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POST/v1/embeddings

Create embeddings

Creates embedding vectors representing the input text, using an OpenAI-compatible request and response format. Any SDK that supports OpenAI embeddings works by changing the base URL and API key.

Calling an asymmetric model

Some embedding models are asymmetric: they encode the same sentence differently depending on whether it is a search query or a stored document. When you call one, embed documents as-is (the default) and set extra.input_type to query for search queries, so the model applies its instruct prefix. Sending queries without it silently degrades retrieval quality. sionic-ai/comsat-embed-ko-8b-preview is asymmetric.

Headers

AuthorizationstringRequired
Bearer token for authentication. Format: Bearer YOUR_API_KEY
x-opengateway-user-idstringOptional
User identifier for analytics and tracking.
x-opengateway-session-idstringOptional
Session identifier for analytics and tracking.

Request body

modelstringRequired
ID of the embedding model to use, in the owner/model format, such as sionic-ai/comsat-embed-ko-8b-preview.
inputstring or arrayRequired
Text to embed — a single string or an array of strings. Each input is limited to 8,192 tokens; longer inputs are rejected with 400 (they are never silently truncated). Batches are limited to 128 inputs per request. Token ID arrays are not supported.
encoding_formatstringOptional
Format of the returned vectors: float (default) or base64.
dimensionsintegerOptional
Number of dimensions for the output vectors. Supported values for comsat-embed-ko-8b-preview are 2048 and 4096 (default). Other values are rejected with 400.
userstringOptional
End-user identifier forwarded to the provider when supported.
extraobjectOptional
OpenGateway-specific extension parameters. OpenAI SDKs pass this via extra_body.
input_typestring

query or document (default). Applies to the whole batch. Use query when embedding search queries for retrieval.

fallbacksarray

List of fallback model IDs to try if the primary target fails.

Returns

Returns an OpenAI-compatible embeddings response.

objectstring
Always list.
dataarray
One embedding object per input, in request order.
data[].embeddingarray or string
The embedding vector — an array of floats, or a base64-encoded string when encoding_format is base64.
data[].indexinteger
Index of the corresponding input.
modelstring
The requested model ID.
usageobject
Token usage. Embeddings have no output tokens, so prompt_tokens equals total_tokens. Query encoding includes the model's instruct prefix tokens.

Request

# Document embedding (default)
curl https://apis.opengateway.ai/v1/embeddings \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $API_KEY" \
  -d '{
    "model": "sionic-ai/comsat-embed-ko-8b-preview",
    "input": "Seoul is the capital of South Korea."
  }'


# Query embedding (for search queries)
curl https://apis.opengateway.ai/v1/embeddings \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $API_KEY" \
  -d '{
    "model": "sionic-ai/comsat-embed-ko-8b-preview",
    "input": "What is the capital of South Korea?",
    "extra": {"input_type": "query"}
  }'

Response

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [0.0388, 0.0105, -0.0030, ...]
    }
  ],
  "model": "sionic-ai/comsat-embed-ko-8b-preview",
  "usage": {
    "prompt_tokens": 7,
    "total_tokens": 7
  }
}
Embeddings — OpenGateway