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

# Batch Evaluate

> Evaluate multiple outputs efficiently with 27 built-in metrics

Run evaluation on multiple outputs in a single request. Ideal for batch processing, dataset evaluation, and regression testing. Uses the same [27 built-in metrics](/api-reference/evaluation/evaluate#-built-in-evaluation-metrics) as the single evaluation endpoint.

<ParamField body="items" type="array" required>
  Array of items to evaluate

  <Expandable title="item object">
    <ParamField body="input" type="string" required>
      User input
    </ParamField>

    <ParamField body="output" type="string" required>
      Agent output
    </ParamField>

    <ParamField body="context" type="array">
      Context documents
    </ParamField>

    <ParamField body="ground_truth" type="string">
      Ground truth
    </ParamField>
  </Expandable>
</ParamField>

<ParamField body="scorers" type="array" required>
  Scorers to apply to all items. Choose from 27 built-in metrics: **Custom**:
  `playval` **RAG**: `answer_relevancy`, `faithfulness`, `contextual_precision`,
  `contextual_recall`, `contextual_relevancy` **Safety**: `bias`, `toxicity`,
  `non_advice`, `misuse`, `pii_leakage`, `role_violation` **Agentic**:
  `task_completion`, `tool_correctness`, `argument_correctness`,
  `step_efficiency`, `plan_adherence`, `plan_quality` **Multi-Turn**:
  `turn_relevancy`, `role_adherence`, `knowledge_retention`,
  `conversation_completeness`, `goal_accuracy`, `tool_use`, `topic_adherence`,
  `turn_faithfulness`, `turn_contextual_precision`, `turn_contextual_recall` Or
  use custom scorer IDs from [Create Custom
  Scorer](/api-reference/evaluation/create-custom-scorer)
</ParamField>

<ParamField body="config" type="object">
  Batch configuration

  <Expandable title="properties">
    <ParamField body="parallel" type="boolean">
      Run evaluations in parallel (default: true)
    </ParamField>

    <ParamField body="fail_fast" type="boolean">
      Stop on first failure (default: false)
    </ParamField>
  </Expandable>
</ParamField>

<ResponseField name="batch_id" type="string" required>
  Batch identifier
</ResponseField>

<ResponseField name="status" type="string" required>
  Batch status: `running`, `completed`, `failed`
</ResponseField>

<ResponseField name="results" type="array" required>
  Per-item evaluation results
</ResponseField>

<ResponseField name="summary" type="object" required>
  Batch summary statistics

  <Expandable title="properties">
    <ResponseField name="total" type="integer">
      Total items
    </ResponseField>

    <ResponseField name="passed" type="integer">
      Items that passed all scorers
    </ResponseField>

    <ResponseField name="failed" type="integer">
      Items that failed
    </ResponseField>

    <ResponseField name="avg_scores" type="object">
      Average scores per scorer
    </ResponseField>
  </Expandable>
</ResponseField>

<RequestExample>
  ```bash cURL theme={null}
  curl -X POST https://api.playgent.com/v1/evaluate/batch \
    -H "Authorization: Bearer your-api-key" \
    -H "Content-Type: application/json" \
    -d '{
      "items": [
        {
          "input": "What is your refund policy?",
          "output": "Returns accepted within 30 days.",
          "context": ["Policy: 30 day returns"]
        },
        {
          "input": "How do I track my order?",
          "output": "You can track your order at tracking.example.com",
          "context": ["Tracking available at tracking.example.com"]
        }
      ],
      "scorers": ["faithfulness", "relevance"],
      "config": {
        "parallel": true,
        "fail_fast": false
      }
    }'
  ```
</RequestExample>

<ResponseExample>
  ```json Response theme={null}
  {
    "batch_id": "batch_stu678",
    "status": "completed",
    "results": [
      {
        "item_index": 0,
        "overall_pass": true,
        "scores": { "faithfulness": 0.95, "relevance": 0.92 }
      },
      {
        "item_index": 1,
        "overall_pass": true,
        "scores": { "faithfulness": 0.88, "relevance": 0.90 }
      }
    ],
    "summary": {
      "total": 2,
      "passed": 2,
      "failed": 0,
      "avg_scores": { "faithfulness": 0.915, "relevance": 0.91 }
    }
  }
  ```
</ResponseExample>