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1ac59d4894
- 新增 priority_first/health_first/latency_first/cost_first 四个调度维度 - 引入 mutex_group 互斥组机制，lru 与 single_account 归入 distribution_mode - 维度 compute_metric 签名扩展 context 参数，支持获取 cost_totals 等上下文 - 各维度增加 evidence_hint 字段描述评分依据 - 健康策略扩展 408/409/423/425/5xx 瞬态状态码冷却，403 按 body 分级冷却 - Codex 配额刷新增强 401/402/403 错误处理，402 生成 fallback 元数据 - 前端号池管理支持账号优先级内联编辑与互斥维度切换 UI - 列表排序改为 internal_priority + created_at，移除 sticky_counts 查询
94 lines
2.8 KiB
Python
94 lines
2.8 KiB
Python
"""Tests for pool preset dimension registry and built-in dimensions."""
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from __future__ import annotations
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from types import SimpleNamespace
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import src.services.provider.pool.dimensions # noqa: F401
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from src.services.provider.pool.dimensions import get_preset_dimension, get_preset_names
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def _key(metadata: dict, *, plan_type: str | None = None) -> SimpleNamespace:
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return SimpleNamespace(upstream_metadata=metadata, oauth_plan_type=plan_type)
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def test_registry_discovers_builtin_dimensions() -> None:
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names = get_preset_names()
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assert {
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"free_team_first",
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"recent_refresh",
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"quota_balanced",
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"single_account",
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"priority_first",
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"health_first",
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"latency_first",
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"cost_first",
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}.issubset(names)
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def test_universal_dimensions_are_applicable_to_any_provider() -> None:
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for name in ("quota_balanced", "single_account"):
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dim = get_preset_dimension(name)
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assert dim is not None
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assert dim.is_applicable("openai") is True
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assert dim.is_applicable("codex") is True
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assert dim.is_applicable("unknown_provider") is True
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def test_provider_specific_dimensions_are_filtered() -> None:
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for name in ("free_team_first", "recent_refresh"):
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dim = get_preset_dimension(name)
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assert dim is not None
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assert dim.is_applicable("codex") is True
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assert dim.is_applicable("kiro") is True
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assert dim.is_applicable("openai") is False
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def test_builtin_dimensions_compute_metric_in_range() -> None:
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all_key_ids = ["k1", "k2", "k3"]
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lru_scores = {"k1": 100.0, "k2": 800.0, "k3": 300.0}
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keys_by_id = {
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"k1": _key(
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{
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"codex": {
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"plan_type": "plus",
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"primary_reset_seconds": 900,
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"primary_used_percent": 60,
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}
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}
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),
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"k2": _key(
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{
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"codex": {
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"plan_type": "free",
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"primary_reset_seconds": 120,
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"primary_used_percent": 20,
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}
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}
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),
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"k3": _key(
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{
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"kiro": {
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"next_reset_at": 4102444800,
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"usage_percentage": 45,
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"subscription_title": "Kiro Team",
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}
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},
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plan_type="team",
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),
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}
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for name in get_preset_names():
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dim = get_preset_dimension(name)
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assert dim is not None
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mode = dim.default_mode
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metric = dim.compute_metric(
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key_id="k1",
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all_key_ids=all_key_ids,
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keys_by_id=keys_by_id,
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lru_scores=lru_scores,
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context={},
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mode=mode,
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)
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assert 0.0 <= metric <= 1.0
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