BAAI/bge-m3 is an interesting model, that is multilingual and with a
context size of 8192. Even with a 16x larger context, it's only 4x slower
to compute it's embeddings on the worst case scenario.
Also includes a minor refactor of the rake task, including setting model
and concurrency levels when running the backfill task.
* FIX: Handle unicode on tokenizer
Our fast track code broke when strings had characters who are longer in tokens than
in UTF-8.
Admins can set `DISCOURSE_AI_STRICT_TOKEN_COUNTING: true` in app.yml to ensure token counting is strict, even if slower.
Co-authored-by: wozulong <sidle.pax_0e@icloud.com>