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
51 lines
1.8 KiB
Python
51 lines
1.8 KiB
Python
"""口述规则归一与 memoir 入口行为。"""
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from unittest.mock import patch
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from app.features.memoir.oral_normalize import (
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apply_oral_normalization_rules,
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normalize_oral_for_memoir,
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)
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def test_apply_rules_mei_kanshang_wo() -> None:
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assert "没看上我" in apply_oral_normalization_rules("我去试镜了 美看上我 张伟")
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def test_apply_rules_mei_kanshang_ni() -> None:
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assert apply_oral_normalization_rules("美看上你") == "没看上你"
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def test_apply_rules_no_false_positive_rong() -> None:
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"""「美容」等不应被误替换。"""
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s = "我去了解美容项目"
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assert apply_oral_normalization_rules(s) == s
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def test_normalize_respects_global_off() -> None:
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raw = "美看上我"
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with patch("app.features.memoir.oral_normalize.settings") as m:
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m.memoir_oral_normalize_enabled = False
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m.memoir_oral_normalize_mode = "rules"
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assert normalize_oral_for_memoir(raw, llm=None) == raw
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def test_normalize_rules_mode_no_llm() -> None:
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raw = "美看上我"
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with patch("app.features.memoir.oral_normalize.settings") as m:
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m.memoir_oral_normalize_enabled = True
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m.memoir_oral_normalize_mode = "rules"
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m.memoir_oral_normalize_llm_max_tokens = 512
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m.memoir_oral_normalize_llm_max_input_chars = 8000
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assert normalize_oral_for_memoir(raw, llm=None) == "没看上我"
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def test_normalize_mode_off_string() -> None:
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raw = "美看上我"
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with patch("app.features.memoir.oral_normalize.settings") as m:
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m.memoir_oral_normalize_enabled = True
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m.memoir_oral_normalize_mode = "off"
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m.memoir_oral_normalize_llm_max_tokens = 512
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m.memoir_oral_normalize_llm_max_input_chars = 8000
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assert normalize_oral_for_memoir(raw, llm=None) == raw
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