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Documentation Index

Fetch the complete documentation index at: https://docs.lemondata.cc/llms.txt

Use this file to discover all available pages before exploring further.

For coding agents, discover the current recommended rerank shortlist first with GET /v1/models?recommended_for=rerank, then send the selected model explicitly to this endpoint.
Rerank documents using semantic similarity models. Useful for improving search results and RAG applications.

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Request Body

Synchronous request timeout: This non-chat endpoint waits for the routed model to finish. Large inputs, long audio, or large batches can exceed common 30s client defaults, so set your HTTP client timeout to at least 120s.
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model
string
required
ID of the reranker model to use (e.g., BAAI/bge-reranker-v2-m3, qwen3-rerank).
​
query
string
required
The query to rank documents against. Maximum length: 32,000 characters.
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documents
array
required
List of documents (strings) to rerank. Limits: up to 1,000 documents, each document up to 100,000 characters, and at most 2,000,000 total document characters.
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top_n
integer
Number of top results to return. Defaults to all documents. Must be at least 1 and no greater than documents.length. LemonData currently has no governed provider-specific lower hard cap; if a provider publishes one later, it must be added to rerank request-shape truth before being documented or enforced.
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return_documents
boolean
default:"false"
Whether to include original document text in response.

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Response

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results
array
Ranked list of documents with scores.Each result contains:
  • index (integer): Original document index
  • relevance_score (number): Relevance score (0-1)
  • document (string): Original text (if return_documents=true)
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model
string
The model used for reranking.
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usage
object
Token usage statistics.
curl -X POST "https://api.lemondata.cc/v1/rerank" \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "BAAI/bge-reranker-v2-m3",
    "query": "What is machine learning?",
    "documents": [
      "Machine learning is a subset of AI",
      "The weather is nice today",
      "Deep learning uses neural networks"
    ],
    "top_n": 2,
    "return_documents": true
  }'

{
  "results": [
    {
      "index": 0,
      "relevance_score": 0.95,
      "document": "Machine learning is a subset of AI"
    },
    {
      "index": 2,
      "relevance_score": 0.82,
      "document": "Deep learning uses neural networks"
    }
  ],
  "model": "BAAI/bge-reranker-v2-m3",
  "usage": {
    "prompt_tokens": 45,
    "total_tokens": 45
  }
}