355 lines
11 KiB
Python
355 lines
11 KiB
Python
"""访谈提示词：精简结构与人格/语气融合回归。"""
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from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
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from app.agents.chat.interview_state_hints import (
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apply_duplicate_question_guard,
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extract_scene_cues,
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)
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from app.agents.state_schema import (
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KnownFact,
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MemoirStateSchema,
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PersonaThread,
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default_slots,
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)
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from app.agents.chat.helpers import format_history_string
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from app.agents.chat.personas import normalize_interview_persona
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from app.agents.chat.prompts_conversation import (
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get_guided_conversation_prompt,
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get_opening_prompt,
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)
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from app.agents.chat.slot_question_bank import SLOT_QUESTION_OUTLINES
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def test_guided_prompt_does_not_embed_raw_user_message_in_system_text():
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p = get_guided_conversation_prompt(
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current_stage="childhood",
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empty_slots=["place"],
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filled_slots={},
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detected_user_stage="childhood",
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user_profile_context="",
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persona="default",
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)
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assert "__USER_SECRET_PHRASE_XYZ__" not in p
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# Signature no longer takes user_message; secret would only leak via profile
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p2 = get_guided_conversation_prompt(
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current_stage="childhood",
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empty_slots=["place"],
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filled_slots={},
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detected_user_stage="childhood",
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user_profile_context="__USER_SECRET_PROFILE__",
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persona="default",
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)
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assert "__USER_SECRET_PROFILE__" in p2
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def test_guided_prompt_injects_slot_question_outline_for_empty_slots():
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p = get_guided_conversation_prompt(
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current_stage="childhood",
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empty_slots=["place", "people"],
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filled_slots={"emotion": "挺开心的"},
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detected_user_stage="childhood",
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user_profile_context="",
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persona="default",
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)
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assert "本阶段问题大纲" in p
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assert "叙述槽" in p or "采集目标" in p
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assert "成长的地方" in p
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assert "重要的人" in p
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def test_guided_prompt_emotion_priority_over_outline():
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p = get_guided_conversation_prompt(
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current_stage="education",
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empty_slots=["school"],
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filled_slots={},
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detected_user_stage="education",
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user_profile_context="",
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persona="default",
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)
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assert "情绪" in p and "大纲" in p
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def test_guided_prompt_includes_memoir_quality_rubric_hints():
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p = get_guided_conversation_prompt(
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current_stage="career",
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empty_slots=["growth"],
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filled_slots={"job": "做过工程师"},
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detected_user_stage="career",
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user_profile_context="",
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persona="default",
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)
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assert "成稿质量导向" in p
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assert "真实性与覆盖" in p
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assert "出版就绪度" in p
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def test_guided_prompt_follow_immersion_whitespace_style_examples():
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p = get_guided_conversation_prompt(
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current_stage="belief",
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empty_slots=["value"],
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filled_slots={},
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detected_user_stage="belief",
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user_profile_context="",
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persona="default",
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)
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assert "跟随" in p and "沉浸" in p
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assert "留白" in p
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assert "风格参考" in p
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assert "这让我想起" in p
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def test_guided_prompt_narrative_weave_and_transition():
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p = get_guided_conversation_prompt(
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current_stage="childhood",
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empty_slots=["place"],
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filled_slots={},
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detected_user_stage="childhood",
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user_profile_context="",
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persona="default",
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)
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assert "编织" in p or "内在线" in p
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assert "通感" in p or "比喻" in p
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assert "下面我们聊聊" in p
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def test_guided_prompt_host_tone_and_context_forward():
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p = get_guided_conversation_prompt(
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current_stage="career",
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empty_slots=["job"],
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filled_slots={},
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detected_user_stage="career",
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user_profile_context="",
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persona="default",
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)
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assert "主持" in p or "播报" in p
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assert "上下文" in p or "既定事实" in p
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assert "行为" in p and "影响" in p
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def test_education_and_family_change_outlines_differ():
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edu = SLOT_QUESTION_OUTLINES[("education", "change")]
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fam = SLOT_QUESTION_OUTLINES[("family", "change")]
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assert edu[0] != fam[0]
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def test_guided_prompt_mentions_empathy_and_scene_strategy():
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p = get_guided_conversation_prompt(
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current_stage="childhood",
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empty_slots=["place"],
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filled_slots={},
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detected_user_stage="childhood",
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user_profile_context="",
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persona="default",
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)
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assert "接住" in p
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assert "画面" in p or "细节" in p
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assert "深挖" in p
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assert "串联" in p
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def test_guided_prompt_era_popculture_open_questions_when_birth_year():
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p = get_guided_conversation_prompt(
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current_stage="childhood",
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empty_slots=["place"],
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filled_slots={},
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detected_user_stage="childhood",
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user_profile_context="",
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persona="default",
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profile_birth_year=1985,
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profile_era_place="潍坊",
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)
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assert "时代与氛围参考" in p
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assert "流行文化" in p
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assert "开放式" in p
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def test_opening_prompt_includes_era_task_when_birth_year_configured():
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p = get_opening_prompt(
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current_stage="childhood",
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empty_slots_readable=["成长的地方"],
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user_profile_context="出生年份：1985年",
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persona="default",
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profile_birth_year=1985,
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profile_era_place="潍坊",
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)
