53 lines
2.0 KiB
Python
53 lines
2.0 KiB
Python
"""叙事分区、口述过短回退、配图字数门闸（纯函数/无 DB）。"""
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import pytest
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from app.agents.memoir.prompts import format_narrative_user_content
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from app.features.memoir import story_pipeline_sync as sps
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def test_format_narrative_user_content_oral_only() -> None:
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assert format_narrative_user_content("hello", "") == "【本段用户口述】\nhello"
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def test_format_narrative_user_content_with_evidence() -> None:
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out = format_narrative_user_content("口述A", "摘录B")
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assert "【本段用户口述】" in out
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assert "口述A" in out
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assert "摘录B" in out
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assert "非本段口述" in out
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def test_should_fallback_to_transcript_short_md(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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monkeypatch.setattr(sps.settings, "memoir_narrative_fallback_body_ratio", 0.5)
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monkeypatch.setattr(sps.settings, "memoir_narrative_fallback_min_chars", 20)
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oral = "我一九九九年出生在上海，后来全家搬到苏州生活了好几年。"
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assert sps._should_fallback_to_transcript("1999", oral) is True
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assert sps._should_fallback_to_transcript(oral, oral) is False
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def test_apply_narrative_fallbacks_json_too_short_returns_oral(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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monkeypatch.setattr(sps.settings, "memoir_narrative_fallback_body_ratio", 0.5)
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monkeypatch.setattr(sps.settings, "memoir_narrative_fallback_min_chars", 20)
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oral = "我1999年出生在上海，小学时爷爷常带我去河边散步。"
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raw = '{"paragraphs": [{"content": "1999"}]}'
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out = sps._apply_narrative_fallbacks(
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raw,
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oral,
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existing_for_narrative="",
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existing_chapter_md="",
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chapter_category="childhood",
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)
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assert out.strip() == oral
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def test_memoir_image_settings_min_body_field() -> None:
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from app.features.memoir.memoir_images.settings import MemoirImageSettings
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cfg = MemoirImageSettings(story_image_min_body_chars=799)
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assert cfg.story_image_min_body_chars == 799
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