Advanced RAG Pipelines with LlamaIndex & Amazon Bedrock

Explore how LlamaIndex and Amazon Bedrock combine to create powerful AI systems capable of breaking down complex queries, reasoning across multiple documents, and delivering comprehensive answers. Learn about advanced techniques like Sub-question Querying and Agentic RAG, and see how to integrate these tools with Amazon Bedrock for state-of-the-art natural language processing.

Resources:
🛠️ LlamaIndex: https://www.llamaindex.ai/
📝 Notebook example https://github.com/aws-samples/amazon...
📝 Notebook example https://github.com/aws-samples/amazon...
🔗 Amazon Bedrock: https://aws.amazon.com/bedrock/
⚡️ LlamaIndex documentation: https://docs.llamaindex.ai/en/stable/

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Chapters:
00:00 - 00:35 Hook/Intro
00:35 - 02:23 Sub-question Query
02:23 - 04:12 Agentic RAG
04:12 - 06:39 Integrate Amazon Bedrock and LlamaIndex
06:39 - 07:12 Call to Action/Close

#LlamaIndex #RAG #AI