Quickly Build high-accuracy Gen-AI applications using Amazon Kendra & LLM

To restrict the GenAI application responses to company data only, we need to use a technique called Retrieval Augmented Generation (RAG). In our previous video , we implemented RAG using AWS & PineCone.
In this video , we are going to use power of Amazon Kendra & LangChain to build RAG for high-accuracy Gen-AI applications.
Prerequisite:
============
Complete Amazon Bedrock In 2.5 Hours | Learn Generative AI on AWS with Python!
• Complete Amazon Bedroc...
Code:
======
github.com/SatadruMukherjee/D...
Documentation Link:
==================
aws.amazon.com/blogs/machine-...
api.python.langchain.com/en/l...
python.langchain.com/docs/int...
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[@moisesarruda5373]

Thank you so much. I tried this only with Bedrock and OpenSearch, your video help me to do this in the correct way!

[@KnowledgeAmplifier1]

Glad I could help @moisesarruda5373! Happy Learning

[@venugopal-nc3nz]

Brother , Are you transitioning from data engineer to AI engineer ?

[@KnowledgeAmplifier1]

@venugopal-nc3nz , trying to have a transition from Data Engineer to 𝐆𝐞𝐧 𝐀𝐈 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 role 😅