Building RAG With OpenAI GPT-4o(omni) Model Using Objectbox Vector Database

In this video we will be using OpenAI GPT-4o model for creating a RAG application using Object Vector Database.GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction-it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time(opens in a new window) in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.
Docs: docs.objectbox...
github code: github.com/kri...
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[@generativegeek]

you are an inspiration for new channels like mine, Krish. May god bless you.

[@FAX_41]

brilliant video as always, keep continuing the grind

[@sashankachakraborty8714]

Nice 😊

[@ArmanMalik-sn5lr]

Tremendous Krish🎉
And also please make a video on Building RAG with Gemini Flash model

[@CodeCraftsman]

Hi Krish, Thanks for creating amazing tuts on RAG and LangChain. I have been following your Langchain series form start, can you upload few videos on Image or video RAG Pipeline? Thanks God Bless you sir
🙏🙏🙏🙏

[@7dainis777]

Great video. Does data chunk conversion to vectors consume tokens same way it does when creating vector store using openai api's directly? Or is it offline process in this case?

[@fkeb37e9w0]

I am not able to pull rag promt from the hub, do we need any langchain/langsmith api key?

[@wzlee-q2p]

Hey, could you please tell me what's the difference between using "create_stuff_documents_chain(llm, prompt) + create_retrieval_chain(retrieval, document_chain)" and using "RetrievalQA in your video" ?😀

[@pranavjain2938]

How can we use this to get search results relevance scores?

[@rambaldotra2221]

Can anyone help me how can we use GPT-4o model to extract the data from pdf documents and give analysis and plot charts on the data.

[@saikashyapcheruku6103]

Is it RAG if I retrieve context from a vectordb using a set of queries which are subquestions derived from the prompt?

[@generativegeek]

yes. something like this should qualify. ua-cam.com/video/4BYo8hlAUJY/v-deo.html

[@harilakshman2048]

can someone guide about how to make this as an webapp or to host somewhere please

[@ArmanMalik-sn5lr]

I made a chatbot using RAG but when I retrieve my data from the vector database, it does not give proper results. I want it to give the same result from my provided data.
So which prompt do I have to use.

[@dleer_defi]

the answer of this question is pretty nuanced; but data in = data out is a good place to start
then look at how you are chunking the data
keep relevant stuff together
etc

[@AymanHaneen]

Can I launch it on ChatGPT Bot?

[@priyashikumari3745]

Is the OpenAI GPT-4o api key now available for everyone to test the model?

[@Dis-Trackted]

Nope. You need to ask for your own. A few dollars should suffice

[@atp700]

Sir why are you not there in pw skills

[@bugsbane]

here are stupid questions...
1) if chatgpt 4.0 can query the vector DB - does it not gain insight into proprietary info? for instance if the embedding model translates proprietary plain text into a vector - isn't the vector itself proprietary? I can see that we have to trust that chatGPT does in ingest the complete vector db of private info. It can be that it's just queries - so only small tidbits of private info get 'leaked'
2) this is all in a jupyter notebook - does that mean we just wrap this in flask and openwebui to expose this to internal corporate users (via vpn)
forgive the newbie questions. i"m just trying to grok this thing
Thanks

[@HDSV10]

Chat Q n A with UA-cam video transcript by uploading yt link + multilingual text to speech sir make this project video