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

# Query Evaluators

> List all evaluators in your organization

## Endpoint

<ParamField path="method" type="string" default="POST">
  POST
</ParamField>

<ParamField path="endpoint" type="string">
  `/v1/evaluator/query`
</ParamField>

## Authentication

This endpoint requires API key authentication. Include your API key in the request headers:

```bash theme={null}
Authorization: Bearer YOUR_API_KEY
```

## Request Body

No specific parameters required. Send an empty object.

## Response

<ResponseField name="data" type="array">
  Array of evaluator objects

  <ResponseField name="id" type="string">
    Unique identifier for the evaluator
  </ResponseField>

  <ResponseField name="name" type="string">
    Evaluator name
  </ResponseField>

  <ResponseField name="scoring_type" type="string">
    Type of scoring: "LLM-BOOLEAN", "LLM-CHOICE", "LLM-RANGE", "PYTHON", or "LASTMILE"
  </ResponseField>

  <ResponseField name="llm_template" type="object">
    LLM configuration for LLM-based evaluators
  </ResponseField>

  <ResponseField name="code_template" type="object">
    Python code for code-based evaluators
  </ResponseField>

  <ResponseField name="last_mile_config" type="object">
    Configuration for LastMile evaluators
  </ResponseField>

  <ResponseField name="organization_id" type="string">
    Organization that owns this evaluator
  </ResponseField>

  <ResponseField name="created_at" type="string">
    Creation timestamp
  </ResponseField>

  <ResponseField name="updated_at" type="string">
    Last update timestamp
  </ResponseField>
</ResponseField>

<ResponseField name="error" type="string | null">
  Error message if the request failed, null otherwise
</ResponseField>

## Example Request

```bash theme={null}
curl -X POST https://api.helicone.ai/v1/evaluator/query \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{}'
```

## Example Response

```json theme={null}
{
  "data": [
    {
      "id": "eval_abc123",
      "name": "Hallucination Detector",
      "scoring_type": "LLM-BOOLEAN",
      "llm_template": {
        "model": "gpt-4",
        "prompt": "Does this response contain hallucinations?"
      },
      "code_template": null,
      "last_mile_config": null,
      "organization_id": "org_xyz789",
      "created_at": "2024-01-10T09:00:00Z",
      "updated_at": "2024-01-15T14:30:00Z"
    },
    {
      "id": "eval_def456",
      "name": "Relevance Score",
      "scoring_type": "LLM-RANGE",
      "llm_template": {
        "model": "gpt-4",
        "prompt": "Rate the relevance from 1-10",
        "min": 1,
        "max": 10
      },
      "code_template": null,
      "last_mile_config": null,
      "organization_id": "org_xyz789",
      "created_at": "2024-01-12T11:00:00Z",
      "updated_at": "2024-01-12T11:00:00Z"
    }
  ],
  "error": null
}
```

## Evaluator Types

### LLM-BOOLEAN

Uses an LLM to return a true/false score

### LLM-CHOICE

Uses an LLM to select from predefined choices

### LLM-RANGE

Uses an LLM to score within a numeric range

### PYTHON

Executes custom Python code for evaluation

### LASTMILE

Integration with LastMile evaluation framework