179b048f07
- 引入了一个新的指标计算模块，用于检索和答案评估。 -通过整合基准生成和评估指标来简化评估服务。 -为新指标和基准生成功能添加了单元测试。 - 更新了前端组件，以利用新的图标，并改进了评估基准的样式。 -将与评估相关的逻辑整合为专门的“知识/评估”结构，以更好地组织。
40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
import os
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os.environ.setdefault("OPENAI_API_KEY", "test-key")
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from yuxi.knowledge.eval.evaluator import aggregate_metrics, build_answer_prompt, normalize_query_result
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def test_normalize_query_result_supports_dict_and_list():
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answer, chunks = normalize_query_result({"answer": "A", "retrieved_chunks": [{"content": "C"}]})
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assert answer == "A"
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assert chunks == [{"content": "C"}]
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answer, chunks = normalize_query_result([{"content": "C"}])
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assert answer == ""
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assert chunks == [{"content": "C"}]
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def test_build_answer_prompt_uses_first_five_non_empty_chunks():
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chunks = [{"content": f"内容{i}"} for i in range(6)] + [{"content": ""}]
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prompt = build_answer_prompt("问题", chunks)
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assert "用户问题：问题" in prompt
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assert "内容0" in prompt
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assert "内容4" in prompt
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assert "内容5" not in prompt
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def test_aggregate_metrics_matches_service_output_shape():
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metrics, overall_score = aggregate_metrics(
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[{"recall@1": 1.0, "f1@1": 0.0}, {"recall@1": 0.0, "f1@1": 1.0}],
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[{"score": 1.0}, {"score": 0.0}],
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include_overall_score=True,
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)
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assert metrics["recall@1"] == 0.5
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assert metrics["f1@1"] == 0.5
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assert metrics["answer_correctness"] == 0.5
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assert metrics["overall_score"] == overall_score
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