69a673e6c6
Chat 访谈 - 新增 persona 系统（default / warm_listener / curious_guide）与 background_voice 语气层 - 回复长度由 compute_reply_plan 统一决策（brief / standard / expanded），融合信息密度启发式 - 输入净稿（input_normalize）：编排层可选 rules/llm 归一用户口语后再喂模型与记忆检索 - 记忆证据注入：按用户话检索 memory evidence 并注入 prompt Memoir 回忆录 - 口述归一（oral_normalize）：segment 原文保留，story 管线取派生净稿作叙事输入 - segment 入队批次门闸：累计字数 + 最长等待秒数，减少零碎提交 - fidelity_check / prompts / narrative_agent 微调 - Alembic 0005：清理跨章节 story 外键 Infra - Dockerfile 加入 ffmpeg - pyproject.toml 新增依赖并同步 uv.lock - .env.example / .env.production 补全新配置项 Tests - 新增 test_background_voice、test_chat_input_normalize、test_experience_regressions - 扩展 test_interview_prompts、test_interview_reply_length、test_story_route_oral_invariant Made-with: Cursor
209 lines
8.6 KiB
Python
209 lines
8.6 KiB
Python
"""面向体验的回归测试：保护"聊得下去"与"回忆录有文笔"两个核心目标。
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与 test_interview_prompts / test_interview_reply_length 不同，这组测试不验证字面规则，
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而是验证体验目标的必要条件是否成立。改 agent 后如果这里挂了，说明体验方向可能在退步。
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"""
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from types import SimpleNamespace
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import pytest
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from app.agents.chat.interview_reply_length import (
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ReplyLengthMode,
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compute_reply_plan,
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heuristic_likely_emotional,
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heuristic_likely_new_detail,
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)
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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.memoir.prompts import (
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get_creative_title_json_prompt,
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get_narrative_editor_system_prompt,
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get_narrative_json_prompt,
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)
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from app.features.memoir import story_pipeline_sync as sps
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def _fake_settings(**overrides: object) -> SimpleNamespace:
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base = {
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"chat_interview_max_tokens": 380,
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"chat_interview_max_segments": 2,
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"chat_interview_max_chars_per_segment": 260,
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"chat_interview_brief_max_tokens": 260,
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"chat_interview_brief_max_chars_per_segment": 200,
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"chat_interview_expanded_max_tokens": 520,
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"chat_interview_expanded_max_chars_per_segment": 380,
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}
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base.update(overrides)
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return SimpleNamespace(**base)
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# ── 聊天体验回归 ──────────────────────────────────────────────────
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class TestChatExperienceRegressions:
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"""保护"聊得下去"体验。"""
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def test_emotional_short_message_not_brief(self) -> None:
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"""用户表达强情绪时不应压成 brief，要给模型足够空间承接情绪。"""
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p = compute_reply_plan(
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"我妈走了以后，我真的很难过",
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background_voice=None,
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settings=_fake_settings(),
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)
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assert p.mode != ReplyLengthMode.brief
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assert heuristic_likely_emotional("我妈走了以后，我真的很难过") is True
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def test_emotional_medium_message_gets_expanded(self) -> None:
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"""中等长度且有情绪的消息应该给 expanded 档位，让模型有空间好好共情。"""
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msg = "那年我奶奶去世的时候，我在外地上学，没来得及见最后一面，到现在想起来还是特别难过"
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assert len(msg) >= 40
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p = compute_reply_plan(msg, background_voice=None, settings=_fake_settings())
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assert p.mode == ReplyLengthMode.expanded
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def test_new_detail_triggers_followup_hint_in_prompt(self) -> None:
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"""用户提到新人名/新关系时，prompt 应明确要求追问（而不是只感慨）。"""
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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={},
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user_message="那个女生叫小芳，是我同桌",
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conversation_turn=2,
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same_topic_turns=2,
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all_stages_coverage=None,
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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 "本轮判定" in p
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assert "追问" in p
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def test_emotional_prompt_prioritizes_empathy(self) -> None:
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"""用户情绪浓时 prompt 应出现情绪承接优先的提示。"""
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p = get_guided_conversation_prompt(
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current_stage="family",
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empty_slots=["relationship"],
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filled_slots={},
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user_message="想起我妈，心酸",
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conversation_turn=3,
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same_topic_turns=1,
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all_stages_coverage=None,
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detected_user_stage="family",
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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
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def test_chit_chat_does_not_force_memoir_question(self) -> None:
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"""闲聊时 prompt 不应强行追问回忆录问题。"""
