2484c207af
Exploration sessions aggregate into a single exploration summary (session counts, goal-achievement rate, issue lists from experience records, judge conclusions when reviewed) that feeds three exits: the campaign report gains an exploration dimension, the v0.7 analysis stage-two input gains the summary (stats only, never full dialogues), and the Markdown export appends a findings appendix after analysis and comparison. With no exploration data every output stays unchanged.
104 lines
3.8 KiB
Python
104 lines
3.8 KiB
Python
"""Exploration summary aggregation (v0.9 票据 05).
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体验记录聚合成探索摘要：会话数、目标达成率、问题清单（blockers/misled
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按出现次数降序）、judge 复核结论（已就位才纳入，只收 poor 档发现）。
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缺则无痕：无会话返回 None。纯函数，不落库。
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"""
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from agenteval.exploration.models import ExplorationSession, ExplorationSessionStatus
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from agenteval.exploration.summary import summarize_exploration
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def _session(experience=None, judge_review=None, status=ExplorationSessionStatus.COMPLETED) -> ExplorationSession:
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return ExplorationSession(
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campaign_id="c-1",
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target_id="t-1",
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persona={"name": "x"},
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goal="查询账单",
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status=status,
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experience=experience,
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judge_review=judge_review,
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)
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def _experience(goal_achieved: bool, blockers=None, misled=None) -> dict:
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return {
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"goal_achieved": goal_achieved,
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"blockers": blockers or [],
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"misled": misled or [],
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"emotion": "neutral",
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"notes": "",
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}
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def test_no_sessions_returns_none():
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assert summarize_exploration([]) is None
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def test_aggregates_counts_rate_and_issue_lists():
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sessions = [
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_session(_experience(True, blockers=["缴费入口难找"])),
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_session(_experience(False, blockers=["缴费入口难找", "验证码收不到"], misled=["被误导选了错误套餐"])),
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_session(_experience(False, blockers=["验证码收不到"])),
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]
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summary = summarize_exploration(sessions)
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assert summary["session_count"] == 3
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assert summary["sessions_with_experience"] == 3
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assert summary["goal_achieved_count"] == 1
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assert summary["goal_achievement_rate"] == round(1 / 3, 4)
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# 问题清单按出现次数降序（同频按首次出现顺序）
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assert summary["issues"] == [
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{"issue": "缴费入口难找", "count": 2},
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{"issue": "验证码收不到", "count": 2},
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]
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assert summary["misled"] == [{"issue": "被误导选了错误套餐", "count": 1}]
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def test_sessions_without_experience_excluded_from_rate_denominator():
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sessions = [
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_session(_experience(True)),
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_session(), # 未关闭/无体验记录
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]
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summary = summarize_exploration(sessions)
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assert summary["session_count"] == 2
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assert summary["sessions_with_experience"] == 1
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assert summary["goal_achievement_rate"] == 1.0
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assert summary["issues"] == []
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def test_no_experience_at_all_rate_is_none():
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summary = summarize_exploration([_session(), _session()])
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assert summary["goal_achievement_rate"] is None
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assert summary["issues"] == [] and summary["misled"] == []
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def test_judge_review_included_only_when_completed():
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good_review = {
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"status": "completed",
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"dimensions": [
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{"dimension": "attitude", "rating": "good", "comment": "友好"},
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{"dimension": "hallucination", "rating": "poor", "comment": "编造了政策"},
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],
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"summary": "存在幻觉",
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}
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failed_review = {"status": "failed", "error": "解析失败"}
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sessions = [
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_session(_experience(True), judge_review=good_review),
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_session(_experience(False), judge_review=failed_review),
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_session(_experience(True)), # 未复核
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]
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summary = summarize_exploration(sessions)
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judge = summary["judge_review"]
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assert judge["reviewed_sessions"] == 1
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# 只收 poor 档发现（问题清单口径）
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assert judge["findings"] == [
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{"dimension": "hallucination", "rating": "poor", "comment": "编造了政策"}
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]
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# 复核总体结论一并纳入
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assert judge["summaries"] == ["存在幻觉"]
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def test_judge_review_absent_when_none_reviewed():
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summary = summarize_exploration([_session(_experience(True))])
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assert summary["judge_review"] is None
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