Files
ragflow/deepdoc/parser/docling_parser.py
euvre 2846a93998 Fix: Remove hardcoded page limits causing parsing failures on large PDFs (>300 pages) (#14382)
### What problem does this PR solve?

Fixes #14196

## Problem

When using DeepDOC to parse large PDFs (over 1000 pages), the parser
silently truncated processing at 300 pages due to a hardcoded default
`page_to=299` in `RAGFlowPdfParser.__images__()`. This caused:

- **Errors** on pages beyond the limit
- **Poor image quality** as the parser attempted to compensate with
missing page data
- **Inconsistent chunk splitting** between full PDF imports and partial
imports

Additionally, the codebase scattered magic numbers (`299`, `600`,
`10000`, `100000`, `100000000`, `10000000000`, `10**9`) across 22 files
as sentinel values for "parse all pages", making future maintenance
error-prone.

## Root Cause

```python
# deepdoc/parser/pdf_parser.py (before)
def __images__(self, fnm, zoomin=3, page_from=0, page_to=299, callback=None):
    # Only the first 300 pages were rendered; everything beyond was silently dropped
```

While most callers in `rag/app/*.py` correctly passed `to_page=100000`,
the base class `RAGFlowPdfParser.__call__()` and `parse_into_bboxes()`
invoked `__images__` **without** forwarding `page_from`/`page_to`,
falling back to the restrictive default of 299.

## Solution

### 1. Define constants in `common/constants.py`

```python
MAXIMUM_PAGE_NUMBER = 100000                        # Used by the parsing layer
MAXIMUM_TASK_PAGE_NUMBER = MAXIMUM_PAGE_NUMBER * 1000  # Used by the task/DB layer
```

### 2. Replace all hardcoded sentinel values

| Layer | Files Changed | Old Values | New Value |
|---|---|---|---|
| **Deepdoc parsers** | `pdf_parser.py`, `mineru_parser.py`,
`docling_parser.py`, `opendataloader_parser.py`, `paddleocr_parser.py`,
`docx_parser.py` | `299`, `600`, `10**9`, `100000000` |
`MAXIMUM_PAGE_NUMBER` |
| **Chunk parsers** | `naive.py`, `book.py`, `qa.py`, `one.py`,
`manual.py`, `paper.py`, `presentation.py`, `laws.py`, `resume.py`,
`email.py`, `table.py` | `100000`, `10000`, `10000000000` |
`MAXIMUM_PAGE_NUMBER` |
| **Task/DB layer** | `db_models.py`, `task_service.py`,
`document_service.py`, `file_service.py` | `100000000` |
`MAXIMUM_TASK_PAGE_NUMBER` |

### 3. Fix `parse_into_bboxes()` missing parameters

Added `from_page`/`to_page` parameters to `parse_into_bboxes()` so that
the `rag/flow/parser/parser.py` DeepDOC path no longer falls back to the
restrictive default.

## Files Changed (22)

- `common/constants.py`
- `deepdoc/parser/pdf_parser.py`
- `deepdoc/parser/mineru_parser.py`
- `deepdoc/parser/docling_parser.py`
- `deepdoc/parser/opendataloader_parser.py`
- `deepdoc/parser/paddleocr_parser.py`
- `deepdoc/parser/docx_parser.py`
- `rag/app/naive.py`
- `rag/app/book.py`
- `rag/app/qa.py`
- `rag/app/one.py`
- `rag/app/manual.py`
- `rag/app/paper.py`
- `rag/app/presentation.py`
- `rag/app/laws.py`
- `rag/app/resume.py`
- `rag/app/email.py`
- `rag/app/table.py`
- `api/db/db_models.py`
- `api/db/services/task_service.py`
- `api/db/services/document_service.py`
- `api/db/services/file_service.py`

