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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# DeepFlow Service
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## Overview
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DeepFlow is an LLM-driven service for planning and reasoning tasks, supporting multiple LLM providers.
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## Architecture
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```
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runtime/deep-flow/
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├── conf.yaml # DeepFlow configuration file
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├── .env # Environment variables
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└── (other source code)
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```
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## Configuration
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### Basic Configuration (conf.yaml)
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```yaml
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# Basic model configuration
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BASIC_MODEL:
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base_url: https://api.example.com/v1
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model: "model-name"
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api_key: your_api_key
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max_retries: 3
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verify_ssl: false # Set to false if using self-signed certificates
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# Reasoning model configuration (optional)
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REASONING_MODEL:
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base_url: https://api.example.com/v1
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model: "reasoning-model-name"
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api_key: your_api_key
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max_retries: 3
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# Search engine configuration (optional)
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SEARCH_ENGINE:
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engine: tavily
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include_domains:
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- example.com
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- trusted-news.com
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exclude_domains:
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- spam-site.com
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search_depth: "advanced"
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include_raw_content: true
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include_images: true
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include_image_descriptions: true
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min_score_threshold: 0.0
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max_content_length_per_page: 4000
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```
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## Supported LLM Providers
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#### OpenAI
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```yaml
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BASIC_MODEL:
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base_url: https://api.openai.com/v1
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model: "gpt-4"
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api_key: sk-...
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```
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#### Ollama (Local Deployment)
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```yaml
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BASIC_MODEL:
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base_url: "http://localhost:11434/v1"
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model: "qwen2:7b"
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api_key: "ollama"
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verify_ssl: false
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```
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#### Google AI Studio
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```yaml
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BASIC_MODEL:
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platform: "google_aistudio"
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model: "gemini-2.5-flash"
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api_key: your_gemini_api_key
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```
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## Development
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### Adding a New LLM Provider
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1. Add new model configuration in `conf.yaml`
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2. Implement corresponding API call logic
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3. Test connection and inference
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### Customizing Prompt Templates
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1. Create a prompt template file
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2. Reference the template in `conf.yaml`
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3. Test prompt effectiveness
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## Documentation
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- [DeepFlow Official Documentation](https://github.com/ModelEngine-Group/DeepFlow)
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## Related Links
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- [Runtime README](../README.md)
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