347 lines
12 KiB
Python
347 lines
12 KiB
Python
"""Stdlib document-to-text extraction for ``read_file``.
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Supports Jupyter notebooks, DOCX, and XLSX without adding hard dependencies.
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When the optional ``firecrawl-anydoc`` package is installed (``pip install
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firecrawl-anydoc``, imports as ``anydoc``), coverage widens to legacy Office
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(.doc/.ppt/.xls), OpenDocument, RTF, EPUB, and PDF — converted to Markdown by
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its Rust core. The stdlib extractors remain authoritative for their three
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formats so behavior is identical whether or not anydoc is present.
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Malformed documents raise :class:`ExtractionError`; callers can then fall back to
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normal text/binary handling.
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"""
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from __future__ import annotations
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import importlib
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import json
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import os
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import posixpath
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import threading
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import time
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import zipfile
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from pathlib import Path
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from typing import Any, Optional
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from xml.etree import ElementTree as ET
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__all__ = ["EXTRACTABLE_EXTENSIONS", "ExtractionError", "extract_document_text", "is_extractable_document"]
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EXTRACTABLE_EXTENSIONS = frozenset({".ipynb", ".docx", ".xlsx"})
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# Formats handled only when the optional anydoc converter is installed.
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ANYDOC_EXTENSIONS = frozenset({
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".doc", ".docm",
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".ppt", ".pps", ".pot", ".pptx", ".pptm", ".ppsx", ".ppsm",
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".xls", ".xlsm", ".xlsb",
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".odt", ".ods", ".odp",
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".rtf", ".epub", ".pdf",
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})
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MAX_XLSX_BYTES = 50 * 1024 * 1024
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# Refuse to convert huge documents. anydoc loads the whole file through its
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# Rust core with no streaming, and the read_file char budget only applies
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# after conversion, so an unbounded input can pin a tool turn and spike RAM.
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MAX_ANYDOC_BYTES = 50 * 1024 * 1024
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_MAX_XLSX_ROWS_PER_SHEET = 5000
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_MAX_XLSX_COLS = 256
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_NS_W = "http://schemas.openxmlformats.org/wordprocessingml/2006/main"
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_NS_S = "http://schemas.openxmlformats.org/spreadsheetml/2006/main"
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_NS_REL = "http://schemas.openxmlformats.org/officeDocument/2006/relationships"
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_NS_PKG_REL = "http://schemas.openxmlformats.org/package/2006/relationships"
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class ExtractionError(Exception):
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"""Raised when a supported-looking document cannot be rendered as text."""
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def _extension(path: str) -> str:
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ext = Path(path).suffix.lower()
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if ext in EXTRACTABLE_EXTENSIONS:
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return ext
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if ext in ANYDOC_EXTENSIONS and _anydoc() is not None:
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return ext
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return ""
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_ANYDOC_UNSET = object()
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_anydoc_module: Any = _ANYDOC_UNSET
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_anydoc_lock = threading.Lock()
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# After a failed first load, wait this long before trying again. The attempt
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# can shell out to pip, so retrying on every call would hammer the network
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# in environments where the install can never succeed.
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ANYDOC_RETRY_SECONDS = 300.0
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_anydoc_failed_at: Optional[float] = None
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def _anydoc() -> Optional[Any]:
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"""Lazily import the optional anydoc converter; None when unavailable.
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A failed load is retried after :data:`ANYDOC_RETRY_SECONDS` rather than
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disabling extraction for the rest of the process, so one transient
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failure (network blip, pip race) does not stick in long-lived workers.
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"""
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global _anydoc_module, _anydoc_failed_at
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if _anydoc_module is not _ANYDOC_UNSET:
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return _anydoc_module
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with _anydoc_lock:
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if _anydoc_module is not _ANYDOC_UNSET:
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return _anydoc_module
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if (
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_anydoc_failed_at is not None
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and time.monotonic() - _anydoc_failed_at < ANYDOC_RETRY_SECONDS
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):
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return None
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try:
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from tools.lazy_deps import ensure as _lazy_ensure
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# prompt=False: read_file must never block on an install prompt.
