@aws-sdk/client-lex-runtime-service/commands/PostContentCommand.ts

AWS SDK for JavaScript Lex Runtime Service Client for Node.js, Browser and React Native

import {
  LexRuntimeServiceClientResolvedConfig,
  ServiceInputTypes,
  ServiceOutputTypes,
} from "../LexRuntimeServiceClient";
import { PostContentRequest, PostContentResponse } from "../models/models_0";
import {
  deserializeAws_restJson1PostContentCommand,
  serializeAws_restJson1PostContentCommand,
} from "../protocols/Aws_restJson1";
import { getSerdePlugin } from "@aws-sdk/middleware-serde";
import { HttpRequest as __HttpRequest, HttpResponse as __HttpResponse } from "@aws-sdk/protocol-http";
import { Command as $Command } from "@aws-sdk/smithy-client";
import {
  FinalizeHandlerArguments,
  Handler,
  HandlerExecutionContext,
  MiddlewareStack,
  HttpHandlerOptions as __HttpHandlerOptions,
  MetadataBearer as __MetadataBearer,
  SerdeContext as __SerdeContext,
} from "@aws-sdk/types";

export type PostContentCommandInput = Omit<PostContentRequest, "inputStream"> & {
  inputStream: PostContentRequest["inputStream"] | string | Uint8Array | Buffer;
};
export type PostContentCommandOutput = PostContentResponse & __MetadataBearer;

/**
 * <p> Sends user input (text or speech) to Amazon Lex. Clients use this API to send text and audio
 *       requests to Amazon Lex at runtime. Amazon Lex interprets the user input using the machine learning model
 *       that it built for the bot. </p>
 *          <p>The <code>PostContent</code> operation supports audio input at 8kHz and 16kHz. You can use
 *       8kHz audio to achieve higher speech recognition accuracy in telephone audio applications. </p>
 *          <p> In response, Amazon Lex returns the next message to convey to the user. Consider the following
 *       example messages: </p>
 *          <ul>
 *             <li>
 *                <p> For a user input "I would like a pizza," Amazon Lex might return a response with a message
 *           eliciting slot data (for example, <code>PizzaSize</code>): "What size pizza would you
 *           like?". </p>
 *             </li>
 *             <li>
 *                <p> After the user provides all of the pizza order information, Amazon Lex might return a
 *           response with a message to get user confirmation: "Order the pizza?". </p>
 *             </li>
 *             <li>
 *                <p> After the user replies "Yes" to the confirmation prompt, Amazon Lex might return a
 *           conclusion statement: "Thank you, your cheese pizza has been ordered.". </p>
 *             </li>
 *          </ul>
 *          <p> Not all Amazon Lex messages require a response from the user. For example, conclusion
 *       statements do not require a response. Some messages require only a yes or no response. In
 *       addition to the <code>message</code>, Amazon Lex provides additional context about the message in
 *       the response that you can use to enhance client behavior, such as displaying the appropriate
 *       client user interface. Consider the following examples: </p>
 *          <ul>
 *             <li>
 *                <p> If the message is to elicit slot data, Amazon Lex returns the following context
 *           information: </p>
 *                <ul>
 *                   <li>
 *                      <p>
 *                         <code>x-amz-lex-dialog-state</code> header set to <code>ElicitSlot</code>
 *                      </p>
 *                   </li>
 *                   <li>
 *                      <p>
 *                         <code>x-amz-lex-intent-name</code> header set to the intent name in the current
 *               context </p>
 *                   </li>
 *                   <li>
 *                      <p>
 *                         <code>x-amz-lex-slot-to-elicit</code> header set to the slot name for which the
 *                 <code>message</code> is eliciting information </p>
 *                   </li>
 *                   <li>
 *                      <p>
 *                         <code>x-amz-lex-slots</code> header set to a map of slots configured for the intent
 *               with their current values </p>
 *                   </li>
 *                </ul>
 *             </li>
 *             <li>
 *                <p> If the message is a confirmation prompt, the <code>x-amz-lex-dialog-state</code>
 *           header is set to <code>Confirmation</code> and the <code>x-amz-lex-slot-to-elicit</code>
 *           header is omitted. </p>
 *             </li>
 *             <li>
 *                <p> If the message is a clarification prompt configured for the intent, indicating that
 *           the user intent is not understood, the <code>x-amz-dialog-state</code> header is set to
 *             <code>ElicitIntent</code> and the <code>x-amz-slot-to-elicit</code> header is omitted.
 *         </p>
 *             </li>
 *          </ul>
 *          <p> In addition, Amazon Lex also returns your application-specific <code>sessionAttributes</code>.
 *       For more information, see <a href="https://docs.aws.amazon.com/lex/latest/dg/context-mgmt.html">Managing Conversation Context</a>. </p>
 */
export class PostContentCommand extends $Command<
  PostContentCommandInput,
  PostContentCommandOutput,
  LexRuntimeServiceClientResolvedConfig
> {
  // Start section: command_properties
  // End section: command_properties

  constructor(readonly input: PostContentCommandInput) {
    // Start section: command_constructor
    super();
    // End section: command_constructor
  }

  /**
   * @internal
   */
  resolveMiddleware(
    clientStack: MiddlewareStack<ServiceInputTypes, ServiceOutputTypes>,
    configuration: LexRuntimeServiceClientResolvedConfig,
    options?: __HttpHandlerOptions
  ): Handler<PostContentCommandInput, PostContentCommandOutput> {
    this.middlewareStack.use(getSerdePlugin(configuration, this.serialize, this.deserialize));

    const stack = clientStack.concat(this.middlewareStack);

    const { logger } = configuration;
    const clientName = "LexRuntimeServiceClient";
    const commandName = "PostContentCommand";
    const handlerExecutionContext: HandlerExecutionContext = {
      logger,
      clientName,
      commandName,
      inputFilterSensitiveLog: PostContentRequest.filterSensitiveLog,
      outputFilterSensitiveLog: PostContentResponse.filterSensitiveLog,
    };
    const { requestHandler } = configuration;
    return stack.resolve(
      (request: FinalizeHandlerArguments<any>) =>
        requestHandler.handle(request.request as __HttpRequest, options || {}),
      handlerExecutionContext
    );
  }

  private serialize(input: PostContentCommandInput, context: __SerdeContext): Promise<__HttpRequest> {
    return serializeAws_restJson1PostContentCommand(input, context);
  }

  private deserialize(output: __HttpResponse, context: __SerdeContext): Promise<PostContentCommandOutput> {
    return deserializeAws_restJson1PostContentCommand(output, context);
  }

  // Start section: command_body_extra
  // End section: command_body_extra
}