Semantic Kernel: A bridge between large language models and your code

At first glance, building a large language model (LLM) like GPT-4 into your code might seem simple. The API is a single REST call, taking in text and returning a response based on the input. But in practice things get much more complicated than that. The API is perhaps better thought of as a domain boundary, where you’re delivering prompts that define the format the model uses to deliver its output. But that’s a critical point: LLMs can be …

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