# Auto Text Classification (A\_DL\_TXC)

These models are designed to classify text into different categories, such as sentiment analysis or topic modeling.

## Sample Request

Build an Auto Text Classifier

```json
{
    "project_id": 1,
    "parent_id": 7,
    "block_id": 8,
    "function_code": "A_DL_TXC_I",
    "args": {
    "hyp_params":{
            "max_trials": 1
        }
    }
}
```

## Building an Auto Text Classifier

## Automated Model Construction

<mark style="color:green;">`POST`</mark> `https://autogon.ai/api/v1/engine/start`

#### Request Body

| Name                                             | Type   | Description                                           |
| ------------------------------------------------ | ------ | ----------------------------------------------------- |
| project\_id<mark style="color:red;">\*</mark>    | int    | The `id` of the current project                       |
| block\_id<mark style="color:red;">\*</mark>      | int    | The `id` of the current block                         |
| function\_code<mark style="color:red;">\*</mark> | string | The function code for current block                   |
| parent\_id<mark style="color:red;">\*</mark>     | int    | The `id` of the previous block                        |
| args<mark style="color:red;">\*</mark>           | object | Block arguments                                       |
| max\_trials                                      | int    | Maximum number of different models that will be tried |

{% tabs %}
{% tab title="200 Statemanagement object" %}

```json
{
    "status": "true",
    "message": {
        "id": 8,
        "project": 1,
        "block_id": 8,
        "parent_id": 7,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": {}
    }
}
```

{% endtab %}
{% endtabs %}

## Sample Request

Compile and train the pre-built TXC model, using passed in Hyper Parameters

```json
{
    "project_id": 1,
    "parent_id": 8,
    "block_id": 9,
    "function_code": "A_DL_TXC_T",
    "args": {
        "model_name": "titanic_model",
        "hyp_params":{
            "epochs": 10
        }
    }
}
```

## Training an Auto Image Classifier

## Automated Model Training

<mark style="color:green;">`POST`</mark> `https://autogon.ai/api/v1`

#### Request Body

| Name                                             | Type   | Description                                         |
| ------------------------------------------------ | ------ | --------------------------------------------------- |
| project\_id<mark style="color:red;">\*</mark>    | int    | The `id` of the current project                     |
| hyp\_params                                      | object | hyper parameters for model compilation and training |
| parent\_id<mark style="color:red;">\*</mark>     | int    | The `id` of the previous block                      |
| block\_id<mark style="color:red;">\*</mark>      | int    | The `id` of the current block                       |
| function\_code<mark style="color:red;">\*</mark> |        | The function code for current block                 |
| args<mark style="color:red;">\*</mark>           | object | Block arguments                                     |
| model\_name<mark style="color:red;">\*</mark>    | String | The name the model would be saved with              |
| epochs                                           | int    | Number of iterations through the dataset            |

{% tabs %}
{% tab title="200: OK Statemanagement Object" %}

```json
{
    "status": "true",
    "message": {
        "id": 9,
        "project": 1,
        "block_id": 9,
        "parent_id": 8,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": {}
    }
}
```

{% endtab %}
{% endtabs %}

## Predictions

Make predictions with the DL\_ANN Predict block

{% tabs %}
{% tab title="Python" %}

```
// Some code
```

{% endtab %}

{% tab title="Node" %}

```
// Some code
```

{% endtab %}
{% endtabs %}