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codex-py/codex/parsing/tex.py
2026-06-04 23:30:58 +02:00

160 lines
5.1 KiB
Python

"""LaTeX parsing utilities.
Provides helpers to extract sections, chunk text, and convert LaTeX to plain
readable prose by stripping markup that is not useful for NLP/embedding.
"""
from __future__ import annotations
import re
# ---------------------------------------------------------------------------
# Internal helpers
# ---------------------------------------------------------------------------
_SECTION_RE = re.compile(
r"\\(?:sub)*section\*?\s*\{([^}]*)\}",
re.DOTALL,
)
# Patterns for LaTeX noise removal (applied in order).
_COMMENT_RE = re.compile(r"%[^\n]*")
_CITE_RE = re.compile(r"\\cite\*?\{[^}]*\}")
_LABEL_RE = re.compile(r"\\label\{[^}]*\}")
_REF_RE = re.compile(r"\\ref\{[^}]*\}")
# Display math: $$...$$ (before single $ to avoid greedy mismatch)
_DISPLAY_DOLLAR_RE = re.compile(r"\$\$.*?\$\$", re.DOTALL)
# Inline math: $...$
_INLINE_MATH_RE = re.compile(r"\$[^$\n]*?\$", re.DOTALL)
# \begin{equation}...\end{equation}
_ENV_EQUATION_RE = re.compile(
r"\\begin\{equation\*?\}.*?\\end\{equation\*?\}",
re.DOTALL,
)
# \begin{align}...\end{align} (covers align, align*, aligned, …)
_ENV_ALIGN_RE = re.compile(
r"\\begin\{align[^}]*\}.*?\\end\{align[^}]*\}",
re.DOTALL,
)
# Collapse excess whitespace
_WHITESPACE_RE = re.compile(r"[ \t]+")
_BLANK_LINES_RE = re.compile(r"\n{3,}")
def _clean_latex(text: str) -> str:
"""Strip LaTeX markup and return readable prose."""
text = _COMMENT_RE.sub("", text)
text = _ENV_EQUATION_RE.sub("", text)
text = _ENV_ALIGN_RE.sub("", text)
text = _DISPLAY_DOLLAR_RE.sub("", text)
text = _INLINE_MATH_RE.sub("", text)
text = _CITE_RE.sub("", text)
text = _LABEL_RE.sub("", text)
text = _REF_RE.sub("", text)
text = _WHITESPACE_RE.sub(" ", text)
text = _BLANK_LINES_RE.sub("\n\n", text)
return text.strip()
# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------
def extract_sections(latex: str) -> list[tuple[str, str]]:
"""Split *latex* on \\section / \\subsection boundaries.
Returns a list of ``(title, cleaned_text)`` tuples, one per section.
Text between the document start and the first section command is
discarded (preamble / abstract handling is out of scope).
"""
# Find all section positions
matches = list(_SECTION_RE.finditer(latex))
if not matches:
return []
sections: list[tuple[str, str]] = []
for idx, match in enumerate(matches):
title = match.group(1).strip()
body_start = match.end()
body_end = matches[idx + 1].start() if idx + 1 < len(matches) else len(latex)
body = latex[body_start:body_end]
cleaned = _clean_latex(body)
sections.append((title, cleaned))
return sections
def chunk_text(text: str, size: int = 512, overlap: int = 64) -> list[str]:
"""Split *text* into overlapping word-based chunks.
Parameters
----------
text:
Plain text to chunk (not raw LaTeX).
size:
Target number of words per chunk.
overlap:
Number of words to carry over into the next chunk.
Each chunk is at most ``size + overlap`` words. Boundaries are snapped
to the nearest ``". "`` (sentence end) within ±20 words of the nominal
boundary when possible.
"""
words = text.split()
if not words:
return []
snap_window = 20
chunks: list[str] = []
start = 0
while start < len(words):
end = min(start + size, len(words))
# Try to snap *end* to a sentence boundary within ±snap_window words.
if end < len(words):
best = end
# Build a small search window
lo = max(start + 1, end - snap_window)
hi = min(len(words), end + snap_window + 1)
# Prefer the closest sentence-end ". " to *end*
for offset in range(0, snap_window + 1):
for candidate in (end - offset, end + offset):
if (
lo <= candidate < hi
and candidate > start
and words[candidate - 1].endswith(".")
):
# Sentence boundary: word at (candidate-1) ends with ".".
best = candidate
break
if best != end:
break
end = best
chunk_words = words[start:end]
chunks.append(" ".join(chunk_words))
if end >= len(words):
break
# Next chunk starts *overlap* words before *end*.
start = max(start + 1, end - overlap)
return chunks
def latex_to_text(latex: str) -> str:
"""Convert a LaTeX document to plain text.
Extracts all sections, cleans each one, and joins them with a blank line.
If no section commands are found, the whole document is cleaned and
returned as a single block.
"""
sections = extract_sections(latex)
if sections:
return "\n\n".join(body for _, body in sections)
# Fallback: no section structure — clean the whole string.
return _clean_latex(latex)