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Comment by byteknight | Hacker News Reader

Is this a gripe with the verbiage used or is this a knock to the library itself?

I have been playing with langchain and llamaindex a bit.

I like the data loading abstraction and am very curious why you say it doesn't work? It uses ChatGPT for the reranking.

It’s just interesting to see the VC money pouring into these tools. My argument is serious integration/scale doesn’t involve a library like these (honestly prototyping doesn’t really need to either).

Id be more bullish on paradigm (platform/cloud level) shifts vs connectors, wrappers, and utility functions

Ymmv and to be fair I haven’t tried to scale these tools. I have worked on scaled platforms around embedding retrieval and rerank (including LLMs) so it’s just my take.

I would argue the level of abstraction it provides lowers the barrier to entry for most average programmers, myself included. LllamaIndex was my entrance to programatically utilizing LLMs. I have since moved to LangChain, with some documents loaded via LlamaIndex, but it has been a blast.

Yes but this is just ETL - LlamaIndex and LangChain are re-inventing it - why use them when you have robust technology already?

1. You ETL your documents into a vector database - you run this pipeline everyday to keep it up to date. You can run scalable, robust pipelines on Spark for this.

2. You have a streaming inference pipeline that has components that make API calls (agents) and between them transform data. This is Spark streaming.

Prophecy is working with large enterprises to implement generative AI use cases, but they don’t talk so much on HN. Here’s our talk from Data+AI Summit:

Build a Generative AI App on Enterprise Data in 13 Minutes

https://www.youtube.com/watch?v=1exLfT-b-GM

Here’s a blog/demo

https://www.prophecy.io/blog/prophecy-generative-ai-platform...

Cool! Lets say I have thousands of documents that I want questions and answers for. Would your solution work for this? I wouldn’t know which documents to send with the prompts though as I want info on the aggregate (like trends and most mentioned phrases or words).

Right on— I should’ve and do recognize the utility of open source abstractions; esp with AI/ML.

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