chatbot.py

import os
import nltk
import ssl
import random 
import json
import ssl
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.linear_model import LogisticRegression

ssl._create_default_https_context = ssl._create_unverified_context
nltk.data.path.append(os.path.abspath("nltk_data"))
nltk.download('punkt')


with open('intents.json', 'r') as file:
    intents = json.load(file)


vectorizer = TfidfVectorizer()
clf = LogisticRegression(random_state=0, max_iter=10000)

tags=[]
patterns=[]
for intent in intents:
    for pattern in intent['patterns']:
         tags.append(intent['tag'])
         patterns.append(pattern)

x = vectorizer.fit_transform(patterns)
y= tags
clf.fit(x,y)
X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=42)
clf = RandomForestClassifier(n_estimators=200, random_state=42)
clf.fit(X_train, y_train)


def chat_bot(input_text):
    input_text= vectorizer.transform([input_text])
    tag = clf.predict(input_text)[0]
    for intent in intents:
        if intent['tag']==tag:
            response=random.choice(intent['responses'])
            return response