diff --git a/skills/ms-ai-advisor/references/architecture/cost-models.md b/skills/ms-ai-advisor/references/architecture/cost-models.md index d402869..1014b3a 100644 --- a/skills/ms-ai-advisor/references/architecture/cost-models.md +++ b/skills/ms-ai-advisor/references/architecture/cost-models.md @@ -587,7 +587,7 @@ Azure AI Foundry er en **orkestreringsplattform** som benytter flere Azure-tjene - [Azure Cost Management](https://azure.microsoft.com/services/cost-management/) **Dokumentasjon:** -- [Azure OpenAI Cost Management](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/manage-costs) +- [Azure OpenAI Cost Management](https://learn.microsoft.com/azure/foundry/concepts/manage-costs) - [Copilot Studio Billing and management](https://learn.microsoft.com/microsoft-copilot-studio/billing-rates-and-management) — Verified (MCP 2026-04) - [AI Builder Credit Management](https://learn.microsoft.com/ai-builder/credit-management) diff --git a/skills/ms-ai-advisor/references/architecture/migration-patterns.md b/skills/ms-ai-advisor/references/architecture/migration-patterns.md index b948fd7..a500d59 100644 --- a/skills/ms-ai-advisor/references/architecture/migration-patterns.md +++ b/skills/ms-ai-advisor/references/architecture/migration-patterns.md @@ -1182,7 +1182,7 @@ Base effort: 200 timer ### Microsoft Learn - [Azure Migration Guide](https://learn.microsoft.com/azure/cloud-adoption-framework/migrate/) - [Copilot Studio Migration](https://learn.microsoft.com/microsoft-copilot-studio/unified-authoring-conversion) -- [Azure AI Foundry Documentation](https://learn.microsoft.com/azure/ai-foundry/) +- [Azure AI Foundry Documentation](https://learn.microsoft.com/azure/foundry/) ### Verktøy - **Azure Migrate:** Assessment og migrering av workloads diff --git a/skills/ms-ai-advisor/references/architecture/poc-template.md b/skills/ms-ai-advisor/references/architecture/poc-template.md index 72025e5..9a3cae3 100644 --- a/skills/ms-ai-advisor/references/architecture/poc-template.md +++ b/skills/ms-ai-advisor/references/architecture/poc-template.md @@ -925,7 +925,7 @@ Legg til ekstra tid hvis: ### Microsoft Documentation - [AI Adoption Framework (CAF)](https://learn.microsoft.com/azure/cloud-adoption-framework/scenarios/ai/) - [Copilot Studio Implementation Guidance](https://learn.microsoft.com/microsoft-copilot-studio/guidance/overview) -- [Azure AI Foundry Evaluation](https://learn.microsoft.com/azure/ai-foundry/concepts/evaluation-evaluators/) +- [Azure AI Foundry Evaluation](https://learn.microsoft.com/azure/foundry/how-to/evaluate-generative-ai-app) - [Responsible AI Standard](https://www.microsoft.com/ai/responsible-ai) ### Tools diff --git a/skills/ms-ai-advisor/references/architecture/regional-availability-verification.md b/skills/ms-ai-advisor/references/architecture/regional-availability-verification.md index 4557927..232f2cd 100644 --- a/skills/ms-ai-advisor/references/architecture/regional-availability-verification.md +++ b/skills/ms-ai-advisor/references/architecture/regional-availability-verification.md @@ -248,9 +248,9 @@ Når en tjeneste ikke er tilgjengelig i Norway East: | Ressurs | URL | Oppdateringsfrekvens | |---------|-----|---------------------| | Azure Products by Region | https://azure.microsoft.com/en-us/explore/global-infrastructure/products-by-region | Fortløpende | -| Azure OpenAI Models & Region | https://learn.microsoft.com/azure/ai-foundry/openai/concepts/models | Ved modellendringer | +| Azure OpenAI Models & Region | https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure | Ved modellendringer | | Azure AI Search Regions | https://learn.microsoft.com/azure/search/search-region-support | Ved regionsendringer | -| Microsoft Foundry Regions | https://learn.microsoft.com/azure/ai-foundry/reference/region-support | Ved regionsendringer | +| Microsoft Foundry Regions | https://learn.microsoft.com/azure/foundry/reference/region-support | Ved regionsendringer | | Azure Status | https://status.azure.com | Sanntid | | Azure Updates | https://azure.microsoft.com/updates | Daglig | diff --git a/skills/ms-ai-advisor/references/copilot-extensibility/copilot-api-rate-limiting-resilience.md b/skills/ms-ai-advisor/references/copilot-extensibility/copilot-api-rate-limiting-resilience.md index de6775f..d342f4f 100644 --- a/skills/ms-ai-advisor/references/copilot-extensibility/copilot-api-rate-limiting-resilience.md +++ b/skills/ms-ai-advisor/references/copilot-extensibility/copilot-api-rate-limiting-resilience.md @@ -244,7 +244,7 @@ while True: **Use case:** Store batch-operasjoner (Azure OpenAI, Azure AI Foundry). -**Verified:** [Batch deployments - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch) +**Verified:** [Batch deployments - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch) --- @@ -299,7 +299,7 @@ while True: - Implementer retry logic med exponential backoff - Unngå skarpe workload-endringer (gradvis økning) -**Verified:** [Quotas and limits - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quotas-limits), [Manage quota - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/quota) +**Verified:** [Quotas and limits - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/quotas-limits), [Manage quota - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/quota) ### Copilot Studio @@ -484,9 +484,9 @@ while True: 3. [Circuit Breaker pattern - Cloud-Native .NET](https://learn.microsoft.com/en-us/dotnet/architecture/cloud-native/application-resiliency-patterns) 4. [What is rate limiting? - Microsoft Cloud Dev](https://learn.microsoft.com/en-us/microsoft-cloud/dev/dev-proxy/concepts/what-is-rate-limiting) 5. [How to handle API throttling - Microsoft Cloud Dev](https://learn.microsoft.com/en-us/microsoft-cloud/dev/dev-proxy/concepts/how-to-handle-api-throttling) -6. [Azure OpenAI quotas and limits](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quotas-limits) -7. [Manage Azure OpenAI quota](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/quota) -8. [Batch deployments - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch) +6. [Azure OpenAI quotas and limits](https://learn.microsoft.com/en-us/azure/foundry/openai/quotas-limits) +7. [Manage Azure OpenAI quota](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/quota) +8. [Batch deployments - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch) 9. [Resolve throttling errors in Copilot Studio agents](https://learn.microsoft.com/en-us/troubleshoot/power-platform/copilot-studio/licensing/throttling-errors-agents) 10. [Error codes - Copilot Studio](https://learn.microsoft.com/en-us/troubleshoot/power-platform/copilot-studio/authoring/error-codes) 11. [Optimize bot with rate limiting in Teams](https://learn.microsoft.com/en-us/microsoftteams/platform/bots/how-to/rate-limit) diff --git a/skills/ms-ai-advisor/references/copilot-extensibility/copilot-context-window-optimization.md b/skills/ms-ai-advisor/references/copilot-extensibility/copilot-context-window-optimization.md index 706e15f..25a2519 100644 --- a/skills/ms-ai-advisor/references/copilot-extensibility/copilot-context-window-optimization.md +++ b/skills/ms-ai-advisor/references/copilot-extensibility/copilot-context-window-optimization.md @@ -538,11 +538,11 @@ Response + Citations **MCP-verified sources (microsoft-learn):** 1. **Azure OpenAI Assistants API — Context Window Management** - - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/assistants#context-window-management + - https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/assistants#context-window-management - Verified: max_prompt_tokens, max_completion_tokens, truncation_strategy 2. **Troubleshooting and best practices for Azure OpenAI On Your Data** - - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/on-your-data-best-practices + - https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/on-your-data-best-practices - Verified: topNDocuments, strictness, chunk_size, workflow funnel 3. **Quotas and limits for Copilot Studio** @@ -558,7 +558,7 @@ Response + Citations - Verified: Known limitations, no long-running task support, context limits 6. **Azure OpenAI Predicted Outputs** - - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/predicted-outputs + - https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/predicted-outputs - Verified: Prediction parameter for latency optimization 7. **Copilot handoff (Teams Bot Framework)** diff --git a/skills/ms-ai-advisor/references/development/agent-framework.md b/skills/ms-ai-advisor/references/development/agent-framework.md index 120ff76..5b0c197 100644 --- a/skills/ms-ai-advisor/references/development/agent-framework.md +++ b/skills/ms-ai-advisor/references/development/agent-framework.md @@ -465,7 +465,7 @@ result = await agent.run() # Automatisk planning ## Ressurser - [Agent Framework Documentation](https://learn.microsoft.com/azure/ai-services/agents) -- [Azure AI Foundry Agent Service](https://learn.microsoft.com/azure/ai-foundry/agent-service) +- [Azure AI Foundry Agent Service](https://learn.microsoft.com/azure/foundry/agents/overview) - [Migration Guide from Semantic Kernel](https://learn.microsoft.com/azure/ai-services/agents/migrate-semantic-kernel) - [GitHub Samples](https://github.com/azure-samples/ai-agent-framework) diff --git a/skills/ms-ai-advisor/references/platforms/azure-ai-foundry.md b/skills/ms-ai-advisor/references/platforms/azure-ai-foundry.md index 3587091..addeb6a 100644 --- a/skills/ms-ai-advisor/references/platforms/azure-ai-foundry.md +++ b/skills/ms-ai-advisor/references/platforms/azure-ai-foundry.md @@ -371,18 +371,18 @@ Microsoft.CognitiveServices/account (kind: AIServices) Adapted from Microsoft Learn documentation ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)): -- [What is Microsoft Foundry?](https://learn.microsoft.com/azure/ai-foundry/what-is-foundry?view=foundry-classic) -- [What's new in Microsoft Foundry (December 2025)](https://learn.microsoft.com/azure/ai-foundry/whats-new-foundry?view=foundry-classic) -- [What's new in Azure OpenAI](https://learn.microsoft.com/azure/ai-foundry/openai/whats-new?view=foundry-classic) -- [What's new in Foundry Agent Service](https://learn.microsoft.com/azure/ai-foundry/agents/whats-new?view=foundry-classic) -- [GPT-5 models](https://learn.microsoft.com/azure/ai-foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic) -- [Build a workflow in Microsoft Foundry](https://learn.microsoft.com/azure/ai-foundry/agents/concepts/workflow?view=foundry) -- [Foundry Local](https://learn.microsoft.com/azure/ai-foundry/foundry-local/what-is-foundry-local?view=foundry-classic) -- [Computer Use (preview)](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/computer-use?view=foundry-classic) -- [Deep Research tool](https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools-classic/deep-research?view=foundry-classic) -- [A2A Agent endpoint (preview)](https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools/agent-to-agent?view=foundry) -- [MCP tool](https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools-classic/model-context-protocol?view=foundry-classic) -- [Model region availability](https://learn.microsoft.com/azure/ai-foundry/openai/concepts/models) +- [What is Microsoft Foundry?](https://learn.microsoft.com/azure/foundry/what-is-foundry?view=foundry-classic) +- [What's new in Microsoft Foundry (December 2025)](https://learn.microsoft.com/azure/foundry/whats-new-foundry?view=foundry-classic) +- [What's new in Azure OpenAI](https://learn.microsoft.com/azure/foundry-classic/openai/whats-new?view=foundry-classic) +- [What's new in Foundry Agent Service](https://learn.microsoft.com/azure/foundry-classic/agents/whats-new?view=foundry-classic) +- [GPT-5 models](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic) +- [Build a workflow in Microsoft Foundry](https://learn.microsoft.com/azure/foundry/agents/concepts/workflow?view=foundry) +- [Foundry Local](https://learn.microsoft.com/azure/foundry-local/what-is-foundry-local?view=foundry-classic) +- [Computer Use (preview)](https://learn.microsoft.com/azure/foundry-classic/openai/how-to/computer-use?view=foundry-classic) +- [Deep Research tool](https://learn.microsoft.com/azure/foundry-classic/agents/how-to/tools-classic/deep-research?view=foundry-classic) +- [A2A Agent endpoint (preview)](https://learn.microsoft.com/azure/foundry/agents/how-to/tools/agent-to-agent?view=foundry) +- [MCP tool](https://learn.microsoft.com/azure/foundry-classic/agents/how-to/tools-classic/model-context-protocol?view=foundry-classic) +- [Model region availability](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure) Content has been translated to Norwegian, reorganized, and augmented with decision guidance. diff --git a/skills/ms-ai-advisor/references/platforms/model-catalog-2026.md b/skills/ms-ai-advisor/references/platforms/model-catalog-2026.md index 42a928a..85516ff 100644 --- a/skills/ms-ai-advisor/references/platforms/model-catalog-2026.md +++ b/skills/ms-ai-advisor/references/platforms/model-catalog-2026.md @@ -390,15 +390,15 @@ Trenger kunden open-source/selvhostet-alternativ? Adapted from Microsoft Learn documentation ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)): -- [Foundry Models sold directly by Azure (azure-openai)](https://learn.microsoft.com/azure/ai-foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic) -- [Foundry Models sold directly by Azure (azure-direct-others)](https://learn.microsoft.com/azure/ai-foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic&pivots=azure-direct-others) -- [Azure OpenAI in Azure AI Foundry Models — model overview](https://learn.microsoft.com/azure/ai-foundry/openai/concepts/models) -- [GPT-5 vs GPT-4.1: choosing the right model](https://learn.microsoft.com/azure/ai-foundry/foundry-models/how-to/model-choice-guide?view=foundry-classic) -- [Azure OpenAI reasoning models](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/reasoning?view=foundry-classic) -- [PTU costs and billing](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding?view=foundry-classic) -- [Foundry Models from partners and community (Phi)](https://learn.microsoft.com/azure/ai-foundry/foundry-models/concepts/models-from-partners?view=foundry-classic) -- [Azure OpenAI models and regions for Foundry Agent Service](https://learn.microsoft.com/azure/ai-foundry/agents/concepts/model-region-support?view=foundry-classic) -- [Azure OpenAI quotas and limits](https://learn.microsoft.com/azure/ai-foundry/openai/quotas-limits?view=foundry-classic) +- [Foundry Models sold directly by Azure (azure-openai)](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic) +- [Foundry Models sold directly by Azure (azure-direct-others)](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic&pivots=azure-direct-others) +- [Azure OpenAI in Azure AI Foundry Models — model overview](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure) +- [GPT-5 vs GPT-4.1: choosing the right model](https://learn.microsoft.com/azure/foundry/foundry-models/how-to/model-choice-guide?view=foundry-classic) +- [Azure OpenAI reasoning models](https://learn.microsoft.com/azure/foundry/openai/how-to/reasoning?view=foundry-classic) +- [PTU costs and billing](https://learn.microsoft.com/azure/foundry/openai/concepts/provisioned-throughput-billing?view=foundry-classic) +- [Foundry Models from partners and community (Phi)](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-from-partners?view=foundry-classic) +- [Azure OpenAI models and regions for Foundry Agent Service](https://learn.microsoft.com/azure/foundry-classic/agents/concepts/model-region-support?view=foundry-classic) +- [Azure OpenAI quotas and limits](https://learn.microsoft.com/azure/foundry/openai/quotas-limits?view=foundry-classic) Content translated to Norwegian, reorganized, and augmented with decision guidance for Norwegian public sector. diff --git a/skills/ms-ai-advisor/references/prompt-engineering/adversarial-prompting-and-jailbreaks.md b/skills/ms-ai-advisor/references/prompt-engineering/adversarial-prompting-and-jailbreaks.md index 0e236ad..40d528d 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/adversarial-prompting-and-jailbreaks.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/adversarial-prompting-and-jailbreaks.md @@ -760,11 +760,11 @@ Start: AI system security design *Verifisert: januar 2026, omfatter AI-1 til AI-7 controls* 3. **Azure AI Red Teaming Agent:** - https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/ai-red-teaming-agent + https://learn.microsoft.com/en-us/azure/foundry/concepts/ai-red-teaming-agent *Verifisert: januar 2026, Public Preview* 4. **Content Filtering (default policies):** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/default-safety-policies + https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/default-safety-policies *Verifisert: januar 2026, GA* 5. **Microsoft Defender for AI Services:** diff --git a/skills/ms-ai-advisor/references/prompt-engineering/chain-of-thought-prompting.md b/skills/ms-ai-advisor/references/prompt-engineering/chain-of-thought-prompting.md index 8e1b1c1..09e7b9e 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/chain-of-thought-prompting.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/chain-of-thought-prompting.md @@ -474,11 +474,11 @@ Chain-of-thought øker token-forbruk betydelig: | Kilde | Konfidensnivå | Verifisert dato | |-------|---------------|-----------------| -| [Prompt engineering techniques - Chain of thought prompting](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering#chain-of-thought-prompting) | **Verified** | 2026-02 | -| [Azure OpenAI On Your Data - Best practices (Chain-of-thought prompting)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data#best-practices) | **Verified** | 2026-02 | -| [Azure OpenAI Evaluation (Preview) - Factuality (uses CoT internally)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/evaluations#types-of-testing-criteria) | **Verified** | 2026-02 | -| [Azure OpenAI reasoning models (o1, o3, GPT-5)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/reasoning) | **Verified** | 2026-02 | -| [Transparency note for Azure OpenAI - Chain-of-thought capabilities](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note?view=foundry-classic#capabilities) | **Verified** | 2026-02 | +| [Prompt engineering techniques - Chain of thought prompting](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering#chain-of-thought-prompting) | **Verified** | 2026-02 | +| [Azure OpenAI On Your Data - Best practices (Chain-of-thought prompting)](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data#best-practices) | **Verified** | 2026-02 | +| [Azure OpenAI Evaluation (Preview) - Factuality (uses CoT internally)](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/evaluations#types-of-testing-criteria) | **Verified** | 2026-02 | +| [Azure OpenAI reasoning models (o1, o3, GPT-5)](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/reasoning) | **Verified** | 2026-02 | +| [Transparency note for Azure OpenAI - Chain-of-thought capabilities](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note?view=foundry-classic#capabilities) | **Verified** | 2026-02 | ### Baseline-kunnskap (fra Claude-modell) @@ -493,7 +493,7 @@ Chain-of-thought øker token-forbruk betydelig: 1. **microsoft_docs_search:** "chain of thought prompting Azure OpenAI" → 10 resultater 2. **microsoft_code_sample_search:** "chain of thought prompt examples" → 20 code snippets -3. **microsoft_docs_fetch:** [Azure OpenAI reasoning models](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/reasoning) → Full dokumentasjon hentet +3. **microsoft_docs_fetch:** [Azure OpenAI reasoning models](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/reasoning) → Full dokumentasjon hentet **Totalt:** 4 MCP-kall, 3 unike Microsoft Learn-kilder. diff --git a/skills/ms-ai-advisor/references/prompt-engineering/domain-specific-prompt-optimization.md b/skills/ms-ai-advisor/references/prompt-engineering/domain-specific-prompt-optimization.md index c753820..638f757 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/domain-specific-prompt-optimization.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/domain-specific-prompt-optimization.md @@ -558,19 +558,19 @@ Basert på testing (Azure OpenAI dokumentasjon): ### Microsoft Learn dokumentasjon (fetched via MCP 2026-02-04) 1. **Prompt engineering techniques** (Azure OpenAI) - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering + https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering *Source for: Best practices, few-shot learning, chain-of-thought, output structure* 2. **Azure OpenAI On Your Data** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data *Source for: RAG configuration, field mapping, strictness, multi-lingual support, token estimation* 3. **Transparency note for Azure OpenAI** - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note + https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note *Source for: Model capabilities, limitations, responsible AI considerations* 4. **Azure OpenAI FAQ** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/faq + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/faq *Source for: Language handling, model behavior, grounding strategies* 5. **Apply prompt engineering with Azure OpenAI Service - Training** diff --git a/skills/ms-ai-advisor/references/prompt-engineering/error-handling-and-fallback-prompting.md b/skills/ms-ai-advisor/references/prompt-engineering/error-handling-and-fallback-prompting.md index 2c06273..ccc4711 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/error-handling-and-fallback-prompting.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/error-handling-and-fallback-prompting.md @@ -686,14 +686,14 @@ User Request ## Kilder og verifisering **Primærkilder (Microsoft Learn):** -1. [Azure OpenAI supported programming languages - Error handling](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/supported-languages) – Offisiell dokumentasjon for retry-mekanismer i alle SDK-er +1. [Azure OpenAI supported programming languages - Error handling](https://learn.microsoft.com/en-us/azure/foundry/openai/supported-languages) – Offisiell dokumentasjon for retry-mekanismer i alle SDK-er 2. [Architecture strategies for self-preservation](https://learn.microsoft.com/en-us/azure/well-architected/reliability/self-preservation) – Azure Well-Architected Framework reliability-mønstre 3. [Azure OpenAI Priority-Based Load Balancer (GitHub)](https://github.com/Azure-Samples/openai-aca-lb) – Referanseimplementasjon av smart load balancing -4. [Troubleshooting Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/on-your-data-best-practices) – Best practices for debugging og error handling +4. [Troubleshooting Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/on-your-data-best-practices) – Best practices for debugging og error handling 5. [llm-content-safety policy (APIM)](https://learn.microsoft.com/en-us/azure/api-management/llm-content-safety-policy) (Re-verified MCP 2026-04) – Content safety enforcement i API Management. Policy-attributter: backend-id, shield-prompt, enforce-on-completions, window-size, output-type, threshold (0-7), blocklists. **Sekundærkilder:** -6. [Azure OpenAI FAQ](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/faq) – Vanlige feilsituasjoner og workarounds +6. [Azure OpenAI FAQ](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/faq) – Vanlige feilsituasjoner og workarounds 7. [OWASP Top 10 for LLM - Improper Output Handling](https://genai.owasp.org/llmrisk/llm052025-improper-output-handling/) – Sikkerhetshensyn ved output validation 8. [Reliability Maturity Model](https://learn.microsoft.com/en-us/azure/well-architected/reliability/maturity-model) – Graceful degradation og testing diff --git a/skills/ms-ai-advisor/references/prompt-engineering/few-shot-learning-techniques.md b/skills/ms-ai-advisor/references/prompt-engineering/few-shot-learning-techniques.md index 77568a9..c73b30a 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/few-shot-learning-techniques.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/few-shot-learning-techniques.md @@ -510,11 +510,11 @@ User Query **Verified (MCP microsoft-learn, januar 2026):** 1. **Prompt engineering techniques** (Azure AI Foundry) - - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering + - https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering - Seksjon: Few-shot learning, Zero-shot learning, Examples 2. **Work with chat completions models** - - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chatgpt + - https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/chatgpt - Seksjon: Few-shot learning with chat completion 3. **Zero-shot and few-shot learning** (.NET AI conceptual) (Re-verified MCP 2026-04) @@ -522,11 +522,11 @@ User Query - Primære use cases, performance baselines, caveats (false patterns, token limits, reasoning gaps) 4. **Chat Markup Language ChatML** - - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chat-markup-language + - https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/responses - Few-shot eksempler i ChatML-format 5. **Transparency note for Azure OpenAI** - - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note + - https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note - In-context learning: Zero-shot, One-shot, Few-shot definitioner **Code samples verified:** diff --git a/skills/ms-ai-advisor/references/prompt-engineering/function-calling-and-tool-use.md b/skills/ms-ai-advisor/references/prompt-engineering/function-calling-and-tool-use.md index cc7e17e..caf9d83 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/function-calling-and-tool-use.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/function-calling-and-tool-use.md @@ -272,7 +272,7 @@ assistant = client.beta.assistants.create( ### Azure Logic Apps -[Azure Logic Apps kan integreres](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/assistants-logic-apps) med Assistants API for å håndtere function execution. +[Azure Logic Apps kan integreres](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/assistants-logic-apps) med Assistants API for å håndtere function execution. ### On Your Data (Azure AI Search + OpenAI) @@ -421,7 +421,7 @@ Function calling påvirker kostnaden på flere måter: - Start med én enkel funksjon (f.eks. `get_current_time`) - Bruk `tool_choice: "auto"` og observer modellens oppførsel - Implementer robust error handling før produksjon -- Les Microsoft's [responsible AI guidelines](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/overview) +- Les Microsoft's [responsible AI guidelines](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/overview) **Viderekomne (har bygget noen agenter):** - Implementer parallel function calling for bedre performance @@ -439,11 +439,11 @@ Function calling påvirker kostnaden på flere måter: **Verified (fra Microsoft Learn MCP-research):** -1. [How to use function calling with Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/function-calling) — **Konfidensnivå: Høy** (offisiell dokumentasjon, oppdatert januar 2026) +1. [How to use function calling with Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/function-calling) — **Konfidensnivå: Høy** (offisiell dokumentasjon, oppdatert januar 2026) 2. [Understand OpenAI function calling](https://learn.microsoft.com/en-us/dotnet/ai/conceptual/understanding-openai-functions) — **Konfidensnivå: Høy** (konseptuell guide med Semantic Kernel-eksempler) -3. [Azure OpenAI Assistants function calling](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/assistant-functions) — **Konfidensnivå: Høy** (Assistants API-spesifikk dokumentasjon) -4. [Fine-tuning functions](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/fine-tuning-functions) — **Konfidensnivå: Høy** (for advanced use cases) -5. [Structured outputs](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/structured-outputs) — **Konfidensnivå: Høy** (komplementær teknikk til function calling) +3. [Azure OpenAI Assistants function calling](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/assistant-functions) — **Konfidensnivå: Høy** (Assistants API-spesifikk dokumentasjon) +4. [Fine-tuning functions](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/fine-tuning-functions) — **Konfidensnivå: Høy** (for advanced use cases) +5. [Structured outputs](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/structured-outputs) — **Konfidensnivå: Høy** (komplementær teknikk til function calling) **Baseline (fra modellkunnskap januar 2025):** diff --git a/skills/ms-ai-advisor/references/prompt-engineering/grounding-and-knowledge-injection.md b/skills/ms-ai-advisor/references/prompt-engineering/grounding-and-knowledge-injection.md index d2a8e68..e8b98b7 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/grounding-and-knowledge-injection.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/grounding-and-knowledge-injection.md @@ -496,12 +496,12 @@ Sources: ## Kilder og verifisering **MCP-kilder (Verified):** -1. Microsoft Learn: [Prompt Engineering Techniques](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering) – Groundedness context, citation best practices -2. Microsoft Learn: [Groundedness Detection Filter](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-groundedness) – RAG definition, ungroundedness detection +1. Microsoft Learn: [Prompt Engineering Techniques](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering) – Groundedness context, citation best practices +2. Microsoft Learn: [Groundedness Detection Filter](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-groundedness) – RAG definition, ungroundedness detection 3. Microsoft Learn: [Secure Multitenant RAG](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/secure-multitenant-rag) – Tenant isolation, API-layer, security trimming 4. Microsoft Learn: [Copilot Studio Knowledge Sources](https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-copilot-connectors) – SharePoint, connectors, tenant graph grounding 5. Microsoft Learn: [Web Search in Copilot Studio](https://learn.microsoft.com/en-us/microsoft-copilot-studio/data-privacy-security-web-search) – Bing integration, privacy considerations -6. Microsoft Learn: [Azure AI Agents (Bing Grounding)](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/web-overview) – Web grounding workflow +6. Microsoft Learn: [Azure AI Agents (Bing Grounding)](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/web-overview) – Web grounding workflow **Konfidensnivå per seksjon:** | Seksjon | Konfidensnivå | Kilde | diff --git a/skills/ms-ai-advisor/references/prompt-engineering/multi-turn-conversation-management.md b/skills/ms-ai-advisor/references/prompt-engineering/multi-turn-conversation-management.md index 956c6ed..7598e5d 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/multi-turn-conversation-management.