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Semantic Kernel has different sets of classes for function calling. One set is for the AzureOpenAI and OpenAI connectors, another for the Gemini connector, and a third for the Mistral connector.
These function-calling classes are almost the same, with only small differences, as each set is linked to the internal code of its specific AI connector. This means the same function-calling classes can't be reused across different connectors, so a new set must be created for each new AI connector.
The new function-calling approach solves this problem by being connector/service agnostic. It’s part of the Semantic Kernel’s core design and works with any AI connector that supports function-calling AI models. This makes the function-calling model reusable and flexible, allowing the same configuration and behavior to be used by different AI connectors.
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