Article Data Extractor API

This API is perfect for those that want to retrieve structured data from an article on the web. Only with the URL will you receive an extensive list of information. Try it out!

About the API:

With Article Data Extractor you will be able to scrape and retrieve all the relevant information from any article you find on the web. Forget about ads, banners and other unessential parts as well. Only receive all the data related to the article of your choice. 

 

What your API receives and what your API provides (input/output)?

Article Data Extractor takes only 1 parameter — the URL of any article or blog. It scrapes and extracts any relevant information such as title, text, published time, media links, and many more. Save time and receive all this data structured so you can filter, query, and store all the information that the web has for you. 

 

What are the most common uses cases of this API?

This API is perfect for any marketing agency or any news platform that wants to retrieve the most important information from an article. This is the author's name, the text from the article itself, and do not forget about TAGS. With this API all the tags embedded in the article will be available. 

Also, this is great to compare what images are using other blogs or news forums in different articles. 

So, if you have a large collection of articles, you will be able to filter by author's name, by tag elements, or even by published dates. This API will help you to have your articles better organized. }

 

Are there any limitations with your plans?

Besides API call limitations per month:

  • Basic: 3 requests per second.
  • Pro: 5 requests per second. 

API Documentation

Endpoints


Version 2.0 will allow you to parse any article of your choice. 

Extract main article and metadata from a news entry or blog post.

 
 


                                                                            
GET https://www.zylalabs.com/api/35/article+data+extractor+api/1880/article+data+extractor
                                                                            
                                                                        

Article Data Extractor - Endpoint Features

Object Description
url [Required] The URL of the article.
Test Endpoint

API EXAMPLE RESPONSE

       
                                                                                                        