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/multi-turn-conversation-management.md @@ -294,7 +294,7 @@ AgentSession resumedSession = await agent.DeserializeSessionAsync(serializedSess | gpt-35-turbo | 16K tokens | 14K | | o1, o3-mini, o4-mini | 128K-200K | Varierer per modell | -**Viktig:** Sjekk alltid [models page](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models) for oppdaterte limits. +**Viktig:** Sjekk alltid [models page](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure) for oppdaterte limits. ### Truncation-strategi @@ -638,7 +638,7 @@ User → Copilot Studio → Azure OpenAI ### Microsoft Learn (offisiell dokumentasjon) 1. **Work with chat completions models** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chatgpt + https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/chatgpt *Kjernereferanse for Chat Completion API, conversation loop patterns, token management* 2. **Multi-turn conversations with an agent** @@ -646,19 +646,19 @@ User → Copilot Studio → Azure OpenAI *Agent Framework session management, stateless architecture* 3. **Azure OpenAI stored completions & distillation** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/stored-completions + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/stored-completions *Stored completions feature, metadata enrichment* 4. **Azure OpenAI quotas and limits** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quotas-limits + https://learn.microsoft.com/en-us/azure/foundry/openai/quotas-limits *Token limits per modell, TPM/RPM relationship, rate limiting* 5. **Manage Azure OpenAI quota** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/quota + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/quota *Rate limit mechanics, best practices, token counting for rate limits* 6. **Azure OpenAI Assistants API context window management** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/assistants + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/assistants *Truncation strategies, max_prompt_tokens, max_completion_tokens* 7. **CLU multi-turn conversations** diff --git a/skills/ms-ai-advisor/references/prompt-engineering/multimodal-prompt-design.md b/skills/ms-ai-advisor/references/prompt-engineering/multimodal-prompt-design.md index 019ec16..2eeb8f0 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/multimodal-prompt-design.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/multimodal-prompt-design.md @@ -542,10 +542,10 @@ AzureDiagnostics ## Kilder og verifisering **Microsoft Learn dokumentasjon (verifisert 2026-02):** -- [Use vision-enabled chat models](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/gpt-with-vision) — Offisiell how-to guide for GPT-4o/GPT-4 Turbo with Vision +- [Use vision-enabled chat models](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/gpt-with-vision) — Offisiell how-to guide for GPT-4o/GPT-4 Turbo with Vision - [Image prompt engineering techniques](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/gpt-4-v-prompt-engineering) — Best practices for multimodal prompting - [Multimodal search in Azure AI Search](https://learn.microsoft.com/en-us/azure/search/multimodal-search-overview) (Re-verified MCP 2026-04) — RAG-arkitektur; extraction skill-sammenligning (Document Extraction vs Layout vs Content Understanding); verbalization vs direct embeddings; hybrid query-alternativ -- [Azure OpenAI models](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models) — Modelloversikt og token-kostnader +- [Azure OpenAI models](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure) — Modelloversikt og token-kostnader - [Quickstart: Multimodal search in Azure portal](https://learn.microsoft.com/en-us/azure/search/search-get-started-portal-image-search) — Wizard-basert oppsett - [Get started with multimodal vision chat apps](https://learn.microsoft.com/en-us/azure/developer/ai/get-started-app-chat-vision) — End-to-end sample app med Base64 encoding diff --git a/skills/ms-ai-advisor/references/prompt-engineering/prompt-testing-and-evaluation.md b/skills/ms-ai-advisor/references/prompt-engineering/prompt-testing-and-evaluation.md index fd8b3c0..d08de5b 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/prompt-testing-and-evaluation.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/prompt-testing-and-evaluation.md @@ -1063,15 +1063,15 @@ def grade(sample: dict, item: dict) -> float: ## Kilder og verifisering **Primary Sources (Microsoft Learn):** -1. [Evaluate generative AI models and applications - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — GA +1. [Evaluate generative AI models and applications - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — GA 2. [Evaluation flows and metrics - Azure Machine Learning Prompt Flow](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-develop-an-evaluation-flow?view=azureml-api-2) — GA 3. [Azure AI Evaluation SDK - Python API](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-evaluation-readme?view=azure-python) — GA -4. [Agent evaluation with Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/agent-evaluate-sdk?view=foundry-classic) — GA +4. [Agent evaluation with Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/agent-evaluate-sdk?view=foundry-classic) — GA **Code Samples (Microsoft Learn):** -1. [Cloud evaluation with Azure AI Projects SDK](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/cloud-evaluation?view=foundry-classic) -2. [Continuous evaluation setup](https://learn.microsoft.com/en-us/azure/ai-foundry/observability/how-to/how-to-monitor-agents-dashboard?view=foundry) -3. [Custom evaluator registration](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/cloud-evaluation?view=foundry-classic#specify-custom-evaluators) +1. [Cloud evaluation with Azure AI Projects SDK](https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/cloud-evaluation?view=foundry-classic) +2. [Continuous evaluation setup](https://learn.microsoft.com/en-us/azure/foundry/observability/how-to/how-to-monitor-agents-dashboard?view=foundry) +3. [Custom evaluator registration](https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/cloud-evaluation?view=foundry-classic#specify-custom-evaluators) **Last Verified:** 2026-02-04 **Version:** Azure AI Foundry v2 (2024-2026), Prompt Flow v1.13+ (2024-2026) diff --git a/skills/ms-ai-advisor/references/prompt-engineering/real-time-reasoning-performance.md b/skills/ms-ai-advisor/references/prompt-engineering/real-time-reasoning-performance.md index 491ef45..130173a 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/real-time-reasoning-performance.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/real-time-reasoning-performance.md @@ -485,15 +485,15 @@ Deployment C: Chatbot (variabel prompt, medium output) **Primary sources:** 1. **Performance and latency** (Azure OpenAI) - [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/latency](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/latency) + [https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/latency](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/latency) Hentet: januar 2026. Dekker streaming, max_tokens, content filtering, workload separation, metrics. 2. **GPT Realtime API for speech and audio** - [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/realtime-audio](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/realtime-audio) + [https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/realtime-audio](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/realtime-audio) Hentet: januar 2026. Dekker WebRTC/WebSocket, VAD modes, session configuration, supported models. 3. **GPT-4o Realtime API quickstart** - [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/realtime-audio-quickstart](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/realtime-audio-quickstart) + [https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/realtime-audio](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/realtime-audio) Hentet: januar 2026. Kode-eksempler for Python, JavaScript, deployment steps. 4. **Lower speech synthesis latency using Speech SDK** (Re-verified MCP 2026-04) diff --git a/skills/ms-ai-advisor/references/prompt-engineering/reasoning-models-o1-o3-optimization.md b/skills/ms-ai-advisor/references/prompt-engineering/reasoning-models-o1-o3-optimization.md index 0b93594..61c2964 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/reasoning-models-o1-o3-optimization.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/reasoning-models-o1-o3-optimization.md @@ -516,19 +516,19 @@ Denne kunnskapsreferansen er basert på offisiell Microsoft Learn-dokumentasjon **Primary sources:** 1. **Azure OpenAI reasoning models** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/reasoning + https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/reasoning *Confidence: Verified (MCP fetch 2026-02)* 2. **Azure OpenAI model availability and pricing** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models + https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure *Confidence: Verified (MCP fetch 2026-02)* 3. **Reasoning models with Microsoft Foundry Models** - https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/how-to/use-chat-reasoning + https://learn.microsoft.com/en-us/azure/foundry-classic/foundry-models/how-to/use-chat-reasoning *Confidence: Verified (MCP search 2026-02)* 4. **Azure OpenAI function calling support** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/function-calling + https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/function-calling *Confidence: Verified (MCP search 2026-02)* 5. **GPT-5 prompting guide (OpenAI)** diff --git a/skills/ms-ai-advisor/references/prompt-engineering/regulatory-and-compliance-prompting.md b/skills/ms-ai-advisor/references/prompt-engineering/regulatory-and-compliance-prompting.md index 34da78a..0429789 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/regulatory-and-compliance-prompting.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/regulatory-and-compliance-prompting.md @@ -860,7 +860,7 @@ Før produksjonsdeploy, gjennomfør en 2-dagers compliance sprint: ### Microsoft Official Documentation 1. **Data, privacy, and security for Azure OpenAI** (februar 2026) - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/data-privacy + https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/data-privacy → Autoritativ kilde for data processing, abuse monitoring, residency 2. **Govern AI apps and data for regulatory compliance** (februar 2026) @@ -868,7 +868,7 @@ Før produksjonsdeploy, gjennomfør en 2-dagers compliance sprint: → Compliance Manager, Purview integration, EU AI Act readiness 3. **Azure OpenAI Content Filtering** (februar 2026) - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter + https://learn.microsoft.com/en-us/azure/foundry-classic/foundry-models/concepts/content-filter → Content Safety API, thresholds, custom policies 4. **Azure Data Residency** (februar 2026) diff --git a/skills/ms-ai-advisor/references/prompt-engineering/role-playing-and-persona-techniques.md b/skills/ms-ai-advisor/references/prompt-engineering/role-playing-and-persona-techniques.md index 657a6c3..69bff75 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/role-playing-and-persona-techniques.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/role-playing-and-persona-techniques.md @@ -666,22 +666,22 @@ If uncertain, explain limitations. **Microsoft Learn (offisielle kilder):** -1. [System message design - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/advanced-prompt-engineering) +1. [System message design - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/advanced-prompt-engineering) *Komplett guide til system message design, key concepts, og best practices* -2. [Safety system messages - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message) +2. [Safety system messages - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message) *Authoring techniques, safety components, og testing strategies* -3. [Prompt engineering techniques - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering) +3. [Prompt engineering techniques - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering) *Bredere prompt-veiledning inkludert few-shot og token efficiency* 4. [Use prompts in Copilot Studio](https://learn.microsoft.com/en-us/microsoft-copilot-studio/nlu-prompt-node) (Re-verified MCP 2026-04) *Prompt editor features: natural language creation, template library, model selection (Azure OpenAI/Foundry), temperature, knowledge retrieval, code interpreter. Prompt-nivå: agent-tool, topic-node, agent flow-node.* -5. [Azure OpenAI On Your Data - Best practices](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data) +5. [Azure OpenAI On Your Data - Best practices](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data) *System message bruk i RAG-scenarier* -6. [Responsible AI practices for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/overview) +6. [Responsible AI practices for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/overview) *Metaprompt tuning som mitigation strategy* **Code samples verifisert:** diff --git a/skills/ms-ai-advisor/references/prompt-engineering/structured-output-formatting.md b/skills/ms-ai-advisor/references/prompt-engineering/structured-output-formatting.md index dcc3e23..13d8fdb 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/structured-output-formatting.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/structured-output-formatting.md @@ -420,10 +420,10 @@ Krever Azure OpenAI-ressurs med støttet modell (se over). Ingen spesiell lisens | URL | Tema | Konfidensnivå | |-----|------|---------------| -| [Structured Outputs Guide](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/structured-outputs) | Hovedguide, API-eksempler, schema-begrensninger | **Verified** (2026-02) | -| [JSON Mode Guide](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/json-mode) | JSON Mode (legacy), sammenlikning med structured outputs | **Verified** (2026-02) | -| [API Reference (v1)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/latest) | REST API-detaljer, response_format konfigurasjon | **Verified** (2026-02) | -| [Prompt Engineering Guide](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering) | Output structure best practices | **Verified** (2026-02) | +| [Structured Outputs Guide](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/structured-outputs) | Hovedguide, API-eksempler, schema-begrensninger | **Verified** (2026-02) | +| [JSON Mode Guide](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/json-mode) | JSON Mode (legacy), sammenlikning med structured outputs | **Verified** (2026-02) | +| [API Reference (v1)](https://learn.microsoft.com/en-us/azure/foundry/openai/latest) | REST API-detaljer, response_format konfigurasjon | **Verified** (2026-02) | +| [Prompt Engineering Guide](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering) | Output structure best practices | **Verified** (2026-02) | ### Azure OpenAI API-versjon - **Introduced:** `2024-08-01-preview` diff --git a/skills/ms-ai-advisor/references/prompt-engineering/system-message-design-patterns.md b/skills/ms-ai-advisor/references/prompt-engineering/system-message-design-patterns.md index 5e84db3..dfd4228 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/system-message-design-patterns.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/system-message-design-patterns.md @@ -340,11 +340,11 @@ For store organisasjoner med mange AI-assistenter: ## Kilder og verifisering **Verified (fra Microsoft Learn MCP):** -- System message design concepts: [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/advanced-prompt-engineering](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/advanced-prompt-engineering) -- Prompt engineering techniques: [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering) -- Safety system messages: [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message) -- Code samples (Python SDK): [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chatgpt](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chatgpt) -- Azure OpenAI On Your Data best practices: [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data) +- System message design concepts: [https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/advanced-prompt-engineering](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/advanced-prompt-engineering) +- Prompt engineering techniques: [https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering) +- Safety system messages: [https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message) +- Code samples (Python SDK): [https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/chatgpt](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/chatgpt) +- Azure OpenAI On Your Data best practices: [https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data) **Baseline (modellkunnskap):** - EU AI Act compliance patterns (February 2026) diff --git a/skills/ms-ai-advisor/references/prompt-engineering/temperature-sampling-and-parameters.md b/skills/ms-ai-advisor/references/prompt-engineering/temperature-sampling-and-parameters.md index 09dc72b..79ece1a 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/temperature-sampling-and-parameters.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/temperature-sampling-and-parameters.md @@ -559,13 +559,13 @@ for config in test_configs: ## Kilder og verifisering ### Microsoft Learn dokumentasjon -1. [Prompt engineering techniques — Temperature and Top_p parameters](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering#temperature-and-top_p-parameters) -2. [Azure OpenAI REST API reference — Completions](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/reference#completions) -3. [Reproducible output with seed parameter](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/reproducible-output) -4. [Model Router limitations (o-series)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/model-router#use-model-router-in-chats) +1. [Prompt engineering techniques — Temperature and Top_p parameters](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering#temperature-and-top_p-parameters) +2. [Azure OpenAI REST API reference — Completions](https://learn.microsoft.com/en-us/azure/foundry/openai/reference#completions) +3. [Reproducible output with seed parameter](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/reproducible-output) +4. [Model Router limitations (o-series)](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/model-router#use-model-router-in-chats) ### Code samples -5. [Azure OpenAI Python SDK — Chat Completions](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/supported-languages?pivots=programming-language-python#chat) +5. [Azure OpenAI Python SDK — Chat Completions](https://learn.microsoft.com/en-us/azure/foundry/openai/supported-languages?pivots=programming-language-python#chat) 6. [Semantic Kernel — OpenAIPromptExecutionSettings](https://learn.microsoft.com/en-us/dotnet/api/microsoft.semantickernel.connectors.openai.openaipromptexecutionsettings) ### Validert dato diff --git a/skills/ms-ai-advisor/references/prompt-engineering/token-optimization-and-efficiency.md b/skills/ms-ai-advisor/references/prompt-engineering/token-optimization-and-efficiency.md index 0b7289b..3ab3eeb 100644 --- a/skills/ms-ai-advisor/references/prompt-engineering/token-optimization-and-efficiency.md +++ b/skills/ms-ai-advisor/references/prompt-engineering/token-optimization-and-efficiency.md @@ -583,10 +583,10 @@ Break-even requests/måned: $1,224 / $0.00036 = 3.4M requests ## Kilder og verifisering **Offisiell Microsoft-dokumentasjon:** -1. [Prompt caching for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/prompt-caching) -2. [Plan and manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs) -3. [Performance and latency optimization](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/latency) -4. [Batch API for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch) +1. [Prompt caching for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/prompt-caching) +2. [Plan and manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs) +3. [Performance and latency optimization](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/latency) +4. [Batch API for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch) 5. [Azure OpenAI pricing](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) **Verifisert:** Februar 2026 via microsoft-learn MCP-server diff --git a/skills/ms-ai-engineering/references/agent-orchestration/agent-autonomy-and-control-governance.md b/skills/ms-ai-engineering/references/agent-orchestration/agent-autonomy-and-control-governance.md index dbf5a30..4dc9506 100644 --- a/skills/ms-ai-engineering/references/agent-orchestration/agent-autonomy-and-control-governance.md +++ b/skills/ms-ai-engineering/references/agent-orchestration/agent-autonomy-and-control-governance.md @@ -390,7 +390,7 @@ workflow = ( 3. [Process to build agents across your organization](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/ai-agents/build-secure-process) Confidence: High — Tool boundaries, human-in-the-loop mandates, compliance frameworks -4. [Guardrails and controls overview in Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/guardrails/guardrails-overview) +4. [Guardrails and controls overview in Microsoft Foundry](https://learn.microsoft.com/en-us/azure/foundry/guardrails/guardrails-overview) Confidence: High — Intervention points, risk categories, agent vs. model guardrails 5. [Secure AI agents at scale using Microsoft Agent 365](https://learn.microsoft.com/en-us/security/security-for-ai/agent-365-security) diff --git a/skills/ms-ai-engineering/references/agent-orchestration/agent-evaluation-testing-frameworks.md b/skills/ms-ai-engineering/references/agent-orchestration/agent-evaluation-testing-frameworks.md index dadb103..f773fda 100644 --- a/skills/ms-ai-engineering/references/agent-orchestration/agent-evaluation-testing-frameworks.md +++ b/skills/ms-ai-engineering/references/agent-orchestration/agent-evaluation-testing-frameworks.md @@ -482,19 +482,19 @@ results = mlflow.genai.evaluate( ### Microsoft Learn (MCP-verified) 1. **Evaluate your AI agents (preview)** - https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/agent-evaluate-sdk?view=foundry-classic + https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/agent-evaluate-sdk?view=foundry-classic *Confidence: Verified* — Hovedreferanse for Azure AI Evaluation SDK, evaluator types, model support 2. **Continuously evaluate your AI agents (preview)** - https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/continuous-evaluation-agents?view=foundry-classic + https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/continuous-evaluation-agents?view=foundry-classic *Confidence: Verified* — Continuous evaluation setup, sampling configuration, Application Insights integration 3. **Run evaluations in the cloud by using the Microsoft Foundry SDK** - https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/cloud-evaluation?view=foundry-classic + https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/cloud-evaluation?view=foundry-classic *Confidence: Verified* — Cloud batch evaluation, CI/CD integration, dataset formats 4. **Tutorial: Idea to prototype - Build and evaluate an enterprise agent** - https://learn.microsoft.com/en-us/azure/ai-foundry/tutorials/developer-journey-idea-to-prototype?view=foundry + https://learn.microsoft.com/en-us/azure/foundry/tutorials/developer-journey-idea-to-prototype?view=foundry *Confidence: Verified* — End-to-end tutorial med cloud evaluation, built-in evaluators 5. **Test and evaluate AI workloads on Azure (Well-Architected Framework)** @@ -502,15 +502,15 @@ results = mlflow.genai.evaluate( *Confidence: Verified* — Agentic workflow testing strategy, tool call validation, security testing 6. **Observability in generative AI** - https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability + https://learn.microsoft.com/en-us/azure/foundry/concepts/observability *Confidence: Verified* — Built-in evaluators list, GenAIOps evaluation stages, simulators 7. **What are hosted agents? (Evaluate and test hosted agents)** - https://learn.microsoft.com/en-us/azure/ai-foundry/agents/concepts/hosted-agents?view=foundry#evaluate-and-test-hosted-agents + https://learn.microsoft.com/en-us/azure/foundry/agents/concepts/hosted-agents?view=foundry#evaluate-and-test-hosted-agents *Confidence: Verified* — Hosted agent evaluation best practices, test dataset creation 8. **Agent evaluators** - https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/evaluation-evaluators/agent-evaluators?view=foundry + https://learn.microsoft.com/en-us/azure/foundry/concepts/evaluation-evaluators/agent-evaluators?view=foundry *Confidence: Verified* — Agent-specific evaluator details (Intent Resolution, Task Adherence, Tool Call Accuracy) 9. **Evaluate and monitor AI agents (MLflow 3 on Databricks)** diff --git a/skills/ms-ai-engineering/references/agent-orchestration/agent-memory-and-context-management.md b/skills/ms-ai-engineering/references/agent-orchestration/agent-memory-and-context-management.md index cdcaf24..4ba0eba 100644 --- a/skills/ms-ai-engineering/references/agent-orchestration/agent-memory-and-context-management.md +++ b/skills/ms-ai-engineering/references/agent-orchestration/agent-memory-and-context-management.md @@ -461,7 +461,7 @@ Gir data lineage tracking og governance-enforcement. Confidence: ✅ Verified (Mem0Provider, WhiteboardProvider documentation) 2. **Foundry Agent Service Memory (preview)** - https://learn.microsoft.com/en-us/azure/ai-foundry/agents/concepts/what-is-memory?view=foundry + https://learn.microsoft.com/en-us/azure/foundry/agents/concepts/what-is-memory?view=foundry Confidence: ✅ Verified (Managed Memory Store, extraction/consolidation/retrieval phases) 3. **Agent Framework Chat History Providers** @@ -485,7 +485,7 @@ Gir data lineage tracking og governance-enforcement. Confidence: ✅ Verified (Hierarchical memory: knowledge, long-term, short-term) 8. **Azure OpenAI Web App Chat History (Cosmos DB)** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/use-web-app + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/use-web-app Confidence: ✅ Verified (Cosmos DB enablement for chat history) ### Konfidensnivå per seksjon @@ -505,13 +505,13 @@ Gir data lineage tracking og governance-enforcement. ### Unique Microsoft Learn URLs accessed 1. `/semantic-kernel/frameworks/agent/agent-memory` -2. `/azure/ai-foundry/agents/concepts/what-is-memory` +2. `/azure/foundry/agents/concepts/what-is-memory` 3. `/agent-framework/integrations/overview` 4. `/azure/copilot/bring-your-own-storage` 5. `/semantic-kernel/concepts/vector-store-connectors/memory-stores` 6. `/agent-framework/tutorials/agents/multi-turn-conversation` 7. `/azure/cloud-adoption-framework/ai-agents/build-secure-process` -8. `/azure/ai-foundry/openai/how-to/use-web-app` +8. `/azure/foundry-classic/openai/how-to/use-web-app` **Total unique sources**: 8 Microsoft Learn URLs **MCP calls**: 6 (3x microsoft_docs_search, 2x microsoft_docs_fetch, 1x microsoft_code_sample_search) diff --git a/skills/ms-ai-engineering/references/agent-orchestration/agent-to-agent-a2a-protocol.md b/skills/ms-ai-engineering/references/agent-orchestration/agent-to-agent-a2a-protocol.md index 2fb1d54..cbd0ac7 100644 --- a/skills/ms-ai-engineering/references/agent-orchestration/agent-to-agent-a2a-protocol.md +++ b/skills/ms-ai-engineering/references/agent-orchestration/agent-to-agent-a2a-protocol.md @@ -654,11 +654,11 @@ app.MapA2A(agent, "/a2a/my-agent", agentCard: new() ### Microsoft Learn (Verified) 1. **Foundry Agent Service — A2A Tool** - - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools/agent-to-agent + - https://learn.microsoft.com/azure/foundry/agents/how-to/tools/agent-to-agent - Confidence: **Verified** (offisiell guide, preview, februar 2026) 2. **A2A Authentication in Foundry** - - https://learn.microsoft.com/azure/ai-foundry/agents/concepts/agent-to-agent-authentication + - https://learn.microsoft.com/azure/foundry/agents/concepts/agent-to-agent-authentication - Confidence: **Verified** (offisiell auth-guide, februar 2026) 3. **Copilot Studio — Connect A2A Agent** diff --git a/skills/ms-ai-engineering/references/agent-orchestration/computer-using-agents-cua.md b/skills/ms-ai-engineering/references/agent-orchestration/computer-using-agents-cua.md index 9dc55e7..cdcadd2 100644 --- a/skills/ms-ai-engineering/references/agent-orchestration/computer-using-agents-cua.md +++ b/skills/ms-ai-engineering/references/agent-orchestration/computer-using-agents-cua.md @@ -482,7 +482,7 @@ Kostnader basert på: ### Microsoft Learn (Verified) 1. **Foundry Agent Service Computer Use Tool** - - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools/computer-use + - https://learn.microsoft.com/azure/foundry/agents/how-to/tools/computer-use - Confidence: **Verified** (offisiell Foundry-dokumentasjon, sep 2025) 2. **Automate web and desktop apps with computer use — Copilot Studio** @@ -494,7 +494,7 @@ Kostnader basert på: - Confidence: **Verified** (Copilot Studio docs, 2025) 4. **Browser Automation (preview) — Foundry Agent Service** - - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools/browser-automation + - https://learn.microsoft.com/azure/foundry/agents/how-to/tools/browser-automation - Confidence: **Verified** (aug 2025, public preview) 5. **CUA vs RPA — Use agent tools to extend agents** diff --git a/skills/ms-ai-engineering/references/agent-orchestration/foundry-agent-service-ga.md b/skills/ms-ai-engineering/references/agent-orchestration/foundry-agent-service-ga.md index 3920f6e..4b6805e 100644 --- a/skills/ms-ai-engineering/references/agent-orchestration/foundry-agent-service-ga.md +++ b/skills/ms-ai-engineering/references/agent-orchestration/foundry-agent-service-ga.md @@ -327,7 +327,7 @@ Foundry Agent Service er tilgjengelig i følgende Azure-regioner (per februar 20 - Code Interpreter er ikke tilgjengelig i alle regioner **Sjekk regional verktøytilgjengelighet:** -[learn.microsoft.com/azure/ai-foundry/agents/concepts/tool-best-practice#tool-support-by-region-and-model](https://learn.microsoft.com/azure/ai-foundry/agents/concepts/tool-best-practice?view=foundry#tool-support-by-region-and-model) +[learn.microsoft.com/azure/foundry/agents/concepts/tool-best-practice#tool-support-by-region-and-model](https://learn.microsoft.com/azure/foundry/agents/concepts/tool-best-practice?view=foundry#tool-support-by-region-and-model) ## Enterprise-sikkerhet og governance @@ -475,27 +475,27 @@ Rate limiting skjer på modell-deployment-nivå, ikke Agent Service-nivå. Se Az ### Microsoft Learn (Verified) 1. **What is Foundry Agent Service?