Release Notes: This release enables multiple instances of the same predictor class at runtime through configuration. Predictive performance can be more finely tailored to the users' specific needs by tuning the resources and configuration of each predictor. The default configuration has been changed to add a custom user-smoothed ngram predictor, which adaptively learns its language model. Its learning performance has been improved.
Release Notes: This release integrates into Notepad++, a powerful Windows text editor, thanks to the new presage predictive Notepad++ plugin NppPresage. It comes with improved configuration profile handling on Windows: it now locates the system profile configuration directory from HKCU/Software/Presage registry key on Windows, and correctly locates the user profile directory. There are improvements to gprompter, including an updated text editing widget and a new invert colours feature. gprompter and pyprompter also come with new (and ugly) icons on the GNOME desktop.
Release Notes: This release offers a new C API to libpresage, in addition to the C++ and Python APIs. gprompter is now written in plain C and uses the new libpresage C API. There are improvements to the experimental D-BUS service interface and start-stop scripts. A D-BUS Python example client is also provided. There are a number of other enhancements and fixes.
Release Notes: This release sports significant performance improvements in its smoothed n-gram predictor. Runtime execution was sped up by approximately a factor of 5 by tuning some expensive SQL queries to the embedded SQLite database. This release comes with refactored configuration and profile handling subsystems. Configuration is read from system-level, installation-level, and user-level XML profiles and from an optional user-specified profile. Changes to configuration variables made at runtime through the config() API can now be persisted to file by calling the new save_profile() API method.
Release Notes: This release includes two new predictive applications, gprompter and pypresagemate. Gprompter is a cross-platform predictive text editor. Pypresagemate is a universal predictive text companion. Pypresagemate works alongside any AT-SPI aware application. This release provides a new callback-aware programming interface to make it easier to develop interactive presage applications. Presage applications no longer need to track user interaction by explicitly updating the context. There are other bugfixes and enhancements.
Release Notes: This release is able to learn "on the fly" from the context and the text currently being entered. The smoothed n-gram predictive plugin dynamically learns from the current context, while generating new predictions. This release provides better predictions by incrementally increasing the depth of prediction generation, and incorporates several bugfixes to the context changes detection code. It includes a new dejavu predictive plugin, and a new GTK application whose aim is to augment any other application with presage predictive functionality.
Release Notes: A new statistical predictive plugin, based on recency promotion, is now available. There is a new simple GUI demonstration program, Prompter. Prompter is a soothsayer-enabled text editor that displays predictions generated by soothsayer through a pop-up autocompletion list. Native Windows support has been added via the MinGW/MSYS platform. There are enhancements to the build system and a number of bugfixes.
Release Notes: This release includes a new Python binding module, which enables Python applications to natively call into soothsayer. It has been ported to Solaris 10, and built with Sun Studio 10 and 11 compilers. It includes bugfixes and improvements to the build system. Library dependencies have been cleaned up. Shared libraries are now built on all supported platforms, including Windows/Cygwin targets.
Release Notes: The new generalized smoothed n-gram statistical predictive plugin is included, which supports arbitrary order n-grams. Used in combination with the text2ngram tool, statistical predictions can be generated by n-gram language models of arbitrary cardinality. It uses an improved heuristic to generate initial completion candidates, by using highest order n-gram statistics. This release includes notable bugfixes and improvements to soothsayer simulator. A bug in the simulator caused the reported Key Stroke Reduction rate to be much lower than the actual KSR achieved by soothsayer.
Release Notes: This release includes the new abbreviation expansion predictive plugin, which allows users to specify a file containing a list of abbreviations/expansions pairs. It also includes bugfixes and documentation improvements.