app.py

#this is simple  FAQ chatbot for python dataset

import tkinter as tk
from tkinter import scrolledtext
import pandas as pd
import nltk
import string
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity


nltk.download('punkt')
nltk.download('stopwords')
nltk.download('wordnet')

from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer

# -------- Load dataset: it is python FAQ FROM Kaggel --------
df = pd.read_csv("./python.csv", encoding='latin1')

# -------- Preprocessing --------
stop_words = set(stopwords.words('english'))
lemmatizer = WordNetLemmatizer()

def preprocess(text):
    tokens = nltk.word_tokenize(text.lower())
    tokens = [t for t in tokens if t not in string.punctuation]
    tokens = [t for t in tokens if t not in stop_words]
    tokens = [lemmatizer.lemmatize(t) for t in tokens]
    return " ".join(tokens)

df['Questions'] = df['Questions'].apply(preprocess)

# -------- Vectorization --------
vectorizer = TfidfVectorizer()
X = vectorizer.fit_transform(df['Questions'])

def get_best_answer(user_input):
    processed_input = preprocess(user_input)
    user_vec = vectorizer.transform([processed_input])
    similarities = cosine_similarity(user_vec, X) # Calculate cosine similarity: user question vs all FAQs until he find the most similar one
    best_match_idx = similarities.argmax()
    return df.iloc[best_match_idx]['Answers']

# -------- Tkinter UI --------
def send_message(event=None):
    user_input = entry.get()
    if not user_input.strip():
        return
    
    add_message(user_input, sender="user")
    bot_response = get_best_answer(user_input)
    add_message(bot_response, sender="bot")
    entry.delete(0, tk.END)

def add_message(message, sender="bot"):
    chat_window.config(state=tk.NORMAL)
    if sender == "user":
        chat_window.insert(tk.END, f"\nYou:\n", "user_name")
        chat_window.insert(tk.END, f"{message}\n", "user_msg")
    else:
        chat_window.insert(tk.END, f"\nBot:\n", "bot_name")
        chat_window.insert(tk.END, f"{message}\n", "bot_msg")
    chat_window.config(state=tk.DISABLED)
    chat_window.yview(tk.END)

# Create main window
root = tk.Tk()
root.title("ChatGPT-Style FAQ Bot")
root.geometry("600x500")
root.configure(bg="#343541")

# Chat display area
chat_window = scrolledtext.ScrolledText(root, wrap=tk.WORD, state=tk.DISABLED, bg="#343541", fg="white", font=("Segoe UI", 11), bd=0, padx=10, pady=10)
chat_window.grid(row=0, column=0, columnspan=2, sticky="nsew", padx=10, pady=10)

# Tag styles for messages
chat_window.tag_config("user_name", foreground="#00A67E", font=("Segoe UI", 10, "bold"))
chat_window.tag_config("bot_name", foreground="#1E90FF", font=("Segoe UI", 10, "bold"))
chat_window.tag_config("user_msg", foreground="white", background="#444654", font=("Segoe UI", 11), spacing3=5, lmargin1=20, lmargin2=20, rmargin=10)
chat_window.tag_config("bot_msg", foreground="white", background="#3E3F4B", font=("Segoe UI", 11), spacing3=5, lmargin1=20, lmargin2=20, rmargin=10)

# Input field
entry = tk.Entry(root, bg="#40414F", fg="white", font=("Segoe UI", 12), insertbackground="white", relief=tk.FLAT)
entry.grid(row=1, column=0, padx=10, pady=10, sticky="ew")
entry.bind("<Return>", send_message)

# Send button
send_button = tk.Button(root, text="Send", command=send_message, bg="#19C37D", fg="white", font=("Segoe UI", 11, "bold"), relief=tk.FLAT, width=8)
send_button.grid(row=1, column=1, padx=10, pady=10)

# Layout resizing
root.grid_rowconfigure(0, weight=1)
root.grid_columnconfigure(0, weight=1)

root.mainloop()