In this repository you have a Graphical User Interface Chatbot, made with python and javascript/html/css.
As mentioned above, in this Repository we have a chatbot with GUI that is made with the help of python and javascript/html/css.
In particular, I used Python/Tensorflow
to train the Chatbot and used javascript/html/css
in order to make the web app.
The communication between Python and Js is being made with the help of Flask
.
This project consist of two parts. The first part is made with the help of python (more specifically the hole bot is written in python), and the rest is made with javascript html/css.
- Tensorflow/Keras, training the bot.
- NLTK, language processing toolkit.
- Flask, creating the api.
- numpy/pickle, utilities.
- javascript/html/css, vanilla. π
In order to use docker you need to install the tensorflow container. You can do that with this command:
.\> docker pull tensorflow/tensorflow
When the tensorflow container installs on your machine, execute this command:
.\> docker-compose up
After a few minutes everything will be set up and ready to Go. The last step is to connect on localhost:8080
and start talking with the Bot.
First of all you need to start the python
server. Open a command-prompt in the chatbot folder and type:
.\> python backend
- This will automatically start the server.
After that open the index.html
file inside the frontend and start chatting with your new friend.
What need to be implemented | Already done |
---|---|
Train the bot | β |
Create a dataset | β |
Process the dataset | β |
Create the API | β |
Make the web application | β |
Design the application | β |
Implement the design | β |
Connect the frontend with the backend | β |
Display the backend answer | β |
This was a small Project that helped me understand some new things. One of them is how to achieve the communication between python/js
.