ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter8/cot-distillation/test_student_pipeline.py

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+import json
+
+from evaluate_student import (
+    BEHAVIORS,
+    behavior_flags,
+    compare_binary,
+    completion_and_findings,
+    exact_two_sided_sign_p_value,
+)
+from train_student import load_verified_messages
+
+
+def test_load_verified_messages_rejects_unverified_shape(tmp_path):
+    path = tmp_path / "bad.jsonl"
+    path.write_text(json.dumps({"messages": [{"role": "user", "content": "q"}]}) + "\n")
+    try:
+        load_verified_messages(path)
+    except ValueError as exc:
+        assert "exactly two" in str(exc)
+    else:
+        raise AssertionError("invalid collection row was accepted for parameter training")
+
+
+def test_paired_sign_test_detects_one_sided_student_gain():
+    baseline = {str(i): False for i in range(8)}
+    student = {str(i): True for i in range(8)}
+    result = compare_binary(baseline, student)
+    assert result["student_only"] == 8
+    assert result["baseline_only"] == 0
+    assert result["exact_two_sided_p_value"] == exact_two_sided_sign_p_value(0, 8)
+    assert result["exact_two_sided_p_value"] < 0.05
+
+
+def test_behavior_flags_cover_acceptance_categories():
+    flags = behavior_flags("Wait, that is not right. Use another approach, then verify by substitution.")
+    assert flags == {"reflection": True, "backtracking": True, "verification": True}
+
+
+def test_negative_uplift_finding_does_not_make_executed_campaign_incomplete():
+    def arm(name, correct):
+        return {
+            "name": name,
+            "accuracy": float(correct),
+            "behavior_rates": {key: 0.0 for key in BEHAVIORS},
+            "records": [{"id": "case-1", "correct": correct}],
+        }
+
+    completion, findings = completion_and_findings(
+        problem_ids={"case-1"},
+        baseline=arm("baseline", False),
+        student=arm("student", False),
+        teacher=arm("teacher", True),
+        paired={"paired_cases": 1, "exact_two_sided_p_value": 1.0},
+        student_training_complete=True,
+        teacher_outputs_complete=True,
+    )
+    assert completion["complete"] is True
+    assert findings["student_improves_over_baseline"] is False
+    assert findings["paired_improvement_significant_p_lt_0_05"] is False