EduBot

by chiragparmar532

This kit is solely created for EduBot under the #BuildWithAI 2021 Hackathon.

Use the open source, cloud APIs, or public libraries listed below in your application development based on your technology preferences, such as primary language. The below list also provides a view of the components' rating on different dimensions such as community support availability, security vulnerability, and overall quality, helping you make an informed choice for implementation and maintenance of your application. Please review the components carefully, having a no license alert or proprietary license, and use them appropriately in your applications. Please check the component page for the exact license of the component. You can also get information on the component's features, installation steps, top code snippets, and top community discussions on the component details page. The links to package managers are listed for download, where packages are readily available. Otherwise, build from the respective repositories for use in your application. You can also use the source code from the repositories in your applications based on the respective license types.
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ChatterBotby gunthercox

ChatterBot is a machine learning, conversational dialog engine for creating chat bots

Python Updated: 6 mo ago License: Permissive

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nltkby nltk

NLTK Source

Python Updated: 3 mo ago License: Permissive

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T

TextBlobby sloria

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.

Python Updated: 3 mo ago License: Permissive

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sentimentby thisandagain

AFINN-based sentiment analysis for Node.js.

JavaScript Updated: 6 mo ago License: Permissive

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twilio-pythonby twilio

A Python module for communicating with the Twilio API and generating TwiML.

Python Updated: 1 d ago License: Permissive

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C

ChatBotby jahnavi13reddy

It is a simple Chatterbot . Firstly import ChatBot from chatterbot library then import ListTrainer from chatterbot.trainers library lastly import OS ,OS is imported inorder to list all the operating system features.Steps to create a Chatterbot:1)Install a chatterbot 2)Get a chatterbot corpus(chatterbot corpus contains all the files with.yml extensions. 3)Coding 4)Training the chatterbot 5)Testing the chatterbot 6)Creating a UI for your chatterbox 7)Deploy .After creating chatterbot if you come across some common errors like no module called chatterbot make sure that chatterbot is installed and chatterbot is installed with 0.8.6 version .If necessary upgrade your chatterbot with 'python -m pip install --upgrade pip' command .If you come across end of line errors then check the quotes are closed properly,use / slashes instead of \ slashes in location address,make sure you entered the/ in English

Python Updated: 2 y ago License: No License

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