• Once the integration is set up, the Lex bot will send intent requests to the Lambda function, which will then process the requests and return a response to the bot. The bot will use the response to generate a response to the user.
  • AWS-Lexbot with API integration using AWS Lambda (Sample Bot)​

    AWS-Lexbot with API integration using AWS Lambda (Sample Bot)

    The release of the AWS-Lexbot with API integration using AWS Lambda function at Vivify Healthcare is part of the company’s research and development efforts to find the best technology stack that is both sustainable and affordable. The company is constantly looking for ways to improve its offerings and stay ahead of the curve in the highly competitive healthcare industry. By utilizing the power and scalability of AWS, Vivify Healthcare aims to deliver a top-notch user experience while keeping costs low and maintaining stability and security. The integration of Lex and Lambda provides a flexible, scalable solution that can be easily adapted to meet the changing needs of the business and its customers

    What is Amazon Lex ?

    Amazon Lex is a conversational interface that allows developers to build chatbots and other conversational applications powered by natural language processing (NLP) and machine learning (ML) technology. It is a part of Amazon Web Services (AWS) and enables developers to create conversational bots that can understand text and voice commands in multiple languages.

    With Amazon Lex, developers can design and build conversational interfaces for a wide range of applications, including customer service, virtual assistants, and voice-enabled IoT devices. It offers a flexible, easy-to-use platform that provides automatic speech recognition, natural language understanding, and dialog management. Developers can also integrate Amazon Lex with other AWS services, such as AWS Lambda and Amazon DynamoDB, to build more complex and powerful conversational applications.

    What is Amazon Lambda ?

    Amazon Lambda is a serverless compute service offered by Amazon Web Services (AWS). It allows developers to run code in response to events, without having to provision or manage servers. Lambda runs the code only when needed and automatically scales to accommodate the size of the workload.

    Developers can use Lambda to build serverless applications that automatically scale in response to incoming traffic, as well as to create event-driven workflows for processing data or triggering actions. It supports a wide range of programming languages, including Python, Node.js, Java, and C#, and integrates with other AWS services such as Amazon S3, Amazon DynamoDB, and Amazon API Gateway or Swagger UI.

    Lambda provides a flexible, cost-effective way to build and run applications without the need for managing infrastructure, enabling developers to focus on writing code and delivering value to their users.

    What is API Integration ?

    API integration refers to the process of connecting different software systems through the use of APIs (Application Programming Interfaces). APIs are sets of protocols and tools used for building software applications and enable different systems to communicate and exchange data.

    API integration is important because it allows applications to share data and functionality, enabling developers to build more powerful and feature-rich applications. With API integration, developers can leverage the functionality of multiple systems without having to build everything from scratch, reducing development time and costs.

    API integration can be done through various methods, such as REST (Representational State Transfer) APIs, SOAP (Simple Object Access Protocol) APIs, and GraphQL. It is an essential aspect of modern software development, enabling developers to build scalable, flexible, and robust applications.

    Showcase Integrated Bot with Amazon LEX

    This is a sample Amazon Lex web interface. It provides a chatbot UI component that can be integrated in your website. The interface allows a user to interact with a Lex bot directly from a browser using text or voice. It can be used as a full page chatbot UI:


    • Mobile ready responsive UI with full page or embeddable widget modes
    • Support for voice and text with the ability to seamless switch from one mode to the other
    • Voice support provides automatic silence detection, transcriptions and ability to interrupt responses and replay recordings
    • Display of Lex response cards
    • Ability to programmatically configure and interact with the chatbot UI using JavaScript
    • API Connectivity

    Getting Started

    The easiest way to test drive the chatbot UI is to deploy it using the AWS CloudFormation templates provided by this project. Once you have launched the CloudFormation stack, you will get a fully working demo site hosted in your account. For more Details of configuration and activation of AWS Lex Bot in your AWS Account. You can go through https://github.com/vivifyhealthcare/aws-lex-web-ui

    Integrate API’s in AWS Lambda Function

    • To integrate APIs in an AWS Lambda function, you can follow these steps:
      • Create a Lambda function in the AWS Management Console.
      • Select the appropriate runtime (e.g. Node.js, Python, etc.) for your function.
      • Write the code for your function, including the API integration logic.
      • Create a REST API using API Gateway, and configure it to trigger your Lambda function.
      • Deploy the API to a stage and test it by making API requests.
      • Optionally, you can add authentication and authorization to your API using AWS Cognito or IAM.
    • You can also integrate API in AWS Lambda by using the Serverless Framework or AWS CloudFormation. These tools allow you to automate the deployment and management of your API and Lambda function.

    Connect AWS Lambda Function in AWS Lex Bot

    • To connect an AWS Lambda function to an AWS Lex bot, follow these steps:
      • Create a Lambda function in the AWS Management Console or using the AWS CLI.
      • Write the code for your function, which should contain the logic for handling the intent requests from the Lex bot.
      • In the AWS Management Console, navigate to the Lex bot and select the appropriate intent.
      • In the Intent Editor, go to the “Fulfillment” section.
      • Choose “AWS Lambda Function” as the fulfillment method and select the Lambda function you created.
      • Save and build the bot.
      • Test the integration by using the “Test Bot” feature in the Lex Console.
    • Once the integration is set up, the Lex bot will send intent requests to the Lambda function, which will then process the requests and return a response to the bot. The bot will use the response to generate a response to the user.
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