# Model Inferences

All model inference requests are asynchronous, meaning you must make the request and then poll for the status.

## Request Inference

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

Creates an model inference job to be run on one or more source files

#### Headers

| Name                                            | Type   | Description                                                                                                                                                                                        |
| ----------------------------------------------- | ------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Authorization<mark style="color:red;">\*</mark> | string | <p>Where you put your api key. Requesting inferences requires a "Model Run" permission on the project where sources exist<br><code>{"Authorization": "Api-Key XXXXXXX-XXXXXXX-XXXXXXX"}</code></p> |

#### Request Body

| Name                                                    | Type            | Description                                                                                            |
| ------------------------------------------------------- | --------------- | ------------------------------------------------------------------------------------------------------ |
| projectIdentifier<mark style="color:red;">\*</mark>     | string          | Identifier of the project that contains the source files. Either id or the unique name of the project. |
| modelIdentifier<mark style="color:red;">\*</mark>       | string          | Identifier of the model that will be run. Either id or the unique name of the model.                   |
| sourceIds<mark style="color:red;">\*</mark>             | array           | array of source ids pointing to where models will be run                                               |
| outputLayerIdentifier<mark style="color:red;">\*</mark> | string\|integer | layer in which predictions will be generated                                                           |
| groupName<mark style="color:red;">\*</mark>             | String          | name of the group user belongs to                                                                      |

{% tabs %}
{% tab title="201 The inference job was created and is in queue" %}

```json
{
    "inferenceJobId": 12,
    "status": "Queued",
    "projectName": "Sample Project",
    "projectId": 1,
    "outputLayerName": "Gold Set",
    "outputLayerId": 12,
    "sourceIds": [3240, 4414],
}
```

{% endtab %}

{% tab title="400 The inference could not be started" %}

```
{
    "message": "explanation for why directory could not be created"
}
```

{% endtab %}
{% endtabs %}

## Request Inference Status

<mark style="color:blue;">`GET`</mark> `https://api.annolab.ai/v1/infer/batch/{job_id}`

Returns the status of the inference job

#### Path Parameters

| Name                                    | Type    | Description                                             |
| --------------------------------------- | ------- | ------------------------------------------------------- |
| jobId<mark style="color:red;">\*</mark> | Integer | Integer representing the inference job that was spawned |

#### Headers

| Name                                            | Type   | Description                                                                                                                                                                                        |
| ----------------------------------------------- | ------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Authorization<mark style="color:red;">\*</mark> | string | <p>Where you put your api key. Requesting inferences requires a "Model Run" permission on the project where sources exist<br><code>{"Authorization": "Api-Key XXXXXXX-XXXXXXX-XXXXXXX"}</code></p> |

{% tabs %}
{% tab title="201 The inference job was created and is in queue" %}

```
{
    "inferenceJobId": 12,
    "status": "Queued",
    "projectId": 1,
    "sourceIds": [3240, 4414]
}
```

{% endtab %}

{% tab title="400 The inference could not be started" %}

```
{
    "message": "explanation for why directory could not be created"
}
```

{% endtab %}

{% tab title="404: Not Found Permissions problem or job doesn't exist" %}

```javascript
{
    // Response
}
```

{% endtab %}
{% endtabs %}

This code shows how to call a specific model on 2 sources, poll status until the model inference is complete, then retrieve the results.

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

```python
import requests
import time

ANNO_LAB_API_KEY = 'XXXXXXX-XXXXXXX-XXXXXXX-XXXXXXX'

inferenceBody = {
  'groupName': 'Company Name',
  'projectIdentifier': 'My Project',
  'sourceIds': [4024, 5853],
  'modelIdentifier': 'Staple + Classify Documents',
  'outputLayerIdentifier': 'Gold Set'
}

headers = {
  'Authorization': 'Api-Key '+ANNO_LAB_API_KEY,
}

url = 'https://api.annolab.ai/v1/infer/batch'

response = requests.post(url, headers=headers, json=inferenceBody)

print(response.json())

get_url = 'https://api.annolab.ai/v1/infer/batch/'+response.json()['inferenceJobId']
maximum_timeout_seconds = 1800
time_taken = 0 
inference_is_finished = False

start_time = time.time()
while not inference_is_finished and time_taken < maximum_timeout_seconds:
  status_response = requests.get(get_url, headers=headers, json=inferenceBody).json()
  if status_response['status'] in ['Finished', 'Errored']:
    print("Inference Finished")
    print(status_response)
    inference_is_finished = True
  time_taken = time.time() - start_time
```

{% endtab %}
{% endtabs %}