Hey folks! I'm using llamaindex with pgvector. I'm usiong text-embedding-large-3 with embedding size of 1536. When using the vector store and asking a question, I get this error: sqlalchemy.exc.StatementError: (builtins.ValueError) expected 1536 dimensions, not 3072 This is odd because embedding with 3072 doesn't work with pgvector due to postgres max dimensions. I'm assuming that there must be a dimension size that is hardcoded somewhere? Does anyone have a similar issue?
Swapping to ada-2 works, even though a different embedding model was used to embed it. The results are wrong, but at least it doesn't give an error. I'm assuming there is a hardcoded 3072 somewhere for what it is expecting. But we can actually use 1536 dimensions with embedding-3-large. Any thoughts, friends?
