly equals limit"""
|
|
|
|
session, peers = sample_session_with_peers
|
|
peer = peers[0]
|
|
|
|
# Create messages that test the exact boundary
|
|
limit = settings.DERIVER.REPRESENTATION_BATCH_MAX_TOKENS
|
|
token_counts = [
|
|
limit // 2,
|
|
limit // 2,
|
|
1,
|
|
] # First two exactly at limit, third exceeds
|
|
|
|
# Create and save messages to the database first
|
|
messages: list[models.Message] = []
|
|
for i, token_count in enumerate(token_counts):
|
|
message = models.Message(
|
|
session_name=session.name,
|
|
workspace_name=session.workspace_name,
|
|
peer_name=peer.name,
|
|
content=f"Test message {i}",
|
|
token_count=token_count,
|
|
seq_in_session=i + 1,
|
|
)
|
|
db_session.add(message)
|
|
messages.append(message)
|
|
|
|
await db_session.commit()
|
|
|
|
# Refresh to get the actual IDs
|
|
for message in messages:
|
|
await db_session.refresh(message)
|
|
|
|
# Create queue items
|
|
payload_entries = [
|
|
(
|
|
create_queue_payload( # type: ignore[reportUnknownArgumentType]
|
|
message=msg,
|
|
task_type="representation",
|
|
observed=peer.name,
|
|
observer=peer.name,
|
|
),
|
|
msg,
|
|
)
|
|
for msg in messages
|
|
]
|
|
|
|
# Add items to queue
|
|
queue_items: list[models.QueueItem] = []
|
|
for payload, message in payload_entries:
|
|
task_type = payload.get("task_type", "unknown")
|
|
work_unit_key = construct_work_unit_key(session.workspace_name, payload)
|
|
|
|
queue_item = models.QueueItem(
|
|
session_id=session.id,
|
|
task_type=task_type,
|
|
work_unit_key=work_unit_key,
|
|
payload=payload,
|
|
processed=False,
|
|
workspace_name=session.workspace_name,
|
|
message_id=message.id,
|
|
)
|
|
db_session.add(queue_item)
|
|
queue_items.append(queue_item)
|
|
|
|
await db_session.commit()
|
|
for item in queue_items:
|
|
await db_session.refresh(item)
|
|
|
|
# Mock process_items to capture batches
|
|
processed_batches: list[dict[str, Any]] = []
|
|
|
|
async def mock_process_representation_batch(
|
|
messages: list[models.Message],
|
|
observed: str | None = None, # pyright: ignore[reportUnusedParameter]
|
|
observer: str | None = None, # pyright: ignore[reportUnusedParameter]
|
|
) -> None:
|
|
processed_batches.append(
|
|
{
|
|
"task_type": "representation",
|
|
"payload_count": len(messages),
|
|
}
|
|
)
|
|
|
|
qm = QueueManager()
|
|
work_unit_key = queue_items[0].work_unit_key
|
|
worker_id = "test_worker"
|
|
|
|
# Manually claim and assign ownership
|
|
claimed_units = await qm.claim_work_units(db_session, [work_unit_key])
|
|
aqs_id = claimed_units[work_unit_key]
|
|
qm.worker_ownership[worker_id] = WorkerOwnership(
|
|
work_unit_key=work_unit_key, aqs_id=aqs_id
|
|
)
|
|
|
|
with patch(
|
|
"src.deriver.queue_manager.process_representation_batch",
|
|
side_effect=mock_process_representation_batch,
|
|
):
|
|
await qm.process_work_unit(work_unit_key, worker_id)
|
|
|
|
# Should create 2 batches: first two messages together (exactly at limit), third alone
|
|
assert len(processed_batches) == 2
|
|
assert (
|
|
processed_batches[0]["payload_count"] == 2
|
|
) # First two messages (exactly at limit)
|
|
assert (
|
|
processed_batches[1]["payload_count"] == 1
|
|
) # Third message (exceeds limit)
|
|
assert all(b["task_type"] == "representation" for b in processed_batches)
|