** - - https://learn.microsoft.com/azure/ai-foundry/agents/overview?view=foundry-classic + - https://learn.microsoft.com/azure/foundry/agents/overview?view=foundry-classic - Confidence: **Verified** (offisiell oversikt, GA-dokumentasjon) 2. **What's new in Foundry Agent Service (GA mai 2025)** - - https://learn.microsoft.com/azure/ai-foundry/agents/whats-new?view=foundry-classic + - https://learn.microsoft.com/azure/foundry-classic/agents/whats-new?view=foundry-classic - Confidence: **Verified** (changelog, mai–juni 2025) 3. **Connected Agents** - - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/connected-agents?view=foundry-classic + - https://learn.microsoft.com/azure/foundry-classic/agents/how-to/connected-agents?view=foundry-classic - Confidence: **Verified** (multi-agent SDK guide og eksempler) 4. **Foundry Agent Service limits, quotas, and regional support** - - https://learn.microsoft.com/azure/ai-foundry/agents/concepts/limits-quotas-regions?view=foundry + - https://learn.microsoft.com/azure/foundry/agents/concepts/limits-quotas-regions?view=foundry - Confidence: **Verified** (komplett region- og grense-tabell) 5. **MCP tool — Foundry Agent Service** - - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools-classic/model-context-protocol-samples?view=foundry-classic + - https://learn.microsoft.com/azure/foundry-classic/agents/how-to/tools-classic/model-context-protocol-samples?view=foundry-classic - Confidence: **Verified** (C# og Python code samples) 6. **Threads, runs, and messages** - - https://learn.microsoft.com/azure/ai-foundry/agents/concepts/threads-runs-messages?view=foundry-classic + - https://learn.microsoft.com/azure/foundry-classic/agents/concepts/threads-runs-messages?view=foundry-classic - Confidence: **Verified** (kjernekonsept-dokumentasjon) 7. **AzureAIAgent Foundry GA Migration Guide (SK Python)** @@ -503,11 +503,11 @@ Rate limiting skjer på modell-deployment-nivå, ikke Agent Service-nivå. Se Az - Confidence: **Verified** (breaking changes og migrasjonsguide) 8. **Transparency Note for Azure Agent Service** - - https://learn.microsoft.com/azure/ai-foundry/responsible-ai/agents/transparency-note?view=foundry-classic + - https://learn.microsoft.com/azure/foundry/responsible-ai/agents/transparency-note?view=foundry-classic - Confidence: **Verified** (ansvarlig AI-rammeverk) 9. **Foundry Agent Service FAQ (prising)** - - https://learn.microsoft.com/azure/ai-foundry/agents/faq?view=foundry-classic + - https://learn.microsoft.com/azure/foundry/agents/faq?view=foundry-classic - Confidence: **Verified** (offisiell prisingsforklaring) ### Confidence per seksjon diff --git a/skills/ms-ai-engineering/references/agent-orchestration/foundry-workflows-visual-orchestration.md b/skills/ms-ai-engineering/references/agent-orchestration/foundry-workflows-visual-orchestration.md index 073429c..72f0bc7 100644 --- a/skills/ms-ai-engineering/references/agent-orchestration/foundry-workflows-visual-orchestration.md +++ b/skills/ms-ai-engineering/references/agent-orchestration/foundry-workflows-visual-orchestration.md @@ -583,19 +583,19 @@ Foundry Workflows' visuelle designer gir offentlig sektor-organisasjoner en unik ### Microsoft Learn (Verified) 1. **Build a workflow in Microsoft Foundry** - - https://learn.microsoft.com/azure/ai-foundry/agents/concepts/workflow?view=foundry + - https://learn.microsoft.com/azure/foundry/agents/concepts/workflow?view=foundry - Confidence: **Verified** (offisiell workflow-guide, Foundry new portal) 2. **Agent development lifecycle** - - https://learn.microsoft.com/azure/ai-foundry/agents/concepts/development-lifecycle?view=foundry + - https://learn.microsoft.com/azure/foundry/agents/concepts/development-lifecycle?view=foundry - Confidence: **Verified** (versjonering, publisering, livssyklus, januar 2025) 3. **Publish and share agents in Microsoft Foundry** - - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/publish-agent?view=foundry + - https://learn.microsoft.com/azure/foundry/agents/how-to/agent-applications?view=foundry - Confidence: **Verified** (Agent Application deployment, API-kall, RBAC) 4. **Monitor agents with the Agent Monitoring Dashboard** - - https://learn.microsoft.com/azure/ai-foundry/observability/how-to/how-to-monitor-agents-dashboard?view=foundry + - https://learn.microsoft.com/azure/foundry/observability/how-to/how-to-monitor-agents-dashboard?view=foundry - Confidence: **Verified** (token usage, latency, success rate, evaluators) 5. **Declarative Workflows — Overview (Agent Framework)** @@ -607,7 +607,7 @@ Foundry Workflows' visuelle designer gir offentlig sektor-organisasjoner en unik - Confidence: **Verified** (HITL-mønster, pause og resume, compliance) 7. **Transparency Note for Azure Agent Service** - - https://learn.microsoft.com/azure/ai-foundry/responsible-ai/agents/transparency-note?view=foundry-classic + - https://learn.microsoft.com/azure/foundry/responsible-ai/agents/transparency-note?view=foundry-classic - Confidence: **Verified** (Foundry Workflows capabilities, visioning, governance) ### Microsoft Dev Blog (Verified) diff --git a/skills/ms-ai-engineering/references/agent-orchestration/tool-use-and-function-calling-patterns.md b/skills/ms-ai-engineering/references/agent-orchestration/tool-use-and-function-calling-patterns.md index c840d51..5cd071d 100644 --- a/skills/ms-ai-engineering/references/agent-orchestration/tool-use-and-function-calling-patterns.md +++ b/skills/ms-ai-engineering/references/agent-orchestration/tool-use-and-function-calling-patterns.md @@ -448,12 +448,12 @@ def update_citizen_record(ssn: str, field: str, value: str) -> str: ### Microsoft Learn-kilder (Verified via MCP) -1. [Azure OpenAI Function Calling](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/function-calling) — **Verified 2026-02** +1. [Azure OpenAI Function Calling](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/function-calling) — **Verified 2026-02** 2. [Semantic Kernel Agent Functions](https://learn.microsoft.com/en-us/semantic-kernel/frameworks/agent/agent-functions) — **Verified 2026-02** 3. [Agent Framework - Agent as Function Tool](https://learn.microsoft.com/en-us/agent-framework/tutorials/agents/agent-as-function-tool) — **Verified 2026-02** 4. [AG-UI Backend Tool Rendering](https://learn.microsoft.com/en-us/agent-framework/integrations/ag-ui/backend-tool-rendering) — **Verified (MCP 2026-04)** — AIFunctionFactory.Create() med serializerOptions for komplekse typer (C#), @tool decorator med Annotated/Field (Python), TOOL_CALL_START/ARGS/END/RESULT events, FunctionCallContent/.Arguments og FunctionResultContent/.Result (C#), klasse-baserte tools-moenster (Python) -5. [Azure OpenAI Assistants Function Calling](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/assistant-functions) — **Verified 2026-02** -6. [Structured Outputs](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/structured-outputs) — **Verified 2026-02** +5. [Azure OpenAI Assistants Function Calling](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/assistant-functions) — **Verified 2026-02** +6. [Structured Outputs](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/structured-outputs) — **Verified 2026-02** ### Konfidensnivå per seksjon diff --git a/skills/ms-ai-engineering/references/api-management/multi-region-ai-gateway-design.md b/skills/ms-ai-engineering/references/api-management/multi-region-ai-gateway-design.md index b2f2a9f..0214c33 100644 --- a/skills/ms-ai-engineering/references/api-management/multi-region-ai-gateway-design.md +++ b/skills/ms-ai-engineering/references/api-management/multi-region-ai-gateway-design.md @@ -423,7 +423,7 @@ Hver region krever eget VNet med nødvendige NSG-regler: - [Use a gateway in front of multiple Azure OpenAI deployments or instances](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-multi-backend) — Arkitekturmønstre for AI gateway - [AI gateway in Azure API Management](https://learn.microsoft.com/en-us/azure/api-management/genai-gateway-capabilities) — Oversikt over AI gateway-kapabiliteter - [Access Azure OpenAI through a gateway](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-guide) — Well-Architected Framework-veiledning -- [Azure OpenAI deployment types](https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/concepts/deployment-types) — Deployment types og data residency +- [Azure OpenAI deployment types](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/deployment-types) — Deployment types og data residency --- diff --git a/skills/ms-ai-engineering/references/api-management/streaming-support-apim.md b/skills/ms-ai-engineering/references/api-management/streaming-support-apim.md index 88e6ac9..820a755 100644 --- a/skills/ms-ai-engineering/references/api-management/streaming-support-apim.md +++ b/skills/ms-ai-engineering/references/api-management/streaming-support-apim.md @@ -505,7 +505,7 @@ For ikke-streaming requests, bruk standard `llm-emit-token-metric` i outbound: - [Configure API for server-sent events](https://learn.microsoft.com/en-us/azure/api-management/how-to-server-sent-events) — Offisiell SSE-guide for APIM - [AI gateway in Azure API Management](https://learn.microsoft.com/en-us/azure/api-management/genai-gateway-capabilities) — AI gateway oversikt -- [Azure OpenAI REST API reference - Chat Completions](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/reference#chat-completions) — Stream-parameter dokumentasjon +- [Azure OpenAI REST API reference - Chat Completions](https://learn.microsoft.com/en-us/azure/foundry/openai/reference#chat-completions) — Stream-parameter dokumentasjon - [forward-request policy](https://learn.microsoft.com/en-us/azure/api-management/forward-request-policy) — Policy-referanse for forwarding - [Log token usage, prompts, and completions](https://learn.microsoft.com/en-us/azure/api-management/api-management-howto-llm-logs) — LLM-logging i APIM diff --git a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-api-best-practices.md b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-api-best-practices.md index 82dfe1a..cdd35a5 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-api-best-practices.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-api-best-practices.md @@ -709,11 +709,11 @@ AzureDiagnostics - Confidence: **Verified** (MCP fetch) 4. **Get started using provisioned deployments on Azure OpenAI** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-get-started + - URL: https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/provisioned-get-started - Confidence: **Verified** (MCP fetch) 5. **Getting started with Azure OpenAI batch deployments** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch + - URL: https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch - Confidence: **Verified** (MCP search) 6. **Azure AI services authentication and authorization using .NET** diff --git a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-cost-optimization.md b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-cost-optimization.md index 86235f8..26e359b 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-cost-optimization.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-cost-optimization.md @@ -331,15 +331,15 @@ PTU er en kapasitetsbasert prismodell for Azure OpenAI, primært for produksjons *Sist sjekket: 2026-02* 2. **Provisioned Throughput Concepts** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/provisioned-throughput + https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput *Sist sjekket: 2026-02* 3. **Provisioned Throughput Onboarding (PTU Cost Management)** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding + https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput-billing *Sist sjekket: 2026-02* 4. **Plan and Manage Costs for Azure OpenAI** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs + https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs *Sist sjekket: 2026-02* 5. **Govern AI Costs (Cloud Adoption Framework)** @@ -374,7 +374,7 @@ PTU er en kapasitetsbasert prismodell for Azure OpenAI, primært for produksjons - microsoft_docs_search: "Azure AI Services reserved capacity commitment tier" - microsoft_docs_search: "Azure AI Services budget management cost estimation" - microsoft_docs_fetch: `/azure/ai-services/commitment-tier` -- microsoft_docs_fetch: `/azure/ai-foundry/openai/how-to/manage-costs` +- microsoft_docs_fetch: `/azure/foundry/concepts/manage-costs` - microsoft_docs_fetch: `/azure/cloud-adoption-framework/scenarios/ai/platform/governance` - microsoft_docs_search: "Azure OpenAI provisioned throughput PTU cost optimization" diff --git a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-enterprise-architecture.md b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-enterprise-architecture.md index 8778484..fad1eff 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-enterprise-architecture.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-enterprise-architecture.md @@ -545,7 +545,7 @@ TOTAL: ~46 700 NOK/måned (høyere cost, men forutsigbar) **Microsoft Learn Documentation (offisiell, 2026-02):** 1. [AI Ready - Cloud Adoption Framework](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/ready) -2. [BCDR for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/business-continuity-disaster-recovery) +2. [BCDR for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/high-availability-resiliency) 3. [Baseline Foundry Chat Architecture (Foundry Agent Service + Microsoft Agent Framework)](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/architecture/baseline-microsoft-foundry-chat) — Verified (MCP 2026-04) 4. [Azure API Management - AI Gateway Capabilities](https://learn.microsoft.com/en-us/azure/api-management/genai-gateway-capabilities) 5. [Reliability in Azure AI Search](https://learn.microsoft.com/en-us/azure/reliability/reliability-ai-search) @@ -559,7 +559,7 @@ TOTAL: ~46 700 NOK/måned (høyere cost, men forutsigbar) **Verifikasjon:** - ✅ Alle arkitekturdiagrammer basert på Microsoft offisiell dokumentasjon -- ✅ Deployment-typer (Global/Data Zone/Regional/PTU) verifisert mot [Deployment Types](https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/concepts/deployment-types) +- ✅ Deployment-typer (Global/Data Zone/Regional/PTU) verifisert mot [Deployment Types](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/deployment-types) - ✅ APIM circuit breaker pattern bekreftet i [Backends Documentation](https://learn.microsoft.com/en-us/azure/api-management/backends) - ✅ Zone redundancy requirements verifisert mot [Availability Zones Overview](https://learn.microsoft.com/en-us/azure/reliability/availability-zones-overview) diff --git a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-monitoring-logging.md b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-monitoring-logging.md index d66fc91..f183394 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-monitoring-logging.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-monitoring-logging.md @@ -544,7 +544,7 @@ Hvis du bruker ITSM-integrasjoner (ServiceNow, etc.) via Action Groups, kan det **Verified (MCP-research, januar 2026):** - [Enable diagnostic logging for Foundry Tools](https://learn.microsoft.com/en-us/azure/ai-services/diagnostic-logging) – Offisiell guide, sist oppdatert 2024 -- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) – Kusto queries, diagnostic settings, dashboards +- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) – Kusto queries, diagnostic settings, dashboards - [Introduction to Application Insights](https://learn.microsoft.com/en-us/azure/azure-monitor/app/app-insights-overview) – OpenTelemetry-basert APM - [Monitor Azure AI services (Training module)](https://learn.microsoft.com/en-us/training/modules/monitor-ai-services/) – Microsoft Learn offisiell kurs diff --git a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-networking-security.md b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-networking-security.md index 83a9840..3542024 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-networking-security.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-networking-security.md @@ -591,8 +591,8 @@ Test-NetConnection -ComputerName 10.0.2.5 -Port 443 **Verified (MCP microsoft-learn, 2026-02):** - [Configure Foundry Tools virtual networks](https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-virtual-networks) - Hovedkilde for VNet-konfigurasjon, service endpoints, IP-regler, private endpoints - [Configure secure networking for Azure AI platform services](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/platform/networking) - Arkitektur-guide fra Cloud Adoption Framework -- [Configure Azure OpenAI networking](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/network) - Private endpoint oppsett for Azure OpenAI -- [Network and access configuration for Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/on-your-data-configuration) - Trusted services bypass, managed identity setup +- [Configure Azure OpenAI networking](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/network) - Private endpoint oppsett for Azure OpenAI +- [Network and access configuration for Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/on-your-data-configuration) - Trusted services bypass, managed identity setup - [Azure security baseline for Azure AI services](https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/cognitive-services-security-baseline) - NSG-støtte (ikke støttet), private link (støttet), disable public access - [Create a private endpoint for a secure connection to Azure AI Search](https://learn.microsoft.com/en-us/azure/search/service-create-private-endpoint) - Shared private link-mønster diff --git a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-vs-foundry-tools-selection.md b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-vs-foundry-tools-selection.md index 8200194..54fe825 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-vs-foundry-tools-selection.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-vs-foundry-tools-selection.md @@ -675,7 +675,7 @@ START: Hvilken AI-kapabilitet trenger du? Dato: 2026-02 (verifisert) 3. **Choose an Azure resource type for Foundry** - https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/resource-types + https://learn.microsoft.com/en-us/azure/foundry-classic/concepts/resource-types Dato: 2026-02 (verifisert) 4. **Choose the right Foundry tool for document processing** @@ -683,11 +683,11 @@ START: Hvilken AI-kapabilitet trenger du? Dato: 2026-02 (verifisert) 5. **What is Foundry Agent Service?** - https://learn.microsoft.com/en-us/azure/ai-foundry/agents/overview + https://learn.microsoft.com/en-us/azure/foundry/agents/overview Dato: 2026-02 (verifisert) 6. **Plan and manage costs for Microsoft Foundry** - https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/manage-costs + https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs Dato: 2026-02 (verifisert) 7. **Azure OpenAI pricing page** diff --git a/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-image-analysis.md b/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-image-analysis.md index 5282faf..d594ac8 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-image-analysis.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-image-analysis.md @@ -360,7 +360,7 @@ Azure AI Vision er en **Azure resource** som faktureres direkte via Azure-abonne 3. [Object detection (version 4.0)](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-object-detection-40) - Bounding box-basert objektdeteksjon 4. [Image tagging with Image Analysis version 4.0](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-tag-images-40) - Tagging av tusenvis av objekter 5. [What's new in Azure Vision in Foundry Tools](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/whats-new) - Florence integration (mars 2023), GA-lansering (november 2023) -6. [Transparency note: Image Analysis](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/computer-vision/image-analysis-transparency-note) - Florence foundation model, bounding boxes, confidence scores +6. [Transparency note: Image Analysis](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/computer-vision/image-analysis-transparency-note) - Florence foundation model, bounding boxes, confidence scores 7. [Call the Image Analysis 4.0 Analyze API (Python)](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/call-analyze-image-40?pivots=programming-language-python) - SDK implementation 8. [Azure Image Analysis client library for Python](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-vision-imageanalysis-readme) - Visual features, gender-neutral captions diff --git a/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-ocr-processing.md b/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-ocr-processing.md index f277b50..3721997 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-ocr-processing.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-ocr-processing.md @@ -334,9 +334,9 @@ Kombiner OCR med LLM for intelligent dokumentforståelse: 3. **Call Azure Vision v3.2 GA Read API**: https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/call-read-api 4. **Quickstart: Azure Vision v3.2 GA Read (Python)**: https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/client-library 5. **Quickstart: Azure Vision v3.2 GA Read (REST API)**: https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/client-library -6. **Data, privacy, and security for OCR**: https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/computer-vision/ocr-data-privacy-security -7. **Transparency note and use cases for OCR**: https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/computer-vision/ocr-transparency-note -8. **Capabilities and limitations of OCR**: https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/computer-vision/ocr-characteristics-and-limitations +6. **Data, privacy, and security for OCR**: https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/computer-vision/ocr-data-privacy-security +7. **Transparency note and use cases for OCR**: https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/computer-vision/ocr-transparency-note +8. **Capabilities and limitations of OCR**: https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/computer-vision/ocr-characteristics-and-limitations 9. **Image Analysis cognitive skill (AI Search)**: https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-image-analysis 10. **Tutorial: Vision with Azure AI services (Synapse)**: https://learn.microsoft.com/en-us/azure/synapse-analytics/machine-learning/tutorial-computer-vision-use-mmlspark 11. **Azure Vision Image Analysis Python SDK**: https://learn.microsoft.com/en-us/python/api/overview/azure/ai-vision-imageanalysis-readme diff --git a/skills/ms-ai-engineering/references/azure-ai-services/content-understanding-multimodal-analysis.md b/skills/ms-ai-engineering/references/azure-ai-services/content-understanding-multimodal-analysis.md index 3a94387..76f87e9 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/content-understanding-multimodal-analysis.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/content-understanding-multimodal-analysis.md @@ -576,7 +576,7 @@ Content Understanding er en **Azure Foundry Tools** tjeneste, inkludert i: | Multimodal search (AI Search integration) | https://learn.microsoft.com/en-us/azure/search/multimodal-search-overview | Verified (Feb 2026) | | Azure AI Video Indexer insights overview | https://learn.microsoft.com/en-us/azure/azure-video-indexer/insights-overview | Verified (Feb 2026) | | Python SDK (ContentUnderstandingClient) | https://learn.microsoft.com/en-us/python/api/overview/azure/ai-contentunderstanding-readme | Verified (Feb 2026) | -| Data privacy and security | https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/content-understanding/data-privacy | Verified (Feb 2026) | +| Data privacy and security | https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/content-understanding/data-privacy | Verified (Feb 2026) | ### Baseline (modellkunnskap) diff --git a/skills/ms-ai-engineering/references/azure-ai-services/speech-services-speaker-recognition.md b/skills/ms-ai-engineering/references/azure-ai-services/speech-services-speaker-recognition.md index 2093a09..191864c 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/speech-services-speaker-recognition.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/speech-services-speaker-recognition.md @@ -474,7 +474,7 @@ Før du anbefaler Speaker Recognition: - Coverage: Feature overview, verification vs. identification, use cases 3. **Data Privacy and Security for Text-to-Speech** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/speech-service/text-to-speech/data-privacy-security + - URL: https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/speech-service/text-to-speech/data-privacy-security - Confidence: **Verified** (MCP fetch 2026-02-03) - Coverage: Speaker Verification for voice talent consent, voice signature processing, DPA compliance diff --git a/skills/ms-ai-engineering/references/azure-ai-services/speech-services-text-to-speech.md b/skills/ms-ai-engineering/references/azure-ai-services/speech-services-text-to-speech.md index 662c866..d7887f4 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/speech-services-text-to-speech.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/speech-services-text-to-speech.md @@ -495,7 +495,7 @@ Billable characters: `Hello, world!` = 13 tegn (ikke `` eller ``) | Customize voice and sound with SSML | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-synthesis-markup-voice | | How to synthesize speech from text | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-services/speech-service/how-to-speech-synthesis | | Text-to-Speech FAQ | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-services/speech-service/faq-tts | -| Transparency note for TTS | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/speech-service/text-to-speech/transparency-note | +| Transparency note for TTS | ✅ Verified | https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/speech-service/text-to-speech/transparency-note | | Language support | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts | | Speech service pricing | ✅ Verified | https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/ | | Batch synthesis API | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-services/speech-service/batch-synthesis | diff --git a/skills/ms-ai-engineering/references/azure-ai-services/translator-document-translation.md b/skills/ms-ai-engineering/references/azure-ai-services/translator-document-translation.md index 55486b8..ade580b 100644 --- a/skills/ms-ai-engineering/references/azure-ai-services/translator-document-translation.md +++ b/skills/ms-ai-engineering/references/azure-ai-services/translator-document-translation.md @@ -329,7 +329,7 @@ General translation Domain-specific terms - Start med **Foundry (classic) portal** for manuell testing - Bruk **Single-file API** for prototyping (enklere enn Blob Storage) - Test med maksimalt 3 språkpar først -- Les [Transparency Note](https://learn.microsoft.com/azure/ai-foundry/responsible-ai/translator/transparency-note) for å forstå begrensninger +- Les [Transparency Note](https://learn.microsoft.com/azure/foundry/responsible-ai/translator/transparency-note) for å forstå begrensninger **Middels (har brukt Text Translation API):** - Migrer til **Batch Translation** for volum > 50 filer/dag @@ -369,7 +369,7 @@ General translation Domain-specific terms *Confidence: Verified (2026-02)* — Rate limits, request size limits 6. **Translator Transparency Note** - https://learn.microsoft.com/azure/ai-foundry/responsible-ai/translator/transparency-note + https://learn.microsoft.com/azure/foundry/responsible-ai/translator/transparency-note *Confidence: Verified (2026-02)* — AI-begrensninger, data privacy, responsible AI ### Konfidensnivå per seksjon diff --git a/skills/ms-ai-engineering/references/data-engineering/data-anonymization-privacy.md b/skills/ms-ai-engineering/references/data-engineering/data-anonymization-privacy.md index 7b4e379..6b52a91 100644 --- a/skills/ms-ai-engineering/references/data-engineering/data-anonymization-privacy.md +++ b/skills/ms-ai-engineering/references/data-engineering/data-anonymization-privacy.md @@ -549,11 +549,11 @@ def privacy_check_before_deployment(model_artifacts_path: str) -> dict: ## Referanser - [What is Azure Language PII detection?](https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/overview) -- PII-deteksjon og maskering -- [PII filter in Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-personal-information) -- PII-filtrering for LLM-er +- [PII filter in Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-personal-information) -- PII-filtrering for LLM-er - [Responsible AI - Privacy and security](https://learn.microsoft.com/en-us/azure/machine-learning/concept-responsible-ai) -- SmartNoise og Counterfit - [Data privacy for cloud-scale analytics](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/cloud-scale-analytics/secure-data-privacy) -- Dataklassifisering og konfidensialitetsskjema - [PII entity categories](https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/concepts/entity-categories) -- Alle stottede PII-kategorier -- [Transparency note for PII](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/language-service/transparency-note-personally-identifiable-information) -- Bruksomrader og begrensninger +- [Transparency note for PII](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/language-service/transparency-note-personally-identifiable-information) -- Bruksomrader og begrensninger - [Data governance with Microsoft Purview](https://learn.microsoft.com/en-us/purview/data-governance-master-data-management) -- Purview for dataklassifisering --- diff --git a/skills/ms-ai-engineering/references/data-engineering/data-quality-ai-frameworks.md b/skills/ms-ai-engineering/references/data-engineering/data-quality-ai-frameworks.md index 02d5d24..f3d10ae 100644 --- a/skills/ms-ai-engineering/references/data-engineering/data-quality-ai-frameworks.md +++ b/skills/ms-ai-engineering/references/data-engineering/data-quality-ai-frameworks.md @@ -550,7 +550,7 @@ def trigger_purview_profiling(data_asset_id, connection_id): ### Code samples (Microsoft Learn) - **Azure ML fine-tuning job with validation data** - https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/fine-tune-serverless + https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/fine-tune-serverless Python SDK sample for creating validation dataset asset. - **AutoML training/validation MLTable inputs** diff --git a/skills/ms-ai-engineering/references/data-engineering/synthetic-data-generation.md b/skills/ms-ai-engineering/references/data-engineering/synthetic-data-generation.md index 7422417..e46c136 100644 --- a/skills/ms-ai-engineering/references/data-engineering/synthetic-data-generation.md +++ b/skills/ms-ai-engineering/references/data-engineering/synthetic-data-generation.md @@ -408,11 +408,11 @@ for metric, result in validation.items(): ## Referanser -- [Generate synthetic and simulated data for evaluation](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/simulator-interaction-data) -- Azure AI Evaluation Simulator -- [Generate synthetic data for fine-tuning in Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/fine-tuning/data-generation) -- Foundry syntetisk data UI +- [Generate synthetic and simulated data for evaluation](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/simulator-interaction-data) -- Azure AI Evaluation Simulator +- [Generate synthetic data for fine-tuning in Microsoft Foundry](https://learn.microsoft.com/en-us/azure/foundry/fine-tuning/data-generation) -- Foundry syntetisk data UI - [Design training data for AI workloads on Azure](https://learn.microsoft.com/en-us/azure/well-architected/ai/training-data-design) -- Well-Architected Framework for treningsdata - [Azure OpenAI for big data](https://learn.microsoft.com/en-us/fabric/data-science/open-ai) -- SynapseML + OpenAI på Fabric -- [Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data) -- RAG for datagenerering +- [Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data) -- RAG for datagenerering --- diff --git a/skills/ms-ai-engineering/references/mlops-genaiops/feedback-loops-continuous-improvement.md b/skills/ms-ai-engineering/references/mlops-genaiops/feedback-loops-continuous-improvement.md index 9e09dcc..9da52e5 100644 --- a/skills/ms-ai-engineering/references/mlops-genaiops/feedback-loops-continuous-improvement.md +++ b/skills/ms-ai-engineering/references/mlops-genaiops/feedback-loops-continuous-improvement.md @@ -715,7 +715,7 @@ mlflow.log_param("user_id_hash", user_id_hash) # Logged 1. [MLflow for GenAI Apps and Agents - Continuous Improvement Cycle](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/overview/) (Verified MCP 2026-04 — updated 10-step cycle; new: Trace UI for pattern identification, evaluation harness, version/prompt management tracking) 2. [Machine Learning Operations v2 - Monitoring & Feedback](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/machine-learning-operations-v2) 3. [Generative AI App Developer Workflow - Production Monitoring](https://learn.microsoft.com/en-us/azure/databricks/generative-ai/tutorials/ai-cookbook/genai-developer-workflow) -4. [Azure AI Foundry - Observability in Generative AI](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability) +4. [Azure AI Foundry - Observability in Generative AI](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability) 5. [MLOps and GenAIOps for AI Workloads - Model Maintenance](https://learn.microsoft.com/en-us/azure/well-architected/ai/mlops-genaiops#model-maintenance) 6. [AI Builder - Continuously Improve Your Model (Feedback Loop)](https://learn.microsoft.com/en-us/ai-builder/feedback-loop) diff --git a/skills/ms-ai-engineering/references/mlops-genaiops/genaiops-llm-specific-practices.md b/skills/ms-ai-engineering/references/mlops-genaiops/genaiops-llm-specific-practices.md index 7a7ead6..29b0688 100644 --- a/skills/ms-ai-engineering/references/mlops-genaiops/genaiops-llm-specific-practices.md +++ b/skills/ms-ai-engineering/references/mlops-genaiops/genaiops-llm-specific-practices.md @@ -350,7 +350,7 @@ MLflow Tracing provides end-to-end observability for GenAI applications: 8. [Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-evaluation-readme) 9. [Mosaic AI capabilities for GenAI](https://learn.microsoft.com/en-us/azure/databricks/generative-ai/guide/mosaic-ai-gen-ai-capabilities) 10. [MLflow Prompt Registry](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/) -11. [Azure AI Foundry monitoring](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/monitor-quality-safety) +11. [Azure AI Foundry monitoring](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/monitor-quality-safety) 12. [MLflow Tracing for GenAI](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/) 13. [GenAI app developer workflow](https://learn.microsoft.com/en-us/azure/databricks/generative-ai/tutorials/ai-cookbook/genai-developer-workflow) 14. [Plan and prepare a GenAIOps solution (Microsoft Learn Training)](https://learn.microsoft.com/en-us/training/modules/plan-prepare-genaiops/) diff --git a/skills/ms-ai-engineering/references/mlops-genaiops/governance-audit-ml-operations.md b/skills/ms-ai-engineering/references/mlops-genaiops/governance-audit-ml-operations.md index 5aaf168..cbb5694 100644 --- a/skills/ms-ai-engineering/references/mlops-genaiops/governance-audit-ml-operations.md +++ b/skills/ms-ai-engineering/references/mlops-genaiops/governance-audit-ml-operations.md @@ -104,7 +104,7 @@ Azure Policy lar deg definere *guardrails* for hvilke modeller som kan deployes, **Kilder:** - [Audit and manage Azure Machine Learning with Azure Policy](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-integrate-azure-policy?view=azureml-api-2) -- [Azure AI Foundry built-in policies](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/azure-policy) +- [Azure AI Foundry built-in policies](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/azure-policy) - [Govern Azure platform services (PaaS) for AI](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/platform/governance) --- diff --git a/skills/ms-ai-engineering/references/mlops-genaiops/inferencing-optimization-caching.md b/skills/ms-ai-engineering/references/mlops-genaiops/inferencing-optimization-caching.md index 9fdaaa6..8ee8037 100644 --- a/skills/ms-ai-engineering/references/mlops-genaiops/inferencing-optimization-caching.md +++ b/skills/ms-ai-engineering/references/mlops-genaiops/inferencing-optimization-caching.md @@ -953,7 +953,7 @@ Diagnostikk: *Verifisert: 2026-02-04* — Komplett guide til ONNX Runtime, model conversion, deployment 2. **Prompt Caching (Azure OpenAI)** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/prompt-caching?view=foundry-classic + https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/prompt-caching?view=foundry-classic *Verifisert: 2026-02-04* — Official docs for prompt caching, supported models, pricing 3. **Application Design for AI Workloads on Azure** diff --git a/skills/ms-ai-engineering/references/mlops-genaiops/llm-evaluation-production.md b/skills/ms-ai-engineering/references/mlops-genaiops/llm-evaluation-production.md index 008c95a..f6660ad 100644 --- a/skills/ms-ai-engineering/references/mlops-genaiops/llm-evaluation-production.md +++ b/skills/ms-ai-engineering/references/mlops-genaiops/llm-evaluation-production.md @@ -1053,16 +1053,16 @@ Production evaluation er ikke komplett uten human review loop. Anbefal: ### Primærkilder (Official Microsoft Documentation) 1. **Azure AI Foundry Evaluation SDK:** - [Evaluate your generative AI application locally with the Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/evaluate-sdk) – Comprehensive guide til local og cloud evaluation + [Evaluate your generative AI application locally with the Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/evaluate-sdk) – Comprehensive guide til local og cloud evaluation 2. **Continuous Evaluation for Agents:** - [Continuously evaluate your AI agents (preview)](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/continuous-evaluation-agents) – Production monitoring architecture og SDK examples + [Continuously evaluate your AI agents (preview)](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/continuous-evaluation-agents) – Production monitoring architecture og SDK examples 3. **MLflow 3 Evaluation & Monitoring:** [Evaluate and monitor AI agents - Azure Databricks](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/) – MLflow 3 evaluation harness og production scorers 4. **Observability Overview:** - [Observability in generative AI - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability) – High-level GenAIOps lifecycle og evaluator taxonomy + [Observability in generative AI - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability) – High-level GenAIOps lifecycle og evaluator taxonomy 5. **Model Monitoring for Generative AI:** [Model monitoring for generative AI applications (preview)](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-monitor-generative-ai-applications) – Azure ML Prompt Flow monitoring approach @@ -1071,7 +1071,7 @@ Production evaluation er ikke komplett uten human review loop. Anbefal: [Azure AI Evaluation client library for Python](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-evaluation-readme) – API docs for all built-in evaluators 7. **Agent Monitoring Dashboard:** - [Monitor agents with the Agent Monitoring Dashboard (preview)](https://learn.microsoft.com/en-us/azure/ai-foundry/observability/how-to/how-to-monitor-agents-dashboard) – Setup guide for continuous evaluation in Foundry portal + [Monitor agents with the Agent Monitoring Dashboard (preview)](https://learn.microsoft.com/en-us/azure/foundry/observability/how-to/how-to-monitor-agents-dashboard) – Setup guide for continuous evaluation in Foundry portal ### Sekundærkilder (Community & Research) diff --git a/skills/ms-ai-engineering/references/mlops-genaiops/model-evaluation-frameworks.md b/skills/ms-ai-engineering/references/mlops-genaiops/model-evaluation-frameworks.md index c7de82f..6722288 100644 --- a/skills/ms-ai-engineering/references/mlops-genaiops/model-evaluation-frameworks.md +++ b/skills/ms-ai-engineering/references/mlops-genaiops/model-evaluation-frameworks.md @@ -473,15 +473,15 @@ Hvis du kjører massive evalueringer (100K+ samples), vurder PTU for judge model ## Kilder og verifisering ### Microsoft Learn (Verified via MCP) -1. [Evaluate generative AI models and applications by using Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — **Verified** — Komplett guide til Foundry UI evaluations, metrics, data mapping. +1. [Evaluate generative AI models and applications by using Microsoft Foundry](https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — **Verified** — Komplett guide til Foundry UI evaluations, metrics, data mapping. 2. [Evaluation flows and metrics (Azure ML Prompt Flow)](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-develop-an-evaluation-flow?view=azureml-api-2) — **Verified** — Custom evaluation flows, aggregation nodes. 3. [MLflow 3 Evaluation and Monitoring](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/) — **Verified** — LLM judges, scorers, production monitoring. 4. [Large language model end-to-end evaluation](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-llm-evaluation-phase) — **Verified** — RAG-specific metrics (utilization, completeness, relevance). 5. [Azure AI Evaluation SDK Overview](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-evaluation-readme?view=azure-python) — **Verified** — Python SDK examples, evaluator initialization. 6. [Test and evaluate AI workloads on Azure](https://learn.microsoft.com/en-us/azure/well-architected/ai/test) — **Verified** — Quality metrics, testing vs. evaluation, baselining strategy. -7. [Observability in generative AI](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability) — **Verified** — Three-stage evaluation (base model selection, pre-production, production). -8. [Azure OpenAI Evaluation API](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/evaluations?view=foundry-classic) — **Verified** — REST API, testing criteria, grading process. -9. [GitHub Action for Evaluation](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluation-github-action?view=foundry-classic) — **Verified** — CI/CD integration. +7. [Observability in generative AI](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability) — **Verified** — Three-stage evaluation (base model selection, pre-production, production). +8. [Azure OpenAI Evaluation API](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/evaluations?view=foundry-classic) — **Verified** — REST API, testing criteria, grading process. +9. [GitHub Action for Evaluation](https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluation-github-action?view=foundry-classic) — **Verified** — CI/CD integration. 10. [Scorers and LLM judges (MLflow 3)](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/concepts/scorers) — **Verified** — Judge models, accuracy validation, partner-powered AI disclaimers. ### Confidence per seksjon diff --git a/skills/ms-ai-engineering/references/mlops-genaiops/model-versioning-registry-management.md b/skills/ms-ai-engineering/references/mlops-genaiops/model-versioning-registry-management.md index d2e91d4..7d3add3 100644 --- a/skills/ms-ai-engineering/references/mlops-genaiops/model-versioning-registry-management.md +++ b/skills/ms-ai-engineering/references/mlops-genaiops/model-versioning-registry-management.md @@ -541,7 +541,7 @@ az ml model list --registry-name my-registry --query "[?created<'$cutoff_date']. - Coverage: CI/CD integration, Azure Pipelines, MLOps automation 6. **Explore Microsoft Foundry Models** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/foundry-models-overview?view=foundry-classic + - URL: https://learn.microsoft.com/en-us/azure/foundry-classic/concepts/foundry-models-overview?view=foundry-classic - Confidence: **Verified** (MCP search results, Feb 2026) - Coverage: Model catalog, deployment options, Azure AI Foundry integration diff --git a/skills/ms-ai-engineering/references/mlops-genaiops/prompt-flow-production-deployment.md b/skills/ms-ai-engineering/references/mlops-genaiops/prompt-flow-production-deployment.md index c8fcb55..178d629 100644 --- a/skills/ms-ai-engineering/references/mlops-genaiops/prompt-flow-production-deployment.md +++ b/skills/ms-ai-engineering/references/mlops-genaiops/prompt-flow-production-deployment.md @@ -647,9 +647,9 @@ Er dette første gang kunden deployer LLM-basert app? ## Kilder og verifisering **Microsoft Learn Dokumentasjon:** -1. [Deploy a flow for real-time inference (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/flow-deploy?view=foundry-classic) – Offisiell guide for deployment via portal +1. [Deploy a flow for real-time inference (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/flow-deploy?view=foundry-classic) – Offisiell guide for deployment via portal 2. [GenAIOps with Prompt Flow and GitHub](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-end-to-end-llmops-with-prompt-flow?view=azureml-api-2) – CI/CD pipeline patterns og lifecycle management -3. [Enable tracing and collect feedback for a flow deployment](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/trace-production-sdk?view=foundry-classic) – Application Insights integration og metrics +3. [Enable tracing and collect feedback for a flow deployment](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/trace-production-sdk?view=foundry-classic) – Application Insights integration og metrics 4. [Deploy a flow to online endpoint with CLI/SDK](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-deploy-to-code?view=azureml-api-2) – Advanced deployment configuration (concurrency, FastAPI, etc.) 5. [Integrate Prompt Flow with DevOps](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-integrate-with-llm-app-devops?view=azureml-api-2) – Local-to-cloud development workflow diff --git a/skills/ms-ai-engineering/references/rag-architecture/citation-tracking.md b/skills/ms-ai-engineering/references/rag-architecture/citation-tracking.md index ff9d460..019b2db 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/citation-tracking.md +++ b/skills/ms-ai-engineering/references/rag-architecture/citation-tracking.md @@ -284,9 +284,9 @@ result = groundedness_eval( ### Verified (MCP-research) - [RAG overview in Azure AI Search](https://learn.microsoft.com/en-us/azure/search/retrieval-augmented-generation-overview) - [Agentic retrieval overview](https://learn.microsoft.com/en-us/azure/search/agentic-retrieval-overview) -- [Transparency note for Azure AI Search](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/search/transparency-note) +- [Transparency note for Azure AI Search](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/search/transparency-note) - [Grounding data design](https://learn.microsoft.com/en-us/azure/well-architected/ai/grounding-data-design) -- [Azure AI Foundry agents - AI Search tools](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/ai-search) +- [Azure AI Foundry agents - AI Search tools](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/ai-search) ### Baseline (modellkunnskap) - Norsk lovgivning (Forvaltningsloven, Offentleglova, Arkivloven) diff --git a/skills/ms-ai-engineering/references/rag-architecture/graphrag-knowledge-graphs.md b/skills/ms-ai-engineering/references/rag-architecture/graphrag-knowledge-graphs.md index d3af6c7..f8778ed 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/graphrag-knowledge-graphs.md +++ b/skills/ms-ai-engineering/references/rag-architecture/graphrag-knowledge-graphs.md @@ -280,7 +280,7 @@ GraphRAG introduserer spesifikke personvernrisiki i offentlig sektor: | CosmosAIGraph arkitektur | https://learn.microsoft.com/en-us/azure/cosmos-db/gen-ai/cosmos-ai-graph | ✅ Verified (2026-02) | | Graph semantics i KQL | https://learn.microsoft.com/en-us/kusto/query/graph-semantics-overview | ✅ Verified (2026-02) | | Entity Recognition skill (v3) | https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-entity-recognition-v3 | ✅ Verified (2026-02) | -| Azure AI Search transparency note | https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/search/transparency-note | ✅ Verified (2026-02) | +| Azure AI Search transparency note | https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/search/transparency-note | ✅ Verified (2026-02) | | RAG solution design guide | https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-solution-design-and-evaluation-guide | ✅ Verified (2026-02) | | Labeled Property Graphs (LPG) | https://learn.microsoft.com/en-us/fabric/graph/graph-data-models | ✅ Verified (2026-02) | diff --git a/skills/ms-ai-engineering/references/rag-architecture/late-chunking-patterns.md b/skills/ms-ai-engineering/references/rag-architecture/late-chunking-patterns.md index 8f0452a..0504a39 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/late-chunking-patterns.md +++ b/skills/ms-ai-engineering/references/rag-architecture/late-chunking-patterns.md @@ -244,5 +244,5 @@ for i, chunk in enumerate(chunks): | arXiv:2409.04701 (forskningspaper) | **Verified** | [arxiv.org](https://arxiv.org/abs/2409.04701) | | Jina Embeddings on Azure Marketplace | **Verified** | [azuremarketplace.microsoft.com](https://azuremarketplace.microsoft.com/en-us/marketplace/apps/jinaai.jina-embeddings-v4) | | Jina Embeddings v3 announcement | **Verified** | [jina.ai](https://jina.ai/news/jina-embeddings-v3-a-frontier-multilingual-embedding-model/) | -| Azure OpenAI Embeddings | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/tutorials/embeddings) | +| Azure OpenAI Embeddings | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/azure/foundry/openai/tutorials/embeddings) | | Late Chunking tutorial (DataCamp) | **Baseline** | [datacamp.com](https://www.datacamp.com/tutorial/late-chunking) | diff --git a/skills/ms-ai-engineering/references/rag-architecture/rag-context-windows.md b/skills/ms-ai-engineering/references/rag-architecture/rag-context-windows.md index 4d56c38..8d44c45 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/rag-context-windows.md +++ b/skills/ms-ai-engineering/references/rag-architecture/rag-context-windows.md @@ -388,7 +388,7 @@ Hvis du har 10,000 queries per måned: **11,300 NOK/måned** (kun LLM-kostnad, i ### Microsoft Learn (Verified via MCP) 1. **Azure OpenAI Assistants API — Context Window Management** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/assistants#context-window-management + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/assistants#context-window-management *Dekning: max_prompt_tokens, max_completion_tokens, truncation strategy, File Search recommendations* **Confidence: Verified** @@ -398,12 +398,12 @@ Hvis du har 10,000 queries per måned: **11,300 NOK/måned** (kun LLM-kostnad, i **Confidence: Verified** 3. **Azure OpenAI in Microsoft Foundry Models — Quotas and Limits** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quotas-limits + https://learn.microsoft.com/en-us/azure/foundry/openai/quotas-limits *Dekning: TPM limits per model, context window sizes, rate limits* **Confidence: Verified** 4. **Azure OpenAI On Your Data — Token Usage Estimation** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data *Dekning: Intent prompt vs. generation prompt token breakdown, RAG pipeline token costs* **Confidence: Verified** @@ -413,12 +413,12 @@ Hvis du har 10,000 queries per måned: **11,300 NOK/måned** (kun LLM-kostnad, i **Confidence: Verified** 6. **Chat Markup Language ChatML — Managing Conversations** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chat-markup-language#preventing-unsafe-user-inputs + https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/responses#preventing-unsafe-user-inputs *Dekning: Token counting med tiktoken, conversation history truncation* **Confidence: Verified** 7. **Code Sample: Token Counting with tiktoken (Python)** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chatgpt + https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/chatgpt *Dekning: Praktisk implementasjon av token management i conversation loops* **Confidence: Verified** diff --git a/skills/ms-ai-engineering/references/rag-architecture/rag-cost-optimization.md b/skills/ms-ai-engineering/references/rag-architecture/rag-cost-optimization.md index a544d04..2c9eb83 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/rag-cost-optimization.md +++ b/skills/ms-ai-engineering/references/rag-architecture/rag-cost-optimization.md @@ -501,15 +501,15 @@ Metrics: - [Vector compression best practices](https://techcommunity.microsoft.com/blog/azure-ai-services-blog/azure-ai-search-cut-vector-costs-up-to-92-5-with-new-compression-techniques/4404866) — *Verified: Compression techniques (92.5% reduction)* **Azure OpenAI Cost Management:** -- [Plan and manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs) — *Verified: Token-based billing, fine-tuning costs* -- [Azure OpenAI Batch API](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch) — *Verified: 50% cost reduction for batch workloads* -- [Fine-tuning cost management](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/fine-tuning-cost-management) — *Verified: Hosting + inference + training costs* +- [Plan and manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs) — *Verified: Token-based billing, fine-tuning costs* +- [Azure OpenAI Batch API](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch) — *Verified: 50% cost reduction for batch workloads* +- [Fine-tuning cost management](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/fine-tuning-cost-management) — *Verified: Hosting + inference + training costs* **RAG Architecture & Optimization:** - [RAG design and evaluation guide](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-solution-design-and-evaluation-guide) — *Verified: End-to-end RAG considerations* - [RAG chunking economics](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-chunking-phase#understand-chunking-economics) — *Verified: Chunking cost optimization* - [RAG embedding economics](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-generate-embeddings#understand-embedding-economics) — *Verified: Embedding model selection trade-offs* -- [Retrieval cost and latency considerations](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/retrieval-augmented-generation#cost-and-latency-considerations) — *Verified: Query cost analysis* +- [Retrieval cost and latency considerations](https://learn.microsoft.com/en-us/azure/foundry/concepts/retrieval-augmented-generation#cost-and-latency-considerations) — *Verified: Query cost analysis* **Cloud Adoption Framework:** - [Manage AI costs](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/manage#manage-ai-costs) — *Verified: Enterprise cost governance* diff --git a/skills/ms-ai-engineering/references/rag-architecture/rag-evaluation-frameworks.md b/skills/ms-ai-engineering/references/rag-architecture/rag-evaluation-frameworks.md index 5d066e8..b8e78c0 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/rag-evaluation-frameworks.md +++ b/skills/ms-ai-engineering/references/rag-architecture/rag-evaluation-frameworks.md @@ -311,11 +311,11 @@ Bruk `mlflow.log_feedback()` med `AssessmentSourceType.HUMAN` for å logge menne ## Kilder og verifisering ### Verified (MCP-research) -- [Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/evaluate-sdk) +- [Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/evaluate-sdk) - [RAG LLM Evaluation Phase](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-llm-evaluation-phase) - [RAG Solution Design Guide](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-solution-design-and-evaluation-guide) -- [Built-in RAG Evaluators](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/evaluation-evaluators/rag-evaluators) -- [Azure AI Foundry Observability](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability) +- [Built-in RAG Evaluators](https://learn.microsoft.com/en-us/azure/foundry/concepts/evaluation-evaluators/rag-evaluators) +- [Azure AI Foundry Observability](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability) - [RAG Experiment Accelerator](https://github.com/microsoft/rag-experiment-accelerator) ### Baseline (modellkunnskap) diff --git a/skills/ms-ai-engineering/references/rag-architecture/rag-hallucination-mitigation.md b/skills/ms-ai-engineering/references/rag-architecture/rag-hallucination-mitigation.md index 1830976..4900ffe 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/rag-hallucination-mitigation.md +++ b/skills/ms-ai-engineering/references/rag-architecture/rag-hallucination-mitigation.md @@ -385,9 +385,9 @@ Hvis AI-systemet gir feil informasjon som fører til skade: **Microsoft Learn (Verified via MCP):** - [Groundedness Detection Concepts](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/groundedness) — **Verified** - [Groundedness Detection Quickstart](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/quickstart-groundedness) — **Verified** -- [Groundedness Detection Filter](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-groundedness) — **Verified** -- [Prompt Engineering Techniques](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering) — **Verified** -- [Transparency Note: Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note) — **Verified** +- [Groundedness Detection Filter](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-groundedness) — **Verified** +- [Prompt Engineering Techniques](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering) — **Verified** +- [Transparency Note: Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note) — **Verified** - [RAG Solution Design Guide](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-solution-design-and-evaluation-guide) — **Verified** - [Secure Multitenant RAG](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/secure-multitenant-rag) — **Verified** diff --git a/skills/ms-ai-engineering/references/rag-architecture/rag-iterative-refinement.md b/skills/ms-ai-engineering/references/rag-architecture/rag-iterative-refinement.md index 8e18e04..e13b5dc 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/rag-iterative-refinement.md +++ b/skills/ms-ai-engineering/references/rag-architecture/rag-iterative-refinement.md @@ -418,7 +418,7 @@ public async Task ApplyRetentionPolicyAsync() | [Multi-turn conversations with an agent](https://learn.microsoft.com/en-us/agent-framework/tutorials/agents/multi-turn-conversation) | Agent Framework session management | **Verified** | | [Chat history (Semantic Kernel)](https://learn.microsoft.com/en-us/semantic-kernel/concepts/ai-services/chat-completion/chat-history) | ChatHistory API, reduction strategies | **Verified** | | [Using memory with Agents](https://learn.microsoft.com/en-us/semantic-kernel/frameworks/agent/agent-memory) | Whiteboard memory, memory providers | **Verified** | -| [Use the Azure OpenAI web app](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/use-web-app) | Cosmos DB chat history enablement | **Verified** | +| [Use the Azure OpenAI web app](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/use-web-app) | Cosmos DB chat history enablement | **Verified** | | [RAG with Azure DocumentDB](https://learn.microsoft.com/en-us/azure/documentdb/rag) | History-aware retrieval chains | **Verified** | | [Storing Chat History in 3rd Party Storage](https://learn.microsoft.com/en-us/agent-framework/tutorials/agents/third-party-chat-history-storage) | Custom ChatHistoryProvider | **Verified** | | [IChatClient documentation](https://learn.microsoft.com/en-us/dotnet/ai/ichatclient) | Stateless vs stateful clients | **Verified** | diff --git a/skills/ms-ai-engineering/references/rag-architecture/rag-security-rbac.md b/skills/ms-ai-engineering/references/rag-architecture/rag-security-rbac.md index 20347dc..64900a8 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/rag-security-rbac.md +++ b/skills/ms-ai-engineering/references/rag-architecture/rag-security-rbac.md @@ -473,7 +473,7 @@ Authorization: Bearer - Dekning: Hierarchical permissions, POSIX-like ACLs, indexer configuration 5. **Azure OpenAI On Your Data - Document-level access control** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/on-your-data-configuration#document-level-access-control + - URL: https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/on-your-data-configuration#document-level-access-control - Confidence: **Verified** (MCP-search 2026-02) - Dekning: RAG integration, filter parameter, group_ids field