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring

---------

Signed-off-by: noob <yixiao121314@outlook.com>
2026-04-27 14:57:20 +08:00

588 lines
23 KiB
Python

#
# Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from __future__ import annotations
import logging
import re
import base64
import os
from dataclasses import dataclass
from enum import Enum
from io import BytesIO
from os import PathLike
from pathlib import Path
from typing import Any, Callable, Iterable, Optional
import pdfplumber
import requests
from PIL import Image
from common.constants import MAXIMUM_PAGE_NUMBER
try:
from docling.document_converter import DocumentConverter
except Exception:
DocumentConverter = None
try:
from deepdoc.parser.pdf_parser import RAGFlowPdfParser
except Exception:
class RAGFlowPdfParser:
pass
from deepdoc.parser.utils import extract_pdf_outlines
class DoclingContentType(str, Enum):
IMAGE = "image"
TABLE = "table"
TEXT = "text"
EQUATION = "equation"
@dataclass
class _BBox:
page_no: int
x0: float
y0: float
x1: float
y1: float
def _extract_bbox_from_prov(item, prov_attr: str = "prov") -> Optional[_BBox]:
prov = getattr(item, prov_attr, None)
if not prov:
return None
prov_item = prov[0] if isinstance(prov, list) else prov
pn = getattr(prov_item, "page_no", None)
bb = getattr(prov_item, "bbox", None)
if pn is None or bb is None:
return None
coords = [getattr(bb, attr) for attr in ("l", "t", "r", "b")]
if None in coords:
return None
return _BBox(page_no=int(pn), x0=coords[0], y0=coords[1], x1=coords[2], y1=coords[3])
class DoclingParser(RAGFlowPdfParser):
def __init__(self, docling_server_url: str = "", request_timeout: int = 600):
self.logger = logging.getLogger(self.__class__.__name__)
self.page_images: list[Image.Image] = []
self.page_from = 0
self.page_to = 10_000
self.outlines = []
self.docling_server_url = (docling_server_url or "").rstrip("/")
self.request_timeout = request_timeout
def _effective_server_url(self, docling_server_url: Optional[str] = None) -> str:
return (docling_server_url or self.docling_server_url or "").rstrip("/") or (
os.environ.get("DOCLING_SERVER_URL", "").rstrip("/")
)
@staticmethod
def _is_http_endpoint_valid(url: str, timeout: int = 5) -> bool:
try:
response = requests.head(url, timeout=timeout, allow_redirects=True)
return response.status_code in [200, 301, 302, 307, 308]
except Exception:
try:
response = requests.get(url, timeout=timeout, allow_redirects=True)
return response.status_code in [200, 301, 302, 307, 308]
except Exception:
return False
def check_installation(self, docling_server_url: Optional[str] = None) -> bool:
server_url = self._effective_server_url(docling_server_url)
if server_url:
for path in ("/openapi.json", "/docs", "/v1/convert/source"):
if self._is_http_endpoint_valid(f"{server_url}{path}", timeout=5):
return True
self.logger.warning(f"[Docling] external server not reachable: {server_url}")
return False
if DocumentConverter is None:
self.logger.warning("[Docling] 'docling' is not importable, please: pip install docling")
return False
try:
_ = DocumentConverter()
return True
except Exception as e:
self.logger.error(f"[Docling] init DocumentConverter failed: {e}")
return False
def __images__(self, fnm, zoomin: int = 1, page_from=0, page_to=MAXIMUM_PAGE_NUMBER, callback=None):
self.page_from = page_from
self.page_to = page_to
bytes_io = None
try:
if not isinstance(fnm, (str, PathLike)):
bytes_io = BytesIO(fnm)
opener = pdfplumber.open(fnm) if isinstance(fnm, (str, PathLike)) else pdfplumber.open(bytes_io)
