How To Use Semantic Kernel
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What it is
Semantic Kernel is Microsoft’s open-source SDK for orchestrating LLMs, plugins, and planners in C#, Python, or Java.
Install / sign up
Where LangChain optimises for breadth and experimentation, Semantic Kernel targets enterprise apps: strong typing, dependency injection, telemetry, and first-class support for Azure OpenAI. It’s the framework powering much of Microsoft’s own Copilot surface.
First session
Semantic Kernel exposes a Kernel object that wires together AI services (chat, embeddings, image), plugins (callable functions the model can invoke), memory (vector stores), and planners that turn a goal into a sequence of function calls. It’s available as NuGet, PyPI, and Maven packages with near-parity across languages.
Everyday workflows
Create a Kernel, register a chat service, and add a plugin. The model can then call your plugin functions automatically when it decides they’re relevant.
Gotchas and tips
Semantic Kernel leans heavily on dependency injection; in .NET especially, register services on the host builder rather than newing up a Kernel manually — you’ll get proper logging and configuration. Use the OpenTelemetry integration early so you can debug long plugin chains.
Who it’s for
Planners can burn tokens quickly; prefer explicit function composition when the workflow is known and reserve planners for open-ended goals. The Python and .NET SDKs occasionally drift — pin versions in production and check release notes for breaking changes in the preview packages.