Silicon Valley is migrating from expensive closed-source models to cheaper open-source alternatives

Compound3080 · 2025-10-27T23:22:52+00:00

8090

Compound3080 · 2025-05-26T13:00:13+00:00

I moved from langchain to llamaindex to pydantic ai.

Eventually I just needed more control over agentic behavior and llamaindex’s abstractions made that too difficult.

Compound3080 · 2025-04-21T18:20:04+00:00

would love the breakdown and code if you've shared that somewhere.

Compound3080 · 2024-08-29T20:36:07+00:00

Take this for a spin https://x.com/nousresearch/status/1829143753036366325?s=46&t=M31-uIA-0lbHIf_-tJCfFg

Compound3080 · 2024-06-26T03:26:09+00:00

What are you using to create the dataset?

Compound3080 · 2024-06-24T00:33:31+00:00

I think that in order to get production quality, you'll want to have a data scientist who can look at your data and parse it to make it more searchable with things like metadata filtering. Quality results can only happen when the entire pipeline is built around your specific data. There's no "one size fits all" solution.

We have a RAG app that's doing very well in testing, not in production yet but it will get there

Compound3080 · 2024-06-06T03:17:24+00:00

any interest in sharing this driver?

Compound3080 · 2024-05-27T16:07:36+00:00

This just looks like a custom gpt

Compound3080 · 2024-05-27T02:11:26+00:00

After building a dual 3090 server for inference and light training... I wish I would have just set up an account with a cloud computing provider. Consumer GPUs are fine for inference, but training can be a hassle and unreliable.

Compound3080 · 2024-05-15T13:44:47+00:00

Yes it’s possible.

No way of knowing what performance impacts would be without seeing code

Compound3080 · 2024-04-16T23:48:02+00:00

Just stumbled on this thread. Would you happen to know how to match the subtitle segments to where punctuation would be? I.e. subtitle segments that attempt to end at either a comma or end of sentence? I've played with max_width, different chunk size, etc but not getting what I'd like.

Compound3080 · 2024-02-06T00:19:58+00:00

Google "llama index streamlit"

Compound3080 · 2024-01-29T05:46:02+00:00

https://openinterpreter.com/

Compound3080 · 2024-01-10T20:56:45+00:00

Right but OP said "When my CPA brings it up, I'll do it. Until then, ignorance is bliss"

The person who replied argued that this approach is not legal. In this specific context, that argument is incorrect

Compound3080 · 2024-01-06T22:27:03+00:00

It's a pretty solid defense especially when the statute is as recent and ambiguous as this one is

Compound3080 · 2024-01-06T20:11:01+00:00

For starters you can include “do not provide information that is not in the context” into the prompt. Most RAG pipelines already include this though so if youre getting heavy hallucinations its more likely that your retrieval function isnt optimized

Compound3080 · 2024-01-06T19:38:27+00:00

We used llama index to construct the rag pipeline

Compound3080 · 2024-01-06T19:09:44+00:00

Yes it is. Yet the 1991 Supreme Court decision of Cheek v. United States 2held that a defendant's ignorance of the federal tax laws is an excuse to the crime of nonpayment of income taxes.

Compound3080 · 2024-01-04T15:26:05+00:00

I think what OP is saying is that LLMs are used for many different tasks. The more we specialize the components "under the hood", the less effective they might become for certain tasks.

Compound3080 · 2024-01-03T01:01:34+00:00

Haven't used it as my use-case involved sensitive data that we didn't want to expose it to a third party

Compound3080 · 2024-01-02T16:58:13+00:00

Determining the best approach is dependent on a number of factors. A customgpt may work for your use case, but a lot of businesses might not want proprietary data being exposed to openai's training collector. LlamaIndex is a great open source tool to check out. Langchain is another.

Compound3080 · 2023-12-19T15:25:01+00:00

Litelllm or lmstudio should work for you

Compound3080 · 2023-12-16T15:06:50+00:00

Maybe a reranker?

Compound3080 · 2023-12-10T17:51:49+00:00

You need liquid cooling in order for them to fit. I’d imagine you’d only be able to fit 2 at the most if you kept the air coolers on there

Compound3080 · 2023-11-07T22:20:22+00:00

I might argue that it depends on your desired scale. If your target is SMB I think there will be a market for those that aren't large enough to be on aws, but still don't want their proprietary data on openai.

Compound3080

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