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

# Hallucination

This detector takes a request text and the corresponding response text to check for potential Hallucination in the output of a LLM response. If the response text contains Hallucination, is\_hallucination will be set to 1, otherwise, it will be set to 0. The detector also provides a prompt\_based score to indicate the extent to which the hallucination is based on the prompt.

* **NOTE: This is unavailable at the moment.** *(Coming soon)*

## Example request:

<CodeGroup>
  ```python Python theme={"system"}
  import requests
  import json
  import os

  url = "https://api.enkryptai.com/guardrails/hallucination"

  payload = json.dumps({
    "request_text": "What is the capital of France?",
    "response_text": "Tokyo is the capital of france.",
    "context": ""
  })

  headers = {
      'Content-Type': 'application/json',
      'apikey': os.getenv('ENKRYPTAI_API_KEY')
  }

  response = requests.request("POST", url, headers=headers, data=payload)

  formatted_response = json.dumps(json.loads(response.text), indent=4)
  print(formatted_response)
  ```

  ```python Python SDK theme={"system"}
  import os
  from enkryptai_sdk import *
  from dotenv import load_dotenv

  load_dotenv()

  ENKRYPT_API_KEY = os.getenv("ENKRYPTAI_API_KEY")
  ENKRYPT_BASE_URL = os.getenv("ENKRYPTAI_BASE_URL") or "https://api.enkryptai.com"

  guardrails_client = GuardrailsClient(api_key=ENKRYPT_API_KEY, base_url=ENKRYPT_BASE_URL)

  request_text = "What is the capital of France?"
  response_text = "Tokyo is the capital of france."
  context = ""

  hallucination_response = guardrails_client.hallucination(
      request_text=request_text,
      response_text=response_text,
      context=context
  )

  print(hallucination_response)

  # Print as a dictionary
  print(hallucination_response.to_dict())
  ```
</CodeGroup>

## Example response:

```json JSON theme={"system"}
{
  "summary": {
    "is_hallucination": 1
  },
  "details": {
    "prompt_based": 1.0
  }
}
```