                                                                                                                                                                                                                            {"error":0,"message":"Article extraction success","data":{"url":"https://ventureburn.com/2024/12/amazon-bedrock-expands-ai-horizons-with-100-new-models/","title":"Amazon Bedrock Expands AI Horizons with 100+ New Models","description":"At this year’s AWS re:Invent, Amazon Web Services unveiled a major expansion to its Amazon Bedrock platform, introducing over 100 new AI models alongside tools designed to make generative AI more accessible and efficient for businesses.\n“Amazon Bedrock is tackling the toughest challenges developers face today,” said Dr Swami Sivasubramanian, AWS’s Vice President of AI and Data.\nSmarter AI at Lower CostsTwo features, Prompt Caching and Intelligent Prompt Routing, aim to make AI usage more cost-effective.\nFor instance, Amazon Bedrock Data Automation enables businesses to extract and organise data from documents, videos, and more, significantly reducing manual workloads.\nA Growing EcosystemThe adoption of Amazon Bedrock is accelerating....","links":["https://ventureburn.com/2024/12/amazon-bedrock-expands-ai-horizons-with-100-new-models/"],"image":"https://s5.cdn.ventureburn.com/wp-content/uploads/sites/2/2024/12/cropRIV24_D3_KeynoteSwami_04906a-1-scaled.jpg","content":"<div><p class=\"shareaholic-canvas\"></p><p>At this year&#8217;s AWS re:Invent, Amazon Web Services unveiled a major expansion to its <a href=\"https://aws.amazon.com/bedrock/?gclid=Cj0KCQiAu8W6BhC-ARIsACEQoDC8e4KDrO97xwZYgolFmfPG7IRMCvq3Ja0jA8GwbSlnEBHmRGNez9QaAiAIEALw_wcB&amp;trk=36201f68-a9b0-45cc-849b-8ab260660e1c&amp;sc_channel=ps&amp;ef_id=Cj0KCQiAu8W6BhC-ARIsACEQoDC8e4KDrO97xwZYgolFmfPG7IRMCvq3Ja0jA8GwbSlnEBHmRGNez9QaAiAIEALw_wcB:G:s&amp;s_kwcid=AL!4422!3!692006004850!e!!g!!amazon%20bedrock!21048268689!159639953975\">Amazon Bedrock</a> platform, introducing over 100 new AI models alongside tools designed to make generative AI more accessible and efficient for businesses. The updates are part of AWS&#8217;s broader push to simplify how companies integrate AI into their workflows, from creative content production to complex data processing.</p>\n<p>&#8220;Amazon Bedrock is tackling the toughest challenges developers face today,&#8221; said Dr Swami Sivasubramanian, AWS&#8217;s Vice President of AI and Data. &#8220;These new capabilities help customers unlock the full potential of generative AI.&#8221;</p> \n        <p id=\"div-gpt-ad-1613727659655-0\">\n           \n          </p>\n          <p><strong>An Expanded Model Marketplace</strong></p>\n<p>Central to the announcement is the Amazon Bedrock Marketplace, a new hub offering businesses a diverse selection of models to suit specific needs. From Luma AI&#8217;s Ray 2, which enables realistic video creation, to <a href=\"https://poolside.ai/\">poolside</a>&#8217;s malibu and point models, which streamline software engineering tasks, the marketplace delivers options for nearly every industry.</p>\n<p>Stability AI&#8217;s Stable Diffusion 3.5 Large, also part of the new lineup, focuses on generating high-quality images from text descriptions. Whether a company is creating marketing assets or visual effects, the model offers flexibility and efficiency.</p>\n<p>Customers can easily browse and deploy these models through Bedrock&#8217;s unified interface, streamlining what has traditionally been a resource-intensive process.</p>\n<p><strong>Smarter AI at Lower Costs</strong></p>\n<p>Two features, Prompt Caching and Intelligent Prompt Routing, aim to make AI usage more cost-effective. Prompt Caching eliminates redundant computations, reducing latency by up to 85% and cutting costs by as much as 90%. Meanwhile, Intelligent Prompt Routing dynamically directs queries to the most appropriate model based on cost and complexity.</p>\n<p>Argo Labs, a developer of AI-driven voice assistants, has already embraced these tools to optimise customer interactions. &#8220;By routing simpler queries to smaller models and reserving complex questions for more advanced ones, we&#8217;ve saved time and money without sacrificing quality,&#8221; an Argo Labs spokesperson shared.</p>\n<p><strong>Transforming Data into Insights</strong></p>\n<p>A standout feature of Amazon Bedrock&#8217;s update is its ability to process unstructured data &#8212; everything from PDFs to audio recordings&#8212;into usable formats for analysis and AI applications. For instance, Amazon Bedrock Data Automation enables businesses to extract and organise data from documents, videos, and more, significantly reducing manual workloads.</p>\n<p>BMW Group has used Amazon Bedrock&#8217;s GraphRAG capabilities to power its internal AI assistant, helping employees navigate vast stores of data with greater ease and accuracy. Similarly, digital asset firm Tenovos has leveraged Bedrock&#8217;s tools to boost content reuse by over 50%, saving millions in marketing costs.</p>\n<p><strong>A Growing Ecosystem</strong></p>\n<p>The adoption of Amazon Bedrock is accelerating. Tens of thousands of customers, from Adobe to Zendesk, are using the platform to drive innovation. With a 4.7x increase in users over the past year, AWS&#8217;s investment in generative AI appears to be paying off, positioning Amazon Bedrock as a vital tool in a fast-changing technological landscape.</p>\n<p><strong>Read next: <a href=\"https://ventureburn.com/2024/12/aws-trainium2-unlocks-new-ai-performance-levels/\">AWS Trainium2 Unlocks New AI Performance Levels</a></strong></p>\n<p class=\"shareaholic-canvas\"></p><p class=\"shareaholic-canvas\"></p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t</div>","author":"Brendon Petersen","favicon":"https://ventureburn.com/wp-content/themes/Burnmedia/favicon.ico","source":"ventureburn.com","published":"2024-12-05T15:39:20+00:00","ttr":2.3,"plain_text":"At this year’s AWS re:Invent, Amazon Web Services unveiled a major expansion to its Amazon Bedrock platform, introducing over 100 new AI models alongside tools designed to make generative AI more accessible and efficient for businesses. The updates are part of AWS’s broader push to simplify how companies integrate AI into their workflows, from creative content production to complex data processing.\n\n“Amazon Bedrock is tackling the toughest challenges developers face today,” said Dr Swami Sivasubramanian, AWS’s Vice President of AI and Data. “These new capabilities help customers unlock the full potential of generative AI.”\n\nAn Expanded Model Marketplace\n\nCentral to the announcement is the Amazon Bedrock Marketplace, a new hub offering businesses a diverse selection of models to suit specific needs. From Luma AI’s Ray 2, which enables realistic video creation, to poolside’s malibu and point models, which streamline software engineering tasks, the marketplace delivers options for nearly every industry.\n\nStability AI’s Stable Diffusion 3.5 Large, also part of the new lineup, focuses on generating high-quality images from text descriptions. Whether a company is creating marketing assets or visual effects, the model offers flexibility and efficiency.\n\nCustomers can easily browse and deploy these models through Bedrock’s unified interface, streamlining what has traditionally been a resource-intensive process.\n\nSmarter AI at Lower Costs\n\nTwo features, Prompt Caching and Intelligent Prompt Routing, aim to make AI usage more cost-effective. Prompt Caching eliminates redundant computations, reducing latency by up to 85% and cutting costs by as much as 90%. Meanwhile, Intelligent Prompt Routing dynamically directs queries to the most appropriate model based on cost and complexity.\n\nArgo Labs, a developer of AI-driven voice assistants, has already embraced these tools to optimise customer interactions. “By routing simpler queries to smaller models and reserving complex questions for more advanced ones, we’ve saved time and money without sacrificing quality,” an Argo Labs spokesperson shared.\n\nTransforming Data into Insights\n\nA standout feature of Amazon Bedrock’s update is its ability to process unstructured data — everything from PDFs to audio recordings—into usable formats for analysis and AI applications. For instance, Amazon Bedrock Data Automation enables businesses to extract and organise data from documents, videos, and more, significantly reducing manual workloads.\n\nBMW Group has used Amazon Bedrock’s GraphRAG capabilities to power its internal AI assistant, helping employees navigate vast stores of data with greater ease and accuracy. Similarly, digital asset firm Tenovos has leveraged Bedrock’s tools to boost content reuse by over 50%, saving millions in marketing costs.\n\nA Growing Ecosystem\n\nThe adoption of Amazon Bedrock is accelerating. Tens of thousands of customers, from Adobe to Zendesk, are using the platform to drive innovation. With a 4.7x increase in users over the past year, AWS’s investment in generative AI appears to be paying off, positioning Amazon Bedrock as a vital tool in a fast-changing technological landscape.\n\nRead next: AWS Trainium2 Unlocks New AI Performance Levels","ttr_disclaimer":"Assuming 200 wpm reading speed"}}
                                                                                                                                                                                                                    
