import { ILlmFunction } from "./ILlmFunction";
import { ILlmSchema } from "./ILlmSchema";
/**
 * Application of LLM function calling.
 *
 * `ILlmApplication` is a data structure representing a collection of
 * {@link ILlmFunction LLM function calling schemas}, composed from a native
 * TypeScript class (or interface) type by the `typia.llm.application<App, Model>()`
 * function.
 *
 * Also, there can be some parameters (or their nested properties) which must be
 * composed by Human, not by LLM. File uploading feature or some sensitive information
 * like secret key (password) are the examples. In that case, you can separate the
 * function parameters to both LLM and human sides by configuring the
 * {@link ILlmApplication.IOptions.separate} property. The separated parameters are
 * assigned to the {@link ILlmFunction.separated} property.
 *
 * For reference, when both LLM and Human filled parameter values to call, you can
 * merge them by calling the {@link HttpLlm.mergeParameters} function. In other words,
 * if you've configured the {@link ILlmApplication.IOptions.separate} property, you
 * have to merge the separated parameters before the function call execution.
 *
 * @reference https://platform.openai.com/docs/guides/function-calling
 * @author Jeongho Nam - https://github.com/samchon
 */
export interface ILlmApplication<Model extends ILlmSchema.Model, Class extends object = any> {
    /**
     * Model of the LLM.
     */
    model: Model;
    /**
     * List of function metadata.
     *
     * List of function metadata that can be used for the LLM function call.
     */
    functions: ILlmFunction<Model>[];
    /**
     * Configuration for the application.
     */
    options: ILlmApplication.IOptions<Model>;
    /**
     * Class type, the source of the LLM application.
     *
     * This property is just for the generic type inference,
     * and its value is always `undefined`.
     */
    __class?: Class | undefined;
}
export declare namespace ILlmApplication {
    /**
     * Options for application composition.
     */
    type IOptions<Model extends ILlmSchema.Model> = {
        /**
         * Separator function for the parameters.
         *
         * When composing parameter arguments through LLM function call,
         * there can be a case that some parameters must be composed by human,
         * or LLM cannot understand the parameter.
         *
         * For example, if the parameter type has configured
         * {@link IGeminiSchema.IString.contentMediaType} which indicates file
         * uploading, it must be composed by human, not by LLM
         * (Large Language Model).
         *
         * In that case, if you configure this property with a function that
         * predicating whether the schema value must be composed by human or
         * not, the parameters would be separated into two parts.
         *
         * - {@link ILlmFunction.separated.llm}
         * - {@link ILlmFunction.separated.human}
         *
         * When writing the function, note that returning value `true` means
         * to be a human composing the value, and `false` means to LLM
         * composing the value. Also, when predicating the schema, it would
         * better to utilize the {@link GeminiTypeChecker} like features.
         *
         * @param schema Schema to be separated.
         * @returns Whether the schema value must be composed by human or not.
         * @default null
         */
        separate: null | ((schema: ILlmSchema.ModelSchema[Model]) => boolean);
    } & ILlmSchema.ModelConfig[Model];
}