copyleaks 5.1.0

Copyleaks API gives you access to a variety of plagiarism detection technologies to protect your online content. Get the most comprehensive plagiarism report for your content that is easy to use and integrate.

Copyleaks SDK

The official Copyleaks Python library, supporting Python versions: Python 3.6.+

🚀 Getting Started

Before you start, ensure you have the following:

• An active Copyleaks account. If you don’t have one, Sign up for free.
• You can find your API key on the API Dashboard.

Once you have your account and API key:

Install the SDK:

Use the Python Package Manager - PiPy. When integrating this way, you will automatically be able to update the SDK to its latest version:

pip install copyleaks

📚 Documentation

To learn more about how to use Copyleaks API please check out our Documentation.

💡 Usage Examples

Here are some common usage examples for the Copyleaks SDK. You can also see a comprehensive code example in the example.py file on our GitHub repository: example.py.

Get Authentication Token

This example demonstrates how to log in to the Copyleaks API and obtain an authentication token.

import base64
from copyleaks.copyleaks import Copyleaks
from copyleaks.exceptions.command_error import CommandError

# --- Your Credentials ---
EMAIL_ADDRESS = 'YOUR_EMAIL_ADDRESS' # Replace with your Copyleaks registered email
KEY = 'YOUR_API_KEY'               # Replace with your Copyleaks API Key
# --------------------

# Log in to the Copyleaks API
auth_token = Copyleaks.login(EMAIL_ADDRESS, KEY)
print("✅ Logged in successfully!")

For a detailed understanding of the authentication process, refer to the Copyleaks Login Endpoint Documentation.

Submit Text for Plagiarism Scan

This example shows how to prepare and submit raw text content for a plagiarism scan.

import base64
from copyleaks.copyleaks import Copyleaks
from copyleaks.models.submit.document import FileDocument
from copyleaks.models.submit.properties.scan_properties import ScanProperties

# Prepare your content for scanning
# You can scan a URL, a local file, or raw text.
# This example scans a simple string of text.
print("Submitting text for scanning...")
text_to_scan = "Hello world, this is a test."
base64_content = base64.b64encode(text_to_scan.encode()).decode()

# Configure the scan
scan_id = "my-first-scan" 
scan_properties = ScanProperties("https://your-server.com/webhook/{STATUS}") # IMPORTANT: Replace with your actual webhook URL to receive scan results
scan_properties.set_sandbox(True) # Turn on sandbox mode for testing without consuming credits
file_submission = FileDocument(base64_content, "test.txt")
file_submission.set_properties(scan_properties)

# Submit the scan to Copyleaks
Copyleaks.submit_file(auth_token, scan_id, file_submission)
print(f"🚀 Scan submitted successfully! Scan ID: {scan_id}")
print("You will be notified via your webhook when the scan is complete.")

For a full guide please refer to our step by step Guide

For a detailed understanding of the plagiarism detection process, refer to the Copyleaks Submit Endpoint Documentation

AI-Generated Text Detection

Use the AI detection client to determine if content was generated by artificial intelligence.

import base64
from copyleaks.copyleaks import Copyleaks
from copyleaks.models.submit.document import NaturalLanguageDocument 

scan_id = "your-scan-id"

sample_text = "Lions are social animals, living in groups called prides, typically consisting of several females, their offspring, and a few males. Female lions are the primary hunters, working together to catch prey. Lions are known for their strength, teamwork, and complex social structures."
natural_language_submission = NaturalLanguageDocument(sample_text)
natural_language_submission.set_sandbox(True) # Use sandbox for testing
response = Copyleaks.AiDetectionClient.submit_natural_language(auth_token, scan_id, natural_language_submission)
print("\nAI Detection (Natural Language):")
print(response)

For a full guide please refer to our step by step Guide

For a detailed understanding of the Ai detection process, refer to the Copyleaks detect natural language Endpoint Documentation

Writing Assistant

Get intelligent suggestions for improving grammar, spelling, style, and overall writing quality.

import base64
from copyleaks.copyleaks import Copyleaks
from copyleaks.exceptions.command_error import CommandError
from copyleaks.models.submit.document import WritingAssistantDocument
from copyleaks.models.submit.properties.score_weights import ScoreWeights

scan_id = "your-scan-id"

# Define the text to be assessed
sample_text = "Copyleaks is a comprehensive plagiarism detection platform that performs extensive searches across 60 trillion websites, 15,000+ academic journals, 20+ code data repositories, and 1M+ internal documents. Using AI-powered text analysis, easily scan documents, raw text, code, and URLs and instantly receive detailed reporting on the findings."

