We are pleased to announce the new release of Aspose.Words Cloud 18.8. Fully reworked versions of Ruby and Python SDKs for Aspose.Words Cloud have been released.. Moreover, the release provides Vector graphics support and Table detection and recognition improvements for PDF to Word Conversion. Fully reworked version of Aspose Cloud Ruby SDK has been released. Ruby Cloud SDK is a wrapper around REST API, allowing to process documents in Ruby 2.3 quickly and easily, gaining all benefits of strong types and IDE highlights. New SDK is fully supported and has the many advantages over the previous versions, such as SDK is fully in sync with the API, all missing methods are added, Classes, methods, and properties have comments and are IDE-friendly, Better security, Usage of Request/Response classes to represent long lists of parameters. This allows for cleaner code and easier backward-compatibility going forward and SDK is not backward compatible with the previous generation because of the last item. It should be straightforward to convert program code to using Request/Response objects, if users need any help on migration please ask at Free Support Forums. Fully reworked version of Aspose Cloud Python SDK has been released. Python Cloud SDK is a wrapper around REST API, allowing to process documents in Python 2.7, or higher (>=3.6) quickly and easily, gaining all benefits of strong types and IDE highlights. The distribution is available at pypi.org and source code at GitHub . New SDK is fully supported and has the several advantages over the previous versions. RPDF to Word converter now supports basic vector graphics. Moreover, accuracy of table detection has been significantly improved. Almost all simple tables are detected properly now. Please check Convert PDF Document to Word article for more details on blog announcement page. The taxonomy parameter is responsible for the list of classifier classes. If the parameter is not specified or is set to “default”, the classification is performed according to the IAB-2 taxonomy (10 news classes). Alternatively, there is a taxonomy “documents” (10 classes of documents). If the taxonomy parameter is set to “documents”, the classification will be performed using “documents” taxonomy. Please check Document Classification article for more details.