沃巴蒂
ff22ed3a8b
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）
95 lines
2.5 KiB
Markdown
95 lines
2.5 KiB
Markdown
# FAQ
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## Table of Contents
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- [Where's the name DeepFlow come from?](#wheres-the-name-DeepFlow-come-from)
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- [Which models does DeepFlow support?](#which-models-does-DeepFlow-support)
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- [How do I view complete model output?](#how-do-i-view-complete-model-output)
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- [How do I enable debug logging?](#how-do-i-enable-debug-logging)
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- [How do I troubleshoot issues?](#how-do-i-troubleshoot-issues)
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## Where's the name DeepFlow come from?
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DeepFlow is short for **D**eep **E**xploration and **E**fficient **R**esearch **Flow**. It is named after the deer, which is a symbol of gentleness and elegance. We hope DeepFlow can bring a gentle and elegant deep research experience to you.
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## Which models does DeepFlow support?
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Please refer to the [Configuration Guide](configuration_guide.md) for more details.
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## How do I view complete model output?
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If you want to see the complete model output, including system prompts, tool calls, and LLM responses:
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1. **Enable debug logging** by setting `DEBUG=True` in your `.env` file
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2. **Enable LangChain verbose logging** by adding these to your `.env`:
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```bash
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LANGCHAIN_VERBOSE=true
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LANGCHAIN_DEBUG=true
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```
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3. **Use LangSmith tracing** for visual debugging (recommended for production):
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```bash
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LANGSMITH_TRACING=true
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LANGSMITH_API_KEY="your-api-key"
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LANGSMITH_PROJECT="your-project-name"
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```
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For detailed instructions, see the [Debugging Guide](DEBUGGING.md).
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## How do I enable debug logging?
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To enable debug logging:
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1. Open your `.env` file
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2. Set `DEBUG=True`
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3. Restart your application
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For Docker Compose:
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```bash
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docker compose restart
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```
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For development:
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```bash
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uv run main.py
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```
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You'll now see detailed logs including:
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- System prompts sent to LLMs
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- Model responses
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- Tool execution details
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- Workflow state transitions
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See the [Debugging Guide](DEBUGGING.md) for more options.
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## How do I troubleshoot issues?
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When encountering issues:
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1. **Check the logs**: Enable debug logging as described above
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2. **Review configuration**: Ensure your `.env` and `conf.yaml` are correct
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3. **Check existing issues**: Search [GitHub Issues]() for similar problems
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4. **Enable verbose logging**: Use `LANGCHAIN_VERBOSE=true` for detailed output
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5. **Use LangSmith**: For visual debugging, enable LangSmith tracing
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For Docker-specific issues:
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```bash
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# View logs
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docker compose logs -f
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# Check container status
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docker compose ps
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# Restart services
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docker compose restart
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```
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For more detailed troubleshooting steps, see the [Debugging Guide](DEBUGGING.md).
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