with opener as pdf:
pages = pdf.pages[page_from:page_to]
self.page_images = [p.to_image(resolution=72 * zoomin, antialias=True).original for p in pages]
except Exception as e:
self.page_images = []
self.logger.exception(e)
finally:
if bytes_io:
bytes_io.close()
def _make_line_tag(self,bbox: _BBox) -> str:
if bbox is None:
return ""
x0,x1, top, bott = bbox.x0, bbox.x1, bbox.y0, bbox.y1
if hasattr(self, "page_images") and self.page_images and len(self.page_images) >= bbox.page_no:
_, page_height = self.page_images[bbox.page_no-1].size
top, bott = page_height-top ,page_height-bott
return "@@{}\t{:.1f}\t{:.1f}\t{:.1f}\t{:.1f}##".format(
bbox.page_no, x0,x1, top, bott
)
@staticmethod
def extract_positions(txt: str) -> list[tuple[list[int], float, float, float, float]]:
poss = []
for tag in re.findall(r"@@[0-9-]+\t[0-9.\t]+##", txt):
pn, left, right, top, bottom = tag.strip("#").strip("@").split("\t")
left, right, top, bottom = float(left), float(right), float(top), float(bottom)
poss.append(([int(p) - 1 for p in pn.split("-")], left, right, top, bottom))
return poss
def crop(self, text: str, ZM: int = 1, need_position: bool = False):
imgs = []
poss = self.extract_positions(text)
if not poss:
return (None, None) if need_position else None
GAP = 6
pos = poss[0]
poss.insert(0, ([pos[0][0]], pos[1], pos[2], max(0, pos[3] - 120), max(pos[3] - GAP, 0)))
pos = poss[-1]
poss.append(([pos[0][-1]], pos[1], pos[2], min(self.page_images[pos[0][-1]].size[1], pos[4] + GAP), min(self.page_images[pos[0][-1]].size[1], pos[4] + 120)))
positions = []
for ii, (pns, left, right, top, bottom) in enumerate(poss):
if bottom <= top:
bottom = top + 4
img0 = self.page_images[pns[0]]
x0, y0, x1, y1 = int(left), int(top), int(right), int(min(bottom, img0.size[1]))
crop0 = img0.crop((x0, y0, x1, y1))
imgs.append(crop0)
if 0 < ii < len(poss)-1:
positions.append((pns[0] + self.page_from, x0, x1, y0, y1))
remain_bottom = bottom - img0.size[1]
for pn in pns[1:]:
if remain_bottom <= 0:
break
page = self.page_images[pn]
x0, y0, x1, y1 = int(left), 0, int(right), int(min(remain_bottom, page.size[1]))
cimgp = page.crop((x0, y0, x1, y1))
imgs.append(cimgp)
if 0 < ii < len(poss) - 1:
positions.append((pn + self.page_from, x0, x1, y0, y1))
remain_bottom -= page.size[1]
if not imgs:
return (None, None) if need_position else None
height = sum(i.size[1] + GAP for i in imgs)
width = max(i.size[0] for i in imgs)
pic = Image.new("RGB", (width, int(height)), (245, 245, 245))
h = 0
for ii, img in enumerate(imgs):
if ii == 0 or ii + 1 == len(imgs):
img = img.convert("RGBA")
overlay = Image.new("RGBA", img.size, (0, 0, 0, 0))
overlay.putalpha(128)
img = Image.alpha_composite(img, overlay).convert("RGB")
pic.paste(img, (0, int(h)))
h += img.size[1] + GAP
return (pic, positions) if need_position else pic
def _iter_doc_items(self, doc) -> Iterable[tuple[str, Any, Optional[_BBox]]]:
for t in getattr(doc, "texts", []):
parent = getattr(t, "parent", "")
ref = getattr(parent, "cref", "")
label = getattr(t, "label", "")
if (label in ("section_header", "text") and ref in ("#/body",)) or label in ("list_item",):
text = getattr(t, "text", "") or ""
bbox = _extract_bbox_from_prov(t)
yield (DoclingContentType.TEXT.value, text, bbox)
for item in getattr(doc, "texts", []):
if getattr(item, "label", "") in ("FORMULA",):
text = getattr(item, "text", "") or ""
bbox = _extract_bbox_from_prov(item)
yield (DoclingContentType.EQUATION.value, text, bbox)
def _transfer_to_sections(self, doc, parse_method: str) -> list[tuple[str, ...]]:
