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Two related dispatcher behaviors that have been missing for a while. ## kanban.default_assignee (#27145) Reporter (@agarzon): dashboard creates a task without an assignee, task parks in 'ready' forever even though the operator's intent ('default') is perfectly clear. The dispatcher already had a 'skipped_unassigned' bucket but no fallback routing — users had to manually type 'default' in the assignee field every time. Behavior: when 'kanban.default_assignee' is set in config.yaml, the dispatcher applies that assignee to any unassigned ready task before deciding whether to spawn. The row is mutated (assignee column + an 'assigned' event with source='kanban.default_assignee' for the audit trail). Empty/whitespace config value = no fallback, preserving the existing skipped_unassigned behavior. Dry-run mode reports what WOULD happen via the new 'auto_assigned_default' bucket on DispatchResult, but does NOT mutate the DB — operators using 'hermes kanban dispatch --dry-run' see the routing decision before committing. ## kanban.max_in_progress_per_profile (#21582) Reporter (@edwardchenchen, @simlu, 4 reactions): fan-out workloads saturate one profile's local model / API quota / browser pool while other profiles sit idle. The existing global 'max_in_progress' caps total workers but doesn't balance across profiles. Behavior: when 'kanban.max_in_progress_per_profile' is set to a positive int, the dispatcher tracks per-assignee running counts (one query at tick start) and refuses to spawn for any assignee already at the cap. Tasks blocked this way go to a new 'skipped_per_profile_capped' bucket on DispatchResult as (task_id, assignee, current_running_count) tuples — NOT an operator-actionable failure, just 'try again next tick when the profile has capacity'. Pre-existing 'running' tasks count against the cap (verified via regression test). The cap respects dry_run mode by incrementing its in-memory counter on each would-be spawn so dry_run reports the same balanced subset that a real tick would. Invalid cap values (0, negative, non-int, None) are treated as 'no cap', preserving the existing behavior. Backward-compatible for installs that don't set the config. ## Surfaces - 'hermes kanban dispatch' CLI now prints 'Auto-assigned to kanban.default_assignee=X: ...' and 'Deferred (X at per-profile cap, N running): ...' lines, plus matching JSON keys in --json output. - Gateway dispatcher logs the configured values at startup ('default_assignee=X', 'max_in_progress_per_profile=N'). - 'kanban.max_in_progress_per_profile' added to DEFAULT_CONFIG with inline docs. ## Validation - tests/hermes_cli/test_kanban_default_assignee.py (6 cases): no-cap baseline, auto-assign + DB mutation, dry-run reports without mutating, whitespace treated as None, explicit assignees untouched, DispatchResult field schema. - tests/hermes_cli/test_kanban_per_profile_cap.py (9 cases including 4 parametrized): no-cap baseline, balanced 2-profile fan-out, pre-existing running counts against cap, invalid cap values (0/-1/'abc'/None), capped tasks dispatched on next tick after running task completes, DispatchResult field schema. - Broader kanban suite: 464/464 pass (was 449 baseline; +15 new regression tests across both features). ## Credit #27145 — Jimmy Johansson reported the dispatcher skipped-unassigned gap; @agarzon scoped the simpler 'honor kanban.default_assignee' fix that matches the existing config knob. #21582 — @edwardchenchen filed the per-profile cap ask after hitting model 429s on fan-out research projects; @simlu confirmed the same pain on local-model setups.
167 lines
6.8 KiB
Python
167 lines
6.8 KiB
Python
"""Regression tests for #21582 — per-profile concurrency cap in dispatcher.
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When ``kanban.max_in_progress_per_profile`` is set, no single profile
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gets more than N workers running at once even if the global
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``max_in_progress`` cap would allow it. Prevents one profile's local
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model / API quota / browser pool from being overwhelmed by a fan-out.
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"""
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from __future__ import annotations
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import os
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import sys
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import tempfile
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import pytest
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@pytest.fixture()
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def isolated_kanban_home_with_profiles(monkeypatch):
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"""Spin up a fresh HERMES_HOME with kanban DB + alpha/beta profiles."""
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test_home = tempfile.mkdtemp(prefix="kanban_per_profile_cap_test_")
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for prof in ("alpha", "beta", "default"):
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os.makedirs(os.path.join(test_home, "profiles", prof), exist_ok=True)
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monkeypatch.setenv("HERMES_HOME", test_home)
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for mod in list(sys.modules.keys()):
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if mod.startswith("hermes_cli") or mod.startswith("hermes_state") or mod == "hermes_constants":
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del sys.modules[mod]
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from hermes_cli import kanban_db
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yield kanban_db
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def _fake_spawn(*args, **kwargs):
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return 12345
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def test_no_cap_all_tasks_dispatched(isolated_kanban_home_with_profiles):
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"""Baseline: with no per-profile cap, all ready tasks dispatch."""
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kb = isolated_kanban_home_with_profiles
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with kb.connect_closing() as conn:
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kb.create_board(slug="default", name="Test")
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for i in range(5):
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kb.create_task(conn, title=f"a{i}", assignee="alpha")
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for i in range(3):
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kb.create_task(conn, title=f"b{i}", assignee="beta")
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with kb.connect_closing() as conn:
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res = kb.dispatch_once(conn, spawn_fn=_fake_spawn, dry_run=True)
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assert len(res.spawned) == 8
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assert not res.skipped_per_profile_capped
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def test_cap_2_balances_two_profiles(isolated_kanban_home_with_profiles):
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"""With cap=2: 2 alpha + 2 beta dispatched; remaining 3 alpha + 1 beta
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deferred to skipped_per_profile_capped."""
