Reranks a list of documents based on their relevance to a query.
This endpoint accepts a query and a list of documents, then returns the documents sorted by relevance score in descending order.
Body
Required
-
The search query as a string.
Maximum query length:
- 8,000 tokens for
rerank-2.5andrerank-2.5-lite - 4,000 tokens for
rerank-2 - 2,000 tokens for
rerank-2-lite
Minimum length is
1. - 8,000 tokens for
-
A list of documents to be reranked, provided as strings.
Constraints:
- Maximum number of documents: 1,000
- Maximum tokens per query + document pair:
- 32,000 for
rerank-2.5andrerank-2.5-lite - 16,000 for
rerank-2 - 8,000 for
rerank-2-lite
- 32,000 for
- Maximum total tokens (query tokens × number of documents + sum of all document tokens):
- 600K for
rerank-2.5,rerank-2.5-lite,rerank-2, andrerank-2-lite
- 600K for
At least
1but not more than1000elements. Minimum length of each is1. -
The reranking model to use. Recommended models:
rerank-2.5,rerank-2.5-lite.Values are
rerank-2.5,rerank-2.5-lite,rerank-2, orrerank-2-lite. -
The number of most relevant documents to return. If not specified, all documents are returned with their reranking scores.
Minimum value is
1. -
Whether to include the document text in the response.
false(default): Returns only{"index", "relevance_score"}for each documenttrue: Returns{"index", "document", "relevance_score"}for each document
Default value is
false. -
Whether to truncate inputs that exceed the context length limit.
true(default): The query and documents are automatically truncated to fit within the context length limit.false: An error is returned if the query or any query-document pair exceeds the context length limit.
Default value is
true.
curl \
--request POST 'https://ai.mongodb.com/v1/rerank' \
--header "Authorization: Bearer $ACCESS_TOKEN" \
--header "Content-Type: application/json" \
--data '{"query":"string","documents":["string"],"model":"rerank-2.5","top_k":42,"return_documents":false,"truncation":true}'
{
"query": "string",
"documents": [
"string"
],
"model": "rerank-2.5",
"top_k": 42,
"return_documents": false,
"truncation": true
}
{
"object": "list",
"data": [
{
"index": 42,
"relevance_score": 42.0,
"document": "string"
}
],
"model": "string",
"usage": {
"total_tokens": 42
}
}
{
"detail": "string"
}
{
"detail": "string"
}
{
"detail": "string"
}
{
"detail": "string"
}
{
"detail": "string"
}
{
"detail": "string"
}
{
"detail": "string"
}
{
"detail": "string"
}