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

tests/test_ch8_llm_judge_non_dict_payload.py

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+import pytest
+import json
+import os
+import sys
+import types
+
+sys.path.insert(0, os.path.abspath("chapter9/trajectory-verifier"))
+
+from llm_judge import OpenAIQualityJudge
+
+
+class _FakeClient:
+    model = "fake-model"
+
+    def __init__(self, payload):
+        self._payload = payload
+
+    def complete(self, **kwargs):
+        message = types.SimpleNamespace(content=json.dumps(self._payload))
+        return types.SimpleNamespace(choices=[types.SimpleNamespace(message=message)])
+
+
+def test_quality_judge_tolerates_non_dict_payload_and_items():
+    # When the LLM outputs a top-level JSON list of dimension dicts (or non-dict payload),
+    # OpenAIQualityJudge.evaluate must not crash with AttributeError: 'list' object has no attribute 'get'.
+    payload_list = [
+        {
+            "dimension": "expression_quality",
+            "verdict": "pass",
+            "score": 0.9,
+            "confidence": 0.8,
+            "evidence": ["turn 1"],
+        },
+        "invalid_non_dict_item",
+    ]
+    judge = OpenAIQualityJudge(evidence_client=_FakeClient(payload_list))
+    results = list(judge.evaluate({"messages": [], "process_facts": {}}))
+
+    assert len(results) == 2
+    eq = next(r for r in results if r.dimension == "expression_quality")
+    assert eq.verdict == "pass"
+    assert eq.score == 0.9