hey all. is there a way to use the llama index LLM class (or other llama index abstractions), to access the openai/anthropic Message Batching API?

ALSO its driving me CRAZY that the llama index tokenizer only ENCODES and has no decode im going to scream lol.

hey all: how do you ensure text fits into an embedding model?
you can't know apriori what tokenizer an embedding model uses - or even its input size! Or can you somehow?
if I have some arbitrary string 'text' and I need to trim it shorter so it fits into 'embed_model', whats the approach?

There must be a simple solution I am missing!

there are literally examples in the documentation
https://docs.llamaindex.ai/en/stable/examples/vector_stores/QdrantIndexDemo/
https://legacy.ts.llamaindex.ai/guides/agents/qdrant
https://docs.llamaindex.ai/en/stable/api_reference/storage/vector_store/qdrant/