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RAGKit with Kyle Davis - Weaviate Podcast #93!

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Manage episode 412675596 series 3524543
Content provided by Weaviate. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Weaviate or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Hey everyone! I am SUPER excited to publish our newest Weaviate podcast with Kyle Davis, the creator of RAGKit! At a high-level, the podcast covers our understanding of RAG systems through 4 key areas: (1) Ingest / ETL, (2) Search, (3) Generate / Agents, and (4) Evaluation. Discussing these lead to all sorts of topics from Knowledge Graph RAG, to Function Calling and Tool Selection, Re-ranking, Quantization, and many more! This discussion forced me to re-think many of my previously held beliefs about the current RAG stack, particularly the definition of “Agents”. I came in believing that the best way of viewing “Agents” is an abstraction on top of multiple pipelines, such as an “Email Agent”, but Kyle presented the idea of looking at “Agents” as scoping the tools each LLM call is connected to, such as `read_email` or `calculator`. Would love to know what people think about this one, as I think getting a consensus definition of “Agents” can clarify a lot of the current confusion for people building with LLMs / Generative AI.

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102 episodes

Artwork
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Manage episode 412675596 series 3524543
Content provided by Weaviate. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Weaviate or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Hey everyone! I am SUPER excited to publish our newest Weaviate podcast with Kyle Davis, the creator of RAGKit! At a high-level, the podcast covers our understanding of RAG systems through 4 key areas: (1) Ingest / ETL, (2) Search, (3) Generate / Agents, and (4) Evaluation. Discussing these lead to all sorts of topics from Knowledge Graph RAG, to Function Calling and Tool Selection, Re-ranking, Quantization, and many more! This discussion forced me to re-think many of my previously held beliefs about the current RAG stack, particularly the definition of “Agents”. I came in believing that the best way of viewing “Agents” is an abstraction on top of multiple pipelines, such as an “Email Agent”, but Kyle presented the idea of looking at “Agents” as scoping the tools each LLM call is connected to, such as `read_email` or `calculator`. Would love to know what people think about this one, as I think getting a consensus definition of “Agents” can clarify a lot of the current confusion for people building with LLMs / Generative AI.

  continue reading

102 episodes

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