Update app.py for improved UI

app.py

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+import streamlit as st
+from transformers import pipeline
+
+# Title of the app
+st.title("Sentiment Analysis App") #Sets the title of the Streamlit app to "Sentiment Analysis App".
+
+# Input text from the user
+user_input = st.text_area("Enter text to analyze") #Creates a text area where users can input the text they want to analyze.
+
+# Select pretrained model
+#distilbert-base-uncased-finetuned-sst-2-english: A DistilBERT model fine-tuned for sentiment analysis on the SST-2 dataset.
+#nlptown/bert-base-multilingual-uncased-sentiment: A BERT model trained for sentiment analysis on multiple languages.
+
+model_name = st.selectbox("Select a pretrained model", ["distilbert-base-uncased-finetuned-sst-2-english", "nlptown/bert-base-multilingual-uncased-sentiment"]) #Provides a dropdown menu for users to select a pretrained model provided by the HuggingFace Transformers library
+
+# Initialize the sentiment analysis pipeline
+sentiment_analysis = pipeline("sentiment-analysis", model=model_name,device=-1) #Initializes the sentiment analysis pipeline using the selected model.
+
+# Perform sentiment analysis when the button is clicked
+if st.button("Analyze"): #reates a button labeled "Analyze". When clicked, it triggers the sentiment analysis.
+    if user_input:
+        results = sentiment_analysis(user_input) #If text is entered, the sentiment analysis pipeline processes the text
+        st.write(results) #results are displayed 
+    else:
+        st.write("Please enter some text to analyze") #If no text is entered, a message prompting the user to enter some text is displayed

requirements.txt

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+streamlit
+transformers
+torch
+torchaudio
+torchvision