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azure-ai-evaluation: PromptyEvaluatorBase falls back to the first digit anywhere in the judge's reply, and the threshold turns a stray digit into a wrong pass/fail (15 evaluators)

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Issue 类型
缺陷
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技术栈
python
领域
ai, testing-qa

调研方向

该错误位于 sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_evaluators/_common/_base_prompty_eval.py 的第196-198行。首先阅读 _do_eval 方法并理解正则表达式回退机制。编写一个测试，重现 issue 中列出的有问题的裁判回复。修复应改进正则表达式以找到预期的分数，而不是第一个数字。检查继承自 PromptyEvaluatorBase 的十五个评估器，确保修复适用于所有。运行现有测试以验证没有回归。

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描述

Evaluation Service Attention

sdk/evaluation/azure-ai-evaluation/azure/ai/evaluation/_evaluators/_common/_base_prompty_eval.py (HEAD 4993311), _do_eval:

  • line 188 — structured path: score = parsed_output.get("score", math.nan) ✓
  • lines 196-198 — fallback when the reply is not parseable JSON: 
    match = re.search(r"\d", llm_output)
if match:
    score = float(match.group())
  • lines 115-123 — the score is then compared to self._threshold (default 3) to produce the boolean result.

re.search(r"\d", …) returns the first digit anywhere in the text. The prompts ask for a bare integer, but nothing enforces it, and judge models routinely add reasoning before the number.

Measured

The fallback expression executed verbatim, with the threshold applied as at lines 115-123:

reply                                                                      first-digit score   >= 3 ?
'5'                                                                        5.0                 pass   (correct)
'The answer is grounded. 5'                                                5.0                 pass   (correct)
'The answer makes 3 claims, all supported by the context. Score: 5'        3.0                 pass   (score wrong: judge said 5)
'2 of the statements are unsupported, so this is not grounded: 1'          2.0                 fail   (score wrong: judge said 1)
'Score: 4 (one minor gap)'                                                 4.0                 pass   (correct)
'10 out of 10'                                                             1.0                 fail   (wrong: reads "10" as 1)
'0'                                                                        0.0                 fail   (out of range, no check)

Rows 3 and 4 are the point: the judge's verdict is correct, the recorded score is a number lifted from its explanation, and the pass/fail derived from it can differ from what the judge concluded. There is also no range check, so 0 and 7 are accepted on a 1–5 scale, and 10 becomes 1.

Stated plainly: I ran the fallback expression rather than importing the package; it is a two-line regex and the class wrapper does not alter it.

Who inherits this

grep -rl PromptyEvaluatorBase _evaluators/ — fifteen: coherence, fluency, groundedness, intent_resolution, relevance, response_completeness, retrieval, similarity, task_adherence, task_completion, tool_call_accuracy, tool_call_success, tool_input_accuracy, tool_output_utilization, tool_selection. One base class, one fix site.

Related

The deprecated promptflow-evals carried the identical re.search(r"\d") in five evaluators; this SDK inherited it into the base class and added the threshold on top, which is what turns a wrong number into a wrong verdict.

Suggested fix

In the fallback, prefer an anchored or labelled match before a bare digit: re.fullmatch(r"\s*(\d+)\s*", llm_output) (the whole reply is the number), then re.search(r"[Ss]core\s*[:=]?\s*(\d+)", llm_output), then the last number in the reply rather than the first; validate the result against the evaluator's declared range and return math.nan (which the aggregation already skips) with the raw reply in the reason field when it fails. One parametrized test with rows 3 and 4 above would pin it.

Happy to open the PR.

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