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_lazy_ensure("tool.doc_extract", prompt=False)
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except Exception:
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pass # lazy install unavailable — fall through to a plain import
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try:
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_anydoc_module = importlib.import_module("anydoc")
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except Exception: # ImportError or a broken native binding
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_anydoc_failed_at = time.monotonic()
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return None
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return _anydoc_module # type: ignore[return-value]
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def is_extractable_document(path: str) -> bool:
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return bool(_extension(path))
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def extract_document_text(path: str) -> str:
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ext = _extension(path)
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if ext == ".ipynb":
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return _extract_notebook(path)
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if ext == ".docx":
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return _extract_docx(path)
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if ext == ".xlsx":
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return _extract_xlsx(path)
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if ext in ANYDOC_EXTENSIONS:
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return _extract_anydoc(path)
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raise ExtractionError(f"Unsupported document type: {path!r}")
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def _extract_anydoc(path: str) -> str:
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mod = _anydoc()
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if mod is None:
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raise ExtractionError(f"Unsupported document type: {path!r}")
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try:
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size = os.path.getsize(path)
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except OSError as exc:
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raise ExtractionError(str(exc)) from exc
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if size > MAX_ANYDOC_BYTES:
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raise ExtractionError(
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f"Document too large to convert ({size:,} bytes, limit is {MAX_ANYDOC_BYTES:,})"
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)
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try:
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text = mod.to_markdown(path)
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except OSError as exc:
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raise ExtractionError(str(exc)) from exc
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except Exception as exc:
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# anydoc raises one ConvertError subclass per failure mode
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# (Unsupported, Malformed, Encrypted, ResourceLimit, MissingPart).
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# Any of them means "no meaningful text": fall back to the normal
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# path/binary handling rather than crash read_file.
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raise ExtractionError(f"{type(exc).__name__}: {exc}") from exc
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if not isinstance(text, str) or not text.strip():
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raise ExtractionError("Document contains no extractable text")
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return text.rstrip("\n") + "\n"
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def _source_text(source) -> str:
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if isinstance(source, str):
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return source
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if isinstance(source, list):
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return "".join(item for item in source if isinstance(item, str))
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return ""
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def _extract_notebook(path: str) -> str:
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try:
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with open(path, encoding="utf-8", errors="replace") as fh:
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nb = json.load(fh)
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except (OSError, ValueError, json.JSONDecodeError) as exc:
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raise ExtractionError(f"Not a valid notebook: {exc}") from exc
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if not isinstance(nb, dict):
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raise ExtractionError("Notebook root is not an object")
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cells = nb.get("cells")
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if not isinstance(cells, list):
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cells = [
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cell
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for ws in nb.get("worksheets", [])
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if isinstance(ws, dict)
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for cell in ws.get("cells", [])
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]
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if not cells:
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raise ExtractionError("Notebook contains no cells")
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counts = {"markdown": 0, "code": 0, "raw": 0}
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labels = {"markdown": "Markdown", "code": "Code", "raw": "Raw"}
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out: list[str] = []
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for cell in cells:
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if not isinstance(cell, dict):
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continue
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typ = cell.get("cell_type")
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if typ not in labels:
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continue
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counts[typ] += 1
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suffix = f" {counts[typ]}" if typ != "raw" else ""
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out.extend((f"# ── {labels[typ]} cell{suffix} ──", _source_text(cell.get("source", "")).rstrip("\n"), ""))
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if not out:
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raise ExtractionError("Notebook contains no readable cells")
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return "\n".join(out).rstrip("\n") + "\n"
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def _zip_xml(zf: zipfile.ZipFile, name: str) -> ET.Element:
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try:
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return ET.fromstring(zf.read(name))
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except KeyError as exc:
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raise ExtractionError(f"Missing {name}") from exc
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except ET.ParseError as exc:
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raise ExtractionError(f"Malformed XML in {name}: {exc}") from exc
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def _extract_docx(path: str) -> str:
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try:
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with zipfile.ZipFile(path) as zf:
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root = _zip_xml(zf, "word/document.xml")
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except zipfile.BadZipFile as exc:
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raise ExtractionError(f"Not a valid DOCX: {exc}") from exc
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except OSError as exc:
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raise ExtractionError(str(exc)) from exc
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w = f"{{{_NS_W}}}"
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lines: list[str] = []
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for para in root.iter(f"{w}p"):
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buf: list[str] = []
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for node in para.iter():
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if node.tag == f"{w}t":
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buf.append(node.text or "")
