## Execute AI model

`client.ai.run(stringmodelName, AIRunParamsparams, RequestOptionsoptions?): AIRunResponse`

**post** `/accounts/{account_id}/ai/run/{model_name}`

This endpoint provides users with the capability to run specific AI models on-demand.

By submitting the required input data, users can receive real-time predictions or results generated by the chosen AI
model. The endpoint supports various AI model types, ensuring flexibility and adaptability for diverse use cases.

Model specific inputs available in [Cloudflare Docs](https://developers.cloudflare.com/workers-ai/models/).

### Parameters

- `modelName: string`

- `AIRunParams = TextClassification | TextToImage | TextToSpeech | 12 more`

  - `AIRunParamsBase`

  - `TextClassification extends AIRunParamsBase`

  - `TextToImage extends AIRunParamsBase`

  - `TextToSpeech extends AIRunParamsBase`

  - `TextEmbeddings extends AIRunParamsBase`

  - `AutomaticSpeechRecognition extends AIRunParamsBase`

  - `ImageClassification extends AIRunParamsBase`

  - `ObjectDetection extends AIRunParamsBase`

  - `Prompt extends AIRunParamsBase`

  - `Messages extends AIRunParamsBase`

  - `Translation extends AIRunParamsBase`

  - `Summarization extends AIRunParamsBase`

  - `ImageToText extends AIRunParamsBase`

  - `Variant12 extends AIRunParamsBase`

  - `Variant13 extends AIRunParamsBase`

  - `MultimodalEmbeddings extends AIRunParamsBase`

### Returns

- `AIRunResponse = Array<TextClassification> | Uploadable | Audio | 12 more`

  An array of classification results for the input text

  - `Array<TextClassification>`

    - `label?: string`

      The classification label assigned to the text (e.g., 'POSITIVE' or 'NEGATIVE')

    - `score?: number`

      Confidence score indicating the likelihood that the text belongs to the specified label

  - `Uploadable`

  - `Audio`

    - `audio?: string`

      The generated audio in MP3 format, base64-encoded

  - `Uploadable`

  - `TextEmbeddings`

    - `data?: Array<Array<number>>`

      Embeddings of the requested text values

    - `shape?: Array<number>`

  - `AutomaticSpeechRecognition`

    - `text: string`

      The transcription

    - `vtt?: string`

    - `word_count?: number`

    - `words?: Array<Word>`

      - `end?: number`

        The ending second when the word completes

      - `start?: number`

        The second this word begins in the recording

      - `word?: string`

  - `Array<ImageClassification>`

    - `label?: string`

      The predicted category or class for the input image based on analysis

    - `score?: number`

      A confidence value, between 0 and 1, indicating how certain the model is about the predicted label

  - `Array<ObjectDetection>`

    - `box?: Box`

      Coordinates defining the bounding box around the detected object

      - `xmax?: number`

        The x-coordinate of the bottom-right corner of the bounding box

      - `xmin?: number`

        The x-coordinate of the top-left corner of the bounding box

      - `ymax?: number`

        The y-coordinate of the bottom-right corner of the bounding box

      - `ymin?: number`

        The y-coordinate of the top-left corner of the bounding box

    - `label?: string`

      The class label or name of the detected object

    - `score?: number`

      Confidence score indicating the likelihood that the detection is correct

  - `UnionMember8`

    - `response: string`

      The generated text response from the model

    - `tool_calls?: Array<ToolCall>`

      An array of tool calls requests made during the response generation

      - `arguments?: unknown`

        The arguments passed to be passed to the tool call request

      - `name?: string`

        The name of the tool to be called

    - `usage?: Usage`

      Usage statistics for the inference request

      - `completion_tokens?: number`

        Total number of tokens in output

      - `prompt_tokens?: number`

        Total number of tokens in input

      - `total_tokens?: number`

        Total number of input and output tokens

  - `Uploadable`

  - `Translation`

    - `translated_text?: string`

      The translated text in the target language

  - `Summarization`

    - `summary?: string`

      The summarized version of the input text

  - `ImageToText`

    - `description?: string`

  - `ImageTextToText`

    - `description?: string`

  - `MultimodalEmbeddings`

    - `data?: Array<Array<number>>`

    - `shape?: Array<number>`

### Example

```node
import Cloudflare from 'cloudflare';

const client = new Cloudflare({
  apiToken: process.env['CLOUDFLARE_API_TOKEN'], // This is the default and can be omitted
});

const response = await client.ai.run('model_name', {
  account_id: '023e105f4ecef8ad9ca31a8372d0c353',
  text: 'x',
});

console.log(response);
```

#### Response

```json
{
  "result": [
    {
      "label": "label",
      "score": 0
    }
  ]
}
```