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RELEASE.md

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# Release 2.0.3
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# Release X.X.X
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<INSERT SMALL BLURB ABOUT RELEASE FOCUS AREA AND POTENTIAL TOOLCHAIN CHANGES>
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* <NOTES SHOULD BE GROUPED PER AREA>
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# Release 2.0.3 (Up coming Release )
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# Release Candidate
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Bug fixes
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## Major Features and Improvements
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## Bug Fixes and Other Changes
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* [] Updated documentation
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# Release 2.0.3
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Bug fixes
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## Major Features and Improvements
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* [209](https://github.com/navigateconsulting/eva/pull/209) Rasa version upgrade to 1.10.3

Readme.md

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<p><h2>Enterprise Virtual Assistant (EVA)</h2></p>
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</div>
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## Table of Contents
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# Table of Contents
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* [About the Project](#about-the-project)
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* [Built With](#built-with)
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* [Getting Started](#getting-started)
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* [Prerequisites](#prerequisites)
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* [Installation](#installation)
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* [Usage](#usage)
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* [Documentation](#Documentation)
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## About The Project
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# About The Project
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### Built With
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An Easy to use application to build train and deploy chat bots. This project intends to be a one stop shop for all production grade chat bot needs
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We used below projects to build the application stack.
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A snippet of how this application works !
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[Rasa Open Source](https://github.com/RasaHQ/rasa)
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![Try Now screen Demo](docs/assets/gifs/try-now.gif)
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## Built With
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The Application stack is built with below technologies
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We used below projects as chat bot framework.
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Angular - For front end development.
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Python Flask - For API backend.
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mongodb - As a Database for storing Rasa projects.
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* [Rasa Open Source](https://github.com/RasaHQ/rasa) Version 1.10.3
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redis - As a caching layer between UI and Backend.
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The Application stack is built with Python as backend and Angular as front end.
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## Getting Stated
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We use [Docker hub](https://hub.docker.com/u/navigateconsulting) to publish docker container images.
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### Prerequisites
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## Prerequisites
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- Docker version 18.09 onwards. (not tested on previous versions)
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- Docker Compose version 1.24 onwards (not tested on previous versions)
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- Linux Distributions (Windows not supported as of now, tested on ubuntu)
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### Installation
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## Installation
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If the project is to be deployed for production, please follow instructions for production deployment in below section
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#### Quick Installation
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### Quick Installation
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Download the docker-compose.yml file with below command
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This will start the application user interface on port 8080.
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#### Production Mode
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### Production Mode
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For production deployment, all the user interface containers are recommended to be on TLS. Refer docker-compose.tls_example.yml file
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for how to configure and secure the deployment. Example contains a Letscert container which handles certificates and reissue on expiry.
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docker-compose up -d
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#### For Development
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### For Development
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If you intent to extend the stack and make changes to the code base , follow below instructions to clone the repo and build containers from source
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**Note: docker-compose.yml file uses docker hub to pull docker containers and does not build from source.
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### Documentation
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# Documentation
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Below are some short examples on how to use this application , detailed documentation on usage can be found [here](https://navigateconsulting.github.io/eva/docs/usage/)
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1. Creating a Project
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![Creating a Project](docs/assets/gifs/create-project.gif)
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2. Creating a Domain
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![Creating a Domain](docs/assets/gifs/create-domain.gif)
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3. Creating an Intent
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![Creating an Intent](docs/assets/gifs/create-intent.gif)
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4. Creating a Response
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![Creating a Response](docs/assets/gifs/create-response.gif)
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5. Creating a Story
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![Creating a Story](docs/assets/gifs/create-story.gif)
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6. Training a Project
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![Training a Project](docs/assets/gifs/train-project.gif)
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7. Try your Project
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![Try your Project](docs/assets/gifs/try-now.gif)
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8. Deploy the Project
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![Deploy the Project](docs/assets/gifs/deploy-project.gif)
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# Roadmap
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See the open issues for a list of proposed features (and known issues).
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# Contributing
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Any contributions are Welcome ! To contribute,
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You can find detailed documentation [here](https://navigateconsulting.github.io/virtual-assistant/)
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1. Fork the Project
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2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
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3. Commit your Changes (git commit -m 'Add some AmazingFeature')
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4. Push to the Branch (git push origin feature/AmazingFeature)
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5. Open a Pull Request
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## Usage
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Usage instructions : [click here](docs/usage/Readme.md)
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## License
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# License
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[Apache 2.0](LICENSE)

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