openframe-oss-frontend README

The project's README from github.com/flamingo-stack/openframe-oss-frontend. As one markdown file: README.md.

OpenFrame

License

OpenFrame OSS Frontend

OpenFrame OSS Frontend is the primary web application for the OpenFrame platform — a unified, AI-driven interface for Managed Service Providers (MSPs). It replaces expensive proprietary MSP software with intelligent open-source alternatives, bringing device management, ticketing, monitoring, scripts, and AI assistance into a single cohesive operational interface.

Built and maintained by Flamingo, this project is the human-facing layer of the OpenFrame ecosystem — connecting backend services into an AI-first MSP experience.


Features

Feature Description
Device Management Unified device model, remote shell, file manager, remote desktop via MeshCentral
Customer Management Per-organization AI configuration, guardrails templates, aggregated device counts
Ticketing Kanban boards, AI-assisted replies, approval workflows, assignment management
Knowledge Base Article management, folder organization, attachment handling
Mingo AI (Technician) Streaming AI assistant with tool execution, context awareness, and approval flows
Customer AI (Fae) Embeddable AI for client-facing portals
Monitoring Fleet MDM policies, osquery live query campaigns, query execution
Scripts Script library, scheduling, execution history
Audit Logs Organization and device-level log viewer with cursor-based pagination
Settings & Billing Tenant config, SSO, API keys, subscription management
Onboarding Step-by-step guided setup for new tenants
Feature Flags Runtime-configurable feature toggles via Zustand

Technology Stack

flowchart TD
    FE["Next.js 16 App Router (React 19)"]
    FE --> TS["TypeScript 5.8"]
    FE --> GQL["GraphQL — graphql + Relay v20"]
    FE --> RQ["TanStack Query v5"]
    FE --> ZS["Zustand v5"]
    FE --> TW["Tailwind CSS v3"]
    FE --> FC["openframe-frontend-core"]
    FE --> API["API Service Core"]
    FE --> Chat["AI / Chat Service"]
    FE --> Auth["Authorization Service"]
    FE --> Fleet["Fleet MDM"]
    FE --> Mesh["MeshCentral"]

Core Dependencies

Package Version Purpose
next ^16.2.4 SSR + App Router framework
react ^19.2.0 UI library
react-relay ^20.1.1 GraphQL fragment system
@tanstack/react-query ^5.90.16 Server-state caching and pagination
zustand ^5.0.8 Client-side state management
tailwindcss ^3.4.17 Utility-first CSS
@xterm/xterm ^6.0.0 Terminal emulator for remote shell
@monaco-editor/react ^4.7.0 Script editor
zod ^4.3.6 Runtime schema validation
@flamingo-stack/openframe-frontend-core ^0.0.480 Shared UI component library

Architecture

OpenFrame OSS Frontend acts as the presentation and orchestration layer on top of OpenFrame backend services.

flowchart LR
    Browser["User Browser"] --> Frontend["OpenFrame OSS Frontend"]
    Frontend -->|"GraphQL /api/graphql"| ApiService["API Service Core"]
    Frontend -->|"REST /chat/api"| ChatService["AI / Chat Service"]
    Frontend -->|"OAuth 2.0"| AuthService["Authorization Service"]
    Frontend -->|"/tools/fleetmdm-server"| Fleet["Fleet MDM"]
    Frontend -->|"/tools/meshcentral"| Mesh["MeshCentral"]
    ApiService --> DataLayer["MongoDB / Cassandra / Apache Pinot"]
    ChatService --> StreamLayer["Kafka / NATS"]

Application Domain Structure

The application is organized by feature domain under src/app:

flowchart TD
    App["src/app"]
    App --> Customers["customers/"]
    App --> Devices["devices/"]
    App --> Tickets["tickets/"]
    App --> KnowledgeBase["knowledge-base/"]
    App --> Logs["logs-page/"]
    App --> Monitoring["monitoring/"]
    App --> Scripts["scripts/"]
    App --> Settings["settings/"]
    App --> Mingo["mingo/"]
    App --> Onboarding["onboarding/"]
    App --> Lib["src/lib/ — API, Auth, Relay, MeshCentral"]
    App --> Stores["src/stores/ — Zustand global state"]

State Management

The application uses three complementary state management approaches:

Pattern Technology Used For
Server state TanStack Query v5 REST API calls, optimistic mutations, cursor pagination
GraphQL fragments Relay v20 Logs, scripts, notifications (streaming + pagination)
Client UI state Zustand v5 Feature flags, onboarding, Mingo chat, device filters

Quick Start

Prerequisites: Node.js 18+, npm 9+, Git. See the Prerequisites Guide for full details.

