> ## Documentation Index
> Fetch the complete documentation index at: https://arize-ax.mintlify.dev/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Online Tasks API

## When to use Online Tasks API

The Online Tasks API programmatically creates or updates automated evaluation tasks that **run in the Arize AX platform**. Use this for real-time evaluation of spans from your application.

## Creating an Evaluation Task

You can programmatically create an evaluation task using the `createEvalTask` mutation. This allows you to set up evaluations based on your specific criteria for LLM applications.

```ruby theme={null}
mutation CreateOnlineEvalTask {
  createEvalTask(input: {
    modelId: "MODEL_ID"            # Your model's ID
    samplingRate: 1                # Desired sampling rate for task
    queryFilter: "attributes.openinference.span.kind = 'AGENT'"  # Filter to define the task scope
    name: "test"                   # Name of the evaluation task
    templateEvaluators: {
      name: "test evaluator",       # Column name for the evaluator
      rails: ["incorrect","correct"], # Output labels for evaluation
      template: "template",         # Template for the evaluation
      position: 1,
      includeExplanations: true,    # Include explanations in the results
      useFunctionCallingIfAvailable: false
    }
    runContinuously: true
    llmConfig: {
      modelName: GPT_4o,            # LLM Model name
      provider: openAI,             # LLM provider
      temperature: 0                # Temperature for generation
    }
  }) {
    evalTask {
      name
      samplingRate
      queryFilter
    }
  }
}
```

#### Key Parameters:

* `modelId`: The unique identifier for your project.

* `samplingRate`: Set the percentage of inputs the task will sample for evaluation.

* `queryFilter`: Define conditions to filter which inputs are included in the evaluation.

* `name`: The name of the evaluation task.

* `templateEvaluators`: Settings for how the evaluation will be performed (e.g., evaluator name, template, rails, explanations).

* `llmConfig`: Specify the LLM configuration, such as model provider and temperature settings.

### Updating an Evaluation Task

To update an existing evaluation task, use the `patchEvalTask` mutation. You can choose to modify any parameters you wish to update without needing to include parameters you want to leave unchanged.

```python theme={null}
mutation UpdateOnlineEvalTask {
  patchEvalTask(input: {
    onlineTaskId: "TASK_ID"         # The unique identifier for your task
    samplingRate: 1                 # Updated sampling rate
    queryFilter: "attributes.openinference.span.kind = 'LLM'"  # Updated filter
    name: "test"                    # Updated task name
  }) {
    evalTask {
      name
      samplingRate
      filters {
        dimension {
          id
          name
        }
        operator
      }
      queryFilter
    }
  }
}
```

### Running Task

To programmatically run a task on historical data, use the `runOnlineTask` mutation. This allows you to run your task on specific time range.

```python theme={null}
mutation RunOnlineTask {
  runOnlineTask(
    input: {
      onlineTaskId: "TASK_ID",                   # The unique identifier for your task
      dataStartTime: "2024-10-08T00:01:41.644Z", # start time for your data
      dataEndTime: "2024-12-07T01:01:41.644Z",   # end time of your data
      maxSpans: 100                              # the maximum number of spans
  ) {
    result {
      ... on CreateTaskRunResponse {
        runId
      }
      ... on TaskError {
        message
        code
      }
    }
  }
}
```

#### Key Input Parameters:

* `onlineTaskId`: The unique identifier for your task

* `dataStartTime`: A date-time string at UTC (such as 2007-12-03T10:15:30Z) for the start of your historical data.

* `dataEndTime`: The end time for your historical data

* `maxSpans`: The maximum number of spans you would like to evaluate. Defaults to 10,000 if not specified.

#### Response Types:

The response to this mutation is a union type, meaning it can return one of two types:

* `TaskError`: Indicates a failure to start the task run. It includes an error message explaining the reason for the failure.

* \`