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kb = isolated_kanban_home_with_profiles
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with kb.connect_closing() as conn:
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kb.create_board(slug="default", name="Test")
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for i in range(5):
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kb.create_task(conn, title=f"a{i}", assignee="alpha")
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for i in range(3):
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kb.create_task(conn, title=f"b{i}", assignee="beta")
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with kb.connect_closing() as conn:
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res = kb.dispatch_once(
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conn, spawn_fn=_fake_spawn, dry_run=True,
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max_in_progress_per_profile=2,
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)
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spawn_assignees = [s[1] for s in res.spawned]
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capped_assignees = [c[1] for c in res.skipped_per_profile_capped]
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assert spawn_assignees.count("alpha") == 2
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assert spawn_assignees.count("beta") == 2
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assert capped_assignees.count("alpha") == 3
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assert capped_assignees.count("beta") == 1
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def test_pre_existing_running_counts_against_cap(isolated_kanban_home_with_profiles):
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"""A task already in 'running' status when dispatch_once starts counts
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toward the per-profile cap. With 1 alpha pre-running and cap=1, NO new
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alpha tasks should spawn; beta is independent so 1 beta spawns."""
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kb = isolated_kanban_home_with_profiles
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with kb.connect_closing() as conn:
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kb.create_board(slug="default", name="Test")
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running_alpha = kb.create_task(conn, title="running alpha", assignee="alpha")
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with kb.write_txn(conn):
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conn.execute(
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"UPDATE tasks SET status = 'running', claim_lock = 'test:1' WHERE id = ?",
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(running_alpha,),
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)
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for i in range(2):
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kb.create_task(conn, title=f"a{i}", assignee="alpha")
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for i in range(2):
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kb.create_task(conn, title=f"b{i}", assignee="beta")
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with kb.connect_closing() as conn:
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res = kb.dispatch_once(
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conn, spawn_fn=_fake_spawn, dry_run=True,
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max_in_progress_per_profile=1,
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)
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spawn_assignees = [s[1] for s in res.spawned]
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capped_assignees = [c[1] for c in res.skipped_per_profile_capped]
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assert spawn_assignees.count("alpha") == 0
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assert spawn_assignees.count("beta") == 1
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assert capped_assignees.count("alpha") == 2
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assert capped_assignees.count("beta") == 1
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@pytest.mark.parametrize("cap", [0, -1, "abc", None])
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def test_invalid_cap_treated_as_no_cap(isolated_kanban_home_with_profiles, cap):
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"""Cap values that don't represent a positive int should be treated as
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'no cap' — silently falling through rather than crashing the dispatcher."""
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kb = isolated_kanban_home_with_profiles
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with kb.connect_closing() as conn:
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kb.create_board(slug="default", name="Test")
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for i in range(3):
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kb.create_task(conn, title=f"a{i}", assignee="alpha")
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with kb.connect_closing() as conn:
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res = kb.dispatch_once(
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conn, spawn_fn=_fake_spawn, dry_run=True,
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max_in_progress_per_profile=cap,
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)
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assert not res.skipped_per_profile_capped
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assert len(res.spawned) == 3
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def test_capped_tasks_dispatched_on_subsequent_tick(isolated_kanban_home_with_profiles):
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"""A task deferred this tick because its profile was at cap should be
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eligible for dispatch on the next tick (after running tasks complete).
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This verifies the cap is per-tick state, not a permanent block."""
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kb = isolated_kanban_home_with_profiles
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with kb.connect_closing() as conn:
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kb.create_board(slug="default", name="Test")
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ids = [kb.create_task(conn, title=f"a{i}", assignee="alpha") for i in range(3)]
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# First tick: cap=1, only 1 alpha dispatched
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with kb.connect_closing() as conn:
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res1 = kb.dispatch_once(
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conn, spawn_fn=_fake_spawn, dry_run=False,
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max_in_progress_per_profile=1,
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)
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assert len(res1.spawned) == 1
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assert len(res1.skipped_per_profile_capped) == 2
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# Simulate the running task completing — set it back to done so the
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# 'running' count drops
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spawned_id = res1.spawned[0][0]
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with kb.connect_closing() as conn:
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with kb.write_txn(conn):
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conn.execute(
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"UPDATE tasks SET status = 'done', claim_lock = NULL WHERE id = ?",
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(spawned_id,),
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)
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# Second tick: 1 more alpha should now dispatch
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with kb.connect_closing() as conn:
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res2 = kb.dispatch_once(
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conn, spawn_fn=_fake_spawn, dry_run=False,
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max_in_progress_per_profile=1,
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)
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assert len(res2.spawned) == 1
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assert len(res2.skipped_per_profile_capped) == 1
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assert res2.spawned[0][0] != spawned_id # different task this time
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def test_dispatch_result_has_skipped_per_profile_capped_field():
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"""Schema-level invariant: DispatchResult exposes the
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skipped_per_profile_capped field as a list of
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(task_id, assignee, current_running) tuples."""
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from hermes_cli.kanban_db import DispatchResult
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r = DispatchResult()
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assert hasattr(r, "skipped_per_profile_capped")
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assert r.skipped_per_profile_capped == []
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