Add About and Main pages to Streamlit app; update requirements

app.py

@@ -1,16 +1,16 @@
 import streamlit as st
-import transformers
-from transformers import pipeline
+#import transformers
+#from transformers import pipeline
 
 st.title('My first app')
 x = st.slider('Select a value')
 st.write(x, 'squared is', x * x)
 
-classifier = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")
+# classifier = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")
 
-# Example input text
-input_text = "I love using Hugging Face models!"
+# # Example input text
+# input_text = "I love using Hugging Face models!"
 
-# Get the classification result
-result = classifier(input_text)
-st.write(result)
+# # Get the classification result
+# result = classifier(input_text)
+# st.write(result)

pages/About.py

@@ -0,0 +1,4 @@
+import streamlit as st
+
+st.title('About')
+st.write('This app performs text analysis using Hugging Face transformers.')

pages/Analysis

@@ -0,0 +1,15 @@
+import streamlit as st
+#import transformers
+#from transformers import pipeline
+
+st.title('Text Analysis')
+
+# classifier = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")
+
+# input_text = st.text_area("Enter text to analyze:")
+# if st.button('Analyze'):
+#     if input_text:
+#         result = classifier(input_text)
+#         st.write(result)
+#     else:
+#         st.warning('Please enter some text')

pages/Main.py

@@ -0,0 +1,4 @@
+import streamlit as st
+
+st.title('Welcome to Text Analysis App')
+st.write('Use the sidebar to navigate between pages')

requirements.txt

@@ -1,3 +1,3 @@
 streamlit
-transformers
-torch
+#transformers
+#torch