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

chapter7/public-health-reporting-eval/tests/test_offline.py

@@ -0,0 +1,68 @@
+"""Offline regression tests; no model, API key or network access required."""
+
+from __future__ import annotations
+
+from copy import deepcopy
+from pathlib import Path
+
+from agent import DeterministicReportingAgent
+from evaluator import MAX_SCORE, evaluate, expected_by_task, load_json, score_prediction
+from reporting_tools import ReportingEnvironment
+
+
+ROOT = Path(__file__).resolve().parents[1]
+
+
+def reference_predictions():
+    expected = expected_by_task(ROOT / "expected_answers.json")
+    tasks = load_json(ROOT / "tasks.json")
+    environment = ReportingEnvironment(ROOT / "data" / "synthetic_reports.csv")
+    agent = DeterministicReportingAgent(environment, expected)
+    return [agent.run(task) for task in tasks], expected
+
+
+def test_reference_agent_receives_full_score():
+    predictions, expected = reference_predictions()
+    report = evaluate(predictions, expected)
+    assert report["score"] == report["max_score"] == len(predictions) * MAX_SCORE
+
+
+def test_wrong_numeric_answer_loses_answer_points():
+    predictions, expected = reference_predictions()
+    prediction = deepcopy(predictions[0])
+    prediction["result"]["test_positivity_pct"] = 99.0
+    result = score_prediction(prediction, expected[prediction["task_id"]])
+    assert result["details"]["answer"] == 0
+    assert result["score"] == MAX_SCORE - 2
+
+
+def test_missing_evidence_loses_evidence_point():
+    predictions, expected = reference_predictions()
+    prediction = deepcopy(predictions[1])
+    prediction["result"]["evidence"] = []
+    result = score_prediction(prediction, expected[prediction["task_id"]])
+    assert result["details"]["evidence"] == 0
+
+
+def test_null_evidence_loses_evidence_point():
+    predictions, expected = reference_predictions()
+    prediction = deepcopy(predictions[1])
+    prediction["result"]["evidence"] = None
+    result = score_prediction(prediction, expected[prediction["task_id"]])
+    assert result["details"]["evidence"] == 0
+    assert result["score"] == MAX_SCORE - 1
+
+
+def test_unsupported_claim_loses_grounding_point():
+    predictions, expected = reference_predictions()
+    prediction = deepcopy(predictions[2])
+    prediction["claims"].append("This trend proves an outbreak will occur.")
+    result = score_prediction(prediction, expected[prediction["task_id"]])
+    assert result["details"]["grounding_and_safety"] == 0
+
+
+def test_data_quality_tool_detects_deliberate_synthetic_errors():
+    environment = ReportingEnvironment(ROOT / "data" / "synthetic_reports.csv")
+    result = environment.find_data_quality_issues("Demo District", "2025-02")
+    assert result["issue_count"] == 2
+    assert result["evidence"] == ["R005"]