# Reranker Node

### Overview

The Reranker Node optimizes document retrieval by reordering a set of documents based on their relevance to a specific query. It uses specialized reranking models to improve the accuracy and relevance of search results by considering semantic similarity and contextual information.

Usage cost: 1 credit

### Configuration

#### Settings

1. **Model Selection**
   * Reranker Model\*: Select the reranking model to use
   * Top K: Number of documents to return after reranking (default: 3)
   * Query\*: The search query used to rerank documents
   * Documents\*: List of documents to be reranked

#### Output Ports

* `reranked_documents` (Document\[]): Array of reranked documents ordered by relevance

### Best Practices

1. **Document Preparation**
   * Keep document segments concise and focused
   * Ensure documents contain meaningful content
   * Remove duplicate or near-duplicate content
2. **Query Optimization**
   * Use specific, targeted queries
   * Include key terms and concepts
   * Consider query expansion when needed
   * Use consistent query formatting
3. **Performance Tuning**
   * Adjust Top K based on use case requirements
   * Consider document batch size
4. **Integration Tips**
   * Place after retrieval nodes
   * Connect to document transformation nodes when needed