sections: list[tuple[str, ...]] = []
for typ, payload, bbox in self._iter_doc_items(doc):
if typ == DoclingContentType.TEXT.value:
section = payload.strip()
if not section:
continue
elif typ == DoclingContentType.EQUATION.value:
section = payload.strip()
else:
continue
tag = self._make_line_tag(bbox) if isinstance(bbox,_BBox) else ""
if parse_method in {"manual", "pipeline"}:
sections.append((section, typ, tag))
elif parse_method == "paper":
sections.append((section + tag, typ))
else:
sections.append((section, tag))
return sections
def cropout_docling_table(self, page_no: int, bbox: tuple[float, float, float, float], zoomin: int = 1):
if not getattr(self, "page_images", None):
return None, ""
idx = (page_no - 1) - getattr(self, "page_from", 0)
if idx < 0 or idx >= len(self.page_images):
return None, ""
page_img = self.page_images[idx]
W, H = page_img.size
left, top, right, bott = bbox
x0 = float(left)
y0 = float(H-top)
x1 = float(right)
y1 = float(H-bott)
x0, y0 = max(0.0, min(x0, W - 1)), max(0.0, min(y0, H - 1))
x1, y1 = max(x0 + 1.0, min(x1, W)), max(y0 + 1.0, min(y1, H))
try:
crop = page_img.crop((int(x0), int(y0), int(x1), int(y1))).convert("RGB")
except Exception:
return None, ""
pos = (page_no-1 if page_no>0 else 0, x0, x1, y0, y1)
return crop, [pos]
def _transfer_to_tables(self, doc):
tables = []
for tab in getattr(doc, "tables", []):
img = None
positions = ""
bbox = _extract_bbox_from_prov(tab)
if bbox:
img, positions = self.cropout_docling_table(bbox.page_no, (bbox.x0, bbox.y0, bbox.x1, bbox.y1))
html = ""
try:
html = tab.export_to_html(doc=doc)
except Exception:
pass
tables.append(((img, html), positions if positions else ""))
for pic in getattr(doc, "pictures", []):
img = None
positions = ""
bbox = _extract_bbox_from_prov(pic)
if bbox:
img, positions = self.cropout_docling_table(bbox.page_no, (bbox.x0, bbox.y0, bbox.x1, bbox.y1))
captions = ""
try:
captions = pic.caption_text(doc=doc)
except Exception:
pass
tables.append(((img, [captions]), positions if positions else ""))
return tables
@staticmethod
def _sections_from_remote_text(text: str, parse_method: str) -> list[tuple[str, ...]]:
txt = (text or "").strip()
if not txt:
return []
if parse_method in {"manual", "pipeline"}:
return [(txt, DoclingContentType.TEXT.value, "")]
if parse_method == "paper":
return [(txt, DoclingContentType.TEXT.value)]
return [(txt, "")]
@staticmethod
def _extract_remote_document_entries(payload: Any) -> list[dict[str, Any]]:
if not isinstance(payload, dict):
return []
if isinstance(payload.get("document"), dict):
return [payload["document"]]
if isinstance(payload.get("documents"), list):
return [d for d in payload["documents"] if isinstance(d, dict)]
if isinstance(payload.get("results"), list):
docs = []
for it in payload["results"]:
if isinstance(it, dict):
if isinstance(it.get("document"), dict):
docs.append(it["document"])
elif isinstance(it.get("result"), dict):
docs.append(it["result"])
else:
docs.append(it)
return docs
return []
def _parse_pdf_remote(
self,
filepath: str | PathLike[str],
binary: BytesIO | bytes | None = None,
callback: Optional[Callable] = None,
*,
parse_method: str = "raw",
docling_server_url: Optional[str] = None,
request_timeout: Optional[int] = None,
):
"""
Parses a PDF document using a remote Docling server.
Prioritizes native chunking endpoints (/v1/chunk/source, /v1alpha/chunk/source)
to prevent token overflow, with a graceful fallback to standard conversion
endpoints if chunking is unavailable.
"""
server_url = self._effective_server_url(docling_server_url)
