import { HttpMigration } from "./HttpMigration";
import { OpenApi } from "./OpenApi";
import { OpenApiV3 } from "./OpenApiV3";
import { OpenApiV3_1 } from "./OpenApiV3_1";
import { SwaggerV2 } from "./SwaggerV2";
import { HttpLlmComposer } from "./composers/HttpLlmApplicationComposer";
import { LlmSchemaComposer } from "./composers/LlmSchemaComposer";
import { HttpLlmFunctionFetcher } from "./http/HttpLlmFunctionFetcher";
import { IHttpConnection } from "./structures/IHttpConnection";
import { IHttpLlmApplication } from "./structures/IHttpLlmApplication";
import { IHttpLlmFunction } from "./structures/IHttpLlmFunction";
import { IHttpMigrateApplication } from "./structures/IHttpMigrateApplication";
import { IHttpResponse } from "./structures/IHttpResponse";
import { ILlmFunction } from "./structures/ILlmFunction";
import { ILlmSchema } from "./structures/ILlmSchema";
import { LlmDataMerger } from "./utils/LlmDataMerger";

/**
 * LLM function calling application composer from OpenAPI document.
 *
 * `HttpLlm` is a module for composing LLM (Large Language Model) function calling
 * application from the {@link OpenApi.IDocument OpenAPI document}, and also for
 * LLM function call execution and parameter merging.
 *
 * At first, you can construct the LLM function calling application by the
 * {@link HttpLlm.application HttpLlm.application()} function. And then the LLM
 * has selected a {@link IHttpLlmFunction function} to call and composes its
 * arguments, you can execute the function by
 * {@link HttpLlm.execute HttpLlm.execute()} or
 * {@link HttpLlm.propagate HttpLlm.propagate()}.
 *
 * By the way, if you have configured the {@link IHttpLlmApplication.IOptions.separate}
 * option to separate the parameters into human and LLM sides, you can merge these
 * human and LLM sides' parameters into one through
 * {@link HttpLlm.mergeParameters HttpLlm.mergeParameters()} before the actual LLM
 * function call execution.
 *
 * @author Jeongho Nam - https://github.com/samchon
 */
export namespace HttpLlm {
  /* -----------------------------------------------------------
    COMPOSERS
  ----------------------------------------------------------- */
  /**
   * Properties for the LLM function calling application composer.
   *
   * @template Model Target LLM model
   */
  export interface IApplicationProps<Model extends ILlmSchema.Model> {
    /**
     * Target LLM model.
     */
    model: Model;

    /**
     * OpenAPI document to convert.
     */
    document:
      | OpenApi.IDocument
      | SwaggerV2.IDocument
      | OpenApiV3.IDocument
      | OpenApiV3_1.IDocument;

    /**
     * Options for the LLM function calling schema conversion.
     */
    options?: Partial<IHttpLlmApplication.IOptions<Model>>;
  }

  /**
   * Convert OpenAPI document to LLM function calling application.
   *
   * Converts {@link OpenApi.IDocument OpenAPI document} or
   * {@link IHttpMigrateApplication migrated application} to the
   * {@link IHttpLlmApplication LLM function calling application}. Every
   * {@link OpenApi.IOperation API operations} in the OpenAPI document are converted
   * to the {@link IHttpLlmFunction LLM function} type, and they would be used for
   * the LLM function calling.
   *
   * If you have configured the {@link IHttpLlmApplication.IOptions.separate} option,
   * every parameters in the {@link IHttpLlmFunction} would be separated into both
   * human and LLM sides. In that case, you can merge these human and LLM sides'
   * parameters into one through {@link HttpLlm.mergeParameters} before the actual
   * LLM function call execution.
   *
   * Additionally, if you have configured the {@link IHttpLlmApplication.IOptions.keyword}
   * as `true`, the number of {@link IHttpLlmFunction.parameters} are always 1 and the
   * first parameter type is always {@link ILlmSchemaV3.IObject}. I recommend this option
   * because LLM can understand the keyword arguments more easily.
   *
   * @param props Properties for composition
   * @returns LLM function calling application
   */
  export const application = <Model extends ILlmSchema.Model>(
    props: IApplicationProps<Model>,
  ): IHttpLlmApplication<Model> => {
    // MIGRATE
    const migrate: IHttpMigrateApplication = HttpMigration.application(
      props.document,
    );
    const defaultConfig: ILlmSchema.IConfig<Model> =
      LlmSchemaComposer.defaultConfig(props.model);
    return HttpLlmComposer.application<Model>({
      migrate,
      model: props.model,
      options: {
        ...Object.fromEntries(
          Object.entries(defaultConfig).map(
            ([key, value]) =>
              [key, (props.options as any)?.[key] ?? value] as const,
          ),
        ),
        separate: props.options?.separate ?? null,
        maxLength: props.options?.maxLength ?? 64,
      } as any as IHttpLlmApplication.IOptions<Model>,
    });
  };

