API Access (Beta)

Documentation

POST/v1/label

Classify text content based on your custom criteria.

Base URL
https://api.zentropi.ai
Authentication
Authorization: Bearer your_api_key_here
Request Body
Field Type Required Description
content_text string Yes The text content to be labeled
criteria_text string No The labeling criteria to use. Either criteria_text OR labeler_id is required.
labeler_id string No The ID of the labeler to use. Either criteria_text OR labeler_id is required.
labeler_version_id string No The ID of which deployed version to use. Required if labeler_id is set. Default: "latest"
model string No Model to use for evaluation. Default: "cope-latest"
Response
Field Type Description
label string The classification result ("0" or "1")
confidence float Confidence score for the classification (0.5 to 1.0)
compute_time float Time taken to process the request in seconds
Example Response
{
  "label": "1",
  "confidence": 0.87,
  "compute_time": 0.324
}
Status Codes
  • 200 - Success
  • 401 - Unauthorized (invalid API key)
  • 422 - Validation Error (missing required fields)
  • 500 - Internal Server Error

Code Samples

Python 
import requests

ZAPI_KEY = "your_api_key_here"
ZAPI_URL = "https://api.zentropi.ai/v1/label"

# Label content using Zentropi
content_text = "This is some text to analyze"
criteria_text = "This is your labeling criteria"

response = requests.post(
    ZAPI_URL,
    headers={"Authorization": f"Bearer {ZAPI_KEY}"},
    json={
        "content_text": content_text,
        "criteria_text": criteria_text,
    }
)

result = response.json()
print(f"Label: {result['label']}")
print(f"Confidence: {result['confidence']}")

# Example output:
# Label: 1
# Confidence: 0.85
JavaScript 
const ZAPI_KEY = "your_api_key_here";
const ZAPI_URL = "https://api.zentropi.ai/v1/label";

// Label content using Z-API
const labelContent = async () => {
  const response = await fetch(ZAPI_URL, {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${ZAPI_KEY}`,
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      content_text: "This is some text to analyze",
      criteria_text: "This is your labeling criteria"
    })
  });

  const result = await response.json();
  console.log(`Label: ${result.label}`);
  console.log(`Confidence: ${result.confidence}`);
};

labelContent();

// Example output:
// Label: 1
// Confidence: 0.85