import { setupManifest } from '@start9labs/start-sdk'

/**
 * Boardroom Map manifest.
 *
 * Like the LLaMA-Factory and Nightshift services, this is a CONTROL PLANE — it
 * does not run any GPU workload itself. It is a small web UI + job runner that
 * SSHes into one or two NVIDIA DGX Sparks to:
 *   1. serve a panel of local LLMs with vLLM (loaded in waves to fit GPU memory),
 *   2. extract text from documents you drop in (PDF/DOCX/TXT/MD — done on the
 *      StartOS box), ship it to the Sparks, and launch a panel of sandboxed
 *      "reviewer" containers (each a model + a persona) that read the documents
 *      and write a report,
 *   3. optionally run a local "lead reviewer" that synthesizes the panel's
 *      reports into one consolidated report.
 *
 * There is NO frontier model and NO cloud API key. In the default `airgapped`
 * network mode the reviewer containers can reach ONLY the on-Spark model proxy —
 * the documents and their reviews never touch the internet.
 *
 * NOTE: s9pk.mk extracts the package identifier from the single-quoted value on
 * the line below, so keep that field on one line and avoid stray quotes above it.
 */
export const manifest = setupManifest({
  id: 'boardroom-map',
  title: 'Boardroom Map',
  license: 'Apache-2.0',
  packageRepo: 'https://github.com/ten31/boardroom-map',
  upstreamRepo: 'https://github.com/ten31/boardroom-map',
  marketingUrl: 'https://github.com/ten31/boardroom-map',
  donationUrl: null,
  description: {
    short: 'A private panel of local LLMs that reviews your confidential documents on your DGX Sparks',
    long:
      'Boardroom Map lets you drop confidential documents in and convene a panel of ' +
      'local LLMs running on your NVIDIA DGX Sparks to review them. You choose ' +
      'which models and which personas (lenses) sit on the panel and how many ' +
      'reviews to run. Each reviewer reads the documents and writes a report; an ' +
      'optional local lead reviewer synthesizes them into one consolidated ' +
      'report. There is no frontier model and no cloud key: in the default ' +
      'air-gapped mode the reviewers reach only the on-Spark model endpoint, so ' +
      'your documents and their reviews never leave your hardware. No GPU is ' +
      'needed on the StartOS host.',
  },
  // Arch-agnostic orchestrator. Docker build paths are relative to the PROJECT
  // ROOT (where the Makefile runs), matching the Start9 convention.
  images: {
    main: {
      source: {
        dockerBuild: {
          dockerfile: './orchestrator.Dockerfile',
          workdir: '.',
        },
      },
      arch: ['x86_64', 'aarch64'],
      // The orchestrator only SSHes out + extracts document text on CPU; it never
      // touches a local GPU.
      nvidiaContainer: false,
    },
  },
  volumes: ['main'],
  dependencies: {},
  hardwareRequirements: {
    ram: 2048,
  },
  alerts: {
    install:
      'Boardroom Map drives work on REMOTE machines (your DGX Sparks) over SSH; ' +
      'nothing serves or runs on your StartOS server. After install: ' +
      '(1) "Configure Sparks" for SSH access, (2) "Configure Models" for the ' +
      'local models to serve, (3) "Configure Reviewers" for the panel + personas, ' +
      '(4) "Configure Review" for the rubric and air-gap mode. Then drop ' +
      'documents in the inbox and run "Run Review".',
  },
})