Build a Multi-Interface Ai Assistant using Amazon Q and Slack with Amazon CloudFront Quezerforent Realles from Amazon S3 baker S3

There is a fixed customer's response that AI assistance have used harder when users can contact within productivity tools that are already using daily, to avoid rotating applications and contexts. Web applications such as Amazon q business and SLACK have been key to the support of AI modern. This post tests how different vacancies improve user interaction, and to provide a variety of preferences.

By providing seamless experiences in all areas, organizations may increase users' satisfaction and acquisition prices. Assistant is renting a rate of a miracle (RAG), the process that includes reliable and authoritative sources within the responses throughout these compounds, the trust and the number of education. This is a variety of visible, the power of the RAG should not strive to meet modern users' users, but also promotes the basis of an experienced and more user, eventually increases the performance of the help and access. By combining the rag with many communication sites, the assistant brings unwanted, accurate, and relevant information information regardless of the user-choice and manufacturing tools.

Looking for everything

The next drawing indicates the formation of the property app.

You can find the complete code and shipping measures solution to GitTub Repository.

Click here to open AWS console and follow.

Requirements

You must have the following requirements:

Use a solution

For setup steps, look at the reader in Gimitub Repo.

Solution solutions

In this section, we discuss two important of the solution: Data sources and vector database.

Data sources

We use spack documents whenever the assistant returns it as a resource, it will be linked to a portion of the spack texts and not at the top of the source page. For example, parking pictures without Docker Hub.

Spack is a variety of package manager for SuperComputers, Linux, and Macos that change scientific software installs by allowing many types, Configuration, Places, and consumers to meet one machine. Developed by Todd Gamblin in Lawrence Livermore Liveremore in 2013, a spark facilitates the restrictions of traditional Guncasters in computer operations on top (HPC). Brian Weston, cloud transformation of a machine science program leaded to Wellnl, advised in its development.

Additionally, we use text files that are uploaded to the S3 bucket available in the Amazon CloudFFFFFFFFLONG link. There is also a job additions from the SLACK discussion details in the S3 bakery given power for AWS Lamburda. This makes a helper and previous discussions from users to answer questions and release its resources. We have chosen to use the conflicting cloudfront links by using Slack links because when the source is cited to Amazon Q, the user may not access slack data. There is another way of this method using Slack Connector for Amazon Kendra.

This solution can support some types of data such as PDF, words, and more as long as their text is not released and offer a vector database with specific code changes. Their green files can be submitted to cloud distribution.

The next screen displays the Sample Cloundfffront URL.

When submission, existing data is automatically uploaded to the S3 baker and processed to be used by the assistant. The solution also includes the automatic submission of data from slack on the app using Amazon forums.

Vector database

This solution uses Amazon Kendra as its Vector database, which provides major benefits and expenses. As a fully owned AWS service, the Amazon Kendra reduces the cost of improving and maintenance. Amazon q, supporting two traditional returns and Amazon Kendra), combined with seams in this application. By using Amazon Kendra, the solution is well uses the same return to both the Amazon Q and Slack. This method is not just by spreading complete construction but also provides a user experience that suits both areas. The result is a very good plan, which uses the cost that keeps similarities in the restoration of information and presentation, regardless of the user's enlistment.

Amazon Kendra also supports the use of Metadata with each file file, which allows both the UIS to provide a link to its sources, whether the Spack Document Website or CloudFF. In addition, the Amazon Kendra supports the compliance clearance, enabling to reinforce certain data resources. Through this solution, we strengthened text consequences in the park.

User Communication

At this stage, we discuss the UIS used in this site.

Amazon's business q

Amazon q Business uses RAG to provide a secure AI assistant made of information designed for your organization. As a traditional AWS solution, it meets outside the seams and other AWS services and includes its easy-to-use interface. This integration, integrated with its direct setup and shipping process, provides a smootha initiation experience. By installing AI's strengths in the restoration of intelligent information from your business plans, Amazon q creates specific answers, which are strongly focused on specific information and documents, promoting its compliance with its accuracy.

The next screen is an amazon Q Business UI.

Rainflow

Slack is a popular partnership service that has become an integral part of many communication communications organizations. Its operation reaches more than group messages to act as an active adjoining. By combining AI powerful assistants in Slack, companies can use their normal location to give users instant access to information.

The following icon displays an instance of the Slack UI for the message string.

Watch

Amazon Q has a designated feature within the Analytics Dashboard that provides understanding in user involvement within a specific Amazon Q business. It provides important information on the use patterns, dynamic energy, user's response, and questions, which allows you to analyze and do your AI assistance and user interface.

With Slack, we collect users' response, as shown in the preceding UI screw. Users can add a “thumbs” or “thumbs down” to the response to the response. In addition, we create a custom solution that uses the Amazon Cloudwatch Dashboard to imitate the Amazon q the dashboard to re-change the experience between two applications.

This next screen shows an example of the slack clockatch dashboard.

In addition, there is a scheduled slackbot daily message summarizing the slackbot data on the previous day, as shown in the following screenshot.

Clean

To avoid crashing cases, clean up the services you created as part of this post in the command mentioned in the readme.

Store

The implementation of Multi-Interface A Assistant use RAG represents jumping to jump in an organization's international interactions. By combining the Amazon Q and Slack with a strong powerful backfare enabled by Amazon Kendra, this solution provides seamlessness access, natural-acnostic access to accurate, knowledge. The power of buildings are lying on their agreement in all areas, automated data access processes, full energy and energy efficiency. This approach does not increase the production of user and manufacture, but also placed the organizations to achieve immediately to achieve the A-Centric Needs, marks the administrative and understandable and understandable information.

To learn more about the AWS services used in this solution, see the Amazon Q Guide q from the highest Amazon Bedrock, and Amazon Kendra Developer Guide.

About the authors

Nick boso The engineer to study the machine in the AWS Professional Services. You solve complex challenges of the organization and technical plans that use data sciences and engineering. In addition, he built and put AI / ML models in the AW cloud. His love reaches his earning and cultural experience.

Dr. Ian Lunsford He is aerospace's classroom advisor at the AWS Professional Services. It includes clouds of the clouds of Aerospace. In addition, IAN focuses on creating AI / ML solutions using AWS services.