if not server_url:
raise RuntimeError("[Docling] DOCLING_SERVER_URL is not configured.")
timeout = request_timeout or self.request_timeout
if binary is not None:
if isinstance(binary, (bytes, bytearray)):
pdf_bytes = bytes(binary)
else:
pdf_bytes = bytes(binary.getbuffer())
else:
src_path = Path(filepath)
if not src_path.exists():
raise FileNotFoundError(f"PDF not found: {src_path}")
with open(src_path, "rb") as f:
pdf_bytes = f.read()
if callback:
callback(0.2, f"[Docling] Requesting external server: {server_url}")
filename = Path(filepath).name or "input.pdf"
b64 = base64.b64encode(pdf_bytes).decode("ascii")
# Standard payloads
# Standard fallback payloads (no chunking)
v1_payload_standard = {
"options": {"from_formats": ["pdf"], "to_formats": ["json", "md", "text"]},
"sources": [{"kind": "file", "filename": filename, "base64_string": b64}],
}
v1alpha_payload_standard = {
"options": {"from_formats": ["pdf"], "to_formats": ["json", "md", "text"]},
"file_sources": [{"filename": filename, "base64_string": b64}],
}
# --- NEW: Correct API Contract for Chunking ---
chunking_opts = {
"from_formats": ["pdf"],
"to_formats": ["json", "md", "text"],
"do_chunking": True,
"chunking_options": {
"max_tokens": 512,
"overlap": 50,
"tokenizer": "sentencepiece" # Required by Docling contract
}
}
v1_payload_chunked = {
"options": chunking_opts,
"sources": [{"kind": "file", "filename": filename, "base64_string": b64}],
}
v1alpha_payload_chunked = {
"options": chunking_opts,
"file_sources": [{"filename": filename, "base64_string": b64}],
}
errors = []
response_json = None
is_chunked_response = False
# Try chunked endpoints first, then fall back to standard if the server is older
for endpoint, payload, chunk_flag in (
("/v1/convert/source", v1_payload_chunked, True),
("/v1alpha/convert/source", v1alpha_payload_chunked, True),
("/v1/convert/source", v1_payload_standard, False),
("/v1alpha/convert/source", v1alpha_payload_standard, False),
):
try:
resp = requests.post(
f"{server_url}{endpoint}",
json=payload,
timeout=timeout,
)
if resp.status_code < 300:
response_json = resp.json()
is_chunked_response = chunk_flag
if chunk_flag:
self.logger.info(f"[Docling] Successfully used native chunking on: {endpoint}")
else:
self.logger.info(f"[Docling] Chunking unavailable, fell back to standard: {endpoint}")
break
# If chunking request is rejected (e.g., 422 Unprocessable Entity on older servers),
# log it and let the loop naturally fall back to the standard payload.
if chunk_flag:
self.logger.warning(f"[Docling] Server rejected chunking parameters: HTTP {resp.status_code}")
continue
errors.append(f"{endpoint}: HTTP {resp.status_code} {resp.text[:300]}")
except Exception as exc:
self.logger.error(f"[Docling] Request error on {endpoint}: {exc}")
errors.append(f"{endpoint}: {exc}")
if response_json is None:
raise RuntimeError("[Docling] remote convert failed: " + " | ".join(errors))
sections: list[tuple[str, ...]] = []
tables = []
# --- NEW: Handle Native Chunked Response ---
if is_chunked_response:
# The chunking endpoint returns an array of chunk items
chunks = response_json if isinstance(response_json, list) else response_json.get("results", [])
for chunk_data in chunks:
if not isinstance(chunk_data, dict):
continue
# Depending on the exact docling-serve spec, the text might be nested
chunk_text = chunk_data.get("text", "")
if not chunk_text and isinstance(chunk_data.get("chunk"), dict):
chunk_text = chunk_data["chunk"].get("text", "")
