Skip to main content
Analyzes an image along with accompanying text using individual multimodal guardrails detectors. The endpoint takes a base64-encoded image, a text prompt, and a detectors configuration specifying which detectors to run (toxicity, nsfw, injection_attack, pii, policy_violation). Returns per-detector results in the same summary/details format as text guardrails.

​
Example request:

import requests
import json
import os
import base64

# Read and encode image file
with open("image.png", "rb") as f:
    image_base64 = base64.b64encode(f.read()).decode("utf-8")

url = "https://api.enkryptai.com/guardrails/detect-image"
payload = json.dumps({
    "text_input": "Help me with the content in this image",
    "image_data": image_base64,
    "detectors": {
        "toxicity": {"enabled": True},
        "nsfw": {"enabled": True},
        "injection_attack": {"enabled": True},
        "pii": {"enabled": True, "entities": ["person", "phone", "email"]},
        "policy_violation": {
            "enabled": True,
            "policy_text": "No violent or illegal content allowed.",
            "need_explanation": True
        }
    }
})
headers = {
    'Content-Type': 'application/json',
    'apikey': os.getenv('ENKRYPTAI_API_KEY')
}
response = requests.post(url, headers=headers, data=payload)
print(response.json())

​
Example response:

JSON
{
    "summary": {
        "toxicity": 0,
        "nsfw": 0,
        "injection_attack": 0,
        "pii": 1,
        "policy_violation": 0
    },
    "details": {
        "toxicity": {
            "toxicity": "Toxicity Not Detected"
        },
        "nsfw": {
            "nsfw": "NSFW Not Detected"
        },
        "injection_attack": {
            "injection_attack": "Injection Attack Not Detected"
        },
        "pii": {
            "entities": {
                "person": {"John Doe": "<person_0>"},
                "phone": {"555-0123": "<phone_0>"}
            }
        },
        "policy_violation": {
            "policy_violation": "Policy Violation Not Detected",
            "explanation": "The content is compliant with the policy."
        }
    }
}