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https://github.com/VectifyAI/PageIndex.git
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9980fc9414
Parsers self-report counts via ParsedDocument.metadata (pymupdf page_count; markdown len(lines)); the backend merges them generically into the stored document row at index time. New page_count/line_count columns are added in place for pre-existing DBs. Local status is always "completed" (indexing is synchronous), matching the cloud backend's field. Align the agentic demo's get_document tool docstring (and its col -> collection naming) accordingly.
105 lines
4.3 KiB
Python
105 lines
4.3 KiB
Python
import re
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from pathlib import Path
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from .protocol import ContentNode, ParsedDocument
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from ..tokens import count_tokens
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class MarkdownParser:
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def supported_extensions(self) -> list[str]:
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return [".md", ".markdown"]
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def parse(self, file_path: str, **kwargs) -> ParsedDocument:
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path = Path(file_path)
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model = kwargs.get("model")
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# utf-8-sig strips a leading BOM if present (common from Windows
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# editors/exporters) and is otherwise identical to plain utf-8. Without
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# it, a BOM-prefixed first line fails the header regex below (the BOM
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# isn't whitespace, so .strip() doesn't remove it), misclassifying the
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# document's first heading as unrecognized preamble text.
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with open(path, "r", encoding="utf-8-sig") as f:
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content = f.read()
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lines = content.split("\n")
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headers = self._extract_headers(lines)
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nodes = self._build_nodes(headers, lines, model, doc_title=path.stem)
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return ParsedDocument(doc_name=path.stem, nodes=nodes,
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metadata={"line_count": len(lines)})
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def _extract_headers(self, lines: list[str]) -> list[dict]:
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header_pattern = r"^(#{1,6})\s+(.+)$"
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# CommonMark allows both backtick and tilde fences, and a fence is
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# closed only by one of the SAME character. Track which char opened the
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# block so a ~~~ line inside a ```-fenced block (or vice versa) is
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# treated as content, not a close — otherwise the block appears to end
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# early and '#'-prefixed lines inside it get misparsed as headings.
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fence_pattern = r"^(`{3,}|~{3,})"
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headers = []
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open_fence = None # the fence char ('`' or '~') of the open block, or None
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for line_num, line in enumerate(lines, 1):
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stripped = line.strip()
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fence = re.match(fence_pattern, stripped)
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if fence:
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marker = fence.group(1)[0]
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if open_fence is None:
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open_fence = marker # open a block
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elif open_fence == marker:
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open_fence = None # matching char closes it
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# a non-matching fence char while a block is open is content
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continue
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if open_fence is None and stripped:
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match = re.match(header_pattern, stripped)
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if match:
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headers.append({
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"title": match.group(2).strip(),
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"level": len(match.group(1)),
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"line_num": line_num,
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})
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return headers
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def _build_nodes(self, headers: list[dict], lines: list[str], model: str | None,
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doc_title: str = "Document") -> list[ContentNode]:
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nodes = []
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# A file with no headings at all still has content — index it as a
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# single node instead of producing zero nodes (which would push an
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# empty page list into the LLM pipeline).
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if not headers:
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text = "\n".join(lines).strip()
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if text:
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nodes.append(ContentNode(
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content=text,
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tokens=count_tokens(text, model=model),
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title=doc_title,
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index=1,
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level=1,
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))
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return nodes
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# Content before the first heading (abstract, preamble) would
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# otherwise be silently dropped and become unretrievable.
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preamble = "\n".join(lines[: headers[0]["line_num"] - 1]).strip()
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if preamble:
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nodes.append(ContentNode(
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content=preamble,
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tokens=count_tokens(preamble, model=model),
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title=doc_title,
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index=1,
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level=headers[0]["level"],
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))
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for i, header in enumerate(headers):
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start = header["line_num"] - 1
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end = headers[i + 1]["line_num"] - 1 if i + 1 < len(headers) else len(lines)
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text = "\n".join(lines[start:end]).strip()
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tokens = count_tokens(text, model=model)
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nodes.append(ContentNode(
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content=text,
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tokens=tokens,
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title=header["title"],
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index=header["line_num"],
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level=header["level"],
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))
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return nodes
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