freezed88

Hey all! Jerry here (from LlamaIndex).

We love the feedback, and one main point especially seems to be around making the docs better: - Improve the organization to better expose both our basic and our advanced capabilities - Improve the documentation around customization (from LLM's to retrievers etc.) - Improve the clarity of our examples/notebooks.

Will have an update in a day or two :)

100%, if the API itself can choose to call a function or an LLM, then it's way easier to build any agent loop without extensive prompt engineering + worrying about errors.

Tweeted about it here as well: https://twitter.com/jerryjliu0/status/1668994580396621827?s=...

Hi all - Jerry (co-founder/CEO) here, here to help answer any questions you might have!

We're building a data framework to unlock the full capabilities of LLMs on top of your private data. We can’t wait for the future - this space is moving so rapidly and there’s so many things we want to do on both the open-source and enterprise side.

Feel free to shoot me a personal note on Twitter/Discord as well.

depending on what questions you're asking, you could check out LlamaIndex query capabilities - can define different index structures for different queries + can plugin to your langchain workflow: https://gpt-index.readthedocs.io/en/latest/use_cases/queries...

would love to have CozoDB be a part of llamaindex too! have a bunch of integrations with existing vector db's https://github.com/jerryjliu/llama_index/tree/main/gpt_index...

author of llamaindex here:

there's some overlap but our primary use case is going deep into indexing+retrieval for LLM's (and going deep in that area). Not really doing agents/chatbots/prompt management/etc.

E.g. this is a good example of our use cases: https://gpt-index.readthedocs.io/en/latest/use_cases/queries...

You can actually use us as a retrieval/tool in langchain too: https://gpt-index.readthedocs.io/en/latest/how_to/integratio...

Making retrieval really really good is part of the mission of LlamaIndex! Given a natural language input, find the best way to return a set of documents that is relevant to your LLM use case (question-answering, summarization, more complex queries too).

- We integrate with vector db's + ChatGPT Retrieval Plugin

- Submitted a Retrieval PR to langchain here: https://github.com/hwchase17/langchain/pull/2014

- would love to explore further integrations as a plugin in any outer agent system

This is what llama-index was designed for! https://gpt-index.readthedocs.io/en/latest/ Would love to incorporate this Github repo loader into LlamaHub

LlamaIndex offers ways to chunk up your data and store them in data structures for response synthesis: https://gpt-index.readthedocs.io/en/latest/guides/primer.htm...

This is exactly what LlamaIndex is meant to solve!

A set of data structures to augment LLM's with your data: https://github.com/jerryjliu/gpt_index

This is what we've designed LlamaIndex for! https://github.com/jerryjliu/gpt_index. Designed to help you "index" over a large doc corpus in different ways for use with LLM prompts.

(creator of gpt index / llamaindex here https://github.com/jerryjliu/gpt_index)

Funny that we had just rebranded our tool from GPT Index to LlamaIndex about a week ago to avoid potential trademark issues with OpenAI, and turns out Meta has similar ideas around LLM+llama puns :). Must mean the name is good though!

Also very excited to try plugging in the LLaMa model into LlamaIndex, will report the results.