Batch semantic search indexing

This MR addresses ots/llm/meta#61 (closed) by batching embedding requests during indexing for Semantic Search so that we can take advantage of RunPod GPUs. It is a companion MR to ots/llm/llm-api!62 (merged)

Steps to Test

Follow the steps in ots/llm/llm-api!62 (merged).

In settings.py, make sure SEMANTIC_SEARCH_EMBEDDING_API_BASE_URL is pointed at http://localhost:8889 or equivalent.

pipenv install -e ../semantic-search/django-torque-semantic-search
pipenv run python manage.py shell

from torque import models
models.WikiConfig.objects.get(collection__name="DemoView", group="TorqueAdmin").rebuild_search_index()