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docs(architect): weekly KB update — 106 files refreshed (2026-04)

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Updates across all 5 skills: ms-ai-advisor, ms-ai-engineering,
ms-ai-governance, ms-ai-security, ms-ai-infrastructure.

Key changes:
- Language Services (Custom Text Classification, Text Analytics, QnA):
  retirement warning 2029-03-31, migration guides to Foundry/GPT-4o
- Agentic Retrieval: 50M free reasoning tokens/month (Public Preview)
- Computer Use: Claude Sonnet 4.5 (preview) + OpenAI CUA models
- Agent Registry: Risks column (M365 E7), user-shared/org-published types
- Declarative agents: schema v1.5 → v1.6, Store validation requirements
- MLflow 3: 13 built-in LLM judges, production monitoring, Genie Code
- AG-UI HITL: ApprovalRequiredAIFunction (C#) + @tool(approval_mode) (Python)
- Entra ID Ignite 2025: Agent ID Admin/Developer RBAC roles, Conditional Access
- Security Copilot: 400 SCU/month per 1000 M365 E5 licenses, auto-provisioned
- Fast Transcription API: phrase lists, 14-language multi-lingual transcription
- Azure Monitor Workbooks: Bicep support, RBAC specifics
- Power Platform Copilot: data residency (Norway/Europe → EU DB, Bing → USA)
- RAG security-rbac: 4-approach table (GA + 3 preview access control methods)
- IaC MLOps: Well-Architected OE:05 principles, Bicep/Terraform patterns
- Translator: image file batch translation Preview (JPEG/PNG/BMP/WebP)

All 106 files: Last updated 2026-04 | Verified: MCP 2026-04

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Kjell Tore Guttormsen 2026-04-10 09:13:24 +02:00
commit 6645e93205
104 changed files with 1986 additions and 520 deletions
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14
skills/ms-ai-engineering/references/rag-architecture/rag-document-preprocessing.md
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@ -1,6 +1,6 @@
# Document Preprocessing and Pipeline Automation
**Last updated:** 2026-02
**Last updated:** 2026-04 | Verified: MCP 2026-04
**Status:** GA
**Category:** RAG Architecture & Semantic Search
@ -776,3 +776,15 @@ Images (JPEG/PNG)?
**Totalt antall MCP-kilder:** 3 docs_search calls + 2 docs_fetch calls = **5 MCP-kall**
**Totalt antall unike URLer:** 8 Microsoft Learn-artikler + 4 GitHub-repos = **12 kilder**
**Konfidensnivå totalt:** 95% Verified (fra MCP), 5% Baseline (norske forhold og priser)
### Kognitiv søk — bildeprosessering (oppdatert 2026-04)
Azure AI Search støtter tre tilnærminger til bildeinnhold i RAG:
1. **Vektorisering** — Azure Vision genererer bildere presentasjoner som søkbare vektorer
2. **Verbalisering** — GenAI Prompt skill sender bilde til LLM-chat-modell for naturlig tekstbeskrivelse (bedre for RAG-grounding)
3. **Analyse/OCR** — Image Analysis skill (tags, description) og OCR skill (tekst fra bilder)
`imageAction: generateNormalizedImages` er påkrevd for bildebehandling. Maks 1000 bilder ekstraheres per dokument. Kostnader påløper ved `imageAction != none`.
**Skillset tutorial (oppdatert):** Skillsets bygges med OCR, språkdeteksjon, entity recognition og key phrase extraction i pipeline. Output field mappings mapper enriched document tree til søkeindeksfelt.