Retrieval Search backend

Available since 2.3.0

This feature was introduced in version 2.3.0.

For some large dataset search can take a lot of time and memory. To reduce this you can use FaissSearchIndex. To work with it install:

# pip
pip install mteb[faiss-cpu]

# or uv
uv add "mteb[faiss-cpu]"

Usage example:

import mteb
from mteb.models import SearchEncoderWrapper
from mteb.models.search_encoder_index import FaissSearchIndex

model = mteb.get_model(...)
index_backend = FaissSearchIndex(model)
model = SearchEncoderWrapper(
    model,
    index_backend=index_backend
)
...

For example running minishlab/potion-base-2M on SWEbenchVerifiedRR took 694 seconds instead of 769.