voyage-code-2
Model Overview
This embedding model is designed for semantic retrieval of code and related text from both natural language and code-based queries. In a comprehensive evaluation across 11 code retrieval tasks—sourced from popular datasets like HumanEval and MBPP—it achieved a significant 14.52% improvement in recall over competitors, including OpenAI and Cohere. Additionally, it demonstrated consistent gains, averaging 3.03%, across various general-purpose text datasets.
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API Schema
post
Authorizations
Body
modelundefined · enumRequiredPossible values:
inputany ofRequired
string · min: 1 · max: 8000Optional
string[]Optional
input_typestring · enumOptionalDefault:
documentPossible values: encoding_formatstringOptional
Responses
201Success
post
POST /v1/embeddings HTTP/1.1
Host: api.apilaplas.com
Authorization: Bearer <YOUR_LAPLASAPI_KEY>
Content-Type: application/json
Accept: */*
Content-Length: 89
{
"model": "voyage-code-2",
"input": "text",
"input_type": "document",
"encoding_format": "text"
}201Success
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