import pandas as pd
import numpy as np
import gradio as gr

# import matplotlib.pyplot as plt
# %matplotlib inline
import seaborn as sns

from sklearn.feature_extraction.text import CountVectorizer

from sklearn.neighbors import KNeighborsClassifier
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import MultinomialNB

from sklearn.metrics import accuracy_score,precision_score,recall_score,f1_score

k=KNeighborsClassifier()
d=DecisionTreeClassifier()
r=RandomForestClassifier()
l=LogisticRegression()
mb=MultinomialNB()
    
from sklearn.model_selection import train_test_split

from wordcloud import WordCloud, STOPWORDS
from PIL import Image

from textblob import TextBlob

import warnings
warnings.filterwarnings('ignore')

df=pd.read_csv("data.csv")