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elif node.tag == f"{w}tab":
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buf.append("\t")
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elif node.tag in {f"{w}br", f"{w}cr"}:
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buf.append("\n")
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lines.extend("".join(buf).split("\n"))
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if not any(line.strip() for line in lines):
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raise ExtractionError("DOCX contains no extractable text")
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return "\n".join(lines).rstrip("\n") + "\n"
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def _extract_xlsx(path: str) -> str:
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try:
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with zipfile.ZipFile(path) as zf:
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names = set(zf.namelist())
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shared = _shared_strings(zf, names)
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sheets = _workbook_sheets(zf)
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rels = _workbook_rels(zf, names)
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out: list[str] = []
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for name, state, rid in sheets:
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if state in {"hidden", "veryHidden"}:
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continue
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part = _sheet_part(rels.get(rid, ""))
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if part not in names:
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continue
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try:
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rows = _sheet_rows(zf.read(part), shared)
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except ET.ParseError:
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continue
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out.append(f"# ── Sheet: {name} ──")
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out.extend("\t".join(row) for row in rows)
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if not rows:
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out.append("(empty)")
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out.append("")
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except zipfile.BadZipFile as exc:
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raise ExtractionError(f"Not a valid XLSX: {exc}") from exc
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except OSError as exc:
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raise ExtractionError(str(exc)) from exc
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if not out:
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raise ExtractionError("XLSX has no visible sheets with content")
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return "\n".join(out).rstrip("\n") + "\n"
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def _shared_strings(zf: zipfile.ZipFile, names: set[str]) -> list[str]:
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if "xl/sharedStrings.xml" not in names:
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return []
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try:
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root = ET.fromstring(zf.read("xl/sharedStrings.xml"))
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except ET.ParseError:
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return []
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s = f"{{{_NS_S}}}"
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return ["".join(t.text or "" for t in item.iter(f"{s}t")) for item in root.iter(f"{s}si")]
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def _workbook_sheets(zf: zipfile.ZipFile) -> list[tuple[str, str, str]]:
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root = _zip_xml(zf, "xl/workbook.xml")
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s, r = f"{{{_NS_S}}}", f"{{{_NS_REL}}}"
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return [
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(sheet.get("name", "Sheet"), sheet.get("state", "visible"), sheet.get(f"{r}id", ""))
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for sheet in root.iter(f"{s}sheet")
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]
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def _workbook_rels(zf: zipfile.ZipFile, names: set[str]) -> dict[str, str]:
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rels_path = "xl/_rels/workbook.xml.rels"
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if rels_path not in names:
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return {}
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try:
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root = ET.fromstring(zf.read(rels_path))
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except ET.ParseError:
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return {}
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rel_tag = f"{{{_NS_PKG_REL}}}Relationship"
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return {rel.get("Id", ""): rel.get("Target", "") for rel in root.iter(rel_tag) if rel.get("Id")}
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def _sheet_part(target: str) -> str:
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target = target.lstrip("/")
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return posixpath.normpath(target if target.startswith("xl/") else f"xl/{target}")
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def _col_index(ref: str) -> int:
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idx = 0
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for ch in ref:
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if not ch.isalpha():
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break
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idx = idx * 26 + ord(ch.upper()) - ord("A") + 1
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return max(idx - 1, 0)
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def _sheet_rows(xml_bytes: bytes, shared: list[str]) -> list[list[str]]:
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root = ET.fromstring(xml_bytes)
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s = f"{{{_NS_S}}}"
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rows: list[list[str]] = []
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for row in root.iter(f"{s}row"):
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if len(rows) >= _MAX_XLSX_ROWS_PER_SHEET:
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break
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cells: dict[int, str] = {}
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max_col = -1
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for cell in row.iter(f"{s}c"):
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col = _col_index(cell.get("r", "")) if cell.get("r") else max_col + 1
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if col >= _MAX_XLSX_COLS:
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continue
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cells[col] = _cell_value(cell, shared, s)
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max_col = max(max_col, col)
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rows.append([cells.get(i, "") for i in range(max_col + 1)] if max_col >= 0 else [])
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while rows and not any(value.strip() for value in rows[-1]):
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rows.pop()
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return rows
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def _cell_value(cell: ET.Element, shared: list[str], s: str) -> str:
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value = cell.findtext(f"{s}v") or ""
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typ = cell.get("t", "")
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if typ == "s":
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try:
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return shared[int(value)]
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except (ValueError, IndexError):
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return ""
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if typ == "inlineStr":
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inline = cell.find(f"{s}is")
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return "" if inline is None else "".join(t.text or "" for t in inline.iter(f"{s}t"))
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if typ == "b":
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return "TRUE" if value.strip() in {"1", "true", "TRUE"} else "FALSE"
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if typ == "e":
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return value or "#ERROR"
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return value
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