Anouk D.

Ah it's because the model still exists of course, I hoped a new version would be enough 🙂 thanks! In the mean time I did manage to get the embedding projections working from the inferences page. Thanks again for your help! my problems are all solved at the moment

Ah when I removed the "compared to" row it does work! so nevermind

I'm going to share my code here in case I'm missing something obvious. but to me it seems like it should work just fine and the dimensionality shouldn't be an issue. Am I logging it incorrectly?

heyhey, Yes I adjusted my code and I'm using a proper embedding model now to generate the embeddings for the prompt and repsonse. both have consistent dimensions (always 1024). I logged every embedding length before writing it to Arize and it really is all 1024, but the WebApp still keeps telling me that it is inconsistent?

I'm simply logging inferences of an LLM like i would for a regular ML model 🙂 I'm fairly new to the whole embedding thing and couldn't find a lot of clear pointers on how to create the embeddings, so I was just sending the tokenized prompt and response vectors. I'm guessing that's not how it works then as they will have variable length 😅 Thanks, I'll have a look then into adjusting how the embeddings are calculated!

Ah I'm getting an error now. Is it because the vectors are not all of the same length? not sure how I can ensure that they will be all the same length though when the prompts can vary so much 🤔