## Create a decision

**post** `/decisions`

Evaluate ordered classification and scoring questions against shared input. Answers are returned in question order.

Supply input as a string or user messages containing text and inline images. Only user messages with `input_text` and `input_image` parts are supported; non-user roles, function calls, files, audio, and item references are not supported. Images require a data URL, not an external URL or file ID. At most 128 images are allowed across the request.

Each question can return a refusal instead of a scored answer. A refusal has type `refusal` and the corresponding question name, or null if unnamed.

### Body Parameters

- `input: string or array of DecisionInputMessage`

  The text or images to evaluate for every question. Provide a text string or user messages containing text and inline images. Images must be inline data URLs; at most 128 images are allowed across all messages in one request. External URLs, files, audio, tools, and item references are not supported.

  - `string`

  - `array of DecisionInputMessage`

    - `content: string or array of DecisionInputPart`

      Text evidence or an ordered list of text and inline image parts.

      - `string`

      - `Parts = array of DecisionInputPart`

        - `DecisionInputText object { text, type }`

          - `text: string`

          - `type: "input_text"`

            - `"input_text"`

        - `DecisionInputImage object { image_url, type, detail }`

          An inline image. External URLs and file IDs are not supported.

          - `image_url: string`

            A base64-encoded image in a data URL.

          - `type: "input_image"`

            - `"input_image"`

          - `detail: optional "low" or "high" or "auto" or "original" or null`

            The image detail level, using the selected model's image profile. Defaults to auto.

            - `"low"`

            - `"high"`

            - `"auto"`

            - `"original"`

    - `role: "user"`

      - `"user"`

    - `type: optional "message"`

      - `"message"`

- `model: string`

- `questions: array of object { instructions, type, name }  or object { choices, instructions, type, name }  or object { instructions, levels, type, name }`

  - `Predicate object { instructions, type, name }`

    Estimate how likely it is that a statement about the input is true.

    - `instructions: string`

    - `type: "predicate"`

      The type of the object. Always `predicate`.

      - `"predicate"`

    - `name: optional string`

  - `Choice object { choices, instructions, type, name }`

    Choose from the supplied options based on the input.

    - `choices: array of object { value, description }`

      - `value: string or boolean`

        Choice values are typed: a string and a boolean with the same text are distinct.

        - `string`

        - `boolean`

      - `description: optional string`

    - `instructions: string`

    - `type: "choice"`

      The type of the object. Always `choice`.

      - `"choice"`

    - `name: optional string`

  - `Score object { instructions, levels, type, name }`

    Rate the input against the supplied ordered levels.

    - `instructions: string`

    - `levels: array of object { label, description }`

      - `label: string`

      - `description: optional string`

    - `type: "score"`

      The type of the object. Always `score`.

      - `"score"`

    - `name: optional string`

- `safety_identifier: optional string or null`

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

### Returns

- `Decision object { answers, model, usage }`

  - `answers: array of object { name, probability, type }  or object { choice, confidence, name, 2 more }  or object { confidence, name, probabilities, 2 more }  or object { name, type }`

    - `Predicate object { name, probability, type }`

      - `name: string or null`

      - `probability: number`

      - `type: "predicate"`

        The type of the object. Always `predicate`.

        - `"predicate"`

    - `Choice object { choice, confidence, name, 2 more }`

      - `choice: string or boolean`

        Choice values are typed: a string and a boolean with the same text are distinct.

        - `string`

        - `boolean`

      - `confidence: number`

      - `name: string or null`

      - `probabilities: array of object { probability, value }`

        - `probability: number`

        - `value: string or boolean`

          Choice values are typed: a string and a boolean with the same text are distinct.

          - `string`

          - `boolean`

      - `type: "choice"`

        The type of the object. Always `choice`.

        - `"choice"`

    - `Score object { confidence, name, probabilities, 2 more }`

      - `confidence: number`

      - `name: string or null`

      - `probabilities: array of object { label, probability, value }`

        - `label: string`

        - `probability: number`

        - `value: number`

      - `score: number`

      - `type: "score"`

        The type of the object. Always `score`.

        - `"score"`

    - `Refusal object { name, type }`

      The model declined to answer this question. Other questions in the same request can still receive answers.

      - `name: string or null`

      - `type: "refusal"`

        The type of the object. Always `refusal`.

        - `"refusal"`

  - `model: string`

  - `usage: object { input_tokens, input_tokens_details, output_tokens, 2 more }`

    - `input_tokens: number`

    - `input_tokens_details: object { cache_write_tokens, cached_tokens }`

      - `cache_write_tokens: number`

      - `cached_tokens: number`

    - `output_tokens: number`

    - `output_tokens_details: object { reasoning_tokens }`

      - `reasoning_tokens: number`

    - `total_tokens: number`

### Example

```http
curl https://api.openai.com/v1/decisions \
    -H 'Content-Type: application/json' \
    -H "Authorization: Bearer $OPENAI_API_KEY" \
    -d '{
          "input": "string",
          "model": "model",
          "questions": [
            {
              "instructions": "instructions",
              "type": "predicate"
            }
          ]
        }'
```

#### Response

```json
{
  "answers": [
    {
      "name": "name",
      "probability": 0,
      "type": "predicate"
    }
  ],
  "model": "model",
  "usage": {
    "input_tokens": -2147483648,
    "input_tokens_details": {
      "cache_write_tokens": -2147483648,
      "cached_tokens": -2147483648
    },
    "output_tokens": -2147483648,
    "output_tokens_details": {
      "reasoning_tokens": -2147483648
    },
    "total_tokens": -2147483648
  }
}
```

### Example

```http
curl https://api.openai.com/v1/decisions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-6-luna",
    "input": "The package arrived with a broken screen.",
    "questions": [
      {
        "type": "predicate",
        "name": "damaged",
        "instructions": "Does the customer report a damaged item?"
      }
    ]
  }'
```

#### Response

```json
{
  "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
  }
}
```