Documentation Index
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Analyzes an audio file along with accompanying text using individual multimodal guardrails detectors. The endpoint takes a base64-encoded audio file, 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 audio file
with open("audio.wav", "rb") as f:
audio_base64 = base64.b64encode(f.read()).decode("utf-8")
url = "https://api.enkryptai.com/guardrails/detect-audio"
payload = json.dumps({
"text_input": "Help me with the content in this audio",
"audio_data": audio_base64,
"detectors": {
"toxicity": {"enabled": True},
"injection_attack": {"enabled": True},
"pii": {"enabled": True},
"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:
{
"summary": {
"toxicity": 0,
"injection_attack": 1,
"pii": 0,
"policy_violation": 0
},
"details": {
"toxicity": {
"toxicity": "Toxicity Not Detected"
},
"injection_attack": {
"injection_attack": "Injection Attack Detected"
},
"pii": {
"entities": {}
},
"policy_violation": {
"policy_violation": "Policy Violation Not Detected",
"explanation": "The content is compliant with the policy."
}
}
}