import { ILlmSchema } from "./structures/ILlmSchema";
import { IMcpLlmApplication } from "./structures/IMcpLlmApplication";
import { IMcpTool } from "./structures/IMcpTool";
/**
 * Application of LLM function calling from MCP document.
 *
 * `McpLlm` is a module for composing LLM (Large Language Model) function
 * calling application from MCP (Model Context Protocol) document.
 *
 * The reasons why `@samchon/openapi` recommends to use the function calling
 * feature instead of directly using the
 * [`mcp_servers`](https://openai.github.io/openai-agents-python/mcp/#using-mcp-servers)
 * property of LLM API are:
 *
 * - Model Specification: {@link ILlmSchema}
 * - Validation Feedback: {@link IMcpLlmFunction.validate}
 * - Selector agent for reducing context: [Agentica > Orchestration Strategy](https://wrtnlabs.io/agentica/docs/concepts/function-calling/#orchestration-strategy)
 *
 * @author Jeongho Nam - https://github.com/samchon
 */
export declare namespace McpLlm {
    /**
     * Properties for the LLM function calling application composer.
     *
     * @template Model Target LLM model
     */
    interface IApplicationProps<Model extends ILlmSchema.Model> {
        /**
         * Target LLM model.
         */
        model: Model;
        /**
         * List of tools.
         *
         * A list of tools defined in the MCP (Model Context Protocol) document.
         *
         * It would better to validate the tools by
         * [`typia.assert<T>()`](https://typia.io/docs/validate/assert) function
         * for the type safety.
         */
        tools: Array<IMcpTool>;
        /**
         * Options for the LLM function calling schema conversion.
         */
        options?: Partial<IMcpLlmApplication.IOptions<Model>>;
    }
    /**
     * Convert MCP document to LLM function calling application.
     *
     * Converts MCP (Model Context Protocol) to LLM (Large Language Model)
     * function calling application.
     *
     * The reasons why `@samchon/openapi` recommends to use the function calling
     * feature instead of directly using the
     * [`mcp_servers`](https://openai.github.io/openai-agents-python/mcp/#using-mcp-servers)
     * property of LLM API are:
     *
     * - Model Specification: {@link ILlmSchema}
     * - Validation Feedback: {@link IMcpLlmFunction.validate}
     * - Selector agent for reducing context: [Agentica > Orchestration Strategy](https://wrtnlabs.io/agentica/docs/concepts/function-calling/#orchestration-strategy)
     *
     * @param props Properties for composition
     * @returns LLM function calling application
     */
    const application: <Model extends ILlmSchema.Model>(props: IApplicationProps<Model>) => IMcpLlmApplication<Model>;
}