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chore(ms-ai-architect): scrub identifying references from fixtures + remove screenshots

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Removes:
- All 6 PNG screenshots (playground/screenshots/) and the capture script
  (scripts/screenshots/capture-playground.py).
- "Screenshots" section from plugin README.
- "Screenshot-suite" section from plugin CLAUDE.md.
- Screenshots bullet from marketplace root README's ms-ai-architect listing.

Scrubs the 17 synthetic fixtures + CHANGELOG/CLAUDE/README of identifying
references: organization names, government-agency names, agency-specific
terminology, sector-specific use cases. Replaced with generic placeholder
data ("Acme AS" / "Demosystem") that exercises the same parser archetypes.

Plugin's domain-target wording (Datatilsynet, offentlig sektor, offentlig
myndighet, rettshåndhevelse, NS 5814, Utredningsinstruksen, EU AI Act
Annex III categories) is intact — those describe the plugin's intended
audience, not any specific entity.

This is a cleanup commit. Earlier git history still contains the prior
references; force-push or rebase is required if scrubbing the history is
desired. That decision is out of scope here — please run it separately
if needed.

Verified post-scrub:
- bash tests/validate-plugin.sh -> 215/215 PASS
- bash tests/run-e2e.sh --playground -> 240/240 PASS (170 + 70)
This commit is contained in:
Kjell Tore Guttormsen 2026-05-03 20:53:49 +02:00
commit e57dee5a03
28 changed files with 89 additions and 469 deletions
Download patch file Download diff file Expand all files Collapse all files

12
plugins/ms-ai-architect/playground/test-fixtures/adr.md
View file

@ -1,14 +1,14 @@
# ADR-001 — Velg Azure AI Foundry som primær AI-plattform for ANPR-trafikkanalyse
# ADR-001 — Velg Azure AI Foundry som primær AI-plattform for Demosystem
Status: accepted
Date: 2026-04-30
Deciders: AI-arkitekt, sikkerhetsarkitekt, seksjonsleder
Consulted: personvernombud, juridisk rådgiver, Drift
Informed: prosjekteierskap, KI-seksjonen
Consulted: Datatilsynet, juridisk rådgiver, Drift
Informed: prosjekteierskap, AI-teamet
## Context and Problem Statement
Statens vegvesen skal modernisere ANPR-trafikkanalyse fra on-prem OCR-løsning til skybasert AI-plattform. Plattformen må støtte custom modell-trening, audit-logging på inferens-nivå, real-time inferens (<100ms P95), og full compliance med EU AI Act + GDPR + sikkerhetsloven.
Acme AS skal modernisere Demosystem fra on-prem OCR-løsning til skybasert AI-plattform. Plattformen må støtte custom modell-trening, audit-logging på inferens-nivå, real-time inferens (<100ms P95), og full compliance med EU AI Act + GDPR + sikkerhetsloven.
## Decision Drivers
@ -17,7 +17,7 @@ Statens vegvesen skal modernisere ANPR-trafikkanalyse fra on-prem OCR-løsning t
- Customer-managed keys og Private Endpoints
- Custom modell-trening kapabilitet
- Total cost of ownership over 3 år
- Driftbarhet for KI-seksjonen
- Driftbarhet for AI-teamet
## Considered Options
@ -32,7 +32,7 @@ Chosen option: **Azure AI Foundry**, fordi det balanserer compliance, driftbarhe
### Consequences
- Good: full compliance-pakke for offentlig sektor, raskere time-to-prod, integrert med eksisterende Entra ID
- Good: full compliance-pakke for leverandøren, raskere time-to-prod, integrert med eksisterende Entra ID
- Good: customer-managed keys og Customer Lockbox tilgjengelig
- Bad: lock-in til Azure, men mitigert via standardiserte modell-formater (ONNX) og data-portabilitet
- Bad: høyere månedlig kostnad enn ren Azure ML — kompenseres ved redusert egen-drift