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.babelrc (241, 2018-11-09)
.circleci (0, 2018-11-09)
.circleci\config.yml (2828, 2018-11-09)
.flowconfig (103, 2018-11-09)
.npmignore (54, 2018-11-09)
LICENSE (33893, 2018-11-09)
debug.html (782, 2018-11-09)
demo.html (1882, 2018-11-09)
index.css (638, 2018-11-09)
index.html (743, 2018-11-09)
package.json (1115, 2018-11-09)
rasa_utils (0, 2018-11-09)
rasa_utils\__init__.py (0, 2018-11-09)
rasa_utils\bot.py (5205, 2018-11-09)
rasa_utils\bot_server_channel.py (6838, 2018-11-09)
rasa_utils\requirements.txt (26, 2018-11-09)
src (0, 2018-11-09)
src\Chatroom.js (6098, 2018-11-09)
src\Chatroom.scss (5355, 2018-11-09)
src\ConnectedChatroom.js (7319, 2018-11-09)
src\DebuggerView.js (3367, 2018-11-09)
src\Message.js (2747, 2018-11-09)
src\SpeechInput.js (2875, 2018-11-09)
src\index.js (6076, 2018-11-09)
src\messages.json (9790, 2018-11-09)
src\utils.js (377, 2018-11-09)
yarn.lock (255567, 2018-11-09)

# React-based Chatroom Component for Rasa Stack [](https://circleci.com/gh/scalableminds/chatroom) [Watch a demo of our Chatroom in action](https://npm-scalableminds.s3.eu-central-1.amazonaws.com/@scalableminds/chatroom@master/demo.html) [Try a live chatbot](https://scalableminds.com/) ## Features * React-based component * Markdown, Images, Buttons * Customizable with SASS variables * Generates a unique session id and keeps it in `sessionStorage` * Queues consecutive bot messages for better readability * Speech input (only in Chrome for now) * Demo mode included (ideal for scripted screencasts) * Hosted on S3 for easy use * Includes a `BotServerChannel` for use with [Rasa Core](https://github.com/rasahq/rasa_core) (under `rasa_utils`) ## Usage Embed the `chatroom.js` in the HTML of your website and configure it to connect to your Rasa bot. (see below) ```html ``` Note, the version of the Chatroom's Javascript file is encoded in the URL. `chatroom@master` is always the latest version from the GitHub master branch. Use e.g. `chatroom@0.8.2` to load a specific release. [All Releases can be found here.](https://github.com/scalableminds/chatroom/releases) | Chatroom Version | Compatible Rasa Core Version | |------------------|------------------------------| | 0.9.x | 0.11.4+ | | 0.8.x | 0.11.4+ | | 0.7.8 | 0.10.4+ | ### Basic usage * Clone repository * Install frontend dependencies `yarn install` * Build frontend files `yarn build` * Create an HTML page for your Chatroom (see usage example above or modify [index.html](./index.html)) * Make sure to adjust the `host` option. Use `http://localhost:5005` when testing locally * Run `yarn serve` to launch a web server with your Chatroom on `http://localhost:8080` * Integrate with a Rasa Core project (see standard or custom project below) ### Usage with a standard Rasa Core project * Copy `rasa_utils` to your project * Install the Python dependencies from `rasa_utils/requirements.txt` * Run your bot with `python -m rasa_utils.bot -d models/current/dialogue -u models/current/nlu` * The bot server will be available at `0.0.0.0:5005` ### Simple Usage with a custom Rasa Core project on CLI * Copy the `rasa_utils/bot_server_channel.py` to your project * Install the Python dependencies from `rasa_utils/requirements.txt` * Create or Modifiy `credentials.yml` file and add: ``` rasa_utils.bot_server_channel.BotServerInputChannel: # pass ``` * Start the Rasa bot using the command line and pass the `--credentials` flag: ``` python -m rasa_core.run \ --core models/current/dialogue \ --nlu models/current/nlu \ --endpoints endpoints.yml \ --credentials credentials.yml ``` ### Advanced Usage with a custom Rasa Core project as Custom Channel from Python * Copy the `rasa_utils/bot_server_channel.py` to your project * Install the Python dependencies from `rasa_utils/requirements.txt` * Register the `BotServerInputChannel` with your Rasa Core `Agent` (see below) * Run your bot. By default the bot server will be available at `0.0.0.0:5005` ```python from bot_server_channel import BotServerInputChannel # Creating the Interpreter and Agent def load_agent(): ... # Creating the server def main_server(): agent = load_agent() channel = BotServerInputChannel(agent, port=5005) agent.handle_channels([channel], http_port=5005) main_server() ``` ## Development ### Install dependencies ``` yarn install ``` ### Continuously build the Chatroom component ``` yarn watch yarn serve ``` Open `http://localhost:8080/demo.html` in your browser. ## Build ``` yarn build ``` Distributable files will be created in folder `dist`. ## License AGPL v3 Made by [scalable minds](https://scalableminds.com)

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