YEEEE

app.py

@@ -3,7 +3,8 @@ import torch
 from transformers import AutoModelForSequenceClassification, pipeline, AutoTokenizer, DistilBertForSequenceClassification, DistilBertTokenizerFast
 import pandas as pd
 import comments
-from random import randint
+from random import randin
+import kanye
 
 
 def predict_cyberbullying_probability(sentence, tokenizer, model):
@@ -65,7 +66,7 @@ def perform_default_analysis(model_name):
 
 # main -->
 st.title("Toxic Tweets Analyzer")
-image = "kanye_tweet.jpg"
+image = "kanye_loves_tweet.jpg"
 st.image(image, use_column_width=True)
 
 labels = ['comment', 'toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']
@@ -80,12 +81,17 @@ with st.form("my_form"):
         tweet = st.text_area(label="Enter Text:",value=default)
         submitted = st.form_submit_button("Analyze textbox")
         random = st.form_submit_button("Analyze a random 😈😈😈 tweet (warning!!)")
+        kanye = st.form_submit_button("Get a ye quote 🐻🎤🎧🎶")
         
         if random:
             tweet = comments.comments[randint(0, 354)]
             st.write(tweet)
             submitted = True
         
+        if kanye:
+            tweet = kanye.quote()
+            st.write(tweet)
+        
         if submitted:
             df = perform_cyberbullying_analysis(tweet)
             st.table(df)

requirements.txt

@@ -1,2 +1,4 @@
 transformers
-torch
+torch
+kanye
+pandas