It's an alternative, does a similar job, depends on/abstracts over langchain for some things. It's easier to use than langchain and you'll probably get moving much faster.

They've aimed to make a framework that starts concise and simple, has useful defaults, then lets you adjust or replace specific parts of the overall "answer questions based on a vectorized document collection" workflow as needed.

This works well overall, but some bits have kept me scratching my head for hours. Partly due to huge holes in the documentation when it comes to specifics ("plenty of examples but little documentation" another commenter wrote and I agree). Partly due to the frenetic release schedule, this project is highly active even by frothy LLM craze standards and interfaces change rapidly.

Overall recommend, LlamaIndex has helped me make good progress on my project

Complement

This stuff is like redis. Great for the infra folks

Langchain is like ruby on rails. Great for the AI app devs

There is overlap, where you might start and stay on langchain as a kitchen sink... But as you do full app dev, esp SaaS, the bottom starts falling out for more data infra centric tooling.

That is what I am specifically going for with simpleaichat: https://news.ycombinator.com/item?id=36393782

It still needs a lot of work, but the goal is to decouple tools from LLM business logic (e.g. you would bring your on vector retrieval logic)

I just switched back to langchain when I realized that llamaindex doesn't support any kind of memory modules, at least not in a documented way...