Exclusive Content:

Haiper steps out of stealth mode, secures $13.8 million seed funding for video-generative AI

Haiper Emerges from Stealth Mode with $13.8 Million Seed...

VOXI UK Launches First AI Chatbot to Support Customers

VOXI Launches AI Chatbot to Revolutionize Customer Services in...

Microsoft launches new AI tool to assist finance teams with generative tasks

Microsoft Launches AI Copilot for Finance Teams in Microsoft...

Utilize Amazon Q Business’ Web Crawler Connector to Index Website Contents

Building Interactive Chat Applications with Amazon Q Business: A Step-by-Step Guide

Today, we will be exploring the Amazon Q Business Web Crawler connector, a powerful tool that allows you to build interactive chat applications using your enterprise data. This fully managed service can generate answers based on your data or a large language model (LLM) knowledge without using your data for training purposes. In this blog post, we will walk you through the process of creating an Amazon Q Business application and indexing website contents using the Amazon Q Web Crawler connector.

The process begins with understanding how enterprise data is distributed across different sources such as Amazon S3 buckets, database engines, and websites. We will be using two data sources for this example: an employee onboarding guide and the official documentation for Amazon Q Business. We will demonstrate how to set up authentication for the Web Crawler and apply advanced settings like regular expressions to crawl only relevant pages and links related to Amazon Q Business.

The Amazon Q Web Crawler connector relies on the Selenium Web Crawler Package and a Chromium driver to crawl and index the contents of webpages and attachments. Each document has its own attributes, or metadata, which can be mapped to fields in your Amazon Q Business index. By creating index fields, you can boost results based on document attributes such as category, URL, and title.

The connector allows you to synchronize website domains, subdomains, and webpages included in links. Additionally, you can use regular expressions to filter URLs to include or exclude in the crawling process. The Web Crawler connector supports various authentication types including basic authentication, NTLM/Kerberos authentication, form-based authentication, and SAML authentication.

After setting up the Web Crawler connector for both data sources, we will guide you through creating an Amazon Q Business application, adding groups and users, and synchronizing the data sources. Finally, we will show you how to run sample queries to test the solution and provide troubleshooting tips for common issues you may encounter.

In conclusion, the Amazon Q Business Web Crawler is a versatile tool that enables you to connect websites to your Amazon Q Business applications seamlessly. Whether you are building generative AI applications or enhancing customer support with chatbots, the Web Crawler connector offers a wide range of capabilities to meet your needs. To learn more about Amazon Q Business and its features, refer to the Amazon Q Business Developer Guide and explore the possibilities of connecting Web Crawler to Amazon Q Business.

About the Author: Guillermo Mansilla is a Senior Solutions Architect with a passion for serverless architectures and generative AI applications. With over a decade of experience in software development, Guillermo enjoys challenging himself in chess tournaments outside of his work hours.

Latest

Comprehending the Receptive Field of Deep Convolutional Networks

Exploring the Receptive Field of Deep Convolutional Networks: From...

Using Amazon Bedrock, Planview Creates a Scalable AI Assistant for Portfolio and Project Management

Revolutionizing Project Management with AI: Planview's Multi-Agent Architecture on...

Boost your Large-Scale Machine Learning Models with RAG on AWS Glue powered by Apache Spark

Building a Scalable Retrieval Augmented Generation (RAG) Data Pipeline...

YOLOv11: Advancing Real-Time Object Detection to the Next Level

Unveiling YOLOv11: The Next Frontier in Real-Time Object Detection The...

Don't miss

Haiper steps out of stealth mode, secures $13.8 million seed funding for video-generative AI

Haiper Emerges from Stealth Mode with $13.8 Million Seed...

VOXI UK Launches First AI Chatbot to Support Customers

VOXI Launches AI Chatbot to Revolutionize Customer Services in...

Microsoft launches new AI tool to assist finance teams with generative tasks

Microsoft Launches AI Copilot for Finance Teams in Microsoft...

Investing in digital infrastructure key to realizing generative AI’s potential for driving economic growth | articles

Challenges Hindering the Widescale Deployment of Generative AI: Legal,...

Using Amazon Bedrock, Planview Creates a Scalable AI Assistant for Portfolio...

Revolutionizing Project Management with AI: Planview's Multi-Agent Architecture on Amazon Bedrock Businesses today face numerous challenges in managing intricate projects and programs, deriving valuable insights...

YOLOv11: Advancing Real-Time Object Detection to the Next Level

Unveiling YOLOv11: The Next Frontier in Real-Time Object Detection The YOLO (You Only Look Once) series has been a game-changer in the field of object...

New visual designer for Amazon SageMaker Pipelines automates fine-tuning of Llama...

Creating an End-to-End Workflow with the Visual Designer for Amazon SageMaker Pipelines: A Step-by-Step Guide Are you looking to streamline your generative AI workflow from...