Rerank

POST /v1/rerank

Reorder documents by relevance to a query using cross-encoder models, improving retrieval accuracy in RAG pipelines.

Request

POST https://api.chuizi.ai/v1/rerank

Authentication

Authorization: Bearer ck-your-api-key

Parameters

Parameter	Type	Required	Default	Description
`model`	string	Yes	—	Model name, e.g. `cohere/rerank-v3.5`, `jina/jina-reranker-v2`
`query`	string	Yes	—	The search query to rank documents against
`documents`	string[]	Yes	—	Array of document strings to rerank

Request Example

config.json

json

{
  "model": "cohere/rerank-v3.5",
  "query": "What is the capital of France?",
  "documents": [
    "Paris is the capital and largest city of France.",
    "Berlin is the capital of Germany.",
    "The Eiffel Tower is located in Paris, France.",
    "London is the capital of the United Kingdom."
  ],
  "top_n": 3,
  "return_documents": true
}

Response

config.json

json

{
  "id": "gen-xxxxxxxxxxxxxxxx",
  "model": "cohere/rerank-v3.5",
  "results": [
    {
      "index": 0,
      "relevance_score": 0.9985,
      "document": { "text": "Paris is the capital and largest city of France." }
    },
    {
      "index": 2,
      "relevance_score": 0.8721,
      "document": { "text": "The Eiffel Tower is located in Paris, France." }
    },
    {
      "index": 3,
      "relevance_score": 0.1503,
      "document": { "text": "London is the capital of the United Kingdom." }
    }
  ],
  "usage": {
    "total_tokens": 82
  }
}

Code Examples

terminal

bash

curl -X POST https://api.chuizi.ai/v1/rerank \
  -H "Authorization: Bearer ck-your-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "cohere/rerank-v3.5",
    "query": "What is the capital of France?",
    "documents": [
      "Paris is the capital and largest city of France.",
      "Berlin is the capital of Germany."
    ],
    "top_n": 2
  }'

Next Steps

Embeddings API — generate vector embeddings for semantic search
Choose a Model — compare reranking model options
Pricing — reranking model costs