According to the documentation, I set Embedding Dimensions to 768 and used the provided SQL for Supabase.
I then proceeded to Crawl Pydantic AI Docs. Crawling is successful. The log shows all but 3 URLs were processed and stored.
But they were never actually stored. Database Statistics shows zero.
I checked my Docker logs, and requests to store the data in the database were unsuccessful because embedding dimension was expected to be 768 but it was actually 1536.
I deleted the database and recreated it as 1536 (even though I am using Ollama) and also left it as nomic-embed-text. It worked.
Therefore, is Ollama not always 768? Does it have something to do with the new qwq:32b? I’m confused, how can we be sure what to set this to?
This is actually baffling to me because I’m 99% sure nomic-embed-text is always 768 dimensions! Even did a sanity check Google search just now to confirm. The LLM you use shouldn’t matter since it’s all up to the embedding model. What command did you use to pull nomic-embed-text? And did you change anything through config/environment variables for Ollama?
Haven’t used this in archon but my previous use of ollama tells me that standard practice was to run ollama pull from the cli. I believe it will also pull automatically if you try to use a model you don’t have locally. Not sure how archon uses the info provided. If it assumes ollama is already running then maybe you need to pull it.
Yeah exactly! @Dupre Archon won’t pull the embedding model for you so it’s assuming you already ran the “ollama pull” command to pull nomic-embed-text, like
I’m getting the same problem. But when I check my logs in the docker container, it looks like the documentation insert isn’t adjusting to the dimensions I set for the embedding model. I am using the nomic-embed-text, and specifically created the database with the 768 dimension. But when the documentation is trying to insert, it still tries to use 1536.
I didn’t find a solution, but I just did what OP did, and updated the table to handle 1536 dimension, and ran the application again. It worked well and the database was seeded properly.