mapping @@ -493,7 +493,7 @@ Authorization: Bearer - Dekning: RAG challenges, security & governance 9. **Retrieval augmented generation (RAG) and indexes (AI Foundry)** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/retrieval-augmented-generation?view=foundry-classic + - URL: https://learn.microsoft.com/en-us/azure/foundry/concepts/retrieval-augmented-generation?view=foundry-classic - Confidence: **Verified** (MCP-search 2026-02) - Dekning: Security considerations, access control at retrieval time diff --git a/skills/ms-ai-engineering/references/rag-architecture/self-reflective-rag.md b/skills/ms-ai-engineering/references/rag-architecture/self-reflective-rag.md index 13b6642..4b8bbd2 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/self-reflective-rag.md +++ b/skills/ms-ai-engineering/references/rag-architecture/self-reflective-rag.md @@ -265,7 +265,7 @@ Hvis self-reflective RAG reduserer feilaktige svar fra 15% til 5%: | Kilde | Konfidens | URL | |-------|-----------|-----| -| RAG Evaluators (Azure AI Foundry) | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/evaluation-evaluators/rag-evaluators) | +| RAG Evaluators (Azure AI Foundry) | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/azure/foundry/concepts/evaluation-evaluators/rag-evaluators) | | RAG LLM Evaluation Phase | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-llm-evaluation-phase) | | Semantic Kernel Agent RAG | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/semantic-kernel/frameworks/agent/agent-rag) | | Corrective RAG (CRAG) paper | **Verified** | [arxiv.org](https://arxiv.org/abs/2401.15884) | diff --git a/skills/ms-ai-engineering/references/rag-architecture/streaming-rag-responses.md b/skills/ms-ai-engineering/references/rag-architecture/streaming-rag-responses.md index 6c58b4b..1d4c2b2 100644 --- a/skills/ms-ai-engineering/references/rag-architecture/streaming-rag-responses.md +++ b/skills/ms-ai-engineering/references/rag-architecture/streaming-rag-responses.md @@ -407,11 +407,11 @@ Ved bruk av streaming med `code_interpreter` tool: ### Verified (fra MCP microsoft-learn) -- Azure OpenAI Responses API streaming: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/responses (Verified: 2026-02) +- Azure OpenAI Responses API streaming: https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/responses (Verified: 2026-02) - Semantic Kernel Agent streaming: https://learn.microsoft.com/en-us/semantic-kernel/frameworks/agent/agent-streaming (Verified: 2026-02) - SSE med Application Gateway: https://learn.microsoft.com/en-us/azure/application-gateway/use-server-sent-events (Verified: 2026-02) -- Azure OpenAI REST API reference: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/reference (Verified: 2026-02) -- Chat Completions API streaming: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/reference#chat-completions (Verified: 2026-02) +- Azure OpenAI REST API reference: https://learn.microsoft.com/en-us/azure/foundry/openai/reference (Verified: 2026-02) +- Chat Completions API streaming: https://learn.microsoft.com/en-us/azure/foundry/openai/reference#chat-completions (Verified: 2026-02) ### Baseline (modellkunnskap) diff --git a/skills/ms-ai-governance/references/monitoring-observability/compliance-monitoring-ai-governance.md b/skills/ms-ai-governance/references/monitoring-observability/compliance-monitoring-ai-governance.md index 441bef3..432a942 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/compliance-monitoring-ai-governance.md +++ b/skills/ms-ai-governance/references/monitoring-observability/compliance-monitoring-ai-governance.md @@ -478,13 +478,13 @@ AppMetrics **Azure Policy & monitoring:** - [Azure Policy Regulatory Compliance controls for Azure AI Search](https://learn.microsoft.com/en-us/azure/search/security-controls-policy) — Verified 2026-02 -- [Control AI model deployment with built-in policies in Microsoft Foundry portal](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/built-in-policy-model-deployment) — Verified 2026-02 +- [Control AI model deployment with built-in policies in Microsoft Foundry portal](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/built-in-policy-model-deployment) — Verified 2026-02 - [AI gateway in Azure API Management (Observability and governance)](https://learn.microsoft.com/en-us/azure/api-management/genai-gateway-capabilities#observability-and-governance) — Verified 2026-02 **Security & observability:** - [Assess your organization's AI risk with Microsoft Security Dashboard for AI (Preview)](https://learn.microsoft.com/en-us/security/security-for-ai/security-dashboard-for-ai) — Verified 2026-02 - [Governance and security for AI agents across the organization](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/ai-agents/governance-security-across-organization) — Verified 2026-02 -- [Monitor Azure OpenAI (Dashboards)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — Verified 2026-02 +- [Monitor Azure OpenAI (Dashboards)](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) — Verified 2026-02 ### Konfidensnivå per seksjon diff --git a/skills/ms-ai-governance/references/monitoring-observability/cost-monitoring-cost-attribution.md b/skills/ms-ai-governance/references/monitoring-observability/cost-monitoring-cost-attribution.md index cbfe49a..4181e0a 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/cost-monitoring-cost-attribution.md +++ b/skills/ms-ai-governance/references/monitoring-observability/cost-monitoring-cost-attribution.md @@ -439,7 +439,7 @@ if ($metrics.Data.Total -eq 0) { ### Kilder (Microsoft Learn) 1. **Plan to manage costs for Azure OpenAI** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs + https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs *Konfidensgrad: Verified* – Komplett guide for cost management (budgets, alerts, export) 2. **Azure OpenAI in Foundry Models gateway monitoring** *(Verified MCP 2026-04)* @@ -455,7 +455,7 @@ if ($metrics.Data.Total -eq 0) { *Konfidensgrad: Verified* – Best practices for TPM/RPM monitoring, commitment billing 5. **Plan and manage costs for Azure AI Foundry** - https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/manage-costs + https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs *Konfidensgrad: Verified* – Marketplace models, fine-tuning costs, HTTP error billing 6. **Azure Cost Management API (Python SDK)** diff --git a/skills/ms-ai-governance/references/monitoring-observability/custom-dashboards-ai-operations.md b/skills/ms-ai-governance/references/monitoring-observability/custom-dashboards-ai-operations.md index 18dfed9..7852173 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/custom-dashboards-ai-operations.md +++ b/skills/ms-ai-governance/references/monitoring-observability/custom-dashboards-ai-operations.md @@ -483,7 +483,7 @@ Når kunden spør om dashboards for AI operations: ### Microsoft Learn - [Azure Workbooks overview](https://learn.microsoft.com/en-us/azure/azure-monitor/visualize/workbooks-overview) - [Create an Azure AI Foundry dashboard](https://learn.microsoft.com/en-us/azure/managed-grafana/azure-ai-foundry-dashboard) -- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) +- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) - [Workbooks programmatic management](https://learn.microsoft.com/en-us/azure/azure-monitor/visualize/workbooks-automate) *(Verified MCP 2026-04)* — ARM/Bicep deployment, RBAC (Monitoring Contributor for redigering, Monitoring Reader for visning), `microsoft.insights/workbooks/write` for custom roles - [Power BI + Azure Monitor](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/log-powerbi) diff --git a/skills/ms-ai-governance/references/monitoring-observability/endpoint-health-and-capacity-planning.md b/skills/ms-ai-governance/references/monitoring-observability/endpoint-health-and-capacity-planning.md index 0dcb690..87fa8aa 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/endpoint-health-and-capacity-planning.md +++ b/skills/ms-ai-governance/references/monitoring-observability/endpoint-health-and-capacity-planning.md @@ -587,19 +587,19 @@ az role assignment create \ ### Microsoft Learn (Verified via MCP) 1. **Monitor Azure OpenAI:** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai *Confidence: Verified* — Komplett guide til diagnostics, metrics, alerts, og KQL-queries 2. **Manage Azure OpenAI quota:** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/quota + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/quota *Confidence: Verified* — TPM/RPM-allokering, quota requests, 429-feilhåndtering 3. **Azure OpenAI quotas and limits:** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quotas-limits + https://learn.microsoft.com/en-us/azure/foundry/openai/quotas-limits *Confidence: Verified* — Rate limits per modell, Usage tiers, regional constraints 4. **Dynamic quota (Preview):** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/dynamic-quota + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/dynamic-quota *Confidence: Verified* — Opportunistic burst-kapasitet for Standard deployments 5. **Supported metrics for Microsoft.CognitiveServices/accounts:** diff --git a/skills/ms-ai-governance/references/monitoring-observability/log-analytics-kql-ai-queries.md b/skills/ms-ai-governance/references/monitoring-observability/log-analytics-kql-ai-queries.md index 1ae108c..80503b0 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/log-analytics-kql-ai-queries.md +++ b/skills/ms-ai-governance/references/monitoring-observability/log-analytics-kql-ai-queries.md @@ -723,7 +723,7 @@ AzureDiagnostics - **KQL Quick Reference:** [learn.microsoft.com/kusto/query/kql-quick-reference](https://learn.microsoft.com/en-us/kusto/query/kql-quick-reference) - **Azure Monitor KQL Samples:** [learn.microsoft.com/azure/azure-monitor/logs/queries](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/queries) -- **Azure OpenAI Monitoring:** [learn.microsoft.com/azure/ai-foundry/openai/how-to/monitor-openai](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) +- **Azure OpenAI Monitoring:** [learn.microsoft.com/azure/foundry-classic/openai/how-to/monitor-openai](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) - **Optimize Log Queries:** [learn.microsoft.com/azure/azure-monitor/logs/query-optimization](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/query-optimization) ## Nøkkelinnsikter @@ -743,7 +743,7 @@ AzureDiagnostics ## Referanser -- Microsoft Learn: [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) +- Microsoft Learn: [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) - Microsoft Learn: [Get started with log queries in Azure Monitor](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/get-started-queries) - Microsoft Learn: [Optimize log queries in Azure Monitor](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/query-optimization) *(Verified MCP 2026-04)* - Microsoft Learn: [Configure diagnostic logging for Azure AI Search](https://learn.microsoft.com/en-us/azure/search/search-monitor-enable-logging) diff --git a/skills/ms-ai-governance/references/monitoring-observability/model-performance-drift-detection.md b/skills/ms-ai-governance/references/monitoring-observability/model-performance-drift-detection.md index 0b9684e..f2ae3de 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/model-performance-drift-detection.md +++ b/skills/ms-ai-governance/references/monitoring-observability/model-performance-drift-detection.md @@ -377,8 +377,8 @@ Model monitoring er inkludert i Azure Machine Learning workspace, men du betaler - [Azure Machine Learning model monitoring (concept)](https://learn.microsoft.com/en-us/azure/machine-learning/concept-model-monitoring?view=azureml-api-2) — **Verified** (fetched 2026-02) - [Monitor performance of models deployed to production](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-model-performance?view=azureml-api-2) — **Verified** (fetched 2026-02) - [Data drift monitoring (legacy, retiring)](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-datasets?view=azureml-api-1) — **Verified** (fetched 2026-02, kontext: migrering til Model Monitor) -- [Evaluate generative AI models (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — **Verified** (fetched 2026-02) -- [Observability in generative AI (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability?view=foundry-classic) — **Verified** (fetched 2026-02) +- [Evaluate generative AI models (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — **Verified** (fetched 2026-02) +- [Observability in generative AI (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability?view=foundry-classic) — **Verified** (fetched 2026-02) - [Test and evaluate AI workloads on Azure](https://learn.microsoft.com/en-us/azure/well-architected/ai/test) — **Verified** (fetched 2026-02) ### Baseline (Model knowledge) diff --git a/skills/ms-ai-governance/references/monitoring-observability/real-time-streaming-monitoring.md b/skills/ms-ai-governance/references/monitoring-observability/real-time-streaming-monitoring.md index 0191a8e..ddabf53 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/real-time-streaming-monitoring.md +++ b/skills/ms-ai-governance/references/monitoring-observability/real-time-streaming-monitoring.md @@ -525,7 +525,7 @@ Real-Time Dashboard er IKKE erstatning for data warehouse. Bruk for operational **Confidence:** Verified (Feb 2026) - Real-time architecture patterns 7. **Observability in generative AI** - https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability + https://learn.microsoft.com/en-us/azure/foundry/concepts/observability **Confidence:** Verified (Feb 2026) - AI Foundry monitoring integration 8. **Implement advanced monitoring for Azure OpenAI in Foundry Models through a gateway** diff --git a/skills/ms-ai-governance/references/monitoring-observability/response-quality-metrics-rag.md b/skills/ms-ai-governance/references/monitoring-observability/response-quality-metrics-rag.md index 88494a0..34e426f 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/response-quality-metrics-rag.md +++ b/skills/ms-ai-governance/references/monitoring-observability/response-quality-metrics-rag.md @@ -591,14 +591,14 @@ PTU equivalent: ~300 PTUs @ $6/PTU = $1800/måned ### Microsoft Learn (Verified via MCP) -1. [Observability in generative AI - What are evaluators?](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability#what-are-evaluators) — RAG evaluators (Retrieval, Groundedness, Relevance, Response Completeness) -2. [Retrieval-Augmented Generation (RAG) evaluators](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/evaluation-evaluators/rag-evaluators) — Detaljert dokumentasjon for alle RAG-evaluatorer, input/output formats +1. [Observability in generative AI - What are evaluators?](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability#what-are-evaluators) — RAG evaluators (Retrieval, Groundedness, Relevance, Response Completeness) +2. [Retrieval-Augmented Generation (RAG) evaluators](https://learn.microsoft.com/en-us/azure/foundry/concepts/evaluation-evaluators/rag-evaluators) — Detaljert dokumentasjon for alle RAG-evaluatorer, input/output formats 3. [Large language model end-to-end evaluation](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-llm-evaluation-phase) — Groundedness, completeness, utilization, relevance, correctness metrics -4. [Evaluate generative AI models and applications](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluate-generative-ai-app) — Foundry portal evaluation workflow, testing criteria configuration -5. [Submit a batch run and evaluate a flow](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/flow-bulk-test-evaluation) — Built-in evaluation methods (QnA Groundedness, Relevance, Coherence) +4. [Evaluate generative AI models and applications](https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluate-generative-ai-app) — Foundry portal evaluation workflow, testing criteria configuration +5. [Submit a batch run and evaluate a flow](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/flow-bulk-test-evaluation) — Built-in evaluation methods (QnA Groundedness, Relevance, Coherence) 6. [Evaluation of RAG performance basics](https://learn.microsoft.com/en-us/fabric/data-science/tutorial-evaluate-rag-performance) — AI-assisted metrics (groundedness, relevance, similarity), top-N retrieval rate -7. [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — Azure Monitor integration, KQL queries, diagnostic settings -8. [Use Risks & Safety monitoring](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/risks-safety-monitor) — Content filtering metrics, severity distribution +7. [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) — Azure Monitor integration, KQL queries, diagnostic settings +8. [Use Risks & Safety monitoring](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/risks-safety-monitor) — Content filtering metrics, severity distribution 9. [Azure AI Evaluation SDK - Python samples](https://github.com/Azure-Samples/azureai-samples/blob/main/scenarios/evaluate/) — Code examples for groundedness, relevance evaluators ### Code samples (Verified via MCP) diff --git a/skills/ms-ai-governance/references/monitoring-observability/security-and-audit-logging-ai.md b/skills/ms-ai-governance/references/monitoring-observability/security-and-audit-logging-ai.md index 9ce8892..0299d3b 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/security-and-audit-logging-ai.md +++ b/skills/ms-ai-governance/references/monitoring-observability/security-and-audit-logging-ai.md @@ -385,8 +385,8 @@ Ingen ekstra lisenser kreves for audit logging — funksjonen er inkludert i Azu | Kilde | URL | Konfidensnivå | |-------|-----|---------------| | **Enable diagnostic logging for Azure AI services** | https://learn.microsoft.com/en-us/azure/ai-services/diagnostic-logging | ✅ Verified | -| **Monitor Azure OpenAI** | https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai | ✅ Verified | -| **Azure security baseline for Azure OpenAI** | https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/azure-openai-security-baseline | ✅ Verified — **OBS:** Basert på MCSB v1.0 (kan inneholde utdatert veiledning). Produktet refereres nå som "Foundry Tools" i baseline-dokumentet. Siste veiledning: [Azure OpenAI docs](https://learn.microsoft.com/en-us/azure/ai-foundry/). *(Verified MCP 2026-04)* | +| **Monitor Azure OpenAI** | https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai | ✅ Verified | +| **Azure security baseline for Azure OpenAI** | https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/azure-openai-security-baseline | ✅ Verified — **OBS:** Basert på MCSB v1.0 (kan inneholde utdatert veiledning). Produktet refereres nå som "Foundry Tools" i baseline-dokumentet. Siste veiledning: [Azure OpenAI docs](https://learn.microsoft.com/en-us/azure/foundry/). *(Verified MCP 2026-04)* | | **Azure security baseline for Microsoft Foundry** | https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/azure-ai-foundry-security-baseline | ✅ Verified — **OBS:** Tjenesten er omdøpt til "Microsoft Foundry" i baseline-dokumentet. Basert på MCSB v1.0. Viktige avvik: Customer Lockbox **ikke støttet** for Foundry, lokal autentisering til data plane **ikke støttet** (positivt for sikkerhet), DLP/sensitive data discovery **ikke støttet** nativt. *(Verified MCP 2026-04)* | | **Microsoft cloud security benchmark: Logging and threat detection** | https://learn.microsoft.com/en-us/security/benchmark/azure/mcsb-logging-threat-detection | ✅ Verified | | **Artificial Intelligence Security (AI-6: Establish monitoring and detection)** | https://learn.microsoft.com/en-us/security/benchmark/azure/mcsb-v2-artificial-intelligence-security | ✅ Verified | diff --git a/skills/ms-ai-governance/references/monitoring-observability/sla-monitoring-ai-services.md b/skills/ms-ai-governance/references/monitoring-observability/sla-monitoring-ai-services.md index e2aad22..93fb512 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/sla-monitoring-ai-services.md +++ b/skills/ms-ai-governance/references/monitoring-observability/sla-monitoring-ai-services.md @@ -351,11 +351,11 @@ Metric Alert ### Microsoft Learn (Verified via MCP) 1. **Monitor Azure OpenAI** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai *Confidence: Verified* — Detaljert guide til Azure Monitor-integrasjon for OpenAI. 2. **Azure OpenAI monitoring data reference** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/monitor-openai-reference + https://learn.microsoft.com/en-us/azure/foundry/openai/monitor-openai-reference *Confidence: Verified* — Fullstendig liste over metrics (inkl. `ModelAvailabilityRate`). 3. **Monitoring and diagnostics guidance** @@ -363,7 +363,7 @@ Metric Alert *Confidence: Verified* — SLA monitoring best practices (generell Azure-arkitektur). Dekker: tilgjengelighetssporing, ytelsesovervåkning, SLA-etterlevelse, sikkerhet/personvern, regulatorisk audit, trend-deteksjon. Brukes i AI-kontekst for å sikre end-to-end synlighet i distribuerte AI-systemer. *(Verified MCP 2026-04)* 4. **Azure OpenAI FAQ - SLA** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/faq#what-are-the-slas-service-level-agreements-in-azure-openai + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/faq#what-are-the-slas-service-level-agreements-in-azure-openai *Confidence: Verified* — Bekreftelse av 99.9% Availability SLA + Latency SLA for PTU. 5. **Supported metrics for Microsoft.CognitiveServices/accounts** diff --git a/skills/ms-ai-governance/references/monitoring-observability/token-usage-tracking-attribution.md b/skills/ms-ai-governance/references/monitoring-observability/token-usage-tracking-attribution.md index 2cd697a..af57e46 100644 --- a/skills/ms-ai-governance/references/monitoring-observability/token-usage-tracking-attribution.md +++ b/skills/ms-ai-governance/references/monitoring-observability/token-usage-tracking-attribution.md @@ -568,11 +568,11 @@ Owner: ## Kilder (Microsoft Learn) -1. [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — Official monitoring guide +1. [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) — Official monitoring guide 2. [Implement advanced monitoring for Azure OpenAI in Foundry Models through a gateway](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-monitoring) *(Verified MCP 2026-04)* — Gateway patterns for usage tracking. Ny brukscase dokumentert: audit av model inputs/outputs for threat detection og data exfiltration detection. Merk: gateway monitoring kan bli single point of failure — vurder redundans. -3. [Plan to manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs) — Cost management strategies -4. [Token usage estimation for Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data) — RAG-specific token calculations -5. [Understanding costs associated with PTU](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding) — PTU billing model +3. [Plan to manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs) — Cost management strategies +4. [Token usage estimation for Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data) — RAG-specific token calculations +5. [Understanding costs associated with PTU](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput-billing) — PTU billing model 6. [Application design for AI workloads](https://learn.microsoft.com/en-us/azure/well-architected/ai/application-design#consider-nonfunctional-requirements) — Cost and chargeback scenarios 7. [Architecture strategies for cost data](https://learn.microsoft.com/en-us/azure/well-architected/cost-optimization/collect-review-cost-data#generate-cost-reports) — Chargeback vs. showback diff --git a/skills/ms-ai-governance/references/norwegian-public-sector-governance/copyright-ai-training-data-norway.md b/skills/ms-ai-governance/references/norwegian-public-sector-governance/copyright-ai-training-data-norway.md index ed2701a..cd7a2e7 100644 --- a/skills/ms-ai-governance/references/norwegian-public-sector-governance/copyright-ai-training-data-norway.md +++ b/skills/ms-ai-governance/references/norwegian-public-sector-governance/copyright-ai-training-data-norway.md @@ -142,7 +142,7 @@ Kunden må ha implementert alle mitigations (tiltak) som kreves i Azure OpenAI-d For å opprettholde CCC-dekning må kunder implementere følgende universelle mitigations: **1. Metaprompt (effektiv fra 1. desember 2023):** -Kundens løsning må inkludere en metaprompt som instruerer modellen til å forhindre opphavsrettsbrudd i output. Eksempel på anbefalt metaprompt finnes i Microsoft Learn: "To Avoid Copyright Infringements" i [System message framework and template recommendations for Large Language Models (LLMs)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message). +Kundens løsning må inkludere en metaprompt som instruerer modellen til å forhindre opphavsrettsbrudd i output. Eksempel på anbefalt metaprompt finnes i Microsoft Learn: "To Avoid Copyright Infringements" i [System message framework and template recommendations for Large Language Models (LLMs)](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message). **2. Testing and Evaluation Report (effektiv fra 1. desember 2023):** Kundens løsning må ha vært gjenstand for evalueringer (f.eks. guided red teaming, systematisk måling, eller annen ekvivalent tilnærming) ved hjelp av tester designet for å oppdage output av tredjepartsinnhold. Betydelig løpende reproduksjon av tredjepartsinnhold oppdaget gjennom evaluering må adresseres. Rapporten over resultater og tiltak må oppbevares av kunden og gjøres tilgjengelig for Microsoft i tilfelle krav. @@ -243,11 +243,11 @@ Når du veileder norsk offentlig sektor om AI og opphavsrett, vurder disse spør - [Commission launches consultation on protocols for reserving rights from text and data mining under the AI Act and the GPAI Code of Practice](https://digital-strategy.ec.europa.eu/en/consultations/commission-launches-consultation-protocols-reserving-rights-text-and-data-mining-under-ai-act-and) ### Microsoft Learn-kilder -- [Customer Copyright Commitment Required Mitigations | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/customer-copyright-commitment?view=foundry-classic) -- [Data, privacy, and security for Azure Direct Models in Microsoft Foundry | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/data-privacy?view=foundry-classic) -- [Transparency note for Azure OpenAI | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note?view=foundry-classic) -- [Azure OpenAI frequently asked questions | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/faq?view=foundry-classic) -- [System message framework and template recommendations for LLMs | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message) +- [Customer Copyright Commitment Required Mitigations | Microsoft Learn](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/customer-copyright-commitment?view=foundry-classic) +- [Data, privacy, and security for Azure Direct Models in Microsoft Foundry | Microsoft Learn](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/data-privacy?view=foundry-classic) +- [Transparency note for Azure OpenAI | Microsoft Learn](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note?view=foundry-classic) +- [Azure OpenAI frequently asked questions | Microsoft Learn](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/faq?view=foundry-classic) +- [System message framework and template recommendations for LLMs | Microsoft Learn](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message) --- diff --git a/skills/ms-ai-governance/references/responsible-ai/ai-impact-assessment-framework.md b/skills/ms-ai-governance/references/responsible-ai/ai-impact-assessment-framework.md index f85ac0d..a59b10c 100644 --- a/skills/ms-ai-governance/references/responsible-ai/ai-impact-assessment-framework.md +++ b/skills/ms-ai-governance/references/responsible-ai/ai-impact-assessment-framework.md @@ -616,7 +616,7 @@ Purview SDK-integrasjon gir: - Status: Azure ML GA feature 6. **Azure AI Foundry Evaluation** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluation-github-action + - URL: https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluation-github-action - Status: Azure AI Foundry GA 7. **Microsoft Purview AI Risk Management** diff --git a/skills/ms-ai-governance/references/responsible-ai/ai-risk-taxonomy-classification.md b/skills/ms-ai-governance/references/responsible-ai/ai-risk-taxonomy-classification.md index e35c7d0..7b2feb5 100644 --- a/skills/ms-ai-governance/references/responsible-ai/ai-risk-taxonomy-classification.md +++ b/skills/ms-ai-governance/references/responsible-ai/ai-risk-taxonomy-classification.md @@ -420,7 +420,7 @@ Anbefal denne kombinasjonen: - Innhold: Cross-product risk monitoring, AI inventory 5. **Default Guidelines & controls policies (Azure AI Foundry)** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/default-safety-policies + - URL: https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/default-safety-policies - Hentet: 2026-02-04 - Innhold: Content filtering categories, severity levels, default thresholds diff --git a/skills/ms-ai-governance/references/responsible-ai/algorithmic-accountability-auditability.md b/skills/ms-ai-governance/references/responsible-ai/algorithmic-accountability-auditability.md index f60d853..7531ada 100644 --- a/skills/ms-ai-governance/references/responsible-ai/algorithmic-accountability-auditability.md +++ b/skills/ms-ai-governance/references/responsible-ai/algorithmic-accountability-auditability.md @@ -516,7 +516,7 @@ registered_model = ml_client.models.create_or_update(model) (Assign unique identities, maintain agent inventory, centralize logging, track and allocate costs) 5. **Trace and observe AI agents in Microsoft Foundry** - https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/trace-agents-sdk?view=foundry-classic + https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/trace-agents-sdk?view=foundry-classic (OpenTelemetry tracing, Application Insights integration, Azure Monitor exporter) 6. **Microsoft Purview data security and compliance protections for generative AI apps** diff --git a/skills/ms-ai-governance/references/responsible-ai/bias-detection-mitigation-strategies.md b/skills/ms-ai-governance/references/responsible-ai/bias-detection-mitigation-strategies.md index 6cc0b28..4faf0fe 100644 --- a/skills/ms-ai-governance/references/responsible-ai/bias-detection-mitigation-strategies.md +++ b/skills/ms-ai-governance/references/responsible-ai/bias-detection-mitigation-strategies.md @@ -937,7 +937,7 @@ Risikokategori (EU AI Act)? Verifisert: 2026-02-03 | Status: GA | Confidence: ✅ High 6. **Content filter