https://github.com/arpitasri1305/conversational-interface-
Science Score: 26.0%
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○CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Scientific vocabulary similarity
Low similarity (11.5%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: arpitasri1305
- License: apache-2.0
- Language: Dockerfile
- Default Branch: main
- Size: 4.33 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
This project is not maintained anymore and will not receive further updates.
Highlights • Features • Quick start • Development
What is it
Botfront is an open-source enterprise-grade conversational platform built with Rasa. It provides super intuitive interfaces and collaborative features to domain experts, conversational designers and engineers.
Highlights
😎Easy to use |
🎓Powerful |
💻️Developer friendly |
|---|---|---|
| Our main goal is to lower the technical barrier to entry in conversational AI. Implementing context-aware conversations should be as easy as chatting. | Botfront uses Rasa, a powerful and production ready conversational AI library. Botfront exposes all Rasa functionalities and abstracts its complexity. | Botfront's intuitive CLI orchestrates all Botfront's services on your development machine. Authoring, training, auto reloading actions code, it just works! |
Features
An intuitive interface for stories and rules |
Botfront provides a unique and natural conversation authoring experience. You can create complex dialog flows in minutes |
A flow chart editor for forms |
A super intuitive flow chart editor for conversations that do not require machine learning |
Automated tests |
Create automated tests in one click from conversations, get detailed reports and deploy in confidence. |
Git integration |
Version your work on a repository with the new Git integration. |
Train & evaluate NLU models |
Botfront comes with a complete NLU toolbox. You can tag vast amounts of data efficiently, train and evaluate models. Several evaluation methods are available depending on the development stage of your model, and you can annotate incoming NLU data |
Rasa integration |
Botfront exposes all Rasa features and concepts and and makes them accessible at a higher level for faster development. You can export a Botfront project and use it with Rasa at any time. |
Enterprise ready |
Scale your conversational AI practice with enterprise grade projects and user management, RBAC and flexible deployment options. |
Quick Start
Botfront only requires a recent version of Docker. You can install the CLI with the following:
bash
npm install -g botfront
Then just run botfrontto get started.
Documentation
The official documentation of Botfront is hosted on botfront.io. It is automatically built and updated on every new release. Once you've installed the cli you can also use botfront docs to open it.
We welcome contributions! It can be as easy as clicking on the "Edit page on Github" link at the bottom of every documentation pages.
Development
Installation
- Botfront is a Meteor app, so the first step is to install Meteor
- Then clone this repo and install the dependencies:
bash git clone https://github.com/botfront/botfront cd botfront/botfront meteor npm install Install the CLI from the source code: ```bash
if you installed Botfront from npm uninstall it.
npm uninstall -g botfront
Install the cli from the source code
cd cli && npm link ``` Botfront needs to be connected to other services, especially Rasa. To do this, you need to create a regular project, and start Botfront with a dedicated configuration:
Create a Botfront project with
botfront init(somewhere else, not in the repo)Start your project with
botfront up -e botfront. This will run all services except the Botfront app, since you are going to run it with Meteor locallyGo back to the botfront checkout
cd botfront/botfrontand run Botfront withmeteor npm run start:docker-compose.dev. Botfront will be available at http://localhost:3000 so open your browser and happy editing :smile_cat:
TroubleShooting
Some botfront cli commands that may help if you run into problems:
shell
botfront init # create a new botfront project
botfront logs # show the logs!
botfront killall # stop all docker services
botfront down # stop all botfront services
botfront up # restart botfront
botfront docs # open the docs in your browser
Note that these should be run from the same directory as your botfront project
Contribute
We ❤️ contributions of all size and sorts. If you find a typo, if you want to improve a section of the documentation or if you want to help with a bug or a feature, here are the steps:
- Fork the repo and create a new branch, say
fix-botfront-typo-1 - Fix/improve the codebase
- Commit the changes. Commit message must follow the naming convention, say
fix(conversation builder): display story groups in alphabetical order - Make a pull request. Pull request name must follow the naming convention. It can simply be one of your commit messages, just copy paste it, e.g.
fix(readme): improve the readability and move sections - Submit your pull request and wait for all checks passed (up to an hour)
- Request reviews from one of the developers from our core team.
- Get a 👍 and PR gets merged.
Well done! Once a PR gets merged, here are the things happened next:
- all Docker images tagged with branch-master will be automatically updated in an hour. You may check the status on the Actions tab.
- your contribution and commits will be included in our release note.
Testing
End to end tests are using the Cypress testing framework.
To manually run the Cypress tests, you need to have Botfront running in development mode. Some tests also require Rasa to be available.
Once you are at the root of the repo, you can enter the following.
```bash cd botfront
if you want to open Cypress' graphical interface
npx cypress open
If you want to run the whole suite in headless mode
This could take up to an hour depending on your computer
npx cypress run
If you want to run a specific test
npx cypress run --spec "cypress/integration/02_training/training.spec.js" ```
Commit messages naming convention
To help everyone with understanding the commit history of Botfront, we employ commitlint to enforce the commit styles:
text
type(scope?): subject
where type is one of the following:
- build
- ci
- chore
- docs
- feat
- fix
- perf
- refactor
- revert
- style
- test
scope is optional, represents the module your commit working on.
subject explains the commit.
As an example, a commit that improved the documentation:
text
docs(conversation builder): update slots manager screenshot.
License
Copyright (C) 2021 Dialogue Technologies Inc.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.(C) 2021 Dialogue Technologies Inc. All rights reserved.
Owner
- Name: ARPITA SRIVASTAVA
- Login: arpitasri1305
- Kind: user
- Company: IMS ENGINEERING COLLEGE
- Repositories: 1
- Profile: https://github.com/arpitasri1305
I am dedicated and performance-driven under graduate engineering student with a strong foundation in software development and consistent academic track record.
GitHub Events
Total
- Create event: 2
Last Year
- Create event: 2
Dependencies
- geoffreybooth/meteor-base 2.0 build
- node 12-buster-slim build