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urbanLifeline/difyPlugin/pdf/tools/pdf_toc.py

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import json
import re
from collections import OrderedDict
from collections.abc import Generator
from typing import Any
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import fitz
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from dify_plugin import Tool
from dify_plugin.entities.model.llm import LLMModelConfig
from dify_plugin.entities.model.message import SystemPromptMessage, UserPromptMessage
from dify_plugin.entities.tool import ToolInvokeMessage
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_TOC_SYSTEM_PROMPT = """你是专业的PDF目录解析助手。请从以下PDF文本中提取文档的目录/章节结构。
要求
1. 识别所有一级和二级标题及其对应的页码
2. 只返回纯JSON数组不要markdown代码块不要任何解释
3. 格式: [{"title": "章节标题", "page": 页码数字}]
4. 页码必须是文档中标注的实际页码数字
5. 如果无法识别目录返回空数组 []"""
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class PdfTocTool(Tool):
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_TOC_PATTERNS = [
r"目录",
r"\s*录",
r"\u3000录",
r"Table of Contents",
r"Contents",
r"目次",
]
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def _invoke(self, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage]:
file = tool_parameters.get("file")
if not file:
yield self.create_text_message("Error: file is required")
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return
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model_config = tool_parameters.get("model")
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doc = fitz.open(stream=file.blob, filetype="pdf")
try:
num_pages = len(doc)
# 1) 优先从PDF元数据提取目录
catalog = self._catalog_from_metadata(doc.get_toc(), num_pages)
# 2) 元数据无目录时使用LLM解析
if not catalog and model_config:
catalog = self._extract_toc_with_llm(doc, num_pages, model_config)
# 3) 无LLM配置时回退到正则解析
if not catalog:
toc_start, toc_end = self._find_toc_pages(doc, num_pages)
if toc_start is not None and toc_end is not None:
toc_text = "\n".join(
doc[index].get_text() or "" for index in range(toc_start, toc_end + 1)
)
printed_catalog = self._parse_toc_lines(toc_text)
catalog = self._attach_page_indexes(printed_catalog, toc_end, num_pages)
if not catalog:
catalog = []
yield self.create_text_message(json.dumps(catalog, ensure_ascii=False))
finally:
doc.close()
def _extract_toc_with_llm(
self, doc: fitz.Document, num_pages: int, model_config: dict[str, Any]
) -> list[dict[str, int | str]]:
# 先尝试定位目录页
toc_start, toc_end = self._find_toc_pages(doc, num_pages)
if toc_start is not None and toc_end is not None:
# 有目录页,提取目录页文本
toc_text = "\n".join(
doc[index].get_text() or "" for index in range(toc_start, toc_end + 1)
)
content_offset = toc_end
else:
# 无目录页提取前15页文本让LLM识别章节结构
sample = min(num_pages, 15)
toc_text = "\n\n--- 第{}页 ---\n".join(
[""] + [doc[i].get_text() or "" for i in range(sample)]
)
toc_text = toc_text.strip()
if not toc_text:
return []
content_offset = 0
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# 截断过长文本
if len(toc_text) > 15000:
toc_text = toc_text[:15000] + "\n...[截断]"
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try:
response = self.session.model.llm.invoke(
model_config=LLMModelConfig(**model_config),
prompt_messages=[
SystemPromptMessage(content=_TOC_SYSTEM_PROMPT),
UserPromptMessage(content=toc_text),
],
stream=False,
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)
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llm_text = self._get_response_text(response)
if not llm_text:
return []
raw_catalog = self._parse_llm_json(llm_text)
if not raw_catalog:
return []
# 转换LLM返回的简单格式为完整catalog
return self._build_catalog_from_llm(raw_catalog, content_offset, num_pages)
except Exception:
return []
def _build_catalog_from_llm(
self, raw: list[dict], content_offset: int, num_pages: int
) -> list[dict[str, int | str]]:
entries: list[tuple[str, int]] = []
for item in raw:
title = str(item.get("title") or "").strip()
page = self._to_int(item.get("page"), None)
if not title or page is None:
continue
entries.append((title, page))
if not entries:
return []
# 计算偏移量:第一个条目的页码与实际内容起始页的差值
first_printed_page = entries[0][1]
offset = (content_offset + 1) - first_printed_page if content_offset > 0 else 0
result: list[dict[str, int | str]] = []
for i, (title, page) in enumerate(entries):
next_page = entries[i + 1][1] if i + 1 < len(entries) else page
page_start_index = max(0, min(page + offset - 1, num_pages - 1))
page_end_index = max(page_start_index, min(next_page + offset - 2, num_pages - 1))
if i == len(entries) - 1:
page_end_index = num_pages - 1
result.append({
"title": title,
"start": page,
"end": max(page, next_page - 1) if i + 1 < len(entries) else page,
"page_start_index": page_start_index,
"page_end_index": page_end_index,
})
return result
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@staticmethod
def _get_response_text(response: Any) -> str:
if not hasattr(response, "message") or not response.message:
return ""
content = response.message.content
if isinstance(content, str):
text = content
elif isinstance(content, list):
text = "".join(
item.data if hasattr(item, "data") else str(item) for item in content
)
else:
text = str(content)
