Reranking

Reranking is an advanced feature that improves the quality and relevance of search results by using specialized models to re-evaluate and reorder the initial results. This second-pass approach significantly enhances result accuracy at the cost of slightly increased latency.

Basic Configuration

The simplest way to enable reranking is to set rerank=True in your search request:

from mixedbread import Mixedbread

mxbai = Mixedbread(api_key="YOUR_API_KEY")

results = mxbai.stores.search(
  query="API authentication methods",
  store_identifiers=["docs"],
  top_k=10,
  search_options={
      "rerank": True
  }
)

This uses our default reranking model (mixedbread-ai/mxbai-rerank-large-v2) with standard settings to improve your search results.

Advanced Configuration

from mixedbread import Mixedbread

mxbai = Mixedbread(api_key="YOUR_API_KEY")

results = mxbai.stores.search(
  query="database optimization techniques",
  store_identifiers=["docs"],
  search_options={
      "rerank": {
          "model": "mixedbread-ai/mxbai-rerank-large-v2",
          "top_k": 15,
          "with_metadata": ["category", "difficulty"]
      }
}
)

Configuration Options:

• Reranking Models: Use any supported reranking model from our inference endpoint. See Inference Models for available models and their capabilities. Defaults to "mixedbread-ai/mxbai-rerank-large-v2" when not specified.
• Top-k Constraint: The top_k value must be smaller than or equal to the first-stage retrieval count (your main top_k parameter). Defaults to null, which returns all results from the first stage (respects your main top_k parameter).
• Metadata Inclusion: Defaults to false. Set to true to include all metadata, or provide a list of specific metadata keys to include.