microsoft-extensions-ai

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Build provider-agnostic .NET AI integrations with `Microsoft.Extensions.AI`, `IChatClient`, embeddings, middleware, structured output, vector search, and evaluation. USE FOR: building or reviewing .NET code that uses Microsoft.Extensions.AI, Microsoft.Extensions.AI.Abstractions, IChatClient, IEmbeddingGenerator, ChatOptions, or AIFunction;. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

AI & Automation 479 stars 35 forks Updated 6 days ago MIT

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Quality Score: 92/100

Stars 20%
89
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Microsoft.Extensions.AI ## Trigger On - building or reviewing `.NET` code that uses `Microsoft.Extensions.AI`, `Microsoft.Extensions.AI.Abstractions`, `IChatClient`, `IEmbeddingGenerator`, `ChatOptions`, or `AIFunction` - adding `IImageGenerator`, local-model chat via Ollama, AI app templates, or the `.NET AI` quickstarts for assistants and MCP - choosing between low-level AI abstractions, provider SDKs, vector-search composition, evaluation libraries, and a fuller agent framework - adding streaming chat, structured output, embeddings, tool calling, telemetry, caching, or DI-based AI middleware - wiring `Microsoft.Extensions.VectorData`, `Microsoft.Extensions.DataIngestion`, MCP tooling, or evaluation packages around a provider-agnostic AI app ## Workflow 1. Classify the request first: plain model access, tool calling, embeddings/vector search, evaluation, image generation, local-model prototyping, MCP bootstrap, or true agent orchestration. 2. Default to `Microsoft.Extensions.AI` for application and service code that needs provider-agnostic chat, embeddings, middleware, structured output, and testability. 3. Reference `Microsoft.Extensions.AI.Abstractions` directly only when authoring provider libraries or lower-level reusable integration packages. 4. Model `IChatClient` and `IEmbeddingGenerator` composition explicitly in DI. Keep options, caching, telemetry, logging, and tool invocation inspectable in the pipeline. 5. Treat chat state deliberately. For stateless provi...

Details

Author
managedcode
Repository
managedcode/dotnet-skills
Created
6 months ago
Last Updated
6 days ago
Language
C#
License
MIT

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