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Overview Models Agents Tools Audio & voice Production API reference

Create a decision

Decision decisions().create(DecisionCreateParamsparams, RequestOptionsrequestOptions = RequestOptions.none())
POST/decisions

Use this endpoint to ask classification or scoring questions about the same input. You’ll get the answers back in the order you asked the questions.

For text, you can pass a string. You can also send user messages containing input_text and input_image parts, with up to 128 images per request. Images can be base64 data URLs or publicly accessible HTTP(S) URLs. File IDs aren’t accepted. Other message roles, function calls, files, audio, and item references aren’t supported.

Sometimes a question returns a refusal instead of an answer. The result has type refusal and includes the question’s name, or null if you didn’t give it one.

ParametersExpand Collapse
DecisionCreateParams params
Input input

The text or images to evaluate for every question. Provide a text string or user messages containing text and images. Images can be base64 data URLs or publicly accessible HTTP(S) URLs; at most 128 images are allowed across all messages in one request. Files, audio, tools, and item references are not supported.

String model
minLength0
maxLength1048576
List<Question> questions
Optional<String> safetyIdentifier

Opaque caller-provided end-user identifier, scoped by the verified org. Match Responses’ limit; this is never the authenticated user identity.

minLength0
maxLength128
ReturnsExpand Collapse
class Decision:
List<Answer> answers
String model
minLength0
Usage usage

Create a decision

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.decisions.Decision;
import com.openai.models.decisions.DecisionCreateParams;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

        DecisionCreateParams params = DecisionCreateParams.builder()
            .input("string")
            .model("model")
            .addPredicateQuestion("instructions")
            .build();
        Decision decision = client.decisions().create(params);
    }
}
{
  "model": "gpt-6-luna",
  "answers": [
    {"type": "predicate", "name": "damaged", "probability": 0.95}
  ],
  "usage": {
    "input_tokens": 42,
    "input_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0},
    "output_tokens": 0,
    "output_tokens_details": {"reasoning_tokens": 0},
    "total_tokens": 42
  }
}
Returns Examples
{
  "model": "gpt-6-luna",
  "answers": [
    {"type": "predicate", "name": "damaged", "probability": 0.95}
  ],
  "usage": {
    "input_tokens": 42,
    "input_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0},
    "output_tokens": 0,
    "output_tokens_details": {"reasoning_tokens": 0},
    "total_tokens": 42
  }
}