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assert "年代氛围" in p
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def test_guided_prompt_persona_tone_warm_listener():
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p = get_guided_conversation_prompt(
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current_stage="education",
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empty_slots=["school"],
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filled_slots={},
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detected_user_stage="education",
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user_profile_context="",
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persona="warm_listener",
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)
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assert "倾听" in p or "柔和" in p
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def test_guided_prompt_persona_curious_guide():
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p = get_guided_conversation_prompt(
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current_stage="education",
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empty_slots=["school"],
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filled_slots={},
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detected_user_stage="education",
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user_profile_context="",
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persona="curious_guide",
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)
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assert "细节" in p
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def test_normalize_interview_persona_unknown_falls_back():
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assert normalize_interview_persona("not_a_real_persona") == "default"
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assert normalize_interview_persona("") == "default"
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def test_guided_prompt_contains_memory_section_when_evidence():
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p = get_guided_conversation_prompt(
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current_stage="childhood",
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empty_slots=["place"],
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filled_slots={},
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detected_user_stage="childhood",
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user_profile_context="",
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persona="default",
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memory_evidence_text="[摘要:rolling] 1990年生于上海。",
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)
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assert "相关记忆摘录" in p
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assert "过往口述" in p
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assert "1990年生于上海" in p
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def test_guided_prompt_military_tone_in_system():
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p = get_guided_conversation_prompt(
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current_stage="childhood",
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empty_slots=["place"],
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filled_slots={},
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detected_user_stage="childhood",
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user_profile_context="",
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persona="default",
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background_voice="military",
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)
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assert "简洁" in p or "利落" in p or "得体" in p
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def test_guided_prompt_includes_known_facts_persona_threads_and_recent_questions():
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p = get_guided_conversation_prompt(
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current_stage="career",
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empty_slots=["job", "decision"],
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filled_slots={"growth": "越做越确定自己适合产品"},
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detected_user_stage="career",
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user_profile_context="",
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persona="default",
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known_facts=[
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KnownFact(
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label="本轮新信息", value="我后来去了瑞士读书", stage="education"
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),
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],
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persona_threads=[
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PersonaThread(trait="执着坚持", evidence="为了训练咬牙坚持了很多年"),
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],
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recent_questions=["你当时为什么会想去瑞士？"],
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)
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assert "已确认事实" in p
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assert "我后来去了瑞士读书" in p
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assert "人物主线" in p
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assert "执着坚持" in p
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assert "最近已经问过的问题" in p
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assert "为什么会想去瑞士" in p
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def test_prompt_empty_slots_excludes_slots_already_covered_by_known_facts():
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state = MemoirStateSchema(
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stage_order=["education"],
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current_stage="education",
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covered_stages=[],
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slots={"education": default_slots()["education"]},
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known_facts=[
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KnownFact(
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label="求学城市",
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value="后来在瑞士读书",
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stage="education",
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slot_name="city",
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)
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],
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)
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assert "city" not in state.prompt_empty_slots_for_current_stage()
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assert "school" in state.prompt_empty_slots_for_current_stage()
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def test_duplicate_question_guard_downgrades_recent_repeat_question():
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state = MemoirStateSchema(
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stage_order=["education"],
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current_stage="education",
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covered_stages=[],
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slots={"education": default_slots()["education"]},
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known_facts=[
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KnownFact(label="本轮新信息", value="我后来去了瑞士读书", stage="education")
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],
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)
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cleaned, touched = apply_duplicate_question_guard(
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["我记住了。你后来去了瑞士读书吗？"],
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state=state,
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recent_questions=["你后来去了瑞士读书吗？"],
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)
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assert touched is True
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assert cleaned == ["我记住了。"]
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def test_extract_scene_cues_picks_up_sensory_keywords():
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cues = extract_scene_cues("我们小时候在河里游泳，冬天溜冰")
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assert any("凉" in c or "水" in c for c in cues)
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assert any("冰" in c or "咔嚓" in c for c in cues)
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def test_extract_scene_cues_empty_for_abstract_text():
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assert extract_scene_cues("我觉得人生需要坚持") == []
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def test_default_persona_now_has_tone_hint():
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from app.agents.chat.personas import get_interview_persona_tone_hint
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hint = get_interview_persona_tone_hint("default")
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assert hint
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assert "画面" in hint or "细节" in hint
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def test_opening_prompt_military_style_rules_not_dialogue_samples() -> None:
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p = get_opening_prompt(
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current_stage="childhood",
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empty_slots_readable=["成长的地方"],
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user_profile_context="",
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persona="default",
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background_voice="military",
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)
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assert "军队相关" in p
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assert "示例" not in p
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def test_format_history_string_includes_system_for_debug_logs() -> None:
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s = format_history_string(
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[
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SystemMessage(content="SYS_INSTRUCTIONS"),
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HumanMessage(content="hi"),
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AIMessage(content="hello"),
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]
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)
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assert "System: SYS_INSTRUCTIONS" in s
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assert "Human: hi" in s
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assert "Assistant: hello" in s
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def test_format_history_string_omit_system_body() -> None:
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s = format_history_string(
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[
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SystemMessage(content="SYS_INSTRUCTIONS"),
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HumanMessage(content="hi"),
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],
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omit_system_body=True,
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)
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assert "SYS_INSTRUCTIONS" not in s
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assert "System: <omitted total_len=16" in s
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assert "sha12=" in s
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assert "Human: hi" in s
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