The aim of our project is to create A COVID-19 Question Answer Chatbot to improve answer selection process on the specific domain of COVID-19. With InferMedica, we hope to learn whether public information from reputable sources could be more effectively organized and shared in the wake of a crisis as well as to understand issues that the public were most immediately curious about. we can run project in local machin or on colab directly how to run local ? step 1 1- Install flask and flask libraries.
$pip install Flask
2- Run virtual environment in case of implementing on local machine. Use a virtual environment to manage the dependencies for your project, both in development and in production. Create an environment Create a project folder and a venv folder within:
> mkdir myproject
> cd myproject
> py -3 -m venv venv
Activate the environment Before you work on your project, activate the corresponding environment:
> venv\Scripts\activate
3- Install ngrok in case of implementing on a cloud like colab. !pip install flask-ngrok 4- Prepare your model to call it in the flask function. Preparing the model differs from one approach to another but the main idea in our project as a chat-bot is to get a function that could take a Question from user and make processes on that input then generate the proper answer. 5- Make your html files in folder named “templates”. 6- Make your Css and is file in folder named “static”. 7- Make your flask function and link your model with the interface you get from html and Css.
- First, we imported the Flask class. An instance of this class will be our WSGI application.
- Next, we create an instance of this class: The first argument is the name of the application’s module or package. name is a convenient shortcut for this that is appropriate for most cases. This is needed so that Flask knows where to look for resources such as templates and static files.
- We then use the route() decorator to tell Flask what URL should trigger our function.
- Use render template method to render the template you want.
- Use request.args.get() to get the get the message/ input the user enter then return it with the function that make response from the model to get the answer.
from flask import Flask, render_template, request, redirect, url_for
from flask_ngrok import run_with_ngrok
app = Flask(__name__)
run_with_ngrok(app)
app.static_folder = 'static'
@app.route("/")
def home():
return render_template("home.html")
@app.route("/get")
def get_bot_response():
userText = request.args.get('msg')
return answer_question(userText)
app.run()
8- Run your code and get your API.