severity levels** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-severity-levels + https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-severity-levels Verifisert: 2026-02-03 | Status: GA | Confidence: ✅ High 7. **Monitor fairness and bias (Databricks)** diff --git a/skills/ms-ai-governance/references/responsible-ai/content-safety-implementation.md b/skills/ms-ai-governance/references/responsible-ai/content-safety-implementation.md index c585aae..d2df0ba 100644 --- a/skills/ms-ai-governance/references/responsible-ai/content-safety-implementation.md +++ b/skills/ms-ai-governance/references/responsible-ai/content-safety-implementation.md @@ -280,7 +280,7 @@ Azure AI Content Safety har PII-detection for completions: | **Record-keeping** | Retain logs i 6+ år (Azure Log Analytics long-term retention) | **Transparency Note:** -Microsoft publiserer [Transparency Note for Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/content-safety/transparency-note) som dekker: +Microsoft publiserer [Transparency Note for Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/content-safety/transparency-note) som dekker: - System capabilities and limitations - Training data og known biases - Best practices for deployment @@ -464,22 +464,22 @@ Scenario: 1 million samtaler/måned, gjennomsnitt 2 meldinger per samtale = 2M t 1. [What is Azure AI Content Safety?](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/overview) *Confidence: High* — Oversikt over features, pricing tiers, region availability, service limits -2. [Content filtering overview (Azure OpenAI)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter) +2. [Content filtering overview (Azure OpenAI)](https://learn.microsoft.com/en-us/azure/foundry-classic/foundry-models/concepts/content-filter) *Confidence: High* — Filter categories, severity levels, scenario details for API response behavior 3. [Harm categories in Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/harm-categories) *Confidence: High* — Detaljert beskrivelse av severity levels 0-7 per kategori (hate, sexual, violence, self-harm) -4. [Data, privacy, and security for Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/content-safety/data-privacy) +4. [Data, privacy, and security for Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/content-safety/data-privacy) *Confidence: High* — Data residency, encryption at rest, customer controls, GDPR compliance statements 5. [Custom categories (preview)](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/custom-categories) *Confidence: Medium* — Preview feature, API-detaljer kan endre seg før GA -6. [Transparency note: Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/content-safety/transparency-note) +6. [Transparency note: Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/content-safety/transparency-note) *Confidence: High* — System capabilities, intended uses, limitations, best practices -7. [Default Guidelines & controls policies (Azure OpenAI)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/default-safety-policies) +7. [Default Guidelines & controls policies (Azure OpenAI)](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/default-safety-policies) *Confidence: High* — Default severity thresholds for text/image models, table of blocked categories 8. [Azure AI Content Safety Quickstart (C# code samples)](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/quickstart-text?pivots=programming-language-csharp) @@ -488,7 +488,7 @@ Scenario: 1 million samtaler/måned, gjennomsnitt 2 meldinger per samtale = 2M t 9. [Mitigate false results in Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/improve-performance) *Confidence: High* — Best practices for severity tuning, custom categories, blocklists -10. [Content Safety in the Microsoft Foundry portal](https://learn.microsoft.com/en-us/azure/ai-foundry/ai-services/content-safety-overview) +10. [Content Safety in the Microsoft Foundry portal](https://learn.microsoft.com/en-us/azure/foundry-classic/ai-services/content-safety-overview) *Confidence: High* — Beskrivelse av Content Safety Studio features, Try it out workflow **Baseline (modellkunnskap, ikke verifisert mot ferske kilder):** diff --git a/skills/ms-ai-governance/references/responsible-ai/continuous-improvement-feedback-loops.md b/skills/ms-ai-governance/references/responsible-ai/continuous-improvement-feedback-loops.md index b444666..c185e1d 100644 --- a/skills/ms-ai-governance/references/responsible-ai/continuous-improvement-feedback-loops.md +++ b/skills/ms-ai-governance/references/responsible-ai/continuous-improvement-feedback-loops.md @@ -48,7 +48,7 @@ Microsoft implementerer feedback loops gjennom hele AI-livssyklusen – fra utvi - Error logs og exception traces - User feedback (thumbs up/down, ratings) -**Confidence:** Verified – [MLflow Tracing](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/), [Azure Monitor](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability) +**Confidence:** Verified – [MLflow Tracing](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/), [Azure Monitor](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability) ### 2. Automated Quality Monitoring @@ -69,7 +69,7 @@ Microsoft bruker automated scorers (LLM judges) for kontinuerlig kvalitetsvurder - Automated alerts ved threshold violations - Integration med Azure AI Foundry evaluation tools -**Confidence:** Verified – [Generation Quality Monitoring](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/monitor-quality-safety?view=foundry-classic) +**Confidence:** Verified – [Generation Quality Monitoring](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/monitor-quality-safety?view=foundry-classic) ### 3. Human Feedback Integration @@ -258,7 +258,7 @@ model_monitor = MonitorSchedule( ) ``` -**Confidence:** Verified – [Azure AI Foundry Monitoring](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/monitor-quality-safety?view=foundry-classic) +**Confidence:** Verified – [Azure AI Foundry Monitoring](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/monitor-quality-safety?view=foundry-classic) ### MLflow on Azure Databricks @@ -531,7 +531,7 @@ Models, prompts, eval datasets, scorers – full reproducibility er non-negotiab - Key content: 10-step feedback loop, human-aligned metrics, production monitoring 2. **Azure AI Foundry Production Monitoring** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/monitor-quality-safety?view=foundry-classic + - URL: https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/monitor-quality-safety?view=foundry-classic - Key content: Continuous evaluation, scorers, threshold configuration 3. **AI Builder Feedback Loop** @@ -571,7 +571,7 @@ Models, prompts, eval datasets, scorers – full reproducibility er non-negotiab - Key content: Feedback mechanisms, bias monitoring, iterative updates 12. **Azure AI Foundry Observability Concepts** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability + - URL: https://learn.microsoft.com/en-us/azure/foundry/concepts/observability - Key content: Tracing, monitoring features, model performance tracking **Code samples (Verified):** diff --git a/skills/ms-ai-governance/references/responsible-ai/gdpr-compliance-ai-systems.md b/skills/ms-ai-governance/references/responsible-ai/gdpr-compliance-ai-systems.md index b2c8154..5c1b1ea 100644 --- a/skills/ms-ai-governance/references/responsible-ai/gdpr-compliance-ai-systems.md +++ b/skills/ms-ai-governance/references/responsible-ai/gdpr-compliance-ai-systems.md @@ -537,7 +537,7 @@ Norge implementerer GDPR gjennom personopplysningsloven. Datatilsynet er tilsyns *How to handle access, rectify, erase, restrict, portability, object requests* 6. **Data, privacy, and security for Azure OpenAI** - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/data-privacy + https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/data-privacy *No training on customer data, no sharing with OpenAI, encryption, CMK support* 7. **Manage personal data in Azure Monitor Logs** diff --git a/skills/ms-ai-governance/references/responsible-ai/human-in-the-loop-oversight.md b/skills/ms-ai-governance/references/responsible-ai/human-in-the-loop-oversight.md index c95f882..f3dc0c2 100644 --- a/skills/ms-ai-governance/references/responsible-ai/human-in-the-loop-oversight.md +++ b/skills/ms-ai-governance/references/responsible-ai/human-in-the-loop-oversight.md @@ -790,7 +790,7 @@ For offentlig sektor i Norge: 3. [Power Automate - Multistage and AI approvals](https://learn.microsoft.com/en-us/microsoft-copilot-studio/flows-advanced-approvals) — Power Platform approvals 4. [FAQ for AI Approvals](https://learn.microsoft.com/en-us/microsoft-copilot-studio/faqs-ai-approvals) — Best practices og limitations 5. [Copilot Studio - Topic escalation analysis](https://learn.microsoft.com/en-us/microsoft-copilot-studio/guidance/deflection-topic-escalation-analysis) — Escalation patterns -6. [Azure AI Agent Service - Transparency Note](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/agents/transparency-note) — Real-time oversight guidance +6. [Azure AI Agent Service - Transparency Note](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/agents/transparency-note) — Real-time oversight guidance 7. [Durable Agent Features - HITL workflows](https://learn.microsoft.com/en-us/agent-framework/user-guide/agents/agent-types/durable-agent/features) — Durable Functions patterns 8. [Responsible AI in Azure workloads](https://learn.microsoft.com/en-us/azure/well-architected/ai/responsible-ai) — Escape hatches og human-in-the-loop checkpoints 9. [Catalog Enrichment Agent - Responsible AI FAQ](https://learn.microsoft.com/en-us/industry/retail/catalog-enrichment-agent/faqs-catalog-enrichment-agent) — Human-in-the-loop implementation example diff --git a/skills/ms-ai-governance/references/responsible-ai/model-explainability-interpretability.md b/skills/ms-ai-governance/references/responsible-ai/model-explainability-interpretability.md index 058f395..8b2c631 100644 --- a/skills/ms-ai-governance/references/responsible-ai/model-explainability-interpretability.md +++ b/skills/ms-ai-governance/references/responsible-ai/model-explainability-interpretability.md @@ -530,7 +530,7 @@ SLUTT: Dokumenter valg i ADR, implementer, valider med stakeholders *Confidence: Verified* - Alternative XAI-teknikk for .NET-utviklere 7. **Azure OpenAI Transparency Note - Limitations** - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note?view=foundry-classic#limitations + https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note?view=foundry-classic#limitations *Confidence: Verified* - Begrensninger i explainability for fine-tuned og reasoning models ### Ekstern dokumentasjon (Baseline knowledge) diff --git a/skills/ms-ai-governance/references/responsible-ai/red-teaming-ai-models.md b/skills/ms-ai-governance/references/responsible-ai/red-teaming-ai-models.md index 6ee1d90..61d3319 100644 --- a/skills/ms-ai-governance/references/responsible-ai/red-teaming-ai-models.md +++ b/skills/ms-ai-governance/references/responsible-ai/red-teaming-ai-models.md @@ -247,7 +247,7 @@ steps: - Azure tool calls (✅ supported) - Function tool calls (❌ not supported) -**Comprehensive tools list:** [Azure AI Foundry Tools](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/overview) +**Comprehensive tools list:** [Azure AI Foundry Tools](https://learn.microsoft.com/en-us/azure/foundry-classic/agents/how-to/tools-classic/overview) ### Azure OpenAI Service @@ -492,10 +492,10 @@ jobs: | Kilde | URL | Verifikasjonsdato | |-------|-----|-------------------| -| **AI Red Teaming Agent (preview)** | https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/ai-red-teaming-agent | 2026-02-03 | +| **AI Red Teaming Agent (preview)** | https://learn.microsoft.com/en-us/azure/foundry/concepts/ai-red-teaming-agent | 2026-02-03 | | **Microsoft Security Benchmark: AI-7 Continuous Red Teaming** | https://learn.microsoft.com/en-us/security/benchmark/azure/mcsb-v2-artificial-intelligence-security#ai-7-perform-continuous-ai-red-teaming | 2026-02-03 | | **AI Red Teaming Training Series** | https://learn.microsoft.com/en-us/security/ai-red-team/training | 2026-02-03 | -| **Planning red teaming for LLMs** | https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/red-teaming | 2026-02-03 | +| **Planning red teaming for LLMs** | https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/red-teaming | 2026-02-03 | | **Prompt Shields (Jailbreak detection)** | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/jailbreak-detection | 2026-02-03 | ### Open-source verktøy diff --git a/skills/ms-ai-governance/references/responsible-ai/responsible-ai-policy-development.md b/skills/ms-ai-governance/references/responsible-ai/responsible-ai-policy-development.md index d078028..4e0a1b8 100644 --- a/skills/ms-ai-governance/references/responsible-ai/responsible-ai-policy-development.md +++ b/skills/ms-ai-governance/references/responsible-ai/responsible-ai-policy-development.md @@ -227,7 +227,7 @@ Start: New AI initiative or capability? | **Content Safety** | Harmful content filtering (text, image, multimodal) | [Azure AI Content Safety](https://learn.microsoft.com/azure/ai-services/content-safety/) - konfigurerbare severity thresholds | | **Evaluation Tools** | Pre-deployment safety, hallucination, bias testing | [Foundry evaluation SDK](https://learn.microsoft.com/azure/ai-studio/) - integreres i CI/CD | | **Model Registry** | Versioning, approval workflows, provenance tracking | [Azure ML Model Registry](https://learn.microsoft.com/azure/machine-learning/concept-model-management-and-deployment) - RBAC-controlled | -| **Monitoring** | Model drift, performance degradation, quality metrics | [Foundry Agent Service metrics](https://learn.microsoft.com/azure/ai-foundry/agents/how-to/metrics) - alert rules | +| **Monitoring** | Model drift, performance degradation, quality metrics | [Foundry Agent Service metrics](https://learn.microsoft.com/azure/foundry/observability/how-to/how-to-monitor-agents-dashboard) - alert rules | | **Data Governance** | Data lineage, sensitivity labels, DLP policies | [Microsoft Purview integration](https://learn.microsoft.com/purview/ai-azure-services) | **Policy Implementation Example (Foundry):** diff --git a/skills/ms-ai-governance/references/responsible-ai/stakeholder-communication-ai-decisions.md b/skills/ms-ai-governance/references/responsible-ai/stakeholder-communication-ai-decisions.md index 9ec9f5f..018462b 100644 --- a/skills/ms-ai-governance/references/responsible-ai/stakeholder-communication-ai-decisions.md +++ b/skills/ms-ai-governance/references/responsible-ai/stakeholder-communication-ai-decisions.md @@ -804,7 +804,7 @@ Hvis noen av disse mangler: **IKKE deploy før de er på plass.** AI uten stakeh - Verifisert: 2026-02 6. **Transparency note for Azure OpenAI** - - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note?view=foundry-classic + - https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note?view=foundry-classic - Status: GA - Verifisert: 2026-02 diff --git a/skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md b/skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md index 77450e1..d6a572b 100644 --- a/skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md +++ b/skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md @@ -380,7 +380,7 @@ rai_insights.save("rai_scorecard.pdf") - Content filter annotations → apps kan forklare hvorfor content ble blocked **Transparency Note URL:** -https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note +https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note --- @@ -699,15 +699,15 @@ Return on investment: Transparency er billigere enn cleanup. Skal vi prioritere **Verified sources (MCP: microsoft-learn):** 1. **Transparency note for Azure OpenAI** - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note + https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note (Status: Verified 2026-02 — Latest updates: o3/o4-mini, Deep Research system cards) 2. **Transparency note for Azure AI Search** - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/search/transparency-note + https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/search/transparency-note (Status: Verified 2026-02 — Recommendations for A/B testing, bias detection) 3. **Transparency note for Document Intelligence** - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/document-intelligence/transparency-note + https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/document-intelligence/transparency-note (Status: Verified 2026-02 — Limitations for prebuilt/custom models) 4. **Responsible AI scorecard documentation** diff --git a/skills/ms-ai-infrastructure/references/bcdr/ai-foundry-disaster-recovery-planning.md b/skills/ms-ai-infrastructure/references/bcdr/ai-foundry-disaster-recovery-planning.md index dea806c..cff5dc5 100644 --- a/skills/ms-ai-infrastructure/references/bcdr/ai-foundry-disaster-recovery-planning.md +++ b/skills/ms-ai-infrastructure/references/bcdr/ai-foundry-disaster-recovery-planning.md @@ -482,10 +482,10 @@ Bruk Azure Chaos Studio for automatisert feilinjeksjon: ## Referanser -- [High availability and resiliency for Microsoft Foundry projects and Agent Services](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/high-availability-resiliency) -- [Foundry Agent Service disaster recovery](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/agent-service-disaster-recovery) -- [Foundry Agent Service resource and data loss recovery](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/agent-service-operator-disaster-recovery) -- [High availability and disaster recovery for hub projects](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/hub-disaster-recovery) +- [High availability and resiliency for Microsoft Foundry projects and Agent Services](https://learn.microsoft.com/en-us/azure/foundry/how-to/high-availability-resiliency) +- [Foundry Agent Service disaster recovery](https://learn.microsoft.com/en-us/azure/foundry/how-to/agent-service-disaster-recovery) +- [Foundry Agent Service resource and data loss recovery](https://learn.microsoft.com/en-us/azure/foundry/how-to/agent-service-operator-disaster-recovery) +- [High availability and disaster recovery for hub projects](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/hub-disaster-recovery) - [Azure security baseline for Azure AI Foundry - Backup and recovery](https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/azure-ai-foundry-security-baseline#backup-and-recovery) - [Continuous backup with point-in-time restore in Azure Cosmos DB](https://learn.microsoft.com/en-us/azure/cosmos-db/continuous-backup-restore-introduction) diff --git a/skills/ms-ai-infrastructure/references/bcdr/capacity-planning-dr-configurations.md b/skills/ms-ai-infrastructure/references/bcdr/capacity-planning-dr-configurations.md index 9b5cdfa..f7a489f 100644 --- a/skills/ms-ai-infrastructure/references/bcdr/capacity-planning-dr-configurations.md +++ b/skills/ms-ai-infrastructure/references/bcdr/capacity-planning-dr-configurations.md @@ -329,7 +329,7 @@ az capacity reservation create \ - [Develop a disaster recovery plan — Optimize your recovery costs](https://learn.microsoft.com/en-us/azure/well-architected/design-guides/disaster-recovery#optimize-your-recovery-costs) — Kostnadsoptimalisering per tier - [Recovery strategy for active-passive (warm standby)](https://learn.microsoft.com/en-us/azure/well-architected/design-guides/disaster-recovery#recovery-strategy-for-active-passive-warm-standby) — Warm standby konfigurasjon - [Recovery strategy for active-active deployments](https://learn.microsoft.com/en-us/azure/well-architected/design-guides/disaster-recovery#recovery-strategy-for-active-active-deployments) — Active-active konfigurasjon -- [BCDR considerations with Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/business-continuity-disaster-recovery) — OpenAI-spesifikk kapasitetsplanlegging +- [BCDR considerations with Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/high-availability-resiliency) — OpenAI-spesifikk kapasitetsplanlegging - [Management recommendations for AI workloads on Azure IaaS](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/infrastructure/management) — AI-workload management - [Azure Site Recovery — Plan capacity and scaling](https://learn.microsoft.com/en-us/azure/site-recovery/site-recovery-plan-capacity-vmware) — Kapasitetsplanlegging diff --git a/skills/ms-ai-infrastructure/references/bcdr/incident-response-ai-systems.md b/skills/ms-ai-infrastructure/references/bcdr/incident-response-ai-systems.md index 11705e5..83efe35 100644 --- a/skills/ms-ai-infrastructure/references/bcdr/incident-response-ai-systems.md +++ b/skills/ms-ai-infrastructure/references/bcdr/incident-response-ai-systems.md @@ -305,7 +305,7 @@ Tiltak: [Hva gjøres for å forhindre gjentakelse] - [Microsoft Defender for AI Services](https://learn.microsoft.com/en-us/azure/defender-for-cloud/ai-threat-protection) — AI-spesifikk trusseloppdaging - [Azure Monitor alerts overview](https://learn.microsoft.com/en-us/azure/azure-monitor/alerts/alerts-overview) — Alert-rammeverk - [Microsoft Sentinel overview](https://learn.microsoft.com/en-us/azure/sentinel/overview) — SIEM/SOAR for sikkerhetshendelser -- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — OpenAI-spesifikk monitoring +- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) — OpenAI-spesifikk monitoring ## For Cosmo diff --git a/skills/ms-ai-infrastructure/references/bcdr/monitoring-alerting-failover-detection.md b/skills/ms-ai-infrastructure/references/bcdr/monitoring-alerting-failover-detection.md index 5c03c1f..221c36a 100644 --- a/skills/ms-ai-infrastructure/references/bcdr/monitoring-alerting-failover-detection.md +++ b/skills/ms-ai-infrastructure/references/bcdr/monitoring-alerting-failover-detection.md @@ -438,7 +438,7 @@ Azure Monitor Application Insights tilbyr nå dedikert støtte for AI-agenter vi ## Referanser -- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — OpenAI monitoring og alerting +- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) — OpenAI monitoring og alerting - [Monitor Azure AI Search](https://learn.microsoft.com/en-us/azure/search/monitor-azure-cognitive-search) — AI Search monitoring - [Azure Monitor alerts overview](https://learn.microsoft.com/en-us/azure/azure-monitor/alerts/alerts-overview) — Alert-rammeverk *(Verified MCP 2026-04)* — Stateful vs. stateless alerts. **Simple Log Search Alerts** (GA) for per-row KQL evaluering — raskere varsling enn tradisjonelle log alerts. **Query-based metric alerts** for Prometheus/OTel (public preview). Alerts stored 30 dager. Fired instances er read-only. Alert processing rules for suppression ved planlagt vedlikehold. **Azure Monitor Baseline Alerts** (`aka.ms/amba`) for policy-basert alerting i skala via Azure Policy. - [Health modeling and observability of mission-critical workloads](https://learn.microsoft.com/en-us/azure/well-architected/mission-critical/mission-critical-health-modeling) — Health modeling diff --git a/skills/ms-ai-infrastructure/references/bcdr/multi-region-azure-openai-deployment.md b/skills/ms-ai-infrastructure/references/bcdr/multi-region-azure-openai-deployment.md index 00f4ed5..4a9d5a2 100644 --- a/skills/ms-ai-infrastructure/references/bcdr/multi-region-azure-openai-deployment.md +++ b/skills/ms-ai-infrastructure/references/bcdr/multi-region-azure-openai-deployment.md @@ -368,11 +368,11 @@ Prioritet 3: Standard Data Zone (EU) ## Referanser -- [Business Continuity and Disaster Recovery (BCDR) considerations with Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/business-continuity-disaster-recovery) +- [Business Continuity and Disaster Recovery (BCDR) considerations with Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/high-availability-resiliency) - [Use a gateway in front of multiple Azure OpenAI deployments or instances](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-multi-backend) - [Backends in API Management - Load-balanced pool](https://learn.microsoft.com/en-us/azure/api-management/backends#load-balanced-pool) -- [Manage Azure OpenAI quota](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/quota) -- [Azure OpenAI model availability by region](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models) +- [Manage Azure OpenAI quota](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/quota) +- [Azure OpenAI model availability by region](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure) - [Smart Load Balancing for OpenAI with Azure API Management](https://github.com/Azure-Samples/openai-apim-lb) ## For Cosmo diff --git a/skills/ms-ai-infrastructure/references/bcdr/rto-rpo-planning-ai-services.md b/skills/ms-ai-infrastructure/references/bcdr/rto-rpo-planning-ai-services.md index e433104..657c3e9 100644 --- a/skills/ms-ai-infrastructure/references/bcdr/rto-rpo-planning-ai-services.md +++ b/skills/ms-ai-infrastructure/references/bcdr/rto-rpo-planning-ai-services.md @@ -251,7 +251,7 @@ NSM (Nasjonal sikkerhetsmyndighet) krever: - [Business continuity and disaster recovery overview](https://learn.microsoft.com/en-us/azure/reliability/concept-business-continuity-high-availability-disaster-recovery) — Grunnleggende BCDR-konsepter og definisjoner - [Develop a disaster recovery plan for multi-region deployments](https://learn.microsoft.com/en-us/azure/well-architected/design-guides/disaster-recovery) — WAF-veiledning for DR-planlegging - [Recommendations for defining reliability targets](https://learn.microsoft.com/en-us/azure/well-architected/reliability/metrics) — SLO, RTO og RPO-definisjoner -- [BCDR considerations with Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/business-continuity-disaster-recovery) — Azure OpenAI-spesifikk BCDR +- [BCDR considerations with Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/high-availability-resiliency) — Azure OpenAI-spesifikk BCDR - [Azure Storage redundancy](https://learn.microsoft.com/en-us/azure/storage/common/storage-redundancy) — GRS, GZRS og replikeringsalternativer - [Azure Storage Geo Priority Replication](https://learn.microsoft.com/en-us/azure/storage/common/storage-redundancy-priority-replication) — SLA-backed RPO for blobs - [Reliability in Azure AI Search](https://learn.microsoft.com/en-us/azure/reliability/reliability-ai-search) — Tilgjengelighet og DR for AI Search diff --git a/skills/ms-ai-security/references/ai-security-engineering/adversarial-input-robustness-testing.md b/skills/ms-ai-security/references/ai-security-engineering/adversarial-input-robustness-testing.md index 1d20ecb..ca2c28a 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/adversarial-input-robustness-testing.md +++ b/skills/ms-ai-security/references/ai-security-engineering/adversarial-input-robustness-testing.md @@ -504,7 +504,7 @@ outputs = await simulator( ## References - [Threat Modeling AI/ML Systems](https://learn.microsoft.com/en-us/security/engineering/threat-modeling-aiml) — Microsoft Security Engineering -- [AI Red Teaming Agent](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/ai-red-teaming-agent) — Azure AI Foundry +- [AI Red Teaming Agent](https://learn.microsoft.com/en-us/azure/foundry/concepts/ai-red-teaming-agent) — Azure AI Foundry - [PyRIT Framework](https://azure.github.io/PyRIT/) — Microsoft open-source red teaming tool - [Artificial Intelligence Security (MCSB)](https://learn.microsoft.com/en-us/security/benchmark/azure/mcsb-v2-artificial-intelligence-security) — Azure Security Benchmark - [Failure Modes in Machine Learning](https://learn.microsoft.com/en-us/security/engineering/failure-modes-in-machine-learning) — Microsoft Security diff --git a/skills/ms-ai-security/references/ai-security-engineering/ai-security-scoring-framework.md b/skills/ms-ai-security/references/ai-security-engineering/ai-security-scoring-framework.md index d254abb..6c66500 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/ai-security-scoring-framework.md +++ b/skills/ms-ai-security/references/ai-security-engineering/ai-security-scoring-framework.md @@ -464,7 +464,7 @@ For statlige AI-prosjekter som krever beslutningsgrunnlag: *Confidence: Verified* — Logging, threat detection, compliance controls 6. **Evaluate generative AI models (Azure AI Foundry)** - https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluate-generative-ai-app + https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluate-generative-ai-app *Confidence: Verified* — AI quality metrics (NLP + AI-assisted), risk and safety metrics (content harm, ASR) 7. **Azure Defender for Cloud - Resource Graph samples** diff --git a/skills/ms-ai-security/references/ai-security-engineering/content-safety-filter-calibration.md b/skills/ms-ai-security/references/ai-security-engineering/content-safety-filter-calibration.md index 6c23f32..29920a0 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/content-safety-filter-calibration.md +++ b/skills/ms-ai-security/references/ai-security-engineering/content-safety-filter-calibration.md @@ -505,10 +505,10 @@ Denne referansen er basert på offisiell Microsoft-dokumentasjon og verifiserte ### Primærkilder (Verified) 1. [Mitigate false results in Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/improve-performance) — Severity tuning, blocklists, custom categories -2. [Configure content filters - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/content-filters) — Deployment + request-level configuration -3. [Content filter configurability](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-configurability) — Severity levels, approval process +2. [Configure content filters - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/content-filters) — Deployment + request-level configuration +3. [Content filter configurability](https://learn.microsoft.com/en-us/azure/foundry-classic/foundry-models/concepts/content-filter) — Severity levels, approval process 4. [Azure AI Content Safety FAQ](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/faq) — Threshold recommendations, multilingual support, pricing -5. [Transparency note: Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/content-safety/transparency-note) — Severity definitions, best practices, bias mitigation +5. [Transparency note: Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/content-safety/transparency-note) — Severity definitions, best practices, bias mitigation 6. [Python SDK code samples](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-contentsafety-readme) — AnalyzeText API, blocklist usage ### Konfidensgradering diff --git a/skills/ms-ai-security/references/ai-security-engineering/data-leakage-prevention-ai.md b/skills/ms-ai-security/references/ai-security-engineering/data-leakage-prevention-ai.md index 408ed57..886b95b 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/data-leakage-prevention-ai.md +++ b/skills/ms-ai-security/references/ai-security-engineering/data-leakage-prevention-ai.md @@ -178,8 +178,8 @@ Invoke-AzRestMethod @patchParams **Konsept:** Implementer network security perimeter for å begrense inbound og outbound access til Azure OpenAI og Foundry-baserte prosjekter. **Implementering:** -- [Add network security perimeter to Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/network-security-perimeter) -- [Add Foundry to a network security perimeter](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/add-foundry-to-network-security-perimeter) +- [Add network security perimeter to Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/network-security-perimeter) +- [Add Foundry to a network security perimeter](https://learn.microsoft.com/en-us/azure/foundry/how-to/add-foundry-to-network-security-perimeter) **Kombiner med:** - Azure Private Link for network-level data isolation diff --git a/skills/ms-ai-security/references/ai-security-engineering/entra-agent-id-zero-trust.md b/skills/ms-ai-security/references/ai-security-engineering/entra-agent-id-zero-trust.md index 47b9f13..2a435e2 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/entra-agent-id-zero-trust.md +++ b/skills/ms-ai-security/references/ai-security-engineering/entra-agent-id-zero-trust.md @@ -427,7 +427,7 @@ Når en Foundry-agent publiseres, endres identiteten fra delt prosjektidentitet 1. [Security for AI agents with Microsoft Entra Agent ID](https://learn.microsoft.com/entra/agent-id/identity-professional/security-for-ai) — Oversikt over sikkerhetsrammeverket 2. [What are agent identities](https://learn.microsoft.com/entra/agent-id/identity-platform/what-is-agent-id) — Kjernekonsepted for agentidentiteter 3. [Agent identity and blueprint concepts in Microsoft Entra ID](https://learn.microsoft.com/entra/agent-id/identity-platform/key-concepts) — Blueprints og arkitektur -4. [Agent identity concepts in Microsoft Foundry](https://learn.microsoft.com/azure/ai-foundry/agents/concepts/agent-identity?view=foundry) — Foundry-integrasjon med agentidentiteter +4. [Agent identity concepts in Microsoft Foundry](https://learn.microsoft.com/azure/foundry/agents/concepts/agent-identity?view=foundry) — Foundry-integrasjon med agentidentiteter 5. [Automatically create Microsoft Entra agent identities for Copilot Studio agents](https://learn.microsoft.com/en-us/microsoft-copilot-studio/admin-use-entra-agent-identities) — Copilot Studio-integrasjon 6. [What is the Microsoft Entra Agent Registry?](https://learn.microsoft.com/entra/agent-id/identity-platform/what-is-agent-registry) — Agent Registry-konsepter 7. [Authorization in Microsoft Entra Agent ID](https://learn.microsoft.com/entra/agent-id/identity-professional/authorization-agent-id) — Roller, tillatelser og blokkerte rettigheter diff --git a/skills/ms-ai-security/references/ai-security-engineering/jailbreak-prevention-production.md b/skills/ms-ai-security/references/ai-security-engineering/jailbreak-prevention-production.md index 727926e..a95a471 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/jailbreak-prevention-production.md +++ b/skills/ms-ai-security/references/ai-security-engineering/jailbreak-prevention-production.md @@ -519,7 +519,7 @@ print(f"Jailbreak resistance score: {results['jailbreak_resistance']}") ### Microsoft Learn Documentation 1. **Prompt Shields in Azure AI Foundry** - [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-prompt-shields](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-prompt-shields) + [https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-prompt-shields](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-prompt-shields) *Offisiell dokumentasjon for Prompt Shields i Azure OpenAI content filtering-systemet.