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Experimental library for scraping websites using OpenAI's GPT API

jamesturk.github.io

11–20 of 149 posts

Re: Experimental library for scraping websites using OpenAI's GPT API

#12
This was one of the first things I built when I got access to the API, the results ranged from excellent to terrible, it was also non deterministic, meaning I could pipe in the site content twice and the results would be different. Eagerly awaiting my gpt4 access to see if the accuracy improves for this usecase.

Re: Experimental library for scraping websites using OpenAI's GPT API

#14
I follow some indie hackers online who are in the scraping space, such as BrowserBear and Scrapingbee, I wonder how they will fare with something like this. The only solace is that this is nondeterministic, but perhaps you can simply ask the API to create Python or JS code that is deterministic, instead.

More generally, I wonder how a lot of smaller startups will fare once OpenAI subsumes their product. Those who are running a product that's a thin wrapper on top of ChatGPT or the GPT API will find themselves at a loss once OpenAI opens up the capability to everyone. Perhaps SaaS with minor changes from the competition really were a zero-interest-rate phenomenon.

This is why it's important to have a moat. For example, I'm building a product that has some AI features (open source email (IMAP and OAuth2) / calendar API), but it would work just fine even without any of the AI parts, because the fundamental benefit is still useful for the end user. It's similar to Notion, people will still use Notion to organize their thoughts and documents even without their Notion AI feature.

Build products, not features. If you think you are the one selling pickaxes during the AI gold rush, you're mistaken; it's OpenAI who's selling the pickaxes (their API) to you who are actually the ones panning for gold (finding AI products to sell) instead.

Re: Experimental library for scraping websites using OpenAI's GPT API

#17

Great use case! - LLMs excel at converting unstructured => structured data - Will become less expensive over time - When GPT-4 image support launches publicly, would be a cool integration / fallback for cases where the code-based extraction fails to produce desired results - In theory works on any website regardless of format / tech

What I think is super compelling is other AI techniques excel at reasoning about structured data and making complex inferences. Using a feedback cycle ensemble model between LLMs and other techniques I think is how the true power of LLMs will be unlocked. For instance many techniques can reason about stuff expressed in RDF, and gpt4 does a pretty good job changing text blobs like web pages into decent and well formed RDF. The output of those techniques are often in RDF, which gpt4 does a good job of ingesting and converting into human consumable format.

Re: Experimental library for scraping websites using OpenAI's GPT API

#18
post #12

This was one of the first things I built when I got access to the API, the results ranged from excellent to terrible, it was also non deterministic, meaning I could pipe in the site content twice and the results would be different. Eagerly awaiting my gpt4 access to see if the accuracy improves for this usecase.

It seems like he's setting temperature=0 which also means it is deterministic. Anecdotally, I've been playing with it since he posted an earlier link & it does shockingly well on 3.5 and nearly perfectly on 4 for my use cases.

(to be clear: I submitted but not the author of the library myself)

Re: Experimental library for scraping websites using OpenAI's GPT API

#20
post #4

[dead]

All I got is this: ```json { "url": " https://www.3sonsbrewingco.com/menus ", "title": "MENU | 3sons", "content": " \r\n\r\nBrewery & Kitchen\r\n\r\nEAT & DRINK\r\n\r\n " } ``` I was hoping for some menu items...

Can you refine further ? Because indeed that look like something beautiful soup would output
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