A deep dive into Retrieval-Augmented Generation with Llamaindex

[@Ari_Shukla]

have gone through 100s of videos for llama index - and this is the best one

[@jasonliu6213]

I think we’re the lucky few who discovered this.

[@HazemAzim]

Best High level coverage on LLamaIndex .. Thank you .. Good job

[@bruinaly]

Best overview I've seen. Thank you!

[@cgintrallying]

Thanks for the clear introduction into the possibilities of llama-index

[@hydtechietalks3607]

your reading text killled the mojo of learning...as if old news reader.... But Hats off to the efforts!

[@randradefonseca]

I would like to see a complete script in which you show all these functionalities, I hope you publish it soon. Thank you.

[@schepa1234]

Thank your for your excellent video!

[@johanteekens4456]

thanks for this very clear overview and explanation!

[@98f5]

Just found your repo today and have been doing this with some custom code to convert sdk docs and code into a graphdb. This looks like it'll be extremely helpful. Thank you

[@cgintrallying]

Interesting - what is your use case if i may ask ? I am about to test such a scenario in the near future as well. The most interesting part for me is to achieve this with open models and completely local datastores in the end. For sure also comparing to enterprise models like GPT-4 and Gemini to see what is possible and where the huge models are helpful and where smaller models reach a comparable output.

[@nguyenne21]

could you share the slide please, I would be appreciated

[@ragsAI]

Hi! Is Langchain integratable/compatible with redshift/databricks? (especially the text-to-sql framework)? Thank you.

[@gustavstressemann7817]

This is nice stuff.

[@explorer945]

Performance makes key differentiator apart from novel techniques. I heard some criticism on langchain. Hoping you guys do better in both performance and most reliable RAG with intuitive implementation

[@_XY_]

Cool 👏

[@WilliamReyor]

Laurie Voss is awesome.

[@98f5]

Even better its in ts!

[@UdaySatapathy]

So many ads!