curl --request POST \
--url https://api.octen.ai/embedding \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"input": [
"What is vector search?"
],
"model": "octen-embedding-8b",
"dimension": 4096,
"input_type": "query"
}
'{
"code": 0,
"msg": "success",
"request_id": "req_abc123def456",
"data": {
"results": [
{
"index": 0,
"embedding": [
0.0123,
-0.0456,
0.0789
]
},
{
"index": 1,
"embedding": [
-0.0011,
0.0234,
0.0567
]
}
],
"model": "octen-embedding-0.6b"
},
"meta": {
"usage": {
"input_tokens": 128
},
"warning": "Input was truncated for one or more items."
}
}{
"code": 400,
"msg": "Missing required parameter",
"request_id": "req_abc123def456"
}{
"code": 401,
"msg": "Invalid API Key",
"request_id": "req_abc123def456"
}{
"code": 403,
"msg": "Insufficient balance in account",
"request_id": "req_abc123def456"
}{
"code": 429,
"msg": "Exceeding the rate limit",
"request_id": "req_abc123def456"
}{
"code": 500,
"msg": "Internal error",
"request_id": "req_abc123def456"
}Embedding
Converts text into vector representations. Supports batch input, multiple models, and configurable output dimensions.
curl --request POST \
--url https://api.octen.ai/embedding \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"input": [
"What is vector search?"
],
"model": "octen-embedding-8b",
"dimension": 4096,
"input_type": "query"
}
'{
"code": 0,
"msg": "success",
"request_id": "req_abc123def456",
"data": {
"results": [
{
"index": 0,
"embedding": [
0.0123,
-0.0456,
0.0789
]
},
{
"index": 1,
"embedding": [
-0.0011,
0.0234,
0.0567
]
}
],
"model": "octen-embedding-0.6b"
},
"meta": {
"usage": {
"input_tokens": 128
},
"warning": "Input was truncated for one or more items."
}
}{
"code": 400,
"msg": "Missing required parameter",
"request_id": "req_abc123def456"
}{
"code": 401,
"msg": "Invalid API Key",
"request_id": "req_abc123def456"
}{
"code": 403,
"msg": "Insufficient balance in account",
"request_id": "req_abc123def456"
}{
"code": 429,
"msg": "Exceeding the rate limit",
"request_id": "req_abc123def456"
}{
"code": 500,
"msg": "Internal error",
"request_id": "req_abc123def456"
}Authorizations
Bearer token used for request authentication. Alternatively, you can send the API key in the x-api-key header. Note: A payment method is required to use the API.
Body
The text to be converted into embeddings. Maximum tokens per element: 32768. Maximum request body size: 2MB
1000The embedding model used for this request. octen-embedding-0.6b (max dim: 1024) for cost/throughput priority; octen-embedding-4b (max dim: 2560) for most applications; octen-embedding-8b (max dim: 4096) for accuracy-critical tasks.
octen-embedding-0.6b, octen-embedding-4b, octen-embedding-8b The dimensionality of the output embedding vectors. Defaults to the model's max dimension (0.6b: 1024, 4b: 2560, 8b: 4096). If set to a value smaller than the model default, the embedding will be truncated to the first N values. Any positive integer ≤ model default dimension is allowed.
Specifies whether the input is a query or a document for retrieval. Different values apply different internal prompts: query → "Represent the query for retrieving supporting" (prepended and counted in input_tokens); document and null mean no special prompt is applied.
query, document Response
Successful embedding response
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