Build a question-answering bot using generative AI

Resumen

This lab offers a comprehensive guide on creating a question-answering chatbot with generative AI capabilities. Utilizing stateless, retrieval augmented generation, this tutorial provides in-depth instructions on leveraging AWS Classroom courses to answer queries effectively.

Objectives:

Successfully completing this lab will enable participants to:

• Understand the application of retrieval augmented generation in enhancing Generative AI outputs.
• Deploy a Lex chatbot integrated with a large language model for dynamic response generation.
• Connect Langchain to Amazon SageMaker for efficient model handling.

Prerequisites:

Participants are recommended to have a technical background in:

• Amazon SageMaker
• Amazon Kendra
• Amazon Lex

A familiarity with FLAN and large language models (LLMs) will be advantageous.

Audience:

This lab is designed for a diverse professional audience, including Solutions Architects, Data Engineers, Data Scientists, and Developers looking to expand their expertise in generative AI and AWS services.

Outline:

The lab encompasses the following tasks:

• Deployment of a Large Language Model (LLM)
• Integration of an Amazon Kendra data source
• Creation of an Amazon Lex V2 chatbot
• Querying your large language model endpoint
• Implementation of a RAG (Retrieval Augmented Generation) workflow
• Deployment of a web application using CloudFormation

Provider:

AWS Skill Builder.

Categories:

Generative AI Courses, Amazon SageMaker Courses, Amazon Lex Courses.

Materias