Working with Reranker

What is a Reranker / CrossEncoder?

A Reranker model provides a powerful semantic boost to the search quality of any keyword or vector search system without requiring overhauls or intensive replacing.

Using Rerankers with Trieve Vector Inference

1. Update embedding_models.yaml

   To use a reranker model with Trieve Vector Inference, you will need to update your embedding_models.yaml file

   embedding_models.yaml

   ...
   models:
     ...
     my-reranker-model:
       replicas: 1
       revision: main
       modelName: BAAI/bge-reranker-large
   ...
   
2. Upgrade your TVI cluster

   Update TVI to include your models

   helm upgrade -i vector-inference \
     oci://709825985650.dkr.ecr.us-east-1.amazonaws.com/trieve/trieve-embeddings \
       -f embedding_models.yaml
   
3. Get embeddings endpoint

   kubectl get ing
   

   NAME                                              CLASS   HOSTS   ADDRESS                                                                 PORTS   AGE
   vector-inference-embedding-bge-reranker-ingress   alb     *       k8s-default-vectorin-b09efe8cf6-890425945.us-west-1.elb.amazonaws.com   80      77m
   

   The output looks like this