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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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user_message="今天天气真好哈哈",
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conversation_turn=0,
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same_topic_turns=0,
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all_stages_coverage=None,
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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 "偏闲聊" in p
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assert "陪聊" in p
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def test_topic_switch_not_triggered_at_3_turns(self) -> None:
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"""聊了 3 轮同话题不应该就要换——用户可能还想继续。"""
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p = get_guided_conversation_prompt(
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current_stage="childhood",
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empty_slots=["place", "people", "emotion"],
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filled_slots={"daily_life": "放学后去河边玩"},
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user_message="对啊，那条河特别浅",
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conversation_turn=4,
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same_topic_turns=3,
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all_stages_coverage=None,
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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 "聊得差不多了" not in p
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def test_prompt_intro_mentions_empathy_first(self) -> None:
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"""prompt 开头应强调"先接住对方"而不是"控制字数"。"""
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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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user_message="小时候家里穷",
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conversation_turn=0,
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same_topic_turns=0,
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all_stages_coverage=None,
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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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# ── 回忆录文风回归 ──────────────────────────────────────────────────
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class TestMemoirStyleRegressions:
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"""保护"回忆录有文笔"体验。"""
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def test_title_prompt_allows_literary_expression(self) -> None:
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"""标题 prompt 不应禁止一切文学性表达——只禁止虚构。"""
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prompt = get_creative_title_json_prompt(
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stage="childhood",
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emotion="warm",
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slots={"place": "湖南老家", "turning_event": "爷爷背我过河"},
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)
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assert "禁止虚构" in prompt
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assert "平实" not in prompt.lower()
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def test_title_prompt_uses_facts_only_not_plain(self) -> None:
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"""标题 prompt 应该走 facts_only（允许文采），而不是 plain（要求平实）。"""
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prompt = get_creative_title_json_prompt(
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stage="childhood",
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emotion="warm",
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slots={"place": "老家"},
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)
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assert "优雅" in prompt or "书面语" in prompt or "文采" in prompt
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def test_narrative_prompt_encourages_literary_quality(self) -> None:
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"""叙事 prompt 应该鼓励"有温度"的书面语，不只是"清楚记事"。"""
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sys_prompt = get_narrative_editor_system_prompt()
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assert "温度" in sys_prompt or "优雅" in sys_prompt
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assert "画面感" in sys_prompt or "生动" in sys_prompt
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def test_narrative_json_prompt_allows_emotion_rendering(self) -> None:
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"""叙事 JSON prompt 应允许情感渲染（不新增事实前提下）。"""
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prompt = get_narrative_json_prompt(
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stage="childhood",
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slots={"turning_event": "爷爷背我过河"},
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new_content="【本段用户口述】\n那年下大雨，爷爷背我过河，鞋全湿了，他一直笑。",
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)
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assert "文采服务于真实" in prompt or "虚构描写" in prompt
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def test_fallback_ratio_is_lenient(self) -> None:
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"""fallback 阈值应该宽松——只有极端压缩才触发，正常书面化改写不触发。"""
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oral = "我一九九九年出生在上海，后来搬到苏州。小学时爷爷常带我去河边散步。"
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half_length_md = oral[: len(oral) // 2 + 5]
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assert not sps._should_fallback_to_transcript(half_length_md, oral)
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def test_merge_shrink_only_on_extreme_loss(self) -> None:
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"""合并场景只有在极端缩水时才触发 fallback，不因正常重组而退回。"""
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existing = "这是一段已有的故事正文，讲述了童年在河边的回忆。" * 20
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assert len(existing) > 400
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half_content = existing[: len(existing) // 2]
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import json
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raw = json.dumps(
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{"paragraphs": [{"content": half_content}]}, ensure_ascii=False
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)
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out, ft = sps._apply_narrative_fallbacks(
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raw, "新的口述补充", existing, chapter_category="childhood"
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)
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assert ft == "none"
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