College Enquiry Chatbot

What does this College Enquiry Chatbot do ?

This chatbot will respond to students' queries regarding university. Questions like "When are holidays ? ", "Can you tell more about teachers?","How long does MCA take ?","What is my CGPA this sem" can be answered by this chatbot.

All features :

• Ask result or CGPA
• Queries related to faculty
• Course details & syllabus
• Ask about holidays

Tech Stack

• database - sqlite3
• server - python & flask
• frontend - html,css,js
• neural network - python & pytorch
• natural language processing - spacy & nltk

Getting started

Go to Instructions.md to know how to use this repo. Watch the Instructions here.

First create a virtual environment using virtualenv venv command in terminal/cmd prompt/powershell. Then activate it. Now we can install our dependencies for this project inside this isolated virtual environment.

We will install the following libraries to get started :

• torch - to create the neural network
• nltk & spacy - for NLP (natural language processing)
• flask - to run the web server where
  • we will interact with our chatbot
  • admin dashboard to manage our teachers, students, courses

I went to Pytorch's official guide to start local developement & got the command I need to install pytorch with cuda.

I used pip install nltk spacy flask to install them together. Then I use python -m spacy download en_core_web_sm to download english core small version.

Note : I have used CUDA (GPU) so torch versions have +cu116 written. When installing from requirements.txt use this command :

pip install -r requirements.txt -f https://download.pytorch.org/whl/torch_stable.html

Project structure

-- flask_server (this is the server)
        -- static (contains css & js files)
        -- templates (contains all html files)
        -- university
            -- __init__.py (to help importing university folder easily throughout the project)
            -- models.py (contains database models)
            -- routes.py (contains routes for university related views & apis)
        -- __init__.py (initializing base flask app throughout the project)
        -- university.db
-- chat.py
-- neural_net.py (base model for neural net)
-- nlp_utils.py
-- train.py (run this file to train our neural net)
-- run.py ( this file will run our flask sever)
-- intents.json (dataset for training)
-- requirement.txt (stores the name & versions of the libraries used)