  /* -----------------------------------------------------------
    FETCHERS
  ----------------------------------------------------------- */
  /**
   * Properties for the LLM function call.
   */
  export interface IFetchProps<Model extends ILlmSchema.Model> {
    /**
     * Application of the LLM function calling.
     */
    application: IHttpLlmApplication<Model>;

    /**
     * LLM function schema to call.
     */
    function: IHttpLlmFunction<ILlmSchema.Model>;

    /**
     * Connection info to the HTTP server.
     */
    connection: IHttpConnection;

    /**
     * Input arguments for the function call.
     */
    input: object;
  }

  /**
   * Execute the LLM function call.
   *
   * `HttmLlm.execute()` is a function executing the target
   * {@link OpenApi.IOperation API endpoint} with with the connection information
   * and arguments composed by Large Language Model like OpenAI (+human sometimes).
   *
   * By the way, if you've configured the {@link IHttpLlmApplication.IOptions.separate},
   * so that the parameters are separated to human and LLM sides, you have to merge
   * these humand and LLM sides' parameters into one through
   * {@link HttpLlm.mergeParameters} function.
   *
   * About the {@link IHttpLlmApplication.IOptions.keyword} option, don't worry anything.
   * This `HttmLlm.execute()` function will automatically recognize the keyword arguments
   * and convert them to the proper sequence.
   *
   * For reference, if the target API endpoinnt responds none 200/201 status, this
   * would be considered as an error and the {@link HttpError} would be thrown.
   * Otherwise you don't want such rule, you can use the {@link HttpLlm.propagate}
   * function instead.
   *
   * @param props Properties for the LLM function call
   * @returns Return value (response body) from the API endpoint
   * @throws HttpError when the API endpoint responds none 200/201 status
   */
  export const execute = <Model extends ILlmSchema.Model>(
    props: IFetchProps<Model>,
  ): Promise<unknown> => HttpLlmFunctionFetcher.execute<Model>(props);

  /**
   * Propagate the LLM function call.
   *
   * `HttmLlm.propagate()` is a function propagating the target
   * {@link OpenApi.IOperation API endpoint} with with the connection information
   * and arguments composed by Large Language Model like OpenAI (+human sometimes).
   *
   * By the way, if you've configured the {@link IHttpLlmApplication.IOptions.separate},
   * so that the parameters are separated to human and LLM sides, you have to merge
   * these humand and LLM sides' parameters into one through
   * {@link HttpLlm.mergeParameters} function.
   *
   * About the {@link IHttpLlmApplication.IOptions.keyword} option, don't worry anything.
   * This `HttmLlm.propagate()` function will automatically recognize the keyword arguments
   * and convert them to the proper sequence.
   *
   * For reference, the propagation means always returning the response from the API
   * endpoint, even if the status is not 200/201. This is useful when you want to
   * handle the response by yourself.
   *
   * @param props Properties for the LLM function call
   * @returns Response from the API endpoint
   * @throws Error only when the connection is failed
   */
  export const propagate = <Model extends ILlmSchema.Model>(
    props: IFetchProps<Model>,
  ): Promise<IHttpResponse> => HttpLlmFunctionFetcher.propagate<Model>(props);

  /* -----------------------------------------------------------
    MERGERS
  ----------------------------------------------------------- */
  /**
   * Properties for the parameters' merging.
   */
  export interface IMergeProps<Model extends ILlmSchema.Model> {
    /**
     * Metadata of the target function.
     */
    function: ILlmFunction<Model>;

    /**
     * Arguments composed by the LLM.
     */
    llm: object | null;

    /**
     * Arguments composed by the human.
     */
    human: object | null;
  }

  /**
   * Merge the parameters.
   *
   * If you've configured the {@link IHttpLlmApplication.IOptions.separate} option,
   * so that the parameters are separated to human and LLM sides, you can merge these
   * humand and LLM sides' parameters into one through this `HttpLlm.mergeParameters()`
   * function before the actual LLM function call wexecution.
   *
   * On contrary, if you've not configured the
   * {@link IHttpLlmApplication.IOptions.separate} option, this function would throw
   * an error.
   *
   * @param props Properties for the parameters' merging
   * @returns Merged parameter values
   */
  export const mergeParameters = <Model extends ILlmSchema.Model>(
    props: IMergeProps<Model>,
  ): object => LlmDataMerger.parameters(props);

  /**
   * Merge two values.
   *
   * If both values are objects, then combines them in the properties level.
   *
   * Otherwise, returns the latter value if it's not null, otherwise the former value.
   *
   * - `return (y ?? x)`
   *
   * @param x Value X to merge
   * @param y Value Y to merge
   * @returns Merged value
   */
  export const mergeValue = (x: unknown, y: unknown): unknown =>
    LlmDataMerger.value(x, y);
}