Files
Jonathan KirkwoodandClaude Fable 5 b1d7aed9f4 Implement BDEF v1.1 grading: scoring core, per-deck pipeline, ledger, dashboard, StartOS layer
- Deterministic scoring.py (quant 60 / qual 40 / flags -15, profitability heaviest)
- Per-company JSON ledger with forecast-target chaining deck N-1 -> N
- Single-shot sandbox agent with guided-JSON fallback ladder (no tool loop)
- Portfolio dashboard with sparklines, KPI hit rates, BDEF category bars
- 48 unit tests green; endpoints smoke-tested; npm check+build green

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-06 14:15:12 -05:00

85 lines
4.0 KiB
TypeScript

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 the board decks you drop into inbox/<company-slug>/
* (PDF/DOCX/TXT/MD — done on the StartOS box), ship it to the Sparks, and
* launch a panel of sandboxed "grader" containers (each a model + a
* persona) that grade each deck against the BDEF v1.1 framework
* (Girdley + Munger/Buffett),
* 3. optionally run a local "adjudicator" that reconciles the panel, after
* which Python computes a deterministic composite (quant KPI attainment 60
* incl. profitability 30, qualitative categories 40, red-flag penalties
* up to -15) and appends it to the company's running scorecard ledger.
*
* There is NO frontier model and NO cloud API key. In the default `airgapped`
* network mode the grader containers can reach ONLY the on-Spark model proxy —
* the decks and their grades 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: 'Grade portfolio-company board decks with local LLMs on your DGX Sparks — BDEF scoring, per-company running scorecards',
long:
'Boardroom Map turns your DGX Sparks into a private board-deck grading ' +
'panel. Drop each portfolio company\'s deck into its inbox folder and a ' +
'panel of local LLMs (each a model + a persona) grades it against the ' +
'BDEF v1.1 framework (Girdley + Munger/Buffett); an optional local ' +
'adjudicator reconciles the panel, then a deterministic scorer computes a ' +
'0-100 composite — quantitative KPI attainment worth 60 (profitability ' +
'alone 30, plus forecast integrity: deck N actuals vs deck N-1 promises), ' +
'qualitative categories worth 40, and red-flag penalties up to -15. Each ' +
'company keeps a running scorecard ledger, and a web dashboard shows the ' +
'trends. There is no frontier model and no cloud key: in the default ' +
'air-gapped mode the graders reach only the on-Spark model endpoint, so ' +
'your confidential decks 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 deck 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, and your confidential ' +
'board decks stay on your LAN. After install: (1) "Configure Sparks" for ' +
'SSH access, (2) "Configure Models" for the local models to serve, ' +
'(3) "Configure Graders" for the panel + personas, (4) "Configure Grading" ' +
'for the BDEF rubric, air-gap mode, and scoring weights, (5) "Configure ' +
'Companies" for slugs and pinned KPI targets. Then drop decks into ' +
'inbox/<company-slug>/ and run "Grade Decks".',
},
})