ragflow/deepdoc/parser/figure_parser.py
Yongteng Lei 9611185eb4
Feat: add VLM-boosted DocX parser (#6307)
### What problem does this PR solve?

Add VLM-boosted DocX parser

### Type of change

- [x] New Feature (non-breaking change which adds functionality)
2025-03-20 11:24:44 +08:00

92 lines
3.3 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 PIL import Image
from rag.app.picture import vision_llm_chunk as picture_vision_llm_chunk
from rag.prompts import vision_llm_figure_describe_prompt
def vision_figure_parser_figure_data_wraper(figures_data_without_positions):
return [(
(figure_data[1], [figure_data[0]]),
[(0, 0, 0, 0, 0)]
) for figure_data in figures_data_without_positions if isinstance(figure_data[1], Image.Image)]
class VisionFigureParser:
def __init__(self, vision_model, figures_data, *args, **kwargs):
self.vision_model = vision_model
self._extract_figures_info(figures_data)
assert len(self.figures) == len(self.descriptions)
assert not self.positions or (len(self.figures) == len(self.positions))
def _extract_figures_info(self, figures_data):
self.figures = []
self.descriptions = []
self.positions = []
for item in figures_data:
# position
if len(item) == 2 and isinstance(item[1], list) and len(item[1]) == 1 and isinstance(item[1][0], tuple) and len(item[1][0]) == 5:
img_desc = item[0]
assert len(img_desc) == 2 and isinstance(img_desc[0], Image.Image) and isinstance(img_desc[1], list), "Should be (figure, [description])"
self.figures.append(img_desc[0])
self.descriptions.append(img_desc[1])
self.positions.append(item[1])
else:
assert len(item) == 2 and isinstance(item, tuple) and isinstance(item[1], list), f"get {len(item)=}, {item=}"
self.figures.append(item[0])
self.descriptions.append(item[1])
def _assemble(self):
self.assembled = []
self.has_positions = len(self.positions) != 0
for i in range(len(self.figures)):
figure = self.figures[i]
desc = self.descriptions[i]
pos = self.positions[i] if self.has_positions else None
figure_desc = (figure, desc)
if pos is not None:
self.assembled.append((figure_desc, pos))
else:
self.assembled.append((figure_desc,))
return self.assembled
def __call__(self, **kwargs):
callback = kwargs.get("callback", lambda prog, msg: None)
for idx, img_binary in enumerate(self.figures or []):
figure_num = idx # 0-based
txt = picture_vision_llm_chunk(
binary=img_binary,
vision_model=self.vision_model,
prompt=vision_llm_figure_describe_prompt(),
callback=callback,
)
if txt:
self.descriptions[figure_num] = txt + "\n".join(self.descriptions[figure_num])
self._assemble()
return self.assembled