chore(repo): initialize Cowork Local Gitea repository

2026-08-09 20:12:05 +07:00
commit 414eaddca3
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+"""Tests for the selector: ranking, filtering, capability gating, policy re-rank."""
+from __future__ import annotations
+
+import pytest
+
+from cowork_local.core.routing.models import (
+    ModelAssessment,
+    ModelMetadata,
+    Policy,
+    ProbeResult,
+    TaskType,
+)
+from cowork_local.core.routing.selector import best_model, rank_models
+
+
+def _assessment(
+    model_id,
+    *,
+    provider="anthropic",
+    quality=0.8,
+    latency_ms=500,
+    cost_in=0.001,
+    cost_out=0.003,
+    available=True,
+    caps=None,
+    task=TaskType.CODING,
+    probe_success=True,
+) -> ModelAssessment:
+    meta = ModelMetadata(
+        provider=provider,
+        model_id=model_id,
+        cost_per_1k_input=cost_in,
+        cost_per_1k_output=cost_out,
+        max_context=100000,
+        capabilities=set(caps or []),
+        available=available,
+    )
+    probe = ProbeResult(
+        latency_ms=latency_ms, success=probe_success,
+        quality_score=quality, tokens_out=50,
+    )
+    return ModelAssessment(metadata=meta, probes={task.value: probe})
+
+
+def test_empty_returns_no_best():
+    assert best_model([], TaskType.CODING) is None
+
+
+def test_best_is_highest_quality_under_quality_policy():
+    weak = _assessment("weak", quality=0.3)
+    strong = _assessment("strong", quality=0.95)
+    best = best_model([weak, strong], TaskType.CODING, Policy.QUALITY)
+    assert best is not None
+    assert best.assessment.metadata.model_id == "strong"
+
+
+def test_unavailable_excluded():
+    down = _assessment("down", quality=0.99, available=False)
+    up = _assessment("up", quality=0.5)
+    ranking = rank_models([down, up], TaskType.CODING)
+    keys = [c.assessment.metadata.model_id for c in ranking.ranked]
+    assert "down" not in keys
+    assert ranking.best.assessment.metadata.model_id == "up"
+
+
+def test_failed_probe_excluded():
+    broken = _assessment("broken", quality=0.99, probe_success=False)
+    ok = _assessment("ok", quality=0.4)
+    best = best_model([broken, ok], TaskType.CODING)
+    assert best.assessment.metadata.model_id == "ok"
+
+
+def test_missing_probe_for_task_excluded():
+    # Only has a CODING probe; asking for REASONING must exclude it.
+    coding_only = _assessment("c", task=TaskType.CODING)
+    assert best_model([coding_only], TaskType.REASONING) is None
+
+
+def test_required_capability_filters_out_incapable():
+    no_vision = _assessment("text", quality=0.95, caps=[])
+    vision = _assessment("vision", quality=0.6, caps=["vision"])
+    best = best_model(
+        [no_vision, vision], TaskType.CODING, required_capabilities=["vision"]
+    )
+    assert best.assessment.metadata.model_id == "vision"
+
+
+def test_policy_change_reranks_without_reprobe():
+    """Same assessments, different policy → different winner, no re-probing."""
+    smart_pricey_slow = _assessment(
+        "opus", quality=0.95, latency_ms=6000, cost_in=0.015, cost_out=0.075
+    )
+    cheap_fast_ok = _assessment(
+        "haiku", quality=0.7, latency_ms=200, cost_in=0.0002, cost_out=0.0004
+    )
+    candidates = [smart_pricey_slow, cheap_fast_ok]
+
+    q_best = best_model(candidates, TaskType.CODING, Policy.QUALITY)
+    c_best = best_model(candidates, TaskType.CODING, Policy.COST)
+    l_best = best_model(candidates, TaskType.CODING, Policy.LATENCY)
+
+    assert q_best.assessment.metadata.model_id == "opus"    # quality wins
+    assert c_best.assessment.metadata.model_id == "haiku"   # cost wins
+    assert l_best.assessment.metadata.model_id == "haiku"   # latency wins
+
+
+def test_ranking_is_descending_and_stable():
+    a = _assessment("a", quality=0.9)
+    b = _assessment("b", quality=0.6)
+    c = _assessment("c", quality=0.3)
+    ranking = rank_models([b, c, a], TaskType.CODING, Policy.QUALITY)
+    scores = [rc.score for rc in ranking.ranked]
+    assert scores == sorted(scores, reverse=True)
+    assert [rc.assessment.metadata.model_id for rc in ranking.ranked] == ["a", "b", "c"]
+
+
+def test_score_of_returns_zero_for_unranked():
+    a = _assessment("a", quality=0.9)
+    ranking = rank_models([a], TaskType.CODING)
+    assert ranking.score_of("anthropic/a") > 0
+    assert ranking.score_of("anthropic/missing") == 0.0