From the course: Building Applications Using Amazon Bedrock
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Conversation history - Amazon Bedrock Tutorial
From the course: Building Applications Using Amazon Bedrock
Conversation history
- [Presenter] One of the limitations of our application in its current form is that you cannot ask the chatbot a follow-up question based on a previous answer. This is an extremely important feature of any chatbot application. In the natural flow of any conversation to give a better user experience, it helps with the chatbot was aware of how it answered previously and uses this as additional context to improve answers in the future. To help us with this process and to do some of the heavy lifting, we are going to introduce a new chain from long chain called conversational retrieval chain. When you provide this chain with a query, it will use documents that will retrieve from the retriever you specify as part of the typical RAG process, but then it goes a bit further. It'll also use the chat history to improve the quality of the RAG by taking into account past queries. This is really awesome and leads to a…
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Conversation history1m 57s
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Coding: Supporting conversation history8m 59s
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Demo: Chatbot conversation history5m 7s
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Introduction to Amazon Kendra1m 42s
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Setting up the Amazon Kendra index7m 12s
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Coding: Amazon Kendra integration3m 17s
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Setting permissions for Amazon Kendra1m 20s
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Demo: Amazon Kendra and Amazon Bedrock integration4m 40s
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Agents for Bedrock2m 17s
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Configuring the Amazon Bedrock agent9m 59s
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Reviewing project files8m 43s
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Testing the agent in the AWS console8m 16s
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