End to end RAG LLM App Using Llamaindex and OpenAI- Indexing and Querying Multiple pdf's

preview_player
Показать описание
In this video we will create a Retrieval augmented generation LLm app using Llamaindex and Openai. Here we will be indexing and query multiple pdf's using llamaindex and openai.
----------------------------------------------------------------------------------------------
Support me by joining membership so that I can upload these kind of videos
----------------------------------------------------------------------------
►Data Science Projects:

►Learn In One Tutorials

End To End RAG LLM APP Using LlamaIndex And OpenAI- Indexing And Querying Multiple Pdf's

►Learn In a Week Playlist

---------------------------------------------------------------------------------------------------
My Recording Gear
Рекомендации по теме
Комментарии
Автор

Fixed the issue and reuploaded the video again

krishnaik
Автор

I really love the way you teach these hard concepts with so much enthusiasm that it sounds so easy. Thank you so so much.

faqs-answered
Автор

You are amazing and your videos taught me more than any of my graduate professors could. Thank you

Venom-gthi
Автор

This session is fantastic! It would be great if you could also demonstrate how to change the default embedding, specify which embedding the model is using, and explain how to switch between different models such as GPT and LLM. Additionally, it would be helpful to cover how to utilize this dataset to answer specific questions.

ajg
Автор

much-awaited series. would be nice if we have even more complex rag applications.

phanindraparashar
Автор

please use open source LLMs

As a student, it's difficult to come up with budgets for openai api key

btw just wanted to thank you for everything you're doing!!

ariondas
Автор

Thanks for the video, I have been constantly learning from your videos

muraliteja
Автор

Hi Krishn sir, very thank you for this video❤

narsimharao
Автор

Thank you - this was a great tutorial. Liked and subscribed.

bernard
Автор

I love how verbose this is. Thank you!

bawbee
Автор

thank you sir making such video these are amzaing video🤩🤩

deepak_kori
Автор

eagerly waiting for a video to include databases.

khalidal-reemi
Автор

Great channel Krish! Is it possible to create a RAG/LLM model to interact with a database to ask statistical type questions? what is the max, min, median, mean? basically to create a chatbot for non-technical users to interact with spreadsheets

bevansmith
Автор

Thank you very much, Sir. In your Llamaindex playlist, it says five videos so far, but 2 unavailable videos are hidden. do I have to pay and become a member to be able to say the full playlist? Thanks again for the amazing videos!

lixiasong
Автор

Hello krish, first of all, I'd like to thank you for all your guidance. Your videos are my main source of study. Now, my query related to this video. The codes have been changed from the one you are showing. Most remain same with addition of core to the library. But I couldn't find any for vectorindexautoretriever, mainly the keywords to be used inside. Currently it's asking for vectorstoreinfo apart from index and similarity top k

summa
Автор

So it is power full than Azure AI Search?? or it does the same thing as AI search(Azure cognitive search).

pavankonakalla
Автор

Hi Krish, I have a doubt regarding the project I am doing. So the project is that from a pdf file I need to create a excel file which have 5 columns and the info in excel can be filled from the pdf. Can I get a an approach to solve the problem using llm. I am looking forward to hearing from you.

aravindraamasamy
Автор

Thanks Sir.
May i know where did we use OpenAI here, Can we use any open source model like Llama-2?

jokthvf
Автор

Since we are using open ai, does it mean we are using one of the gpt models? There was no parameters in the code to choose what llm model to you. How do we select a particular open ai model?

seanrodrigues
Автор

Hello Krish, Thanks for this informative video on RAG and LLAmaIndex. I have one doubt - When you query "what is attention is all you need", the source having 0.78 similarity score is chosen as Final Response instead of the source having similarity score 0.81. Why?

alfatmiuzma