raulcnadal/applivery-api-rosetta repository overview

⁠Applivery API Rosetta

Applivery API Rosetta is a comprehensive, interactive API exploration and AI-context generation tool tailored specifically for the Applivery UEM API.

Designed for both human administrators and autonomous AI agents, it provides a safe, guided interface to manage your device fleet while simultaneously acting as the definitive "source of truth" for AI integration development.

⁠🚀 Features

⁠1. Interactive API Tester

A visual CRUD interface to manage Applivery resources without writing code:

• Device Fleet: Inspect hardware/software profiles, assign tags, manage policies, and execute remote commands (Reboot, Wipe, Lock).
• Identity & Access: Sync and manage MDM Users, Organization Collaborators, and App Store Employees.
• App Distribution: Inspect Enterprise Apps, track build lifecycles, and monitor downloads.
• Advanced Routing: Full CRUD support for Segments, Device Audiences, User Audiences, and Automation Rules.

⁠2. Live API Explorer

An integrated, Postman-style OpenAPI explorer that overlays production-tested business logic onto raw endpoints. When you select an endpoint, the Explorer dynamically warns you about known requirements before you execute the request.

⁠3. Production Console

Every action taken in the UI is logged in the built-in terminal. Inspect exact HTTP methods, request URLs, headers, JSON payloads, and raw API responses in real-time to reverse-engineer calls for your own scripts.

⁠4. AI Context Generation (llms.txt)

The defining feature of Rosetta. The raw Applivery OpenAPI spec lacks critical business logic. Rosetta merges the live structural OpenAPI spec with a curated, battle-tested API Dictionary to generate a golden llms.txt file. Point your Custom GPTs, Claude Projects, or autonomous agents to this file to make them instant Applivery experts.

⁠🐳 Deployment & Quick Start

Deploy Applivery API Rosetta via Docker in seconds. The container packages the FastAPI backend, the Vue 3 frontend, and the Python generation scripts into a single, lightweight image.

⁠Option A: Docker CLI

Run the following command to deploy the container and map it to port 8000:

docker run -d -p 8000:8000 --name applivery-rosetta --restart unless-stopped your-dockerhub-username/applivery-api-rosetta:latest

⁠Option B: Docker Compose (Recommended)

For easier management and updates, you can use Docker Compose. Create a file named docker-compose.yml with the following content:

version: '3.8'

services:
  applivery-rosetta:
    image: your-dockerhub-username/applivery-api-rosetta:latest
    container_name: applivery-rosetta
    ports:
      - "8000:8000"
    restart: unless-stopped

To deploy it, simply run this command in the same directory as your file:

docker compose up -d

⁠Access the Platform

Once the container is running via either method, navigate to the following address in your web browser:

http://localhost:8000

⁠🔐 Administrator Guide

⁠Connecting Your Workspace

Upon launching the platform, you must authenticate your session:

1. Workspace Slug / ID: Enter your human-readable organization slug (e.g., my-company) or your 24-character MongoDB Hex ID. The Rosetta backend will automatically handshake and resolve slugs into the Hex IDs required for sub-resource routing.
2. Service Account Token: Enter your Applivery Service Account Bearer Token. Note that Service Accounts cannot manage or list other Service Accounts due to security restrictions.

⁠Generating the AI Context

To generate the machine-readable context file for your AI agents:

1. Navigate to the API Documentation tab in the UI.
2. Click the Generate llms.txt button.
3. The backend will fetch the latest endpoints, inject the production logic rules, and serve the file at http://localhost:8000/llms.txt.