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Coeus - EARIST A.C.E
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Coeus is an Artificial Conversational Entity for queries in Eulogio "Amang" Rodriguez Institute of Science and Technology, using Open Source Machine Learning Framework RASA NLU.
Implementation
python
installed on your machine.
- Machine Learning Framework Used: RASA https://rasa.com/docs/rasa/
- Repository Software for Python: PythonPackageIndex https://pypi.org/
pip help
python
then hit enter.
If Python is installed correctly, you should see output similar to what is shown below.
Python 3.7.0 (v3.7.0:1bf9cc5093, Jun 27 2018, 04:59:51) [MSC v.1914 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
Front-End Widget Used: RASA Webchat https://github.com/botfront/rasa-webchat.git
<script>!(function () {
let e = document.createElement("script"),
t = document.head || document.getElementsByTagName("head")[0];
(e.src =
"https://cdn.jsdelivr.net/npm/[email protected]/lib/index.js"),
(e.async = !0),
(e.onload = () => {
window.WebChat.default(
{
selector: "#webchat",
initPayload: "/hello",
customData: { language: "en" },
socketUrl: "http://localhost:5005",
title: "Coeus",
subtitle: "Earist Artificial Conversational Entity"
},
null
);
}),
t.insertBefore(e, t.firstChild);
})();
</script>
Usage
I. Quick Installation of RASA Open Source
pip3 install -U pip
pip3 install rasa
II. Virtual Environment Setup
Create a new virtual environment by choosing a Python interpreter and making a .\venv directory to hold it:
C:\> python3 -m venv ./venv
Activate the virtual environment:
C:\> .\venv\Scripts\activate
Initialize RASA:
rasa init
After cloning this repository open a prompt/terminal inside the directory where the files are located. To test the bot type the command below:
rasa shell
If you have a Front-End website to run the bot, enter the command:
rasa run --m ./models --endpoints endpoints.yml --port 5005 -vv --enable-api --cors “*”