What a delightful combination of knowledge, objectivity and calm energy. Thank you!

Llama Index for long term memory and Lang Chain for chaining and agents. This all happened within a year or so. What a time to be alive!

Thank you for the fantastic overview of LlamaIndex functionalities 😊

I like how you added additional info in the yellow text overlays. That helps with retaining info. Great job 👏

Great you mention that those tools are not exclusive. However probably for simpler use cases one of them will be enough.

Too bad that i can't like twice your videos! Thank you, very informative videos. 🙏

Thank you so much, Sophia!

Great content! Thanx ... plz give us more on combining Lamaindex with Langchain ... thanx in advance

Love your videos. Always on my queue! Thanks for sharing!

Really useful stuff! Thanks for making this video.

Another Informative video, didn't know about this.

Please create a breakdown video about different kind of models, chat models, instruction models etc.

Great tutorial, thank you!

Excellent!

Excellent !!!

Thank you lot

Thanks for explaining llmaindex. 👍 Is it also a vectorstore like chromadb?

You look gorgeous 👍👍👍 And very clear and detailed explaination... Thank you ...🌹🌹🌹

try to use llamaindex and huggingface model, but all kinds of issues. It seems model kwargs cannot be passed to hf transformer model?

I used Langchain's dataloader and then converted into a llamaindex. I had to do this because the llamaindex beautifulsoup scraper would return 403's because it wouldn't let me enter the user header. The challenge I am having with both SDKs is they are throwing so much good stuff out but unfortunately the testing seems lacking. YIPPEE!! My question: What if I want to make a local podcast of stuff happening in my town that gets buried. Some things in the town might come from a Wikipedia entry, some will come from our town web site buried in council minutes, etc. some will come from police reports, more investigative. For quality results should everything be indexed? Or when does one just rely on "Do a web search?" Also, what are good methods for fact searching?Funny when I ask why it came up with an answer. ChatGPT 4 told me "Because it makes a good story" That was interesting and made sense that it would do that. But I'd like to have a better handle on fact and fiction. Thank you.

clicked fast

Very nice!!. thank you but can you make more videos about how to structure the data in the documents. and how can we tell llama about the data structure in the documents. for example to tell them that the document have Q&A template structure separated by (----) and if you do a video about hoe tow to make the result better. this would be Awesome. Thank you and good luck!!!!!

Great tutorial, thank you very much! My question is, how can we persist the indices and load them from a storage directory, in the Query multiple documents example? I could not find any example in the llama-index documentation about persisting several indices (from several documents) and load them individually to replicate the SubQuestionQueryEngine example.

Hi Sophia, my team and I found this video very helpful during Berkeley's AI/LLM Hackathon last week :D I'm a rising junior studying CS, and most of my experience thus far has been all sorts of programming NOT related to AI/ML/DS. However, I'm now really interested in experimenting through building meaningful tools/apps on top of the ML layer through frameworks such as LlamaIndex, Pinecone etc. I just wanted to ask if you think its necessary to have a strong understanding in AI ML fundamentals before moving forward with these tools. Thanks

Good video '

Hi Sophia, can I use langchain to load models from TogetherAI or other API LLMs, and then use that loaded model with LlamaIndex?

Hey Sophia, when I tried to query across multiple documents I get this error: "InvalidRequestError: Must provide an 'engine' or 'deployment_id' parameter to create a " Do you know why this happens?

Hey, is there any way you can query mongodb collection? like something similar to langchain sqlchains

hi, how can i do in context learning from a txt file and lengchain but using falcon 7b parameter instead of open ai? i try to query a txt file with lengchain but not using openai as model interpreter but using falcon 7b

How is it different from LangChain?

Thanks, I have a python query engine in llama index. I want that engine as a tool in langchain, can you please make a video or let me know here?

Personally i perfer Llama Index for memory as i like the syntax better. I think I like building my own agents from scratch but seems like LangChain is best game in town for agents.

2:38 Not able to use it withiu openai api key for basic query functionality Is this flow of?

How could this ever be applied to creating a RAG for a customized ChatGPT? Closer to the point, as something with a user interface that my grandmother could use? Obviously the average user simply isn’t going to run anything that has code on the page.. they’ll need a slick UI. Something like the OpenAI Custom GPT. How does that slick UI ever become integrated with what you’re doing?

Is LangChain and Llama Index primarily used by data scientist or is there a new job role that uses them? Or is it machine learning engineers?

This would have been even better if we did not need to use openai

Promo-SM 😪