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    "info": {
        "author": "Colin Gao",
        "author_email": "colin.gao@mykidx.com",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Libraries"
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        "description": "# Rasa Core \n\n\n[![Join the chat on Rasa Community Forum](https://img.shields.io/badge/forum-join%20discussions-brightgreen.svg)](https://forum.rasa.com/?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)\n[![PyPI version](https://img.shields.io/pypi/v/rasa_core.svg)](https://pypi.python.org/pypi/rasa-core)\n[![Supported Python Versions](https://img.shields.io/pypi/pyversions/rasa_core.svg)](https://pypi.python.org/pypi/rasa_core)\n[![Build Status](https://travis-ci.com/RasaHQ/rasa_core.svg?branch=master)](https://travis-ci.com/RasaHQ/rasa_core)\n[![Coverage Status](https://coveralls.io/repos/github/RasaHQ/rasa_core/badge.svg?branch=master)](https://coveralls.io/github/RasaHQ/rasa_core?branch=master)\n[![Documentation Status](https://img.shields.io/badge/docs-stable-brightgreen.svg)](https://rasa.com/docs/core)\n\n\n- **What do Rasa Core & NLU do? \ud83e\udd14**\n  [Read About the Rasa Stack](https://rasa.com/products/rasa-stack/)\n\n- **I'd like to read the detailed docs \ud83e\udd13**\n  [Read The Docs](https://rasa.com/docs/core)\n\n- **I'm ready to install Rasa Core! \ud83d\ude80**\n  [Installation](https://rasa.com/docs/core/installation.html)\n\n- **I have a question \u2753**\n  [Rasa Community Forum](https://forum.rasa.com)\n\n- **I would like to contribute \ud83e\udd17**\n  [How to contribute](#how-to-contribute)\n\n## Introduction\n\nRasa Core is a framework for building conversational software, which includes\nChat Bots on :\n- Facebook Messenger\n- Slack\n- Microsoft Bot Framework\n- Rocket.Chat\n- Mattermost\n- Telegram\n- Twilio\n\nBut you can also build assistants as\n- Alexa Skills\n- Google Home Actions\n\nRasa Core's primary purpose is to help you build contextual, layered\nconversations with lots of back-and-forth. To have a real conversation,\nyou need to have some memory and build on things that were said earlier.\nRasa Core lets you do that in a scalable way.\n\nThere's a lot more background information in this\n[blog post](https://medium.com/rasa-blog/a-new-approach-to-conversational-software-2e64a5d05f2a)\n\n## Where to get help\n\nThere is extensive documentation:\n\n- [master](https://rasa.com/docs/core/master/) \n  (if you install from **github**) or\n- [stable](https://rasa.com/docs/core)  \n  (if you install from **pypi**)\n\n\nPlease use [Rasa Community Forum](https://forum.rasa.com) for quick answers to\nquestions.\n\n\n\n### README Contents:\n- [How to contribute](#how-to-contribute)\n- [Development Internals](#development-internals)\n- [License](#license)\n\n### How to contribute\nWe are very happy to receive and merge your contributions. There is\nsome more information about the style of the code and docs in the\n[documentation](https://nlu.rasa.com/contribute.html).\n\nIn general the process is rather simple:\n1. create an issue describing the feature you want to work on (or\n   have a look at issues with the label\n   [help wanted](https://github.com/RasaHQ/rasa_core/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22))\n2. write your code, tests and documentation\n3. create a pull request describing your changes\n\nYou pull request will be reviewed by a maintainer, who might get\nback to you about any necessary changes or questions. You will\nalso be asked to sign a\n[Contributor License Agreement](https://cla-assistant.io/RasaHQ/rasa_core)\n\n\n## Development Internals\n### Running and changing the documentation\nTo build & edit the docs, first install all necessary dependencies:\n\n```\nbrew install sphinx\npip install -r dev-requirements.txt\n```\n\nAfter the installation has finished, you can run and view the documentation\nlocally using\n```\nmake livedocs\n```\n\nVisit the local version of the docs at http://localhost:8000 in your browser.\nYou can now change the docs locally and the web page will automatically reload\nand apply your changes.\n\n### Running and changing the unit test\nTo build & edit the docs, first install all necessary dependencies:\n\n```\ndocker build -f Dockerfile.dev . -t kidx_core_dev\n\ndocker run --name kidx_core_dev -v \"$PWD\":/app -it kidx_core_dev bash\n```\n\nAfter the docker container start run command in docker\n```\npip install -e . --no-cache-dir -i https://mirrors.aliyun.com/pypi/simple/\nmake lint\nmake test\n```\n\nLook the coverage should be no failure and pass 100%\n\n## License\nLicensed under the Apache License, Version 2.0.\nCopyright 2018 Kidx AI Technologies Education. [Copy of the license](LICENSE.txt).\n\nA list of the Licenses of the dependencies of the project can be found at\nthe bottom of the\n[Libraries Summary](https://libraries.io/github/RasaHQ/rasa_core).\n",
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        "keywords": "nlp machine-learning machine-learning-library bot bots botkit kidx conversational-agents conversational-ai chatbotchatbot-framework bot-framework",
        "license": "Apache 2.0",
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