Example request:
Example response:
JSON
Documentation Index
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
import requests
import json
import os
url = "https://api.enkryptai.com/guardrails/detect"
payload = json.dumps({
"text": "Aluminum alloys can have very high strength-to-weight ratios, making them useful for applications where weight is a critical factor, such as in the aerospace industry",
"detectors": {
"topic_detector": {
"enabled": True,
"topic": ["science"],
"block_message": "Your custom message"
}
}
})
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)
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)
guardrails_config = GuardrailsConfig.topic(topics=["science"])
prompt = "Aluminum alloys can have very high strength-to-weight ratios, making them useful for applications where weight is a critical factor, such as in the aerospace industry"
detect_response = guardrails_client.detect(text=prompt, guardrails_config=guardrails_config)
print(detect_response)
# Print as a dictionary
print(detect_response.to_dict())
{
"summary": {
"on_topic": 1
},
"details": {
"topic_detector": {
"science": 0.9998229146003723
}
},
"result_message": "Your custom message"
}
