Amazon Lex is a service for creating conversational interfaces backed by natural language understanding (NLU) and automatic speech recognition (ASR). This service allows you to make text and voice-based applications easily and quickly by using existing language models.
In this Cloud Lab, you’ll create an intelligent EducativeBot using Amazon Lex and integrate it with an agent powered by Amazon Bedrock. You’ll begin by building the knowledge base using Bedrock’s embedding model, which converts your source content into vector embeddings for efficient semantic search and retrieval. You’ll then create a Bedrock Agent configured to query the knowledge base.
Next, you’ll configure Amazon Lex to build the EducativeBot by defining intents, designing the conversational flow, and connecting the bot to the Bedrock Agent linked to the knowledge base. This integration allows the bot to understand user queries and respond with accurate answers pulled directly from the knowledge base.
By the end of this Cloud Lab, you’ll have practical experience designing a conversational AI bot using Amazon Lex and Amazon Bedrock that can deliver smart, data-informed responses.
The following is the high-level architecture diagram of the infrastructure you’ll create in this Cloud Lab:
