Initial standalone memabra release

tests/test_router_feature_scoring.py

@@ -0,0 +1,137 @@
+from memabra.candidate_types import CandidateObject
+from memabra.router import FeatureScoringRouter, TaskContext
+
+
+def test_feature_scoring_router_computes_score_breakdown_and_selects_best():
+    router = FeatureScoringRouter()
+    memory = CandidateObject(
+        id="mem-1",
+        type="memory",
+        title="m1",
+        summary="s1",
+        confidence=0.9,
+        success_rate=0.9,
+        freshness=0.9,
+        cost=0.1,
+        risk=0.1,
+    )
+    tool = CandidateObject(
+        id="tool-1",
+        type="tool",
+        title="t1",
+        summary="s1",
+        confidence=0.8,
+        success_rate=0.8,
+        freshness=0.8,
+        cost=0.1,
+        risk=0.1,
+    )
+    decision = router.choose(
+        TaskContext(user_input="do something"),
+        memory_candidates=[memory],
+        skill_candidates=[],
+        tool_candidates=[tool],
+    )
+    assert decision.decision_type == "inject_memory"
+    assert "mem-1" in decision.score_breakdown
+    assert "tool-1" in decision.score_breakdown
+    assert decision.score_breakdown["mem-1"] > decision.score_breakdown["tool-1"]
+
+
+def test_feature_scoring_router_applies_failure_penalty():
+    router = FeatureScoringRouter()
+    tool_a = CandidateObject(
+        id="tool-a",
+        type="tool",
+        title="ta",
+        summary="sa",
+        confidence=0.9,
+        success_rate=0.9,
+        freshness=0.9,
+        cost=0.0,
+        risk=0.0,
+    )
+    tool_b = CandidateObject(
+        id="tool-b",
+        type="tool",
+        title="tb",
+        summary="sb",
+        confidence=0.9,
+        success_rate=0.9,
+        freshness=0.9,
+        cost=0.0,
+        risk=0.0,
+    )
+    context = TaskContext(user_input="run tool", recent_failures=["tool-b"])
+    decision = router.choose(
+        context,
+        memory_candidates=[],
+        skill_candidates=[],
+        tool_candidates=[tool_a, tool_b],
+    )
+    assert decision.decision_type == "call_tool"
+    assert decision.selected_ids == ["tool-a"]
+    assert decision.score_breakdown["tool-b"] < decision.score_breakdown["tool-a"]
+
+
+def test_feature_scoring_router_emits_composite_action_for_preconditions():
+    router = FeatureScoringRouter()
+    memory = CandidateObject(
+        id="mem-1",
+        type="memory",
+        title="m1",
+        summary="s1",
+        confidence=0.7,
+        success_rate=0.5,
+        freshness=0.3,
+        cost=0.0,
+        risk=0.0,
+    )
+    tool = CandidateObject(
+        id="tool-1",
+        type="tool",
+        title="t1",
+        summary="s1",
+        confidence=0.9,
+        success_rate=0.9,
+        freshness=0.9,
+        cost=0.0,
+        risk=0.0,
+        preconditions=["memory"],
+    )
+    decision = router.choose(
+        TaskContext(user_input="run tool"),
+        memory_candidates=[memory],
+        skill_candidates=[],
+        tool_candidates=[tool],
+    )
+    assert decision.decision_type == "composite_action"
+    assert len(decision.composite_steps) == 2
+    assert decision.composite_steps[0].decision_type == "inject_memory"
+    assert decision.composite_steps[0].selected_ids == ["mem-1"]
+    assert decision.composite_steps[1].decision_type == "call_tool"
+    assert decision.composite_steps[1].selected_ids == ["tool-1"]
+
+
+def test_feature_scoring_router_fallback_when_precondition_missing():
+    router = FeatureScoringRouter()
+    tool = CandidateObject(
+        id="tool-1",
+        type="tool",
+        title="t1",
+        summary="s1",
+        confidence=0.9,
+        success_rate=0.9,
+        freshness=0.9,
+        cost=0.0,
+        risk=0.0,
+        preconditions=["memory"],
+    )
+    decision = router.choose(
+        TaskContext(user_input="run tool"),
+        memory_candidates=[],
+        skill_candidates=[],
+        tool_candidates=[tool],
+    )
+    assert decision.decision_type == "call_tool"
+    assert decision.selected_ids == ["tool-1"]