[Question]: Failed to exec “uv sync –python 3.10 –all-extras ” on linux manjaro.
![[Question]: Failed to exec "uv sync --python 3.10 --all-extras " on linux manjaro.](https://www.chat-gpts.plus/wp-content/uploads/2026/07/6716-a2505e14-768x403.jpg)
在 Linux Manjaro 上执行 uv sync --python 3.10 --all-extras 安装 RAGFlow 时， datrie 包编译失败，原因是 gcc 将 incompatible-pointer-types 视为错误。优先尝试通过环境变量忽略该编译错误后重新运行命令。
标签： Python
[Feature Request]: The absence of sandbox configuration and image in helm prevents the execution of code and adminServer, whereas they exist
![[Feature Request]: The absence of sandbox configuration and image in helm prevents the execution of code and adminServer, whereas they exist](https://www.chat-gpts.plus/wp-content/uploads/2026/07/12042-b1dc84a7-768x403.jpg)
该报错发生在使用 RAGFlow 的 Helm Chart 部署时，因缺少 sandbox 相关环境变量和镜像引用，导致 code 和 adminServer 无法在沙箱模式下执行。优先排查 Helm values.yaml 与 env.yaml 中是否包含 SANDBOX_HOST 、 SANDB
[Bug]: Seems like Azure OpenAI models are not working anymore when added directly via Azure?
![[Bug]: Seems like Azure OpenAI models are not working anymore when added directly via Azure?](https://www.chat-gpts.plus/wp-content/uploads/2026/07/12397-85330757-768x403.jpg)
RAGFlow 升级到 v0.23.x 后，通过 Azure 直接添加的 OpenAI 模型调用时返回 404 Resource not found。优先排查异步聊天路径是否使用了 Azure 专用异步客户端 ( AsyncAzureOpenAI ) 代替通用 AsyncOpenAI 。
[Bug]: LM Studio not working with LiteLLM Proxy
![[Bug]: LM Studio not working with LiteLLM Proxy](https://www.chat-gpts.plus/wp-content/uploads/2026/07/11733-211b5be4-768x403.jpg)
该报错发生在使用 LiteLLM Proxy 转发请求到仅提供同步 OpenAI 兼容端点的本地模型（如 LM Studio）时，LiteLLM Proxy 默认使用异步请求导致连接失败。优先排查 LiteLLM Proxy 配置中的 api_base 路径是否完整，以及 Docker 环境下的网络
issue: Admin Panel Open Terminal integration saves to user settings endpoint instead of config endpoint
该报错 “Admin Panel Open Terminal integration saves to user settings endpoint instead of config endpoint” 通常发生在用户在 用户个人设置面板 （Settings → Integrations）而非 管
Node ‘ID #98:17’ has no class_type. The workflow may be corrupted or a custom node is missing.
该报错 Node 'ID #98:17' has no class_type. The workflow may be corrupted or a custom node is missing. 通常出现在加载工作流时遇到无法识别的节点 ID，最常见原因是该工作流依赖的自定义节点未安装。优先检查工
bug: run_batched_evaluation mapper parameter’s MapperFunction protocol mismatch
该报错源于 run_batched_evaluation 中 MapperFunction 的参数类型不匹配 —— 函数签名要求 TraceWithFullDetails ，但底层通过 trace.list 返回的是 TraceWithDetails 。优先排查是否使用了 trace‑level 评
bug: Expected Output doesn’t show/display in Datasets/Items/experiments
此报错出现在 Langfuse Cloud 的 Dataset/Items/experiment 页面中，“Expected Output”列始终为空（不显示任何内容），尽管 API 中数据已正确存储。这是前端 UI 转换函数遗漏了 datasetItemId 字段导致的渲染 Bug，不影响数据完整
[BUG]: How to upload a folder with subfolders with files to AnythingLLM?
![[BUG]: How to upload a folder with subfolders with files to AnythingLLM?](https://www.chat-gpts.plus/wp-content/uploads/2026/07/2235-c2ffb740-768x403.jpg)
该诉求是希望 AnythingLLM 支持上传包含子文件夹的文件夹（目录递归），目前桌面版和 Docker 版均未原生提供通过文件选择器上传文件夹的功能。优先排查：确认是否可通过拖拽文件夹到窗口实现部分效果；如需完整路径保留，需等待官方计划中的“Local folder”数据连接器。
[BUG]: Pinned and Watched Documents without RAG
![[BUG]: Pinned and Watched Documents without RAG](https://www.chat-gpts.plus/wp-content/uploads/2026/07/5334-284a6ed2-768x403.jpg)
当你在 AnythingLLM Desktop 中同时将一个文档设为 Pinned （固定）和 Watched （监视），并期望每次新消息都自动注入该文档的最新内容（不通过 RAG 嵌入）时，会遇到 [BUG]: Pinned and Watched Documents without RAG ——