* 2. **Prompt Shields in Azure AI Content Safety** @@ -527,7 +527,7 @@ print(f"Jailbreak resistance score: {results['jailbreak_resistance']}") *Unified API for jailbreak detection med user scenarios og implementation guide.* 3. **Safety System Messages - Step-by-step Authoring Best Practices** - [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message) + [https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message) *Best practices for system message design som første forsvarslinje.* 4. **Security Planning for LLM-based Applications** @@ -535,7 +535,7 @@ print(f"Jailbreak resistance score: {results['jailbreak_resistance']}") *Comprehensive security planning guide med threat modeling for LLM apps.* 5. **Azure OpenAI Default Safety Policies** - [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/default-safety-policies](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/default-safety-policies) + [https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/default-safety-policies](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/default-safety-policies) *Default safety policies inkludert jailbreak detection thresholds.* 6. **API Management - llm-content-safety Policy** diff --git a/skills/ms-ai-security/references/ai-security-engineering/model-fingerprinting-watermarking.md b/skills/ms-ai-security/references/ai-security-engineering/model-fingerprinting-watermarking.md index 7a6f6f3..142a83f 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/model-fingerprinting-watermarking.md +++ b/skills/ms-ai-security/references/ai-security-engineering/model-fingerprinting-watermarking.md @@ -541,7 +541,7 @@ Trenger kunde watermarking/fingerprinting? ## Kilder 1. **C2PA Specification** — https://c2pa.org/specifications/specifications/2.1/specs/C2PA_Specification.html -2. **Azure OpenAI Content Credentials** — https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-credentials +2. **Azure OpenAI Content Credentials** — https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/content-credentials 3. **Azure Text to Speech Content Credentials** — https://learn.microsoft.com/en-us/azure/ai-services/speech-service/text-to-speech-avatar/content-credentials 4. **Microsoft 365 Watermarking** — https://learn.microsoft.com/en-us/copilot/microsoft-365/watermarks 5. **Azure Machine Learning Model Management** — https://learn.microsoft.com/en-us/azure/machine-learning/concept-model-management-and-deployment diff --git a/skills/ms-ai-security/references/ai-security-engineering/output-validation-grounding-verification.md b/skills/ms-ai-security/references/ai-security-engineering/output-validation-grounding-verification.md index adabee0..2ca3f23 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/output-validation-grounding-verification.md +++ b/skills/ms-ai-security/references/ai-security-engineering/output-validation-grounding-verification.md @@ -647,19 +647,19 @@ def cached_groundedness_check(key): [Verified: 2026-02] 3. **Content Filter Groundedness (Azure OpenAI):** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-groundedness + https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-groundedness [Verified: 2026-02] 4. **Azure AI Evaluation SDK (Groundedness Evaluator):** - https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/evaluate-sdk + https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/evaluate-sdk [Verified: 2026-02] 5. **Azure AI Search Grounding (Transparency Note):** - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/search/transparency-note + https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/search/transparency-note [Verified: 2026-02] 6. **Bing Grounding Tools for Agents:** - https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/bing-tools + https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/bing-tools [Verified: 2026-02] 7. **Security Planning for LLM Applications (Output Validation):** diff --git a/skills/ms-ai-security/references/ai-security-engineering/pii-detection-norwegian-context.md b/skills/ms-ai-security/references/ai-security-engineering/pii-detection-norwegian-context.md index ace4241..77fb409 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/pii-detection-norwegian-context.md +++ b/skills/ms-ai-security/references/ai-security-engineering/pii-detection-norwegian-context.md @@ -419,7 +419,7 @@ df_masked = df.withColumn("text_masked", mask_pii_udf(df.text)) - [Recognized PII and PHI Entities](https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/concepts/entity-categories) (inkluderer NOIdentityNumber) - [How to: Redact Text PII](https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/how-to/redact-text-pii) — Oppdatert: ny DisableEntityValidation, EntitySynonyms, ValueExclusionPolicy, per-entity confidence threshold overrides (2025-11-15-preview) - [Quickstart: Detect PII](https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/quickstart) — Quickstart er nå for native document PII; link til text/conversation how-to-guides for tekst-PII -- [Transparency Note for PII](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/language-service/transparency-note-personally-identifiable-information) (GDPR compliance, nå under Azure AI Foundry responsible AI) +- [Transparency Note for PII](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/language-service/transparency-note-personally-identifiable-information) (GDPR compliance, nå under Azure AI Foundry responsible AI) **Baseline (modellkunnskap):** - Norsk fødselsnummer-format (11 siffer, mod11-checksumvalidering) diff --git a/skills/ms-ai-security/references/ai-security-engineering/prompt-injection-defense-patterns.md b/skills/ms-ai-security/references/ai-security-engineering/prompt-injection-defense-patterns.md index 6473ae6..c5bf305 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/prompt-injection-defense-patterns.md +++ b/skills/ms-ai-security/references/ai-security-engineering/prompt-injection-defense-patterns.md @@ -445,8 +445,8 @@ Når du diskuterer prompt injection-forsvar med kunder, still disse spørsmålen - [Prompt Shields - Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/jailbreak-detection) (GA) - [Microsoft Security Benchmark - AI Security Controls](https://learn.microsoft.com/en-us/security/benchmark/azure/mcsb-v2-artificial-intelligence-security) (AI-2, AI-3) - [Security Planning for LLM Applications](https://learn.microsoft.com/en-us/ai/playbook/technology-guidance/generative-ai/mlops-in-openai/security/security-plan-llm-application) -- [Content Filtering Overview](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter) -- [Default Safety Policies](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/default-safety-policies) +- [Content Filtering Overview](https://learn.microsoft.com/en-us/azure/foundry-classic/foundry-models/concepts/content-filter) +- [Default Safety Policies](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/default-safety-policies) **Tools and Services:** - Azure AI Content Safety: [Overview](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/overview) diff --git a/skills/ms-ai-security/references/ai-security-engineering/zero-trust-ai-services.md b/skills/ms-ai-security/references/ai-security-engineering/zero-trust-ai-services.md index 4b44cf7..5038d70 100644 --- a/skills/ms-ai-security/references/ai-security-engineering/zero-trust-ai-services.md +++ b/skills/ms-ai-security/references/ai-security-engineering/zero-trust-ai-services.md @@ -907,7 +907,7 @@ Logging & Monitoring: Denne guiden er basert på følgende Microsoft Learn-dokumentasjon (sist verifisert 2026-04): 1. [Secure networks with SASE, Zero Trust, and AI](https://learn.microsoft.com/en-us/security/zero-trust/deploy/networks) — Offisiell Zero Trust nettverksguide -2. [How to configure Azure OpenAI with managed identities](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/managed-identity) — Managed Identity-konfigurasjon for Azure OpenAI +2. [How to configure Azure OpenAI with managed identities](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/managed-identity) — Managed Identity-konfigurasjon for Azure OpenAI 3. [Managed identities: role-based access control (RBAC)](https://learn.microsoft.com/en-us/azure/ai-services/translator/document-translation/how-to-guides/create-use-managed-identities) — RBAC-implementering for AI Services 4. [Azure security baseline for Azure OpenAI](https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/azure-openai-security-baseline) — Sikkerhetsbaseline med Identity Management-krav 5. [Build a strong security posture for AI](https://learn.microsoft.com/en-us/security/security-for-ai/posture) — Zero Trust-prinsipper for AI-sikkerhet diff --git a/skills/ms-ai-security/references/cost-optimization/azure-ai-foundry-cost-governance.md b/skills/ms-ai-security/references/cost-optimization/azure-ai-foundry-cost-governance.md index 654cc77..585bf52 100644 --- a/skills/ms-ai-security/references/cost-optimization/azure-ai-foundry-cost-governance.md +++ b/skills/ms-ai-security/references/cost-optimization/azure-ai-foundry-cost-governance.md @@ -805,27 +805,27 @@ Savings with PTU: 3 000 NOK/month (17% reduction) *Confidence: Verified (Feb 2026)* — Comprehensive governance framework, 8-step cost governance process 2. **Manage and increase quotas for hub resources** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/hub-quota + URL: https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/hub-quota *Confidence: Verified (Feb 2026)* — Quota management UI, VM quota, model quota allocation 3. **Plan and manage costs for Microsoft Foundry** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/manage-costs + URL: https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs *Confidence: Verified (Feb 2026)* — Budget creation, cost monitoring, RBAC for cost visibility 4. **Azure OpenAI Dynamic quota (Preview)** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/dynamic-quota + URL: https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/dynamic-quota *Confidence: Verified (Feb 2026)* — When to use dynamic quota, cost implications 5. **Consolidated view for Foundry Tools in the Azure portal** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/ai-foundry-consolidated-view + URL: https://learn.microsoft.com/en-us/azure/foundry-classic/concepts/ai-foundry-consolidated-view *Confidence: Verified (Feb 2026)* — Dashboard for costs, quota utilization, alerts 6. **Azure OpenAI quotas and limits** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quotas-limits + URL: https://learn.microsoft.com/en-us/azure/foundry/openai/quotas-limits *Confidence: Verified (Feb 2026)* — Model-specific TPM/RPM limits by tier 7. **Azure OpenAI in Azure AI Foundry Models quota management** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/quota + URL: https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/quota *Confidence: Verified (Feb 2026)* — Quota view, request increases, migrating deployments 8. **Manage AI costs (Cloud Adoption Framework)** @@ -833,7 +833,7 @@ Savings with PTU: 3 000 NOK/month (17% reduction) *Confidence: Verified (Feb 2026)* — Monthly reviews, model selection optimization 9. **Microsoft Foundry rollout across organization (Governance section)** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/planning#governance + URL: https://learn.microsoft.com/en-us/azure/foundry/concepts/planning#governance *Confidence: Verified (Feb 2026)* — Azure Policy for model access, TPM limits at deployment level 10. **Azure API Management generative AI gateway capabilities** diff --git a/skills/ms-ai-security/references/cost-optimization/batch-processing-cost-reduction.md b/skills/ms-ai-security/references/cost-optimization/batch-processing-cost-reduction.md index 479cea8..803023d 100644 --- a/skills/ms-ai-security/references/cost-optimization/batch-processing-cost-reduction.md +++ b/skills/ms-ai-security/references/cost-optimization/batch-processing-cost-reduction.md @@ -307,7 +307,7 @@ Kreves respons < 5 sekunder? ### Microsoft Learn (Verified via MCP) 1. **Getting started with Azure OpenAI batch deployments** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch + - URL: https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch - Konfidens: **Verified** (fetched 2026-02) - Innhold: Deployment types, pricing (50% reduction), dynamic quota, exponential backoff, supported models, API versions @@ -317,24 +317,24 @@ Kreves respons < 5 sekunder? - Innhold: 50% cost reduction for batch vs. global standard 3. **What's new in Azure OpenAI (August 2024)** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/whats-new#august-2024 + - URL: https://learn.microsoft.com/en-us/azure/foundry-classic/openai/whats-new#august-2024 - Konfidens: **Verified** - Innhold: Batch API announcement, key use cases, GA status 4. **Azure OpenAI deployment types** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/deployment-types + - URL: https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/deployment-types - Konfidens: **Verified** - Innhold: Global-Batch vs. Data Zone Batch, dynamic quota ### Code samples (Verified via MCP) 5. **Python: Create batch job with DefaultAzureCredential** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch?pivots=programming-language-python + - URL: https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch?pivots=programming-language-python - Konfidens: **Verified** - Innhold: OpenAI Python SDK examples for batch job creation 6. **Python: Upload batch file with expiration** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch?pivots=programming-language-python#upload-batch-file + - URL: https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch?pivots=programming-language-python#upload-batch-file - Konfidens: **Verified** - Innhold: File upload with 14-30 day expiration diff --git a/skills/ms-ai-security/references/cost-optimization/budget-forecasting-ai-projects.md b/skills/ms-ai-security/references/cost-optimization/budget-forecasting-ai-projects.md index e17879b..16ab400 100644 --- a/skills/ms-ai-security/references/cost-optimization/budget-forecasting-ai-projects.md +++ b/skills/ms-ai-security/references/cost-optimization/budget-forecasting-ai-projects.md @@ -467,7 +467,7 @@ Korrekt forecasting driver kostnadsoptimalisering: *Confidence: Verified* — Komplett guide til forecasting i Azure 2. **Plan to Manage Costs for Azure OpenAI** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs + https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs *Confidence: Verified* — Token-basert pricing, forecasting, budgets 3. **Azure Cost Management - Create Budgets** @@ -491,7 +491,7 @@ Korrekt forecasting driver kostnadsoptimalisering: *Confidence: Verified* — Well-Architected Framework 8. **Fine-Tuning Cost Management** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/fine-tuning-cost-management + https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/fine-tuning-cost-management *Confidence: Verified* — Training + hosting + inference cost --- diff --git a/skills/ms-ai-security/references/cost-optimization/gpt5-gpt41-pricing-models.md b/skills/ms-ai-security/references/cost-optimization/gpt5-gpt41-pricing-models.md index 3d69b46..08f4c80 100644 --- a/skills/ms-ai-security/references/cost-optimization/gpt5-gpt41-pricing-models.md +++ b/skills/ms-ai-security/references/cost-optimization/gpt5-gpt41-pricing-models.md @@ -536,17 +536,17 @@ GPT-4o mini og GPT-4o brukes fortsatt i US Government regions (offer comparable ### Primærkilder (Microsoft Learn, bekreftet februar 2026) 1. **GPT-5 vs GPT-4.1: choosing the right model for your use case** - URL: https://learn.microsoft.com/azure/ai-foundry/foundry-models/how-to/model-choice-guide?view=foundry-classic + URL: https://learn.microsoft.com/azure/foundry/foundry-models/how-to/model-choice-guide?view=foundry-classic Hentet: 2026-02 Innhold: Modellsammenligning, reasoning-nivåer, latens-trade-offs, use-case guidance 2. **Foundry Models sold directly by Azure — GPT-4.1 og GPT-5-serien** - URL: https://learn.microsoft.com/azure/ai-foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic + URL: https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic Hentet: 2026-02 Innhold: Kontekstvindu, max output tokens, treningsdata, versjonsoversikt, tilgjengelighetskrav 3. **Provisioned throughput unit (PTU) costs and billing** - URL: https://learn.microsoft.com/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding?view=foundry-classic + URL: https://learn.microsoft.com/azure/foundry/openai/concepts/provisioned-throughput-billing?view=foundry-classic Hentet: 2026-02 Innhold: PTU-kapasitet per modell (TPM/PTU), min deployment, latens-SLA, input/output-ratio (1:4 for gpt-4.1, 1:8 for gpt-5) @@ -556,7 +556,7 @@ GPT-4o mini og GPT-4o brukes fortsatt i US Government regions (offer comparable Innhold: Priseksempler med gpt-4.1 Global ($2/$8) og gpt-4.1-mini Global ($0.40/$1.60) bekreftet 5. **Azure OpenAI in Microsoft Foundry Models quotas and limits** - URL: https://learn.microsoft.com/azure/ai-foundry/openai/quotas-limits?view=foundry-classic + URL: https://learn.microsoft.com/azure/foundry/openai/quotas-limits?view=foundry-classic Hentet: 2026-02 Innhold: GPT-5- og GPT-4.1-seriens kvotestruktur, usage tiers, deployment-typer @@ -566,12 +566,12 @@ GPT-4o mini og GPT-4o brukes fortsatt i US Government regions (offer comparable Innhold: Copilot Credits-klassifisering (Basic/Standard/Premium) per modell, tilgjengelige modeller 7. **Cost management for fine-tuning** - URL: https://learn.microsoft.com/azure/ai-foundry/openai/how-to/fine-tuning-cost-management?view=foundry-classic + URL: https://learn.microsoft.com/azure/foundry/openai/how-to/fine-tuning-cost-management?view=foundry-classic Hentet: 2026-02 Innhold: Fine-tuning kostnad, hosting $1.70/time (o4-mini eksempel) 8. **Plan and manage costs for Microsoft Foundry** - URL: https://learn.microsoft.com/azure/ai-foundry/concepts/manage-costs?view=foundry-classic + URL: https://learn.microsoft.com/azure/foundry/concepts/manage-costs?view=foundry-classic Hentet: 2026-02 Innhold: Billing-modell, token-basert prising, 1K-token enheter diff --git a/skills/ms-ai-security/references/cost-optimization/inference-endpoint-cost-optimization.md b/skills/ms-ai-security/references/cost-optimization/inference-endpoint-cost-optimization.md index e774cf0..d0de866 100644 --- a/skills/ms-ai-security/references/cost-optimization/inference-endpoint-cost-optimization.md +++ b/skills/ms-ai-security/references/cost-optimization/inference-endpoint-cost-optimization.md @@ -571,9 +571,9 @@ Hvis inference-kostnad per prediction >10% av business value per prediction, er - [Plan to manage costs for Azure Machine Learning](https://learn.microsoft.com/en-us/azure/machine-learning/concept-plan-manage-cost?view=azureml-api-2) — **Verified** **Serverless API Endpoints:** -- [Deploy models as serverless API deployments (AI Foundry Portal)](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-serverless?view=foundry-classic) — **Verified** -- [Plan and manage costs for Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/manage-costs?view=foundry-classic) — **Verified** -- [Plan to manage costs for Azure OpenAI in Azure AI Foundry Models](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs) — **Verified** +- [Deploy models as serverless API deployments (AI Foundry Portal)](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/deploy-models-serverless?view=foundry-classic) — **Verified** +- [Plan and manage costs for Microsoft Foundry](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs?view=foundry-classic) — **Verified** +- [Plan to manage costs for Azure OpenAI in Azure AI Foundry Models](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs) — **Verified** **Cost Governance:** - [Govern Azure platform services (PaaS) for AI](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/platform/governance) — **Verified** diff --git a/skills/ms-ai-security/references/cost-optimization/model-selection-price-performance.md b/skills/ms-ai-security/references/cost-optimization/model-selection-price-performance.md index 50f4003..9e493a9 100644 --- a/skills/ms-ai-security/references/cost-optimization/model-selection-price-performance.md +++ b/skills/ms-ai-security/references/cost-optimization/model-selection-price-performance.md @@ -497,32 +497,32 @@ Bruk alltid confidence markers når du anbefaler modeller: ### Primærkilder (Microsoft Learn) 1. **GPT-5 vs GPT-4.1: choosing the right model for your use case** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/how-to/model-choice-guide?view=foundry-classic + URL: https://learn.microsoft.com/en-us/azure/foundry/foundry-models/how-to/model-choice-guide?view=foundry-classic Hentet: 2026-02 Innhold: Modellsammenligninger, latency trade-offs, reasoning-nivåer 2. **Plan to manage costs for Azure OpenAI in Azure AI Foundry Models** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs + URL: https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs Hentet: 2026-02 Innhold: Billing models, token pricing, cost monitoring 3. **Cost management for fine-tuning** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/fine-tuning-cost-management?view=foundry-classic + URL: https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/fine-tuning-cost-management?view=foundry-classic Hentet: 2026-02 Innhold: Training costs, hosting costs, deployment types 4. **Optimize model cost and performance** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/control-plane/how-to-optimize-cost-performance?view=foundry + URL: https://learn.microsoft.com/en-us/azure/foundry/control-plane/how-to-optimize-cost-performance?view=foundry Hentet: 2026-02 Innhold: Model Router, cost optimization workflows 5. **Azure OpenAI in Azure AI Foundry Models** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models + URL: https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure Hentet: 2026-02 Innhold: Model catalog, capabilities, regional availability 6. **Understanding costs associated with provisioned throughput units (PTU)** - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding + URL: https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput-billing Hentet: 2026-02 Innhold: PTU pricing, throughput per PTU, when to use PTU diff --git a/skills/ms-ai-security/references/cost-optimization/multi-model-strategy-costs.md b/skills/ms-ai-security/references/cost-optimization/multi-model-strategy-costs.md index aa504d9..5ee6203 100644 --- a/skills/ms-ai-security/references/cost-optimization/multi-model-strategy-costs.md +++ b/skills/ms-ai-security/references/cost-optimization/multi-model-strategy-costs.md @@ -638,11 +638,11 @@ az consumption usage list --start-date 2026-02-01 --end-date 2026-02-28 \ ## Kilder og verifisering **Microsoft Learn (MCP-verified):** -1. [Model router for Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/model-router) — **Verified** (MCP fetch, 2026-04) +1. [Model router for Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-router) — **Verified** (MCP fetch, 2026-04) 2. [Use a gateway in front of multiple Azure OpenAI deployments](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-multi-backend) — **Verified** (MCP fetch, 2026-04). Dokument bekrefter: (a) credential termination og reestablishment ved gateway anbefales fremfor pass-through client credentials, (b) gateway gir client-based usage tracking og chargeback-støtte, (c) Azure OpenAI er nå tagget som "Foundry Tools / Azure OpenAI in Foundry Models". -3. [Understanding costs associated with provisioned throughput units (PTU)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding) — **Verified** (MCP search, 2026-04) -4. [Azure OpenAI in Azure AI Foundry Models](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models) — **Verified** (MCP search, 2026-04) -5. [GPT-4o vs GPT-4o mini model selection](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/whats-new) — **Verified** (MCP search, 2026-04) +3. [Understanding costs associated with provisioned throughput units (PTU)](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput-billing) — **Verified** (MCP search, 2026-04) +4. [Azure OpenAI in Azure AI Foundry Models](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure) — **Verified** (MCP search, 2026-04) +5. [GPT-4o vs GPT-4o mini model selection](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/whats-new) — **Verified** (MCP search, 2026-04) **GitHub samples (MCP-referenced):** 1. [Smart load balancing for Azure OpenAI (Azure API Management)](https://github.com/Azure-Samples/openai-apim-lb) — **Verified** diff --git a/skills/ms-ai-security/references/cost-optimization/prompt-engineering-cost-reduction.md b/skills/ms-ai-security/references/cost-optimization/prompt-engineering-cost-reduction.md index 801ca6d..cbddace 100644 --- a/skills/ms-ai-security/references/cost-optimization/prompt-engineering-cost-reduction.md +++ b/skills/ms-ai-security/references/cost-optimization/prompt-engineering-cost-reduction.md @@ -40,7 +40,7 @@ Prompt caching er en kraftig funksjon for kostnadsreduksjon når du har repetere | **Prisreduksjon** | 50% rabatt (Standard), opptil 100% (Provisioned) | | **Støttede modeller** | GPT-4o, GPT-4o-mini, o1-serien, GPT-4.1-serien, o3-mini | -**Verified (MCP):** [Azure AI Foundry - Prompt Caching](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/prompt-caching) +**Verified (MCP):** [Azure AI Foundry - Prompt Caching](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/prompt-caching) ### Token-effektivitet per dataformat @@ -238,7 +238,7 @@ AI Foundry Model Catalog støtter prompt caching for: - o1-serien og o3-mini - GPT-4.1-serien -**Verified (MCP):** [AI Foundry Models - Prompt Caching](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/prompt-caching) +**Verified (MCP):** [AI Foundry Models - Prompt Caching](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/prompt-caching) ### Copilot Studio @@ -369,11 +369,11 @@ Copilot Studio bruker underliggende Azure OpenAI, men: ### Microsoft Learn (Verified via MCP) -1. [Prompt Caching - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/prompt-caching) – **Verified** -2. [Prompt Engineering Techniques](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering) – **Verified** +1. [Prompt Caching - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/prompt-caching) – **Verified** +2. [Prompt Engineering Techniques](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering) – **Verified** 3. [Azure OpenAI Pricing](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) – **Verified** -4. [Manage Costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs) – **Verified** -5. [Token Usage Estimation](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data) – **Verified** +4. [Manage Costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs) – **Verified** +5. [Token Usage Estimation](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data) – **Verified** ### Konfidensnivå per seksjon diff --git a/skills/ms-ai-security/references/cost-optimization/ptu-vs-paygo-economics.md b/skills/ms-ai-security/references/cost-optimization/ptu-vs-paygo-economics.md index 2adcbd3..4328fd5 100644 --- a/skills/ms-ai-security/references/cost-optimization/ptu-vs-paygo-economics.md +++ b/skills/ms-ai-security/references/cost-optimization/ptu-vs-paygo-economics.md @@ -403,23 +403,23 @@ En hybrid tilnærming, der man kombinerer PTU for stabil baseline-traffic og Pay **Microsoft Learn-ressurser (MCP-verified, februar 2026):** 1. **Provisioned Throughput Concepts:** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/provisioned-throughput + https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput *Confidence: Verified* – Offisiell kilde på PTU-konsepter, deployment types, benefits. 