Is your feature request related to a problem? Please describe.
When trying to index and embedd a large vault through the selected embedding model - in my case Azure OpenAI - I run into HTTP 429 Errors, which are indicating that the Rate Limit kicked in on the embedding model. I maxed out the Quota on Azure OpenAI but still getting it.
Describe the solution you'd like
In order to avoid HTTP 429 Errors, it would be great to introduce an option to rate limit the number of request for the embedding creation.
Describe alternatives you've considered
Additionally there may be an option that influences the ramp up speed to the max limit of embedding requests in order to warm up the model and avoid through this the HTTP 429 Error.
Additional context
It would be great to extend the configurability on the vector store, e.g. chunking size, overlap, etc. That helps to experiment a little bit with the retrieval quality.
Is your feature request related to a problem? Please describe. When trying to index and embedd a large vault through the selected embedding model - in my case Azure OpenAI - I run into HTTP 429 Errors, which are indicating that the Rate Limit kicked in on the embedding model. I maxed out the Quota on Azure OpenAI but still getting it.
Describe the solution you'd like In order to avoid HTTP 429 Errors, it would be great to introduce an option to rate limit the number of request for the embedding creation.
Describe alternatives you've considered Additionally there may be an option that influences the ramp up speed to the max limit of embedding requests in order to warm up the model and avoid through this the HTTP 429 Error.
Additional context It would be great to extend the configurability on the vector store, e.g. chunking size, overlap, etc. That helps to experiment a little bit with the retrieval quality.