https://github.com/l1ght14/chatbot

Book Recommender Chatbot is a rule-based web app built with Python and Flask. It uses popularity and collaborative filtering to recommend books based on user preferences, offering personalized suggestions via a chat interface.
https://github.com/l1ght14/chatbot

bookrecommender chatbot css flask html jvascript python rule-based

Last synced: 6 months ago
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Book Recommender Chatbot is a rule-based web app built with Python and Flask. It uses popularity and collaborative filtering to recommend books based on user preferences, offering personalized suggestions via a chat interface.

• Host: GitHub
• URL: https://github.com/l1ght14/chatbot
• Owner: l1ght14
• License: mit
• Created: 2025-03-12T17:36:58.000Z (10 months ago)
• Default Branch: master
• Last Pushed: 2025-06-09T15:21:25.000Z (7 months ago)
• Last Synced: 2025-06-18T17:06:54.539Z (7 months ago)
• Topics: bookrecommender, chatbot, css, flask, html, jvascript, python, rule-based
• Language: Python
• Homepage:
• Size: 51.1 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# 📘 Book Recommender Chatbot

## 🔍 Overview

A rule-based chatbot that provides book recommendations using Popularity-Based and Collaborative Filtering techniques. Built with Python (Flask) for backend and HTML/CSS/JavaScript for frontend.

## 💡 Features

- Recommends books based on user interests or popular titles

- Uses Collaborative Filtering and Popularity-Based Filtering

- Rule-based chatbot for basic conversation

- Google Books API for fetching book info

- Real-time web interface built using Flask

## 🧰 Tech Stack

- **Backend:** Python, Flask, NumPy, Pandas, Pickle

- **Frontend:** HTML, CSS, JavaScript

- **APIs:** Google Books API

- **Tools:** PyCharm

## 💻 Key Functions

- `recommend()`: Returns similar books using cosine similarity

- `GenerateRecommendation()`: Random top-book recommendations

- `responses()`: Rule-based conversation logic

- `sanitizeText()`: Cleans user input

## 📦 Data

- Book Recommendation Dataset from Kaggle (Books, Users, Ratings)

## 🌐 Deployment

- Localhost with Flask, open-source project for learning-based use