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# 清理思考标签
text = re.sub(r"<think>[\s\S]*?</think>", "", text, flags=re.IGNORECASE)
text = re.sub(r"<\|[^>]+\|>", "", text)
return text.strip()
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@staticmethod
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def _parse_llm_json(text: str) -> list[dict]:
# 尝试提取JSON代码块
code_match = re.search(r"```(?:json)?\s*([\s\S]*?)```", text)
if code_match:
text = code_match.group(1).strip()
# 尝试找到JSON数组
bracket_match = re.search(r"\[[\s\S]*\]", text)
if bracket_match:
text = bracket_match.group(0)
try:
result = json.loads(text)
if isinstance(result, list):
return result
except Exception:
pass
return []
def _catalog_from_metadata(self, toc: list, num_pages: int) -> list[dict[str, int | str]]:
top = [(title, max(0, page - 1)) for level, title, page in toc if level <= 2 and page >= 1]
if not top:
return []
result: list[dict[str, int | str]] = []
for index, (title, start_index) in enumerate(top):
end_index = top[index + 1][1] - 1 if index + 1 < len(top) else num_pages - 1
result.append({
"title": title,
"start": start_index + 1,
"end": max(start_index, end_index) + 1,
"page_start_index": start_index,
"page_end_index": max(start_index, end_index),
})
return result
def _find_toc_pages(self, doc: fitz.Document, num_pages: int) -> tuple[int | None, int | None]:
toc_start = None
toc_end = None
for page_number in range(min(num_pages, 30)):
text = doc[page_number].get_text() or ""
if any(re.search(pattern, text, re.IGNORECASE) for pattern in self._TOC_PATTERNS):
if toc_start is None:
toc_start = page_number
toc_end = page_number
elif toc_start is not None:
break
return toc_start, toc_end
def _parse_toc_lines(self, text: str) -> list[dict[str, int | str]]:
marker = re.search(
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r"^(List\s+of\s+Figures|List\s+of\s+Tables|图目录|表目录)",
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text,
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re.IGNORECASE | re.MULTILINE,
)
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if marker:
text = text[: marker.start()]
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pattern = re.compile(r"^\s*(?P<title>.+?)\s*(?:\.{2,}|\s)\s*(?P<page>\d{1,5})\s*$")
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entries: list[tuple[str, int]] = []
for raw in text.splitlines():
line = raw.strip()
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if not line or len(line) < 3 or re.fullmatch(r"\d+", line):
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continue
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match = pattern.match(line)
if not match:
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continue
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title = re.sub(r"\s+", " ", match.group("title")).strip("-_:")
page = self._to_int(match.group("page"), None)
if not title or page is None or len(title) <= 1:
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continue
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if title.lower() in {"page", "pages", "目录", "contents"}:
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continue
entries.append((title, page))
if not entries:
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return []
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dedup: OrderedDict[str, int] = OrderedDict()
for title, page in entries:
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dedup.setdefault(title, page)
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titles = list(dedup.keys())
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pages = [dedup[title] for title in titles]
result: list[dict[str, int | str]] = []
for index, title in enumerate(titles):
start = pages[index]
end = max(start, pages[index + 1] - 1) if index + 1 < len(pages) else start
result.append({"title": title, "start": start, "end": end})
return result
def _attach_page_indexes(
self, catalog: list[dict[str, int | str]], toc_end: int, num_pages: int
) -> list[dict[str, int | str]]:
if not catalog:
return []
first_page = None
for item in catalog:
start = self._to_int(item.get("start"), None)
if start is not None and (first_page is None or start < first_page):
first_page = start
if first_page is None:
return []
offset = (toc_end + 1) - first_page
result: list[dict[str, int | str]] = []
for item in catalog:
start = self._to_int(item.get("start"), None)
end = self._to_int(item.get("end"), start)
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if start is None:
continue
if end is None:
end = start
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page_start_index = max(0, min(start + offset, num_pages - 1))
page_end_index = max(page_start_index, min(end + offset, num_pages - 1))
result.append({
"title": str(item.get("title") or "Untitled"),
"start": start,
"end": max(start, end),
"page_start_index": page_start_index,
"page_end_index": page_end_index,
})
return result
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@staticmethod
def _to_int(value: Any, default: int | None) -> int | None:
try:
if value is None or value == "":
return default
return int(value)
except Exception:
return default