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'...