For all further updates/language fixes please visit the fork by Cognirel - https://cognireltech.github.io/Quillpad-Server/. The original maintainers of Quillpad are maintaining the code there.
Quillpad is an indic language input technology that revolutionized the Indian language typing scene. It is one of the most popular Indic input technologies with more than a billion words typed on the website alone.
Quillpad pioneered the successful use of machine learning for building a predictive language input technology. Quillpad has been rated as the best by many organisations that have embraced Quillpad.
1.0.1
There are several archive files in the repository which have to be extracted, these include trained transliteration models and additional text files necessary for the Quillpad Server
- CherryPy-3.2.2.tar.gz
- EnglishPronouncingTrees.tar.bz2
- IndianPronouncingTrees.tar.bz2
- additional_text_files.zip
- bengali.tar.bz2
- gujarati.tar.bz2
- hindi.tar.bz2
- kannada.tar.bz2
- malayalam.tar.bz2
- marathi.tar.bz2
- nepali.tar.bz2
- punjabi.tar.bz2
- tamil.tar.bz2
- telugu.tar.bz2
- unique_word_files.zip
Kindly extract all of these archives into the repository folder itself.
Quillpad Server requires Python 2.7 to run.
First, we need to compile the Quillpad Model loader that will be used to load the trained transliteration models
$ cd Python\ Cart/python
$ python setup.py build_ext --inplace
$ cp QuillCCart.so ../../
$ cd ../../Now, the Quillpad Server is ready to run
$ python startquill_cherry.py-
Quillpad runs on port number 8090 (Additional configuration parameters are in quill_cherry8088.conf)
-
processWordJSON and processWord are the API endpoints over which the transliteration server can be accessed.
Example:
* localhost:8090/processWordJSON?inString=hello&lang=hindi
* localhost:8090/processWordJSON?inString=hello&lang=kannada
Additional Quillpad Documentation coming soon. Thanks for your patience.