[image] Semantic quick search gives error 500 Support That’s an experimental feature that requires you to enable per post embeddings and to use a re-ranker model, which we are still evaluating the feasibility of. I will move this setting to a hidden one s…

[image] MarcP: I am still getting the error from the linked topic. Getting an error here?

Failed to process hijacked response correctly : ArgumentError : address cannot be nil or empty When I do an AI search - my issue is 1:1 with the topic I linked. [image]

I mean, where is this happening, here on Meta or in your site?

Ah no, on my own instance. I’m not sure if I ever seen it work over there.

Oh it won’t work out of the box indeed, as it requires deployment of a re-reranker model and enabling per post embeddings. One of the hurdles with per post embeddings is the storage cost associated with it, and we just made a big advance there via FEATURE: Index embeddings using bit vectors (#824) …

[image] Falco: Oh it won’t work out of the box indeed, as it requires deployment of a re-reranker model and enabling per post embeddings. I know, I’ve followed every tutorial I could find on this. Not using self hosted models, just OpenAI. Discourse AI - Embeddings Enabling AI search

That is why it is a hidden experimental setting :smile:

Well that was actually my question (see topic title), thanks. Confusion arises because there is no hidden setting. As I recall, this should be set in app.yml and below is the only hidden setting that’s not commented out. [image] tldr; I was able to follow above mentioned guides without “unhiding…

I saw a “quick search” here. Is it supposed to work like the instant search experiment? :open_mouth:

La recherche sémantique d'en-tête est-elle toujours expérimentale ?

Soutien

MarcP (MarcP) Octobre 14, 2024, 9:10 7

Je sais, j’ai suivi tous les tutoriels que j’ai pu trouver à ce sujet. Je n’utilise pas de modèles auto-hébergés, juste OpenAI.

Discourse AI - Embeddings
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La recherche sémantique d'en-tête est-elle toujours expérimentale ?

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