                                                                                                    

Article Data Extractor - CODE SNIPPETS


curl --location --request GET 'https://zylalabs.com/api/35/article+data+extractor+api/1880/article+data+extractor?url=https://www.thestartupfounder.com/use-this-data-extractor-api-to-get-article-data-from-mathrubhumi/' --header 'Authorization: Bearer YOUR_API_KEY' 


    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Article Data Extractor API REST API, simply include your bearer token in the Authorization header.
Headers
Header Description
Authorization [Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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The Article Data Extractor API is designed to extract relevant information from articles or blogs by providing the URL of the desired webpage. It scrapes and retrieves data such as the article's title, text, published time, media links, and more. The API aims to save time by delivering structured data that can be easily filtered, queried, and stored for further use.

The Article Data Extractor API can extract various types of information from articles or blogs. This includes the article's title, main text content, published time, media links (such as images or videos embedded within the article), and potentially other metadata associated with the article.

The accuracy of data extraction depends on factors such as the structure and quality of the webpage, as well as the consistency of its layout and formatting. The API employs scraping techniques to retrieve information, and its accuracy may vary based on these factors. However, it is designed to provide reliable and relevant data from the provided article or blog URL.

No, at the moment batch requests are not supported. You will have to make one API call per article that you want to extract the data from.

The extracted data from the articles or blogs is typically returned in a structured format, such as JSON. This makes it easier to work with the data programmatically, as you can access specific fields and properties. The API organizes the extracted information in a structured manner, allowing you to filter, query, and store the data as per your requirements.

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