2. **PTU Cost Management:** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding + https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput-billing *Confidence: Verified* – Detaljert prisinformasjon, hourly billing, reservations, capacity calculator. 3. **Provisioned Get Started Guide:** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-get-started + https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/provisioned-get-started *Confidence: Verified* – Deployment workflow, quota vs. capacity, utilization monitoring. 4. **Provisioned Migration (Payment Model Framework):** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/provisioned-migration + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/provisioned-migration *Confidence: Verified* – Commitment vs. Reservation models, coexistence, best practices. 5. **Performance and Latency:** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/latency + https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/latency *Confidence: Verified* – Throughput vs. latency, TPM estimation, monitoring metrics. 6. **GenAI Gateway (APIM + PTU Optimization):** @@ -431,11 +431,11 @@ En hybrid tilnærming, der man kombinerer PTU for stabil baseline-traffic og Pay *Confidence: Verified* – Reservation purchase, scope, discounts, management. 8. **Dynamic Quota (Preview):** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/dynamic-quota + https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/dynamic-quota *Confidence: Verified* – PayGo deployment optimization, opportunistic quota increase. 9. **Spillover Traffic Management (Preview):** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/spillover-traffic-management + https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/spillover-traffic-management *Confidence: Verified* – Automatic routing fra PTU til PayGo ved capacity limit. **Code samples (MCP-verified):** diff --git a/skills/ms-ai-security/references/cost-optimization/rag-query-cost-reduction.md b/skills/ms-ai-security/references/cost-optimization/rag-query-cost-reduction.md index 12d9c35..f3703e6 100644 --- a/skills/ms-ai-security/references/cost-optimization/rag-query-cost-reduction.md +++ b/skills/ms-ai-security/references/cost-optimization/rag-query-cost-reduction.md @@ -433,7 +433,7 @@ User → Container App LB → [Azure OpenAI Region 1] **Verified:** 1. [Plan and manage costs of an Azure AI Search service](https://learn.microsoft.com/en-us/azure/search/search-sku-manage-costs) - Comprehensive cost minimization strategies, tier pricing, indexing optimization. -2. [Azure OpenAI On Your Data - Token usage estimation](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data) - Exact token consumption per model, RAG pipeline breakdown, parameter impacts. +2. [Azure OpenAI On Your Data - Token usage estimation](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data) - Exact token consumption per model, RAG pipeline breakdown, parameter impacts. 3. [RAG chunking phase - Understand chunking economics](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-chunking-phase) - Cache-Aside pattern, cost factors for chunking strategies. 4. [Agentic retrieval in Azure AI Search - Pricing example](https://learn.microsoft.com/en-us/azure/search/agentic-retrieval-overview) - Detailed cost calculation for agentic retrieval with subqueries. 5. [Tips for better performance in Azure AI Search](https://learn.microsoft.com/en-us/azure/search/search-performance-tips) - Query design optimization, search tier switching, cost-performance balance. diff --git a/skills/ms-ai-security/references/cost-optimization/request-batching-aggregation.md b/skills/ms-ai-security/references/cost-optimization/request-batching-aggregation.md index 5bc4580..278702e 100644 --- a/skills/ms-ai-security/references/cost-optimization/request-batching-aggregation.md +++ b/skills/ms-ai-security/references/cost-optimization/request-batching-aggregation.md @@ -493,7 +493,7 @@ Bruk denne matrisen for raskt å avgjøre om batching er riktig: ### Microsoft Learn (Verified via MCP) 1. **Azure OpenAI Batch API:** - - [Getting started with Azure OpenAI batch deployments](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch) — **Verified 2026-02** + - [Getting started with Azure OpenAI batch deployments](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch) — **Verified 2026-02** - Dekker: JSONL input format, Global-Batch deployment, 50% cost reduction, exponential backoff queuing 2. **Microsoft Graph JSON Batching:** @@ -505,7 +505,7 @@ Bruk denne matrisen for raskt å avgjøre om batching er riktig: - Dekker: Asynchronous inferencing, pipeline component deployments, low-priority VMs, scale-to-zero 4. **Code Samples (Python):** - - [Azure OpenAI Batch API - Create batch job](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch?pivots=programming-language-python#create-batch-job) — **Verified 2026-02** + - [Azure OpenAI Batch API - Create batch job](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch?pivots=programming-language-python#create-batch-job) — **Verified 2026-02** - [Azure Cosmos DB Transactional Batch](https://learn.microsoft.com/en-us/azure/cosmos-db/transactional-batch#how-to-create-a-transactional-batch-operation) — **Baseline (ikke AI-spesifikk, men relevant pattern)** ### Konfidensnivå per Seksjon diff --git a/skills/ms-ai-security/references/cost-optimization/reserved-capacity-planning.md b/skills/ms-ai-security/references/cost-optimization/reserved-capacity-planning.md index 5cc91e8..8ad7527 100644 --- a/skills/ms-ai-security/references/cost-optimization/reserved-capacity-planning.md +++ b/skills/ms-ai-security/references/cost-optimization/reserved-capacity-planning.md @@ -543,11 +543,11 @@ Tilgjengelig i deployment workflow: | Kilde | Type | Last Verified | |-------|------|---------------| | [Save costs with Microsoft Foundry Provisioned Throughput Reservations](https://learn.microsoft.com/en-us/azure/cost-management-billing/reservations/azure-openai) | Offisiell docs | 2026-01 | -| [Understanding costs associated with provisioned throughput units (PTU)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding) | Offisiell docs | 2026-01 | -| [Azure OpenAI provisioned Managed offering updates](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/provisioned-migration) | Offisiell docs | 2025-08 | +| [Understanding costs associated with provisioned throughput units (PTU)](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput-billing) | Offisiell docs | 2026-01 | +| [Azure OpenAI provisioned Managed offering updates](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/provisioned-migration) | Offisiell docs | 2025-08 | | [Purchase commitment tier pricing](https://learn.microsoft.com/en-us/azure/ai-services/commitment-tier) | Offisiell docs | 2026-01 | -| [What is provisioned throughput?](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/provisioned-throughput) | Offisiell docs | 2026-01 | -| [Azure OpenAI Provisioned Managed Offering in Azure Government](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/gov-provisioned) | Offisiell docs | 2025-05 | +| [What is provisioned throughput?](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput) | Offisiell docs | 2026-01 | +| [Azure OpenAI Provisioned Managed Offering in Azure Government](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure-gov) | Offisiell docs | 2025-05 | | [View Azure reservation utilization](https://learn.microsoft.com/en-us/azure/cost-management-billing/reservations/reservation-utilization) | Cost Management | 2025-12 | | [How reservation discounts are applied](https://learn.microsoft.com/en-us/azure/cost-management-billing/reservations/reservation-discount-application) | Cost Management | 2025-12 | | [Azure Pricing Calculator](https://azure.microsoft.com/pricing/calculator/) | Pricing tool | Live | diff --git a/skills/ms-ai-security/references/cost-optimization/small-language-models-economics.md b/skills/ms-ai-security/references/cost-optimization/small-language-models-economics.md index c33927f..78c606f 100644 --- a/skills/ms-ai-security/references/cost-optimization/small-language-models-economics.md +++ b/skills/ms-ai-security/references/cost-optimization/small-language-models-economics.md @@ -603,12 +603,12 @@ az webapp create --name webapp-slm-phi4 --resource-group rg-slm-norway --plan pl - Innhold: KAITO deployment, Phi-4-mini på AKS, GPU-krav 5. **Azure OpenAI in Azure AI Foundry Models** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models + - URL: https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure - Confidence: **Verified** - Innhold: GPT-4o, GPT-4o-mini pricing, capabilities 6. **Foundry Models from partners and community (Microsoft)** - - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/concepts/models-from-partners + - URL: https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-from-partners - Confidence: **Verified** - Innhold: Phi-4-mini-instruct, Phi-4-multimodal specs diff --git a/skills/ms-ai-security/references/cost-optimization/token-counting-optimization.md b/skills/ms-ai-security/references/cost-optimization/token-counting-optimization.md index 38e8df4..0756b9b 100644 --- a/skills/ms-ai-security/references/cost-optimization/token-counting-optimization.md +++ b/skills/ms-ai-security/references/cost-optimization/token-counting-optimization.md @@ -570,13 +570,13 @@ def track_token_usage(prompt, completion, model="gpt-4o"): ## Kilder og verifisering **Microsoft Learn Documentation:** -1. [Prompt caching - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/prompt-caching) -2. [Work with chat completions models - Token management](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chatgpt#manage-conversations) -3. [Plan and manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs) +1. [Prompt caching - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/prompt-caching) +2. [Work with chat completions models - Token management](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/chatgpt#manage-conversations) +3. [Plan and manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs) 4. [Token counting in AI - Dynamics 365 Business Central](https://learn.microsoft.com/en-us/dynamics365/business-central/dev-itpro/developer/ai-system-app-token-counting) 5. [Use Microsoft.ML.Tokenizers for text tokenization](https://learn.microsoft.com/en-us/dotnet/ai/how-to/use-tokenizers) -6. [Azure OpenAI On Your Data - Token usage estimation](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data) -7. [Cost management for fine-tuning](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/fine-tuning-cost-management) +6. [Azure OpenAI On Your Data - Token usage estimation](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data) +7. [Cost management for fine-tuning](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/fine-tuning-cost-management) **OpenAI Resources:** 8. [OpenAI Cookbook - Token counting](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb) diff --git a/skills/ms-ai-security/references/cost-optimization/vector-storage-cost-optimization.md b/skills/ms-ai-security/references/cost-optimization/vector-storage-cost-optimization.md index 2b1c051..eb27b9b 100644 --- a/skills/ms-ai-security/references/cost-optimization/vector-storage-cost-optimization.md +++ b/skills/ms-ai-security/references/cost-optimization/vector-storage-cost-optimization.md @@ -549,11 +549,11 @@ Hvis vector search brukes som grunnlag for Copilot for Microsoft 365: Confidence: Verified (MCP search results, januar 2026) 6. **Azure OpenAI embeddings models** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models + https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure Confidence: Verified (MCP search results, januar 2026) 7. **Azure OpenAI cost management** - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs + https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs Confidence: Verified (MCP search results, januar 2026) 8. **Storage optimization for vectors** diff --git a/skills/ms-ai-security/references/performance-scalability/async-processing-patterns.md b/skills/ms-ai-security/references/performance-scalability/async-processing-patterns.md index 16f6966..53f32bd 100644 --- a/skills/ms-ai-security/references/performance-scalability/async-processing-patterns.md +++ b/skills/ms-ai-security/references/performance-scalability/async-processing-patterns.md @@ -527,9 +527,9 @@ def publish_ordered_event( ## Referanser -- [Azure OpenAI Batch API](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/batch) — Batch processing -- [Azure OpenAI Responses API — Background tasks](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/responses) — Background mode -- [Azure OpenAI Webhooks](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/webhooks) — Event notifications +- [Azure OpenAI Batch API](https://learn.microsoft.com/azure/foundry/openai/how-to/batch) — Batch processing +- [Azure OpenAI Responses API — Background tasks](https://learn.microsoft.com/azure/foundry/openai/how-to/responses) — Background mode +- [Azure OpenAI Webhooks](https://learn.microsoft.com/azure/foundry/openai/how-to/webhooks) — Event notifications - [Event-driven architecture style](https://learn.microsoft.com/azure/architecture/guide/architecture-styles/event-driven) — Architecture patterns - [Azure Functions on Container Apps](https://learn.microsoft.com/azure/container-apps/functions-unified-platform) — Event-driven compute diff --git a/skills/ms-ai-security/references/performance-scalability/batch-api-usage-optimization.md b/skills/ms-ai-security/references/performance-scalability/batch-api-usage-optimization.md index 00e3ed5..147273a 100644 --- a/skills/ms-ai-security/references/performance-scalability/batch-api-usage-optimization.md +++ b/skills/ms-ai-security/references/performance-scalability/batch-api-usage-optimization.md @@ -206,7 +206,7 @@ with open("large_batch.jsonl", "rb") as data: ) # 2. Konfigurer Azure OpenAI til a bruke Blob Storage -# Se: https://learn.microsoft.com/azure/ai-foundry/openai/how-to/batch-blob-storage +# Se: https://learn.microsoft.com/azure/foundry-classic/openai/how-to/batch-blob-storage ``` ### Filgrenser diff --git a/skills/ms-ai-security/references/performance-scalability/concurrent-request-optimization.md b/skills/ms-ai-security/references/performance-scalability/concurrent-request-optimization.md index 3a246f1..c35157c 100644 --- a/skills/ms-ai-security/references/performance-scalability/concurrent-request-optimization.md +++ b/skills/ms-ai-security/references/performance-scalability/concurrent-request-optimization.md @@ -418,9 +418,9 @@ class FairScheduler: ## Referanser -- [Manage Azure OpenAI quota](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/quota) — RPM/TPM grenser -- [Performance and latency](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/latency) — Concurrent requests og throughput -- [Provisioned throughput](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/provisioned-get-started) — PTU utilization +- [Manage Azure OpenAI quota](https://learn.microsoft.com/azure/foundry-classic/openai/how-to/quota) — RPM/TPM grenser +- [Performance and latency](https://learn.microsoft.com/azure/foundry/openai/how-to/latency) — Concurrent requests og throughput +- [Provisioned throughput](https://learn.microsoft.com/azure/foundry/openai/how-to/provisioned-get-started) — PTU utilization ## For Cosmo diff --git a/skills/ms-ai-security/references/performance-scalability/gpu-compute-sizing.md b/skills/ms-ai-security/references/performance-scalability/gpu-compute-sizing.md index 81033d6..01cd4be 100644 --- a/skills/ms-ai-security/references/performance-scalability/gpu-compute-sizing.md +++ b/skills/ms-ai-security/references/performance-scalability/gpu-compute-sizing.md @@ -419,8 +419,8 @@ ml_client.online_deployments.begin_create_or_update(deployment).result() ## Referanser -- [What is provisioned throughput?](https://learn.microsoft.com/azure/ai-foundry/openai/concepts/provisioned-throughput) — PTU oversikt -- [PTU costs and billing](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding) — PTU-prising per modell +- [What is provisioned throughput?](https://learn.microsoft.com/azure/foundry/openai/concepts/provisioned-throughput) — PTU oversikt +- [PTU costs and billing](https://learn.microsoft.com/azure/foundry/openai/concepts/provisioned-throughput-billing) — PTU-prising per modell - [Foundry PTU calculator](https://ai.azure.com/resource/calculator) — Kapasitetskalkulator - [GPU optimized VM sizes](https://learn.microsoft.com/azure/virtual-machines/sizes-gpu) — Azure GPU VM-oversikt - [Deploy models in Azure ML](https://learn.microsoft.com/azure/machine-learning/how-to-deploy-online-endpoints) — ML endpoint deployment diff --git a/skills/ms-ai-security/references/performance-scalability/load-testing-ai-services.md b/skills/ms-ai-security/references/performance-scalability/load-testing-ai-services.md index 763a2bc..c8776e0 100644 --- a/skills/ms-ai-security/references/performance-scalability/load-testing-ai-services.md +++ b/skills/ms-ai-security/references/performance-scalability/load-testing-ai-services.md @@ -416,10 +416,10 @@ azure-openai-benchmark \ ## Referanser -- [Run a benchmark](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/provisioned-get-started#run-a-benchmark) — Azure OpenAI benchmarking guide +- [Run a benchmark](https://learn.microsoft.com/azure/foundry/openai/how-to/provisioned-get-started#run-a-benchmark) — Azure OpenAI benchmarking guide - [Azure OpenAI Benchmark Tool](https://github.com/Azure/azure-openai-benchmark) — Offisielt CLI-verktøy - [Azure Load Testing overview](https://learn.microsoft.com/azure/load-testing/overview-what-is-azure-load-testing) — Managed lasttesting -- [Performance and latency](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/latency) — Throughput vs latency forklaring +- [Performance and latency](https://learn.microsoft.com/azure/foundry/openai/how-to/latency) — Throughput vs latency forklaring - [Capacity planning](https://learn.microsoft.com/azure/well-architected/performance-efficiency/capacity-planning) — WAF kapasitetsplanlegging ## For Cosmo diff --git a/skills/ms-ai-security/references/performance-scalability/model-distillation-performance.md b/skills/ms-ai-security/references/performance-scalability/model-distillation-performance.md index 917a1c4..e3cb6da 100644 --- a/skills/ms-ai-security/references/performance-scalability/model-distillation-performance.md +++ b/skills/ms-ai-security/references/performance-scalability/model-distillation-performance.md @@ -428,9 +428,9 @@ def route_to_model(user_input: str) -> str: ## Referanser -- [Azure OpenAI stored completions & distillation](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/stored-completions) — Distillation workflow -- [Fine-tuning considerations](https://learn.microsoft.com/azure/ai-foundry/openai/concepts/fine-tuning-considerations) — Når fine-tuning er riktig -- [Customize a model with fine-tuning](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/fine-tuning) — Fine-tuning guide +- [Azure OpenAI stored completions & distillation](https://learn.microsoft.com/azure/foundry-classic/openai/how-to/stored-completions) — Distillation workflow +- [Fine-tuning considerations](https://learn.microsoft.com/azure/foundry/openai/concepts/fine-tuning-considerations) — Når fine-tuning er riktig +- [Customize a model with fine-tuning](https://learn.microsoft.com/azure/foundry/openai/how-to/fine-tuning) — Fine-tuning guide - [Choose the right AI model](https://learn.microsoft.com/azure/architecture/ai-ml/guide/choose-ai-model) — Modellvalg-guide ## For Cosmo diff --git a/skills/ms-ai-security/references/performance-scalability/performance-benchmarking-frameworks.md b/skills/ms-ai-security/references/performance-scalability/performance-benchmarking-frameworks.md index 8258c29..164b156 100644 --- a/skills/ms-ai-security/references/performance-scalability/performance-benchmarking-frameworks.md +++ b/skills/ms-ai-security/references/performance-scalability/performance-benchmarking-frameworks.md @@ -536,9 +536,9 @@ async def ci_benchmark_gate( - [Azure OpenAI Benchmark Tool](https://github.com/Azure/azure-openai-benchmark) — Offisielt CLI-verktøy - [Azure Load Testing](https://learn.microsoft.com/azure/load-testing/overview-what-is-azure-load-testing) — Managed lasttesting -- [Performance and latency](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/latency) — Ytelseskonsepter -- [Evaluate generative AI models](https://learn.microsoft.com/azure/ai-foundry/how-to/evaluate-generative-ai-app) — Kvalitetsevaluering -- [Azure Monitor metrics](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/monitor-openai) — Azure OpenAI monitoring +- [Performance and latency](https://learn.microsoft.com/azure/foundry/openai/how-to/latency) — Ytelseskonsepter +- [Evaluate generative AI models](https://learn.microsoft.com/azure/foundry/how-to/evaluate-generative-ai-app) — Kvalitetsevaluering +- [Azure Monitor metrics](https://learn.microsoft.com/azure/foundry-classic/openai/how-to/monitor-openai) — Azure OpenAI monitoring ## For Cosmo diff --git a/skills/ms-ai-security/references/performance-scalability/prompt-caching-performance.md b/skills/ms-ai-security/references/performance-scalability/prompt-caching-performance.md index 3a4a664..a699889 100644 --- a/skills/ms-ai-security/references/performance-scalability/prompt-caching-performance.md +++ b/skills/ms-ai-security/references/performance-scalability/prompt-caching-performance.md @@ -360,8 +360,8 @@ class CacheAwarePromptManager: ## Referanser -- [Prompt caching](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/prompt-caching) — Offisiell guide -- [Provisioned throughput](https://learn.microsoft.com/azure/ai-foundry/openai/concepts/provisioned-throughput) — PTU caching-fordeler +- [Prompt caching](https://learn.microsoft.com/azure/foundry/openai/how-to/prompt-caching) — Offisiell guide +- [Provisioned throughput](https://learn.microsoft.com/azure/foundry/openai/concepts/provisioned-throughput) — PTU caching-fordeler - [Semantic cache with Cosmos DB](https://learn.microsoft.com/azure/cosmos-db/gen-ai/semantic-cache) — Ekstern caching - [Application design for AI workloads](https://learn.microsoft.com/azure/well-architected/ai/application-design) — Multi-layer caching diff --git a/skills/ms-ai-security/references/performance-scalability/rate-limit-management.md b/skills/ms-ai-security/references/performance-scalability/rate-limit-management.md index 0c0dada..b3f246b 100644 --- a/skills/ms-ai-security/references/performance-scalability/rate-limit-management.md +++ b/skills/ms-ai-security/references/performance-scalability/rate-limit-management.md @@ -474,9 +474,9 @@ Microsoft dokumenterer multi-backend gateway som den anbefalte arkitekturmønste ## Referanser -- [Manage Azure OpenAI quota](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/quota) — Kvotehåndtering -- [Azure OpenAI quotas and limits](https://learn.microsoft.com/azure/ai-foundry/openai/quotas-limits) — Grenser per modell -- [Azure OpenAI SDK retry handling](https://learn.microsoft.com/azure/ai-foundry/openai/supported-languages) — SDK retry-konfigurasjon +- [Manage Azure OpenAI quota](https://learn.microsoft.com/azure/foundry-classic/openai/how-to/quota) — Kvotehåndtering +- [Azure OpenAI quotas and limits](https://learn.microsoft.com/azure/foundry/openai/quotas-limits) — Grenser per modell +- [Azure OpenAI SDK retry handling](https://learn.microsoft.com/azure/foundry/openai/supported-languages) — SDK retry-konfigurasjon - [Use a gateway in front of multiple Azure OpenAI deployments or instances](https://learn.microsoft.com/azure/architecture/ai-ml/guide/azure-openai-gateway-multi-backend) — Multi-region gateway (Azure OpenAI i Foundry Models) — Verified (MCP 2026-04) ## For Cosmo diff --git a/skills/ms-ai-security/references/performance-scalability/regional-deployment-latency.md b/skills/ms-ai-security/references/performance-scalability/regional-deployment-latency.md index 6839a39..6cc4017 100644 --- a/skills/ms-ai-security/references/performance-scalability/regional-deployment-latency.md +++ b/skills/ms-ai-security/references/performance-scalability/regional-deployment-latency.md @@ -399,7 +399,7 @@ Microsoft dokumenterer nå fire formelle topologier for Azure OpenAI gateway: - [Use a gateway in front of multiple Azure OpenAI deployments or instances](https://learn.microsoft.com/azure/architecture/ai-ml/guide/azure-openai-gateway-multi-backend) — Multi-region patterns (Azure OpenAI i Foundry Models) — Verified (MCP 2026-04) - [Azure Front Door](https://learn.microsoft.com/azure/frontdoor/front-door-overview) — Global load balancing - [APIM multi-region deployment](https://learn.microsoft.com/azure/api-management/api-management-howto-deploy-multi-region) — Regional gateway -- [Azure OpenAI deployment types](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/deployment-types) — Global vs Regional +- [Azure OpenAI deployment types](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/deployment-types) — Global vs Regional - [AI Ready — Establish AI reliability](https://learn.microsoft.com/azure/cloud-adoption-framework/scenarios/ai/ready) — Multi-region best practices ## For Cosmo diff --git a/skills/ms-ai-security/references/performance-scalability/response-chunking-strategies.md b/skills/ms-ai-security/references/performance-scalability/response-chunking-strategies.md index 7a4ccd0..8f23e95 100644 --- a/skills/ms-ai-security/references/performance-scalability/response-chunking-strategies.md +++ b/skills/ms-ai-security/references/performance-scalability/response-chunking-strategies.md @@ -464,7 +464,7 @@ class ResilientStreamProcessor: ## Referanser -- [Azure OpenAI streaming](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/responses) — Streaming API +- [Azure OpenAI streaming](https://learn.microsoft.com/azure/foundry/openai/how-to/responses) — Streaming API - [Server-Sent Events with Application Gateway](https://learn.microsoft.com/azure/application-gateway/use-server-sent-events) — SSE proxy - [API Management SSE configuration](https://learn.microsoft.com/azure/api-management/how-to-server-sent-events) — APIM SSE - [Server-Sent Events with App Gateway for Containers](https://learn.microsoft.com/azure/application-gateway/for-containers/server-sent-events) — Container SSE diff --git a/skills/ms-ai-security/references/performance-scalability/throughput-optimization-strategies.md b/skills/ms-ai-security/references/performance-scalability/throughput-optimization-strategies.md index 6100e65..25bcfc5 100644 --- a/skills/ms-ai-security/references/performance-scalability/throughput-optimization-strategies.md +++ b/skills/ms-ai-security/references/performance-scalability/throughput-optimization-strategies.md @@ -433,9 +433,9 @@ def submit_batch(client: AzureOpenAI, filename: str): ## Referanser -- [Performance and latency](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/latency) — Azure OpenAI latency og throughput -- [Azure OpenAI Batch API](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/batch) — Batch processing guide -- [Provisioned throughput onboarding](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding) — PTU sizing og kostnader +- [Performance and latency](https://learn.microsoft.com/azure/foundry/openai/how-to/latency) — Azure OpenAI latency og throughput +- [Azure OpenAI Batch API](https://learn.microsoft.com/azure/foundry/openai/how-to/batch) — Batch processing guide +- [Provisioned throughput onboarding](https://learn.microsoft.com/azure/foundry/openai/concepts/provisioned-throughput-billing) — PTU sizing og kostnader - [Azure OpenAI Benchmark Tool](https://github.com/Azure/azure-openai-benchmark) — Offisielt benchmarking-verktøy ## For Cosmo diff --git a/skills/ms-ai-security/references/performance-scalability/token-per-second-optimization.md b/skills/ms-ai-security/references/performance-scalability/token-per-second-optimization.md index 1978115..e6a174d 100644 --- a/skills/ms-ai-security/references/performance-scalability/token-per-second-optimization.md +++ b/skills/ms-ai-security/references/performance-scalability/token-per-second-optimization.md @@ -328,10 +328,10 @@ print(f"Rejected predictions: {usage.rejected_prediction_tokens}") ## Referanser -- [Performance and latency](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/latency) — TPS og throughput forklaring -- [Provisioned throughput onboarding](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding) — PTU TPS-mål per modell -- [Prompt caching](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/prompt-caching) — Cache-basert TPS-forbedring -- [Predicted outputs](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/predicted-outputs) — Spekulativ generering +- [Performance and latency](https://learn.microsoft.com/azure/foundry/openai/how-to/latency) — TPS og throughput forklaring +- [Provisioned throughput onboarding](https://learn.microsoft.com/azure/foundry/openai/concepts/provisioned-throughput-billing) — PTU TPS-mål per modell +- [Prompt caching](https://learn.microsoft.com/azure/foundry/openai/how-to/prompt-caching) — Cache-basert TPS-forbedring +- [Predicted outputs](https://learn.microsoft.com/azure/foundry/openai/how-to/predicted-outputs) — Spekulativ generering - [Foundry PTU calculator](https://ai.azure.com/resource/calculator) — Kapasitetskalkulator ## For Cosmo