Hybrid - rrf¶
The hybrid_rrf
module is designed to retrieve passages from multiple retrievals.
The hybrid_rrf
module is tailored for retrieving passages from multiple sources of information.
It uses the Reciprocal Rank Fusion (RRF) algorithm to calculate final similarity scores.
This calculation is based on the ranking of passages in each retrieval,
effectively combining retrieval scores from different sources.
❗️Hybrid additional explanation¶
You can specify which rrf_k range that you want to explore. AutoRAG will find the optimal rrf_k parameter among your
specified range.
So, specify the range of rrf_k using weight_range
is important to use hybrid_rrf.
Node Parameters¶
(Required) top_k: Essential parameter for retrieval node.
Module Parameters¶
(Optional) weight_range: The range of the weight(rrf_k) that you want to explore. The parameter name is
weight
, but it is actuallyrrf_k
parameter at rrf algorithm. You have to input this value as tuple. It looks like this.(10, 60)
. Default is(4, 80)
.
Example config.yaml¶
modules:
- module_type: hybrid_rrf
weight_range: (4, 80)