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deepdata/runtime/ops/slicer/segmentation/process.py
T
沃巴蒂 ff22ed3a8b feat(deepdata): 引入修改密码、文件预览组件与清洗算子增强,deepflow 改名为 deep-flow
本次同步 09-12 至 09-28 的代码变更,主要内容:

新增功能
- 修改密码:后端新增 ChangePasswordRequest DTO 与UserController/UserService
  对应接口,前端新增 ChangePasswordDialog 并在 Header 接入入口
- 文件预览组件重构:file-preview 目录拆分出 VideoPreview(支持 blobUrl 直传)、
  ImagePreview、AudioPreview,index.tsx 统一调度各类型预览器
- 新增 my_ops 算子模块:markitdown_parser、mineru_pdf_parser、text_quality_evaluator
- 新增 tools/minio-file-server MinIO 文件服务

功能增强
- 数据清洗:cleaning_task_service/scheduler/routes 重构,
  data_juicer_executor 与 wrapper 增强,OperatorTable/LogsTable/TaskDetail 同步调整
- 数据标注:annotation sync.py、project.py 接口与schema 更新
- 数据采集、算子市场、首页与菜单路由相关页面调整
- DataJuicer 算子接入(useOperatorOperations、dj_ops_schema)

结构调整
- deepflow/ 更名为 deep-flow/(419 个文件重命名)
- 新增 helm 部署编排、GitHub Actions 之外的自建镜像构建脚本

未纳入本次提交
- scripts-backup/、runtime/python-executor-backup/、components_backup/(备份目录)
- *.backup*、__pycache__ 产物
- zh_core_web_sm-3.8.0-py3-none-any.whl(46MB 构建产物)
- DataX/(内嵌独立仓库,远程亦未收录其源码)
2026-10-03 22:44:56 +08:00

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#!/user/bin/python
# -*- coding: utf-8 -*-
"""
Description: 文本切分算子
Create: 2023/11/09 10:17
"""
import random
from typing import List, Dict, Any
from loguru import logger
from deepdata.common.utils.text_splitter import TextSplitter
from deepdata.core.base_op import Slicer
class TextSegmentationOperator:
def __init__(self, max_characters, chunk_size, chunk_overlap):
try:
self.text_splitter = TextSplitter(max_characters, chunk_size, chunk_overlap)
except Exception as err:
logger.exception(f"init text splitter failed, error is: {err}")
raise Exception(83001, "init text splitter failed") from None
def process(self, input_data: str) -> List[str]:
if input_data.strip() == "":
logger.info("input text is empty, return empty chunks.")
return []
return self.text_splitter.split_text(input_data)
class Segmentation(Slicer):
"""切片算法插件"""
def __init__(self, *args, **kwargs):
super(Segmentation, self).__init__(*args, **kwargs)
self.max_characters = kwargs.get("maxCharacters", -1)
self.chunk_size = kwargs.get("chunkSize", 800)
self.chunk_overlap = kwargs.get("chunkOverlap", 100)
self.slice_num = kwargs.get("sliceNum", -1) # -1 means no limit, export all chunks
self.text_splitter_op = TextSegmentationOperator(self.max_characters, self.chunk_size, self.chunk_overlap)
self.last_ops = True
def execute(self, sample: Dict[str, Any]) -> List[Dict]:
try:
chunks = self.text_splitter_op.process(sample[self.text_key])
except Exception as err:
logger.exception(f"split text failed, error is: {err}")
raise Exception(83002, "split text failed") from None
# Determine how many chunks to save
num_to_save = len(chunks) if self.slice_num < 0 else min(self.slice_num, len(chunks))
sample_list = []
# If slice_num is set and less than total chunks, randomly sample; otherwise save all in order
if 0 < self.slice_num < len(chunks):
selected_indices = sorted(random.sample(range(len(chunks)), num_to_save))
else:
selected_indices = list(range(num_to_save))
for idx in selected_indices:
chunk = chunks[idx]
temp_sample = {
self.text_key: chunk,
self.data_key: "",
self.export_path_key: sample[self.export_path_key],
self.filename_key: sample[self.filename_key],
self.fileid_key: sample[self.fileid_key],
"sequenceId": str(idx),
"chunkSize": str(len(chunk)),
}
self.save_patch_sample(temp_sample, idx + 1, save_format="text")
sample_list.append(temp_sample)
sample["fileNum"] = len(chunks)
# Keep original text if not all chunks are saved; clear text if all chunks are saved as slices
if num_to_save < len(chunks):
sample[self.text_key] = chunks[0] if chunks else ""
else:
# All chunks saved as slices, clear text to avoid duplication
sample[self.text_key] = ""
return sample_list