# Configure score weights for different aspects of writing quality
score_weight = ScoreWeights()
score_weight.set_grammar_score_weight(0.2)
score_weight.set_mechanics_score_weight(0.3)
score_weight.set_sentence_structure_score_weight(0.5)
score_weight.set_word_choice_score_weight(0.4)

submission = WritingAssistantDocument(sample_text)
submission.set_score(score_weight)
submission.set_sandbox(True) # Use sandbox for testing

response = Copyleaks.WritingAssistantClient.submit_text(auth_token, scan_id, submission)
print("\nWriting Assistant Feedback:")
print(response)

For a full guide please refer to our step by step Guide

For a detailed understanding of the Writing assistant process, refer to the Copyleaks writing feedback Endpoint Documentation

Text Moderation

Scan and moderate text content for unsafe, inappropriate, or policy-violating material across various categories.

import base64
from copyleaks.copyleaks import Copyleaks
from copyleaks.models.submit.request_model import CopyleaksTextModerationRequestModel
from copyleaks.models.TextModeration.Requests.CopyleaksTextModerationLabel import CopyleaksTextModerationLabel
from copyleaks.models.constants.CopyleaksTextModerationConstants import CopyleaksTextModerationConstants
from copyleaks.models.constants.CopyleaksTextModerationLanguages import CopyleaksTextModerationLanguages

scan_id = "your-scan-id"

labelsArray=[
        CopyleaksTextModerationLabel(id=CopyleaksTextModerationConstants.ADULT_V1),
        CopyleaksTextModerationLabel(id=CopyleaksTextModerationConstants.TOXIC_V1),
        CopyleaksTextModerationLabel(id=CopyleaksTextModerationConstants.VIOLENT_V1),
        CopyleaksTextModerationLabel(id=CopyleaksTextModerationConstants.PROFANITY_V1),
        CopyleaksTextModerationLabel(id=CopyleaksTextModerationConstants.SELF_HARM_V1),
        CopyleaksTextModerationLabel(id=CopyleaksTextModerationConstants.HARASSMENT_V1),
        CopyleaksTextModerationLabel(id=CopyleaksTextModerationConstants.HATE_SPEECH_V1),
        CopyleaksTextModerationLabel(id=CopyleaksTextModerationConstants.DRUGS_V1),
        CopyleaksTextModerationLabel(id=CopyleaksTextModerationConstants.FIREARMS_V1),
        CopyleaksTextModerationLabel(id=CopyleaksTextModerationConstants.CYBERSECURITY_V1),
    ]

model = CopyleaksTextModerationRequestModel(
    text="This is some text to scan.",
    sandbox=True,
    language=CopyleaksTextModerationLanguages.ENGLISH,
    labels=labelsArray
)

textModerationResponse = Copyleaks.TextModerationClient.submit_text(auth_token, scan_id, model)
print("\nText Moderation:")
print(textModerationResponse.model_dump_json())

For a full guide please refer to our step by step Guide

For a detailed understanding of the Text moderation process, refer to the Copyleaks text moderation Endpoint Documentation

Image Detection

Determine if a given image was generated or partially generated by an AI.

import base64
from copyleaks.models.ImageDetection.Requests.CopyleaksAiImageDetectionRequestModel import CopyleaksAiImageDetectionRequestModel
from copyleaks.copyleaks import Copyleaks
from copyleaks.models.constants.CopyleaksAiImageDetectionModels import CopyleaksAiImageDetectionModels

scan_id = "your-scan-id"
print("Submitting a new image for AI image detection...")

# Update the path to your image file
image_path = r"PATH TO IMAGE"

with open(image_path, 'rb') as image_file:
    base64_image = base64.b64encode(image_file.read()).decode('utf-8')

payload = CopyleaksAiImageDetectionRequestModel(
    base64=base64_image,
    file_name='my-image.png',
    sandbox=True,
    model=CopyleaksAiImageDetectionModels.AI_IMAGE_1_ULTRA
)
response = Copyleaks.ImageDetectionClient.submit(auth_token, scan_id, payload)

print("Image Detection Response:")
print(response.model_dump_json())

For a full guide please refer to our step by step Guide

For a detailed understanding of the Image detection process, refer to the Copyleaks image detection Endpoint Documentation

Further Resources

• Copyleaks API Dashboard: Manage your API keys, monitor usage, and view analytics from your personalized dashboard. Access Dashboard
• Copyleaks SDK Documentation: Explore comprehensive guides, API references, and code examples for seamless integration. Read Documentation

Support

• If you need assistance, please contact Copyleaks Support via our support portal: Contact Copyleaks Support.
• To arrange a product demonstration, book a demo here: Booking Link.