"""Build static English reading pages from the research Markdown documents."""
import html
import json
import re
import subprocess
from pathlib import Path
from urllib.parse import urlsplit
from bs4 import BeautifulSoup
from markdown_it import MarkdownIt
ROOT = Path(__file__).resolve().parent.parent
DOCS = ROOT / "outputs/cliff_realistic_dense_v1"
SITE = ROOT / "deployments/cloudflare/site"
DEST = SITE / "materials"
HF = "https://huggingface.co/datasets/0721alex/a-plan-is-not-a-path"
PACK = HF + "/resolve/main/outputs/english_research_pack.zip?download=true"
PAGES = [
("submission", "submission_en.md", "Application", "The question and the study", "Personal experience, a systematic evaluation and proposals for better LLM assistance.", "01"),
("methods", "methods_and_results_en.md", "Methods & results", "Methods and complete results", "The pinned checkpoint, full experimental settings, every cash level and reproduction commands.", "02"),
("theory", "theory_and_improvement_en.md", "Theory & improvements", "From diagnosis to better planning", "The economic mechanism and specific proposals for data, supervision and institutional support.", "03"),
("sources", "source_and_development_en.md", "Sources & development", "Sources and development history", "Published references, synthetic assumptions and every stage of the experiment's development.", "04"),
("data", "data_guide_en.md", "Data guide", "Inside the evaluation data", "A guide to the original records, reading copies, fields and reproduction workflow.", "05"),
("example", "example_task_en.md", "Example task", "The task, in full", "Read all six notices for one saved request, with the exact amounts, dates and funding conditions.", "06"),
("essay", "essay_en.md", "Full essay", "The full research essay", "The extended account, interactive-study captions and complete academic references.", "07"),
]
BY_FILE = {p[1]: p[0] for p in PAGES}
MARKDOWN = MarkdownIt("commonmark", {"html": True}).enable("table")
def clean_source(text):
return text.split("", 1)[-1].lstrip()
def render_math(text):
expressions = []
def take(match):
expr = match.group(1) or match.group(2)
expressions.append({"tex": expr.strip(), "display": match.group(1) is not None})
return f"
MATHTOKEN{len(expressions)-1}
" if match.group(1) else f"MATHTOKEN{len(expressions)-1}"
text = re.sub(r"\$\$(.*?)\$\$|\$([^$\n]+)\$", take, text, flags=re.S)
if not expressions:
return text
js = "const fs=require('fs'), k=require('./code/vendor/katex.cjs');process.stdout.write(JSON.stringify(JSON.parse(fs.readFileSync(0,'utf8')).map(e=>k.renderToString(e.tex,{output:'mathml',displayMode:e.display,throwOnError:true}))));"
result = subprocess.run(["node", "-e", js], input=json.dumps(expressions), text=True, capture_output=True, cwd=ROOT, check=True)
for i, rendered in reversed(list(enumerate(json.loads(result.stdout)))):
text = text.replace(f"MATHTOKEN{i}", rendered)
return text
def fix_link(href):
if href.startswith(("https:", "http:", "#", "mailto:")):
return href
part = urlsplit(href)
name = Path(part.path).name
if name in BY_FILE:
return BY_FILE[name] + ".html" + ("#" + part.fragment if part.fragment else "")
if name == "report.pdf":
return "../assets/report.pdf"
if part.path.startswith("figures_en/"):
return "../assets/figures/" + Path(name).stem + ".svg"
local = (DOCS / part.path).resolve()
relative = local.relative_to(ROOT).as_posix()
kind = "tree" if local.is_dir() else "blob" if local.suffix in {".md", ".py", ".txt"} else "resolve"
return HF + "/" + kind + "/main/" + relative + ("#" + part.fragment if part.fragment else "")
def body_and_toc(text):
text = re.sub(r"^# .+\n", "", clean_source(text), count=1)
soup = BeautifulSoup(MARKDOWN.render(render_math(text)), "html.parser")
toc = []
for heading in soup.select("h2, h3"):
ident = re.sub(r"[^a-z0-9]+", "-", heading.get_text().lower()).strip("-")
heading["id"] = heading.get("id", ident)
if heading.name == "h2":
toc.append((heading["id"], heading.get_text()))
for tag in soup.select("a[href], img[src]"):
attr = "href" if tag.name == "a" else "src"
tag[attr] = fix_link(tag[attr])
for table in soup.select("table"):
wrap = soup.new_tag("div", attrs={"class": "table-scroll", "tabindex": "0", "aria-label": "Scrollable data table"})
table.wrap(wrap)
for image in soup.select("img"):
image["loading"] = "lazy"
figure = soup.new_tag("figure")
image.wrap(figure)
if image.get("alt"):
caption = soup.new_tag("figcaption")
caption.string = image["alt"]
figure.append(caption)
return str(soup), toc
def shell(title, content, active="", description="Research documents and original experimental records."):
links = "".join(f'{number}{label}' for slug, _, label, _, _, number in PAGES)
return f'''{html.escape(title)} · A Plan Is Not a PathSkip to contentA Plan Is Not a PathResearch library
{content}
{links}'''
def main():
DEST.mkdir(parents=True, exist_ok=True)
cards = []
for i, (slug, filename, label, title, description, number) in enumerate(PAGES):
body, toc = body_and_toc((DOCS / filename).read_text())
contents = "".join(f'{html.escape(text)}' for ident, text in toc)
previous = PAGES[i-1] if i else None
following = PAGES[i+1] if i+1 < len(PAGES) else None
neighbours = (f'Previous← {previous[2]}' if previous else 'Collection← Research library')
neighbours += f'Continue reading{following[2]} →' if following else 'ExploreInteractive study ↗'
menu = "".join(f'{p[5]}{p[2]}' for p in PAGES)
content = f'''
Begin with the application. Use the methods and source record to examine how the result was obtained.
{''.join(cards)}
Original experiment
504 responses. Every response is available.
The evaluated prompts and original model prose are Chinese. English prompt copies and outcome records make all 504 tasks and scored results accessible; the original responses remain available alongside them.
'''
(DEST / "index.html").write_text(shell("Research library", content))
print(f"Built {len(PAGES)} English documents and the research-library index.")
if __name__ == "__main__":
main()