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48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
import re
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from pathlib import Path
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from xml.etree import ElementTree
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ROOT = Path(__file__).resolve().parents[1]
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CHAPTER = ROOT / "book-en" / "chapter3.md"
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IMAGE_DIR = ROOT / "book-en" / "images"
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EXPECTED_ANCHORS = {
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1: ("User Memory (Individual Scale)", "Knowledge Base (Group Scale)"),
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2: ("Simple Notes", "Advanced JSON Cards"),
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3: ("v2 (2025 paper)", "v3 (April 2026)"),
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4: ("Working Memory", "Procedural"),
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5: ("① User Query", "④ Generate"),
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6: ("Word2Vec", "BGE-M3"),
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7: ("Layer 2 (sparse · long-range connections)", "O(log N) query complexity"),
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8: ("Term frequency saturation (TF)", "Length normalization (b)"),
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9: ("Dense retrieval", "Sparse retrieval (BM25)", "Neural\nRe-ranking"),
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10: ("Global Summary", "Bottom-up Recursive Abstraction"),
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11: ("My Dentist", "Multi-hop reasoning"),
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12: ("Non-agentic RAG", "Agentic RAG"),
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13: ("Agent (ReAct Loop)", "Knowledge Base Backend (Switchable)"),
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14: ("Traditional chunking (no context)", "Context-aware chunking"),
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15: ("Phase 1: Knowledge Extraction and Structuring", "Phase 2: Factor Analysis and Knowledge Modeling"),
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}
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def svg_text(path: Path) -> str:
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root = ElementTree.parse(path).getroot()
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return "\n".join(text.strip() for text in root.itertext() if text.strip())
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def test_chapter_3_references_each_numbered_figure_once():
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markdown = CHAPTER.read_text(encoding="utf-8")
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references = [
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int(number)
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for number in re.findall(r"images/fig3-(\d+)\.svg", markdown)
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]
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assert references == list(range(1, 16))
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def test_chapter_3_english_figures_match_their_captions():
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for number, anchors in EXPECTED_ANCHORS.items():
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text = svg_text(IMAGE_DIR / f"fig3-{number}.svg")
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for anchor in anchors:
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assert anchor in text, f"Figure 3-{number} is missing {anchor!r}"
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