Create embeddings

/v1/embeddings

Examples verified against code, not live (TI-78). The models plane takes the same ozk_ key as every other plane ($PLUNGE_API_KEY). Errors carry error.code in the body, never an X-Error-Code header.

Authorizations

Authorizationstringheaderrequired

Bearer token: Authorization: Bearer ozk_…. ozk_ platform API key (Authorization: Bearer ozk_…)

Authorizationstringheaderrequired

Bearer token: Authorization: Bearer sk-ocean-…. Legacy sk-ocean- inference key: still accepted on the money plane until the sk-ocean- sunset; new integrations use the ozk_ key

Body

application/json

Money plane, ozk_ auth. Same guardrail/cache enforcement as chat completions.

modelstringrequired

inputanyrequired

A string, or an array of strings

Response

Embeddings result

application/json

Response headers

x-request-idstringfrom code

Server-minted request id.

objectstringrequired

dataobject[]required

modelstringrequired

usageobject

The body failed validation; error.code is in the body (no X-Error-Code on the models plane).

Error code: invalid_request_errorfrom code

Missing or invalid API key

application/json

errorobjectrequired

Show child attributes

codestringrequired

messagestringrequired

byok_required

Error code: insufficient_balancefrom code

application/json

errorobjectrequired

Show child attributes

codestringrequired

messagestringrequired

model_not_allowed or content_blocked

application/json

errorobjectrequired

Show child attributes

codestringrequired

messagestringrequired

rate_limit_exceeded or spend_cap_exceeded

Error code: insufficient_quotafrom code

application/json

errorobjectrequired

Show child attributes

codestringrequired

messagestringrequired

money_plane_unavailable — INFERENCE_GATEWAY_SERVICE not bound on this tier

application/json

errorobjectrequired

Show child attributes

codestringrequired

messagestringrequired

import os import requests response = requests.post( "https://api.plungeai.com/v1/embeddings", headers={"Authorization": f"Bearer {os.environ['PLUNGE_API_KEY']}"}, json={ "model": "openai/text-embedding-3-small", "input": "PlungeAI", }, ) if not response.ok: raise SystemExit(f"{response.status_code} {response.json()['error']['code']}") print(response.json())

const response = await fetch('https://api.plungeai.com/v1/embeddings', { method: 'POST', headers: { Authorization: `Bearer ${process.env.PLUNGE_API_KEY}`, 'Content-Type': 'application/json', }, body: JSON.stringify({ "model": "openai/text-embedding-3-small", "input": "PlungeAI" }), }) if (!response.ok) throw new Error(`${response.status} ${(await response.json()).error?.code}`) console.log(await response.json())

import java.net.URI; import java.net.http.HttpClient; import java.net.http.HttpRequest; import java.net.http.HttpResponse; public class Main { public static void main(String[] args) throws Exception { HttpClient client = HttpClient.newHttpClient(); HttpRequest request = HttpRequest.newBuilder() .uri(URI.create("https://api.plungeai.com/v1/embeddings")) .header("Authorization", "Bearer " + System.getenv("PLUNGE_API_KEY")) .header("Content-Type", "application/json") .POST(HttpRequest.BodyPublishers.ofString("{\"model\":\"openai/text-embedding-3-small\",\"input\":\"PlungeAI\"}")) .build(); HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString()); if (response.statusCode() >= 400) { // Models plane: the machine code is error.code in the JSON body. System.out.println(response.statusCode() + " " + response.body()); return; } System.out.println(response.body()); } }

curl -X POST 'https://api.plungeai.com/v1/embeddings' \ -H "Authorization: Bearer $PLUNGE_API_KEY" \ -H 'Content-Type: application/json' \ -d '{"model":"openai/text-embedding-3-small","input":"PlungeAI"}'

import os from openai import OpenAI client = OpenAI(api_key=os.environ["PLUNGE_API_KEY"], base_url="https://api.plungeai.com/v1") embedding = client.embeddings.create(model="openai/text-embedding-3-small", input="hello") print(len(embedding.data[0].embedding))

import OpenAI from 'openai' const client = new OpenAI({ apiKey: process.env.PLUNGE_API_KEY, baseURL: 'https://api.plungeai.com/v1' }) const embedding = await client.embeddings.create({ model: 'openai/text-embedding-3-small', input: 'hello' }) console.log(embedding.data[0].embedding.length)

Create embeddings

Authorizations

Body

Response

Response headers

Planned: TI-33

Planned: TI-34