Dude, this is a really good information. Thanks. Subscribed! Wish to see more videos of your firsthand experience.

Great overview of pros and cons. Any recommendations for cases where you might want to use both somehow?

I’ve just seen an implementation with both together but it was pretty basic. Llama index was used to preprocess the content and provide context into the LLM for reasoning. I’d love to see more advanced logic with the two integrated and where and how to best write “business logic” TIA

Do you need either of these frameworks if you use openai’s fucntions or use langchain and functions in conjunction?

I started with using llama index… really a big pain in the bum reading the documentation and hard to figure things out since so many tools are not that clear

Man, you've as many tabs on the browser as I do, I think it's my ADHD 😅 Great video, thanks for the comparison

@heymichaeldaigler

9 ай бұрын

lol I have a problem. Thanks for watching!

I think some examples could be helpful especially for Llama Index.

@heymichaeldaigler

Жыл бұрын

Couldn't agree more! I'll work on getting some examples to explain

Is Llama index faster due to better memory control?

@heymichaeldaigler

Жыл бұрын

Llama index allows routing of queries to indexes prior to LLM calls, can break down complex query inputs into subqueries if the information required is from disparate datasets, etc. Think llama index as more of a memory management first for LLMs. You can create more arbitrary data structures over your data

what about haystack? haystack has been there much longer than langchain and it also has almost similar functionalities to the langchain

@heymichaeldaigler

6 ай бұрын

Oh, I feel like I've heard of this, but I haven't given it the attention it deserves. I'll take a deeper dive into haystack.

@dinithkumudika6459

6 ай бұрын

@@heymichaeldaigler great if you could do a comparison between it and the lagchain.

Scope: Langchain is better for beginners and those starting new projects with uncertain needs. Llama Index is better for those with specific project needs and requiring advanced memory management or querying capabilities. Interface: Langchain is easier to learn and use, with more examples and community support. Llama Index has a more complex interface, but it is rapidly improving with recent updates. Storage and Indexing: Langchain is more generic, using the retriever paradigm for querying data. Llama Index is designed for deep querying and response synthesis, allowing for flexible memory architecture. Querying: Langchain has less powerful querying capabilities, but they are still sufficient for most use cases. Llama Index has stronger querying capabilities, with a priori query routing and response synthesis engine. Overall: Langchain is recommended for beginners and those starting new projects. Llama Index is recommended for experienced users with specific project needs and requiring advanced features.

@adscript4713

4 ай бұрын

Does it have to either/or? Can't we just use LlamaIndex for querying and Langchain for everything else?

Please do examples

@heymichaeldaigler

Жыл бұрын

I will get on it! thank you!

You should use a different font

@heymichaeldaigler

4 ай бұрын

good looks

More in depth please😁🦾

@heymichaeldaigler

Жыл бұрын

thank you for the feedback. will add to my list for videos to do soon