if isinstance(chunk_text, str) and chunk_text.strip():
# Feed the pre-sliced chunks directly into RAGFlow's expected format
sections.extend(self._sections_from_remote_text(chunk_text, parse_method=parse_method))
if callback:
callback(0.95, f"[Docling] Native chunks received: {len(sections)}")
return sections, tables
# --- FALLBACK: Standard RAGFlow parsing for older docling servers ---
docs = self._extract_remote_document_entries(response_json)
if not docs:
raise RuntimeError("[Docling] remote response does not contain parsed documents.")
for doc in docs:
md = doc.get("md_content")
txt = doc.get("text_content")
if isinstance(md, str) and md.strip():
sections.extend(self._sections_from_remote_text(md, parse_method=parse_method))
elif isinstance(txt, str) and txt.strip():
sections.extend(self._sections_from_remote_text(txt, parse_method=parse_method))
json_content = doc.get("json_content")
if isinstance(json_content, dict):
md_fallback = json_content.get("md_content")
if isinstance(md_fallback, str) and md_fallback.strip() and not sections:
sections.extend(self._sections_from_remote_text(md_fallback, parse_method=parse_method))
if callback:
callback(0.95, f"[Docling] Remote sections: {len(sections)}")
return sections, tables
def parse_pdf(
self,
filepath: str | PathLike[str],
binary: BytesIO | bytes | None = None,
callback: Optional[Callable] = None,
*,
output_dir: Optional[str] = None,
lang: Optional[str] = None,
method: str = "auto",
delete_output: bool = True,
parse_method: str = "raw",
docling_server_url: Optional[str] = None,
request_timeout: Optional[int] = None,
):
self.outlines = extract_pdf_outlines(binary if binary is not None else filepath)
if not self.check_installation(docling_server_url=docling_server_url):
raise RuntimeError("Docling not available, please install `docling`")
server_url = self._effective_server_url(docling_server_url)
if server_url:
return self._parse_pdf_remote(
filepath=filepath,
binary=binary,
callback=callback,
parse_method=parse_method,
docling_server_url=server_url,
request_timeout=request_timeout,
)
if binary is not None:
tmpdir = Path(output_dir) if output_dir else Path.cwd() / ".docling_tmp"
tmpdir.mkdir(parents=True, exist_ok=True)
name = Path(filepath).name or "input.pdf"
tmp_pdf = tmpdir / name
with open(tmp_pdf, "wb") as f:
if isinstance(binary, (bytes, bytearray)):
f.write(binary)
else:
f.write(binary.getbuffer())
src_path = tmp_pdf
else:
src_path = Path(filepath)
if not src_path.exists():
raise FileNotFoundError(f"PDF not found: {src_path}")
if callback:
callback(0.1, f"[Docling] Converting: {src_path}")
try:
self.__images__(str(src_path), zoomin=1)
except Exception as e:
self.logger.warning(f"[Docling] render pages failed: {e}")
conv = DocumentConverter()
conv_res = conv.convert(str(src_path))
doc = conv_res.document
if callback:
callback(0.7, f"[Docling] Parsed doc: {getattr(doc, 'num_pages', 'n/a')} pages")
sections = self._transfer_to_sections(doc, parse_method=parse_method)
tables = self._transfer_to_tables(doc)
if callback:
callback(0.95, f"[Docling] Sections: {len(sections)}, Tables: {len(tables)}")
if binary is not None and delete_output:
try:
Path(src_path).unlink(missing_ok=True)
except Exception:
pass
if callback:
callback(1.0, "[Docling] Done.")
return sections, tables
if __name__ == "__main__":
logging.basicConfig(level=logging.INFO)
parser = DoclingParser()
print("Docling available:", parser.check_installation())
sections, tables = parser.parse_pdf(filepath="test_docling/toc.pdf", binary=None)
print(len(sections), len(tables))