Yes that is very helpful!
It’s confusing because the docs pages for the text2vec_openai module (text2vec-openai | Weaviate - Vector Database) refer to it in camel case like “baseURL”
However now I’m getting this error:
Failed to import 1 objects
e.g. Failed to import object with error: WeaviateInsertManyAllFailedError(‘Every object failed during insertion. Here is the set of all errors: send POST request: Post “http://host.docker.internal:1234/v1/embeddings”: context deadline exceeded (Client.Timeout exceeded while awaiting headers)’)
And I’m wondering if generating the vector is just taking too long because its a large object. Is there an equivalent in openai_text2vec of the text_fields parameter used in multi2vec-bind ? Like, without using named indexes how do I tell openai_text2vec which properties to use for generating the vector?