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Learn how to integrate Eden AI’s plagiarism detection API with Python to ensure content originality. This article covers implementation steps, including retrieving plagiarism scores, source links, and matched text highlights for accurate analysis.
In this article, you'll discover how to implement plagiarism detection in just five minutes using Python and the Eden AI API.
Eden AI offers a user-friendly and efficient API that enables seamless plagiarism detection, making it easy for developers to integrate into their projects.
A plagiarism detection system, also known as an AI Plagiarism Detection API, analyzes textual content to identify similarities with existing sources.
It leverages advanced deep learning techniques, such as natural language processing (NLP) and machine learning algorithms, to compare text against databases, detect duplicated content, and ensure originality.
1. Sign up: If you haven’t signed up for Eden AI yet, register for a free account using this link. You will be able to get your API key directly from the API Keys section with free credits offered by Eden AI.
2. Access text processing technologies: After logging in, navigate to the text section of the platform.
3. Select the feature: Navigate to plagiarism detection.
Install Python's Requests Module: Before using the API, ensure that the requests library is installed in your Python environment. You can install it by running:
Now, prepare your code, below is an example code that shows how to use Eden AI’s plagiarism detection API in Python.
1. Headers: The Authorization header is used to authenticate your request. Replace "your_api_key_here" with your actual Eden AI API key.
2. URL: The URL https://api.edenai.run/v2/text/plagia_detection is the endpoint for plagiarism detection.
3. Payload:
Providers: This specifies which plagiarism detection provider to use. In this example, we use "originalityai", one of the popular plagiarism detection services.
Text: This is the actual content you want to check for plagiarism. Replace "Your text" with the text you wish to analyze.
Title: This is optional, and you can provide a title for the content.
4. Response handling: The response from the Eden AI API is parsed using json.loads() to convert it into a Python dictionary. The plagiarism results are found in result['originalityai']['items'], which can then be printed or processed further.
When you receive the response, you will get a detailed report on the plagiarism analysis. Here is an example output:
In this example, the text has a 35.5% similarity to content found at example.com. The snippet provides a part of the matched text for reference. This allows you to pinpoint the exact areas where plagiarism might be present.
Using Eden AI API is quick and easy.
Using Eden AI API is quick and easy. It provides a unified API for multiple providers, offering a simple and standardized interface with an easy switch between providers and scalable, cost-effective pricing.
Its real-time plagiarism detection delivers fast results, making it ideal for users with tight deadlines.
Eden AI ensures consistency by delivering a standardized JSON output format across all suppliers. Its advanced matching algorithms further streamline responses, making integration smooth and efficient.
Eden AI allows seamless integration with third-party platforms, and custom connectors can be developed quickly. For advanced customization, explore our documentation to tailor API requests with specific parameters.
Detecting plagiarism is a critical step in ensuring content originality and academic integrity. By utilizing Eden AI's plagiarism detection API, Python developers can easily integrate powerful plagiarism checks into their applications.
The process of sending text to the API using Python and interpreting the results is straightforward. With features like plagiarism scores, source links, and matched text highlights, Eden AI provides accurate and detailed insights.
By leveraging these tools, developers can efficiently monitor and maintain the integrity of their content across various platforms.
Our team is ready to assist with your Plagiarism Detection integration through:
You can directly start building now. If you have any questions, feel free to chat with us!
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