add os.enviorment

app.py

@@ -16,6 +16,9 @@ import pandas as pd
 from transformers import pipeline
 from torch.utils.data import Dataset, DataLoader
 import torch.nn as nn
+import os
+from dotenv import load_dotenv
+load_dotenv()
 
     
 
@@ -143,6 +146,8 @@ def extract_features(tweet):
 # Loading personality model
 
 def personality_detection(text, threshold=0.05, endpoint= 1.0):
+    PERSONALITY_TOKEN =os.environ.get('PERSONALITY_TOKEN', None)
+    print(PERSONALITY_TOKEN)
     tokenizer = AutoTokenizer.from_pretrained ("Nasserelsaman/microsoft-finetuned-personality",token=PERSONALITY_TOKEN)
     model = AutoModelForSequenceClassification.from_pretrained ("Nasserelsaman/microsoft-finetuned-personality",token=PERSONALITY_TOKEN)
     
@@ -368,5 +373,10 @@ def greet(tweet):
 
     return str(predicted_class)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+demo = gr.Interface(
+    title = "Unmasking Hate: An Integrated Approach to Detecting Hate Speech in Social Media",
+    # fn=greet,
+    fn=greet, inputs=gr.Textbox(placeholder="Enter an input sentence...",label="Input Sentence"), 
+    allow_flagging = "never",outputs="text")
+demo.launch()