RailwailRailwail
POST

/api/v1/embeddings

Generate vector embeddings for text input. Use for semantic search, RAG, clustering, and similarity comparison.

Request Body

ParameterTypeDescription
model
required
stringEmbedding model, e.g. "text-embedding-3-small"
input
required
string | string[]Single text or array of texts to embed.
encoding_formatstring"float" or "base64"Default: "float"

Examples

javascript
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "rw_live_xxxxx",
  baseURL: "https://railwail.com/api/v1",
});

const response = await client.embeddings.create({
  model: "text-embedding-3-small",
  input: "Hello world",
});

console.log(response.data[0].embedding.length); // 1536

Response

JSON
{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [0.0023064255, -0.009327292, ...],
      "index": 0
    }
  ],
  "model": "text-embedding-3-small",
  "usage": {
    "prompt_tokens": 2,
    "total_tokens": 2
  }
}

Compatible Models

text-embedding-3-small
text-embedding-3-large
text-embedding-ada-002
nomic-embed-text
bge-large-en-v1.5
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