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Creating an AI agent using Amazon Bedrock involves configuring foundation models, defining tools, and deploying an agent capable of interacting with users and systems. Below is a step-by-step guide with visual references and a clear explanation . Step 1: Understand Amazon Bedrock Architecture Core components: Foundation Model (FM) – Claude, Titan, Llama, etc. Agent – Orchestrates reasoning and actions Knowledge Base – Connects to your data (S3, PDFs, databases) Action Groups – Lambda functions for performing tasks Client Application – Web app, chatbot, or API Step 2: Enable Amazon Bedrock To enable the Amazon Bedrock -  Login to AWS Console Search → Amazon Bedrock Click → Model access Enable models like: Claude (best for agents) Titan Llama Step 3: Create Knowledge Base (Optional but Recommended) A knowledge base allows agents to use your custom data. To create a Knowledge Base -  Steps: Go to Bedrock Console Click → Knowledge Bases ...

In this tutorial, we will see an example of inline-editable rows of a table using mat-table. To create an  inline editable table row  using the  MatTable  component in Angular, you will need to use Angular Material ( @angular/material ) for UI components, along with Angular's built-in data binding to manage the state of each row when the user clicks the  Edit  button. Here's a step-by-step guide to implement this: Step 1: Set Up Angular Material First, you need to install Angular Material in your project. If you haven't already, run the following commands: ng add @angular/material During the installation, you will be prompted to select a theme and some other configuration options. You can choose the default options for now. Step 2: Install Required Angular Material Modules Next, you need to import the relevant Angular Material modules. Open your  app.module.ts  and import the necessary Material components: import { NgModule } from '@angular/core'...

Scheduling automatic start and stop for AWS Elastic Beanstalk environments can help optimise costs by ensuring that environments are only running during required hours. While AWS Elastic Beanstalk doesn't natively support scheduling, you can achieve this through AWS Lambda, EventBridge (formerly CloudWatch Events), and the AWS SDK. Steps to Schedule Automatic Start/Stop: 1. Define Start and Stop Actions Elastic Beanstalk environments are started and stopped by updating their environment configuration. Stopping involves changing the environment's instances to a scaled-down state (e.g., 0 instances). 2. Create AWS Lambda Functions You need two Lambda functions: Start Function: Scales the environment to a desired instance count. Stop Function: Scales the environment to 0 instances. Example Lambda Code (Python): Stop Environment 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 import boto3 def lambda_handler (e...

PRIVACY POLICY Last updated April 19, 2023 This privacy notice for Team CoderzDuniya ( " Company ," " we ," " us ," or " our " ), describes how and why we might collect, store, use, and/or share ( " process " ) your information when you use our services ( " Services " ), such as when you: Download and use our mobile application ( Revenue Calculator) , or any other application of ours that links to this privacy notice Engage with us in other related ways, including any sales, marketing, or events Questions or concerns?  Reading this privacy notice will help you understand your privacy rights and choices. If you do not agree with our policies and practices, please do not use our Services. If you still have any questions or concerns, please contact us at droidamar007@gmail.com . SUMMARY OF KEY POINTS This summary provides key points from our privacy notice, but you can find out more details about any of these t...