@@johannesjolkkonenAlso would love to watch a project like FastAPI + React, or even better FastAPI + Next.js with showing how to extract data from OpenAI without Langchain, and display it in your React or better Next.js webapp. Part of information in one block and part of information in the other block etc. Or even map thru list of information received from OpenAI and display it iteratively as a stack of 1 component.
@@johannesjolkkonenThank you for the tutorial.Also would love to watch another project based on FastAPI + React (or even better - Next.js) without Langchain. Where you extract data from OpenAI and then display it in different frontend blocks. For example map thru the list of information received from OpenAI and display it in repeated React component as a stack of items.
I started watching just for the react front end piece as I want to build something more custom than streamlit I haven’t even gotten past the first half yet but already subscribed. Great stuff. I hadn’t even seen the concept of embedding on demand for any article we want in our vector store. I’ll have to try to connect this to a google extension I made for saving the URL to text file so I can get there in one click
If you enjoyed this video, I made a part 2 where I add streaming, a way to do RAG without LangChain and finally also deploying the app. Check it out here: th-cam.com/video/uEduh6ANplc/w-d-xo.html
![ค้างคืนโรงเก็บกระสวยอวกาศร้างกลางทะเลทราย [Around The World Ep. 3]](http://i.ytimg.com/vi/E5bWZQhABJE/mqdefault.jpg)
Massively underrated channel brother! Would love to see how to do this without langchain.
Thank you!
Already planning a part 2 for this, and I can include a non-langchain version for the RAG function(s) there (:
Awesome stuff man! Can't wait 🔥
@@johannesjolkkonenAlso would love to watch a project like FastAPI + React, or even better FastAPI + Next.js with showing how to extract data from OpenAI without Langchain, and display it in your React or better Next.js webapp. Part of information in one block and part of information in the other block etc. Or even map thru list of information received from OpenAI and display it iteratively as a stack of 1 component.
@@johannesjolkkonenThank you for the tutorial.Also would love to watch another project based on FastAPI + React (or even better - Next.js) without Langchain. Where you extract data from OpenAI and then display it in different frontend blocks. For example map thru the list of information received from OpenAI and display it in repeated React component as a stack of items.
I started watching just for the react front end piece as I want to build something more custom than streamlit
I haven’t even gotten past the first half yet but already subscribed. Great stuff. I hadn’t even seen the concept of embedding on demand for any article we want in our vector store. I’ll have to try to connect this to a google extension I made for saving the URL to text file so I can get there in one click
Great to hear Brian!
Thank you for the tutorial ! You should really zoom in for better code visibility (as well as using a light theme in vscode)
Thanks for the feedback!
I think I'm too attached to my dark mode, but zooming in would probably be a good idea!
If u use light mode means get checked by psychiatrist
this is a miracle, I’m not kidding
Wonderful tutorial. Thank you so much!!
how to dockerize this and do this development into docker
thank you for practical project mate
Excellent!
woaaaaaahhh super helpful thank you!
You're welcome!
Thanks, it was interesting
If you enjoyed this video, I made a part 2 where I add streaming, a way to do RAG without LangChain and finally also deploying the app.
Check it out here: th-cam.com/video/uEduh6ANplc/w-d-xo.html