feat(knowledge): 实现 SQLite/FTS5 数据层与 Markdown Block 解析
Co-Authored-By: Claude <noreply@anthropic.com>
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"""Markdown 解析与 Note Block 切分。
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Block 由 Markdown 文本生成:标题行独立成块(heading_path 含自身),正文按空行分段,
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每块记录其在原文中的 start_offset / end_offset,用于 Citation 跳转定位。block_id 由
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(note_id, heading_path, content) 稳定派生,内容不变则 ID 稳定。
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"""
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from __future__ import annotations
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import hashlib
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import re
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from dataclasses import dataclass, field
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from datetime import datetime
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from pathlib import Path
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from app.contracts import NoteBlock
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from app.textutils import count_tokens
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_HEADING_RE = re.compile(r"^(#{1,6})[ \t]+(.*?)\s*$")
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_FRONTMATTER_KEY_RE = re.compile(r"^([A-Za-z0-9_-]+)\s*:\s*(.*)$")
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@dataclass
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class ParsedNote:
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note_id: str
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title: str
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file_path: str
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folder: str
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tags: list[str]
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created_at: datetime
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updated_at: datetime
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blocks: list[NoteBlock] = field(default_factory=list)
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def note_id_for_path(rel_path: str) -> str:
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"""由相对路径派生稳定 note_id(路径哈希而非路径本身,见团队约定「不用路径当 ID」)。
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MVP 阶段 ID 随文件移动而变化;后续 move 流程会保留原 ID。"""
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normalized = rel_path.replace("\\", "/").strip("/")
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return "note_" + hashlib.sha256(normalized.encode("utf-8")).hexdigest()[:16]
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def parse_note(
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*,
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markdown: str,
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file_path: str,
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folder: str,
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tags: list[str] | None = None,
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created_at: datetime,
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updated_at: datetime,
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) -> ParsedNote:
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"""解析一篇 Markdown,生成 ParsedNote(元数据 + Block 列表)。"""
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note_id = note_id_for_path(file_path)
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frontmatter = _extract_frontmatter(markdown)
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fallback_title = Path(file_path).stem
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title = frontmatter.get("title") or _first_heading(markdown) or fallback_title
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resolved_tags = list(tags) if tags else _parse_tags(frontmatter.get("tags"))
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blocks = parse_blocks(markdown, note_id)
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return ParsedNote(
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note_id=note_id,
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title=title,
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file_path=file_path,
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folder=folder,
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tags=resolved_tags,
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created_at=created_at,
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updated_at=updated_at,
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blocks=blocks,
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)
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def parse_blocks(markdown: str, note_id: str) -> list[NoteBlock]:
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"""把 Markdown 切成 Block,offset 相对原文(含 frontmatter)。"""
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lines = _split_lines(markdown)
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content_start = _content_start(markdown)
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blocks: list[NoteBlock] = []
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heading_stack: list[str] = []
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body: list[tuple[str, int]] = []
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id_counters: dict[str, int] = {}
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def make_block(path: list[str], chunk: list[tuple[str, int]]) -> None:
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if not chunk:
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return
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content = "\n".join(line for line, _ in chunk)
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start = chunk[0][1]
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end = chunk[-1][1] + len(chunk[-1][0])
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block_id = _stable_block_id(note_id, path, content, id_counters)
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blocks.append(
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NoteBlock(
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block_id=block_id,
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note_id=note_id,
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heading_path=list(path),
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start_offset=start,
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end_offset=end,
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content=content,
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content_hash=hashlib.sha256(content.encode("utf-8")).hexdigest()[:16],
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token_count=count_tokens(content),
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)
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)
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def flush_body() -> None:
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nonlocal body
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make_block(heading_stack, body)
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body = []
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for line, offset in lines:
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if offset < content_start:
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continue # 跳过 frontmatter 区域,但保留 offset 准确性
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heading = _HEADING_RE.match(line)
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if heading:
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flush_body()
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level = len(heading.group(1))
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title = heading.group(2).strip()
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heading_stack = heading_stack[: level - 1] + [title]
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# 标题自身作为一个 Block,便于按章节定位
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make_block(heading_stack, [(line, offset)])
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elif line.strip() == "":
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flush_body() # 空行分隔段落
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else:
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body.append((line, offset))
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flush_body()
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return blocks
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def _stable_block_id(note_id: str, path: list[str], content: str, counters: dict[str, int]) -> str:
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base = hashlib.sha256(
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f"{note_id}\x1f{chr(31).join(path)}\x1f{content}".encode("utf-8")
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).hexdigest()[:16]
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block_id = f"blk_{base}"
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# 同一篇笔记内极少出现的重复段落用后缀消歧,保证唯一
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n = counters.get(block_id, 0)
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counters[block_id] = n + 1
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return block_id if n == 0 else f"{block_id}_{n}"
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def _split_lines(text: str) -> list[tuple[str, int]]:
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"""按行拆分并记录每行在原文中的起始字符偏移。"""
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result: list[tuple[str, int]] = []
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start = 0
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for raw in text.splitlines(keepends=True):
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line = raw
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if line.endswith("\r\n"):
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line = line[:-2]
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elif line.endswith("\n") or line.endswith("\r"):
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line = line[:-1]
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result.append((line, start))
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start += len(raw)
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return result
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def _content_start(markdown: str) -> int:
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"""返回正文起始偏移:有 frontmatter 时跳过 --- 分隔块,否则为 0。"""
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if markdown.startswith("---"):
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end = markdown.find("\n---", 3)
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if end != -1:
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return end + 4
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return 0
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def _extract_frontmatter(markdown: str) -> dict[str, str]:
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"""极简 frontmatter 解析,只提取 key: value 行。"""
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if not markdown.startswith("---"):
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return {}
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end = markdown.find("\n---", 3)
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if end == -1:
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return {}
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meta: dict[str, str] = {}
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for line in markdown[3:end].splitlines():
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m = _FRONTMATTER_KEY_RE.match(line)
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if m:
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meta[m.group(1).lower()] = m.group(2).strip()
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return meta
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def _first_heading(markdown: str) -> str | None:
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for line in markdown.splitlines():
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m = re.match(r"^#\s+(.*?)\s*$", line)
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if m and m.group(1).strip():
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return m.group(1).strip()
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return None
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def _parse_tags(raw: str | None) -> list[str]:
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if not raw:
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return []
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raw = raw.strip()
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if raw.startswith("[") and raw.endswith("]"):
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raw = raw[1:-1]
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return [t.strip().strip("'\"") for t in raw.split(",") if t.strip()]
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