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）
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沃巴蒂
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# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
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# SPDX-License-Identifier: MIT
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"""
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Entry point script for the DeepFlow project.
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"""
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import argparse
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import asyncio
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from InquirerPy import inquirer
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from src.config.questions import BUILT_IN_QUESTIONS, BUILT_IN_QUESTIONS_ZH_CN
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from src.workflow import run_agent_workflow_async
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def ask(
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question,
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debug=False,
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max_plan_iterations=1,
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max_step_num=3,
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enable_background_investigation=True,
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enable_clarification=False,
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max_clarification_rounds=None,
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):
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"""Run the agent workflow with the given question.
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Args:
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question: The user's query or request
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debug: If True, enables debug level logging
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max_plan_iterations: Maximum number of plan iterations
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max_step_num: Maximum number of steps in a plan
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enable_background_investigation: If True, performs web search before planning to enhance context
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enable_clarification: If False (default), skip clarification; if True, enable multi-turn clarification
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max_clarification_rounds: Maximum number of clarification rounds (default: None, uses State default=3)
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"""
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asyncio.run(
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run_agent_workflow_async(
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user_input=question,
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debug=debug,
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max_plan_iterations=max_plan_iterations,
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max_step_num=max_step_num,
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enable_background_investigation=enable_background_investigation,
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enable_clarification=enable_clarification,
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max_clarification_rounds=max_clarification_rounds,
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)
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)
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def main(
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debug=False,
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max_plan_iterations=1,
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max_step_num=3,
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enable_background_investigation=True,
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enable_clarification=False,
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max_clarification_rounds=None,
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):
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"""Interactive mode with built-in questions.
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Args:
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enable_background_investigation: If True, performs web search before planning to enhance context
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debug: If True, enables debug level logging
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max_plan_iterations: Maximum number of plan iterations
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max_step_num: Maximum number of steps in a plan
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enable_clarification: If False (default), skip clarification; if True, enable multi-turn clarification
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max_clarification_rounds: Maximum number of clarification rounds (default: None, uses State default=3)
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"""
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# First select language
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language = inquirer.select(
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message="Select language / 选择语言:",
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choices=["English", "中文"],
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).execute()
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# Choose questions based on language
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questions = (
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BUILT_IN_QUESTIONS if language == "English" else BUILT_IN_QUESTIONS_ZH_CN
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)
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ask_own_option = (
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"[Ask my own question]" if language == "English" else "[自定义问题]"
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)
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# Select a question
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initial_question = inquirer.select(
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message=(
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"What do you want to know?" if language == "English" else "您想了解什么?"
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),
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choices=[ask_own_option] + questions,
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).execute()
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if initial_question == ask_own_option:
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initial_question = inquirer.text(
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message=(
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"What do you want to know?"
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if language == "English"
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else "您想了解什么?"
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),
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).execute()
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# Pass all parameters to ask function
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ask(
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question=initial_question,
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debug=debug,
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max_plan_iterations=max_plan_iterations,
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max_step_num=max_step_num,
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enable_background_investigation=enable_background_investigation,
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enable_clarification=enable_clarification,
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max_clarification_rounds=max_clarification_rounds,
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)
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if __name__ == "__main__":
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# Set up argument parser
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parser = argparse.ArgumentParser(description="Run the Deer")
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parser.add_argument("query", nargs="*", help="The query to process")
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parser.add_argument(
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"--interactive",
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action="store_true",
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help="Run in interactive mode with built-in questions",
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)
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parser.add_argument(
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"--max_plan_iterations",
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type=int,
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default=1,
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help="Maximum number of plan iterations (default: 1)",
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)
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parser.add_argument(
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"--max_step_num",
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type=int,
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default=3,
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help="Maximum number of steps in a plan (default: 3)",
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)
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parser.add_argument("--debug", action="store_true", help="Enable debug logging")
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parser.add_argument(
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"--no-background-investigation",
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action="store_false",
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dest="enable_background_investigation",
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help="Disable background investigation before planning",
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)
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parser.add_argument(
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"--enable-clarification",
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action="store_true",
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dest="enable_clarification",
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help="Enable multi-turn clarification for vague questions (default: disabled)",
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)
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parser.add_argument(
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"--max-clarification-rounds",
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type=int,
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dest="max_clarification_rounds",
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help="Maximum number of clarification rounds (default: 3)",
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)
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args = parser.parse_args()
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if args.interactive:
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# Pass command line arguments to main function
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main(
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debug=args.debug,
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max_plan_iterations=args.max_plan_iterations,
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max_step_num=args.max_step_num,
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enable_background_investigation=args.enable_background_investigation,
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enable_clarification=args.enable_clarification,
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max_clarification_rounds=args.max_clarification_rounds,
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)
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else:
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# Parse user input from command line arguments or user input
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if args.query:
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user_query = " ".join(args.query)
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else:
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# Loop until user provides non-empty input
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while True:
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user_query = input("Enter your query: ")
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if user_query is not None and user_query != "":
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break
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# Run the agent workflow with the provided parameters
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ask(
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question=user_query,
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debug=args.debug,
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max_plan_iterations=args.max_plan_iterations,
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max_step_num=args.max_step_num,
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enable_background_investigation=args.enable_background_investigation,
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enable_clarification=args.enable_clarification,
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max_clarification_rounds=args.max_clarification_rounds,
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)
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