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API ReferenceCreate an embedding vector for input text. POST

Create an embedding vector for input text.

Generate high-dimensional vector embeddings for text with nRouter. Fully compatible with OpenAI embeddings endpoints for semantic search, clustering, and RAG.

POST
/v1/embeddings

Authorization

NRouterApiKey
AuthorizationBearer <token>

Your nRouter virtual key (sk-nrouter-…). Sent as Authorization: Bearer sk-nrouter-….

In: header

Request Body

application/json

TypeScript Definitions

Use the request body type in TypeScript.

Response Body

application/json

application/json

application/json

application/json

application/json

application/json

application/json

application/json

application/json

application/json

curl -X POST "https://example.com/v1/embeddings" \  -H "Content-Type: application/json" \  -d '{    "model": "string",    "input": "string"  }'
{  "object": "list",  "model": "text-embedding-3-small",  "data": [    {      "object": "embedding",      "index": 0,      "embedding": [        0.0023,        -0.009,        0.015      ]    }  ],  "usage": {    "prompt_tokens": 5,    "total_tokens": 5  }}
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Models

List available models and their capabilities