# 1. Clone the repository
git clone https://github.com/flamingo-stack/openframe-oss-frontend.git
cd openframe-oss-frontend

# 2. Install dependencies
npm install

# 3. Configure environment
cp .env.example .env.local
# Edit .env.local with your backend URLs

# 4. Start the development server
npm run dev

Open http://localhost:3000 in your browser.

Minimum Environment Variables

NEXT_PUBLIC_TENANT_HOST_URL=https://your-tenant.openframe.dev
NEXT_PUBLIC_SHARED_HOST_URL=https://api.openframe.dev
NEXT_PUBLIC_APP_MODE=oss-tenant
NEXT_PUBLIC_APP_URL=http://localhost:3000

Refer to your environment configuration for actual backend URLs.

Available Scripts

Script Description
npm run dev Start development server with hot reload
npm run build Generate schema enums + Relay artifacts + Next.js production build
npm run start Start production server (after build)
npm run lint Run ESLint (the fast pass; rules come from the core library's shared config)
npm run lint:fix ESLint autofix
npm run lint:types ESLint type-aware pass (slow — needs an 8 GB heap)
npm run format:fix Auto-fix formatting with Prettier
npm run type-check TypeScript type checking without emitting
npm run relay Compile Relay GraphQL fragments
npm run relay:watch Watch and recompile Relay fragments on change
npm run fetch-schema Fetch the latest GraphQL schema from the backend

Documentation

📚 See the Documentation for comprehensive guides including getting started tutorials, development workflows, architecture overviews, and API references.


Community & Support

OpenFrame OSS is supported through the OpenMSP Slack community — the primary channel for discussions, questions, and collaboration.

We do not use GitHub Issues or Discussions. All support and coordination happens in Slack.


Contributing

We welcome contributions! Please read the Contributing Guidelines before opening a pull request.

Key points:


Built with 💛 by the Flamingo team

openframe-oss-frontend (flamingo-stack/openframe-oss-frontend)

Searching Database…

这是什么?它是 OpenFrame 平台的主 Web 应用——一个面向托管服务提供商(MSP)的统一 AI 驱动控制面板,定位为昂贵专有 MSP 软件的开源替代品。
那这是完整的 MSP 平台,还是只是套在上面的界面?只是界面——它是展示和编排层,负责与独立的 OpenFrame 后端服务通信。服务器和数据库逻辑都不在这个仓库里。
我怎么在本地把它跑起来?安装 Node.js 18+、npm 9+ 和 Git,克隆仓库,填入包含你后端 URL 的最少环境变量,然后运行 npm run dev(生产环境则运行 npm run build && npm run start)。
AI 体现在哪里?有两个内置助手:面向技术人员的 Mingo——一个支持工具执行、上下文感知和审批流程的流式 AI;以及面向客户端门户的可嵌入 AI Fae。每个组织还可以拥有自己的 AI 配置,并带有防护栏模板。
它能独立运行,还是必须配合 OpenFrame 后端?必须配合 OpenFrame 后端服务:后端的 URL 来自环境变量,GraphQL schema 也要用 npm run fetch-schema 从后端拉取,所以光有界面做不了什么。
我能直接从它控制客户的机器吗?可以——每台设备都能在浏览器终端里打开远程 shell,通过 MeshCentral 使用文件管理器和远程桌面,还支持全网 osquery 实时查询任务,以及带执行历史的脚本定时执行。
它底层用了什么技术栈?Next.js 16(基于 App Router)配合 React 19,用 Relay v20 处理 GraphQL 片段,TanStack Query v5 管理服务器状态,Zustand v5 管理客户端界面状态,再加上 Tailwind CSS——远程 shell 用了 xterm,脚本编辑器用了 Monaco。
它自带组件库吗?不带——共享的 UI 组件来自 @flamingo-stack/openframe-frontend-core 包,连 ESLint 规则也是继承自这个核心库的共享配置。
Flamingo 为什么要把它开源?他们声明的目标是用智能的开源替代方案取代昂贵的专有 MSP 软件——这个应用是 OpenFrame 生态面向用户的一层,把各个后端服务连接成一个以 AI 为核心的 MSP 体验。
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