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Endpoints / Vectors
POSThttps://api.lazu.ai/v1/embeddings

Embeddings

Create vector embeddings with OpenAI-compatible clients. Use the model catalog to discover which models support embeddings and whether they accept custom dimensions.

BillingUsage tokens at the selected model and lane price; other billable dimensions may apply. Pricing & lanes ↗

Request body

modelstringrequired

Embedding model ID from /api/models/catalog.

inputstring | string[]required

Text input or ordered batch of text inputs. The response preserves order.

dimensionsintegernullable

Optional vector dimension for models that support truncation.

encoding_formatstringnullable

Output encoding format when supported by the upstream provider.

floatbase64

Response

objectstring

Usually list.

dataobject[]

One embedding item per input.

data[].embeddingnumber[] | string

Vector values or base64-encoded vector depending on encoding_format.

usage.prompt_tokensinteger

Input tokens used for embedding.

Batch guidance

Pass an array for small batches. For large data jobs, chunk client-side so each request stays within provider body-size and token limits.

Common models

ModelDimNotes
BAAI/bge-m31024Multilingual
text-embedding-3-small1536OpenAI cheap default
text-embedding-3-large3072OpenAI high quality
gemini-embedding-001768Google default

See also

Get a key
Sent from your browser to api.lazu.ai · key stays in this tab
RequestPOST /v1/embeddings
curl https://api.lazu.ai/v1/embeddings \
  -H "Authorization: Bearer $LAZU_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-6-luna",
    "input": ["doc one", "doc two"]
  }'
ResponseExample
{
  "object": "list",
  "data": [
    { "object": "embedding", "index": 0, "embedding": [0.0021, -0.013] }
  ],
  "model": "text-embedding-3-small",
  "usage": { "prompt_tokens": 6, "total_tokens": 6 }
}
Request receiptIllustrative example
$0.0001200 · 842 ms
Request ID
req_demo_01
Model · Lane
text-embedding-3-small · stable
Tokens · input
1,200
Key
demo-key

Example only — not a quote and not the result of your request. Send the request above to see your own receipt.

Read a real request receipt →

Catalog filter

supported_endpoint_types includes embeddings