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

chapter1/learning-from-experience/tests/test_zero_episodes.py

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+#!/usr/bin/env python3
+"""Regression tests for zero-episode division guards.
+
+Bug: train()/evaluate() divided victory counts by episode counts, so
+num_episodes=0 (accepted by experiment.py's argparse) crashed with
+ZeroDivisionError. Fixed by guarding the divisions and rejecting
+episode counts < 1 in experiment.py's front door.
+"""
+
+import sys
+
+import experiment
+from llm_agent import LLMAgent
+from rl_agent import QLearningAgent
+
+
+def test_rl_train_zero_episodes_no_zero_division():
+    result = QLearningAgent().train(num_episodes=0, verbose=False)
+    assert result["total_episodes"] == 0
+    assert result["victory_rate"] == 0.0
+
+
+def test_rl_evaluate_zero_episodes_no_zero_division():
+    result = QLearningAgent().evaluate(num_episodes=0)
+    assert result["num_episodes"] == 0
+    assert result["victory_rate"] == 0.0
+
+
+def test_llm_evaluate_zero_episodes_no_zero_division():
+    # Dummy key: constructing the client makes no network calls, and
+    # evaluate(num_episodes=0) never reaches the API.
+    agent = LLMAgent(api_key="dummy-key")
+    result = agent.evaluate(num_episodes=0)
+    assert result["victory_rate"] == 0.0
+    assert result["avg_reward"] == 0.0
+    assert result["avg_length"] == 0.0
+
+
+def test_experiment_rejects_zero_episodes(monkeypatch, capsys):
+    monkeypatch.setattr(sys, "argv", ["experiment.py", "--mode", "qlearning",
+                                      "--rl-episodes", "0"])
+    experiment.main()  # must print an error and return before running
+    assert "must all be >= 1" in capsys.readouterr().out