Update app.py

app.py

@@ -1,69 +1,69 @@
-import streamlit as st
-import transformers
-import torch
+# import streamlit as st
+# import transformers
+# import torch
 
-# Load the model and tokenizer
-model = transformers.AutoModelForSequenceClassification.from_pretrained("DeeeTeeee01/twitter-xlm-roberta-base-sentiment_dee")
-tokenizer = transformers.AutoTokenizer.from_pretrained("DeeeTeeee01/twitter-xlm-roberta-base-sentiment_dee")
+# # Load the model and tokenizer
+# model = transformers.AutoModelForSequenceClassification.from_pretrained("DeeeTeeee01/twitter-xlm-roberta-base-sentiment_dee")
+# tokenizer = transformers.AutoTokenizer.from_pretrained("DeeeTeeee01/twitter-xlm-roberta-base-sentiment_dee")
 
-# Define the function for sentiment analysis
-@st.cache_resource
-def predict_sentiment(text):
-    # Load the pipeline.
-    pipeline = transformers.pipeline("sentiment-analysis")
+# # Define the function for sentiment analysis
+# @st.cache_resource
+# def predict_sentiment(text):
+#     # Load the pipeline.
+#     pipeline = transformers.pipeline("sentiment-analysis")
 
-    # Predict the sentiment.
-    prediction = pipeline(text)
-    sentiment = prediction[0]["label"]
-    score = prediction[0]["score"]
+#     # Predict the sentiment.
+#     prediction = pipeline(text)
+#     sentiment = prediction[0]["label"]
+#     score = prediction[0]["score"]
 
-    return sentiment, score
+#     return sentiment, score
 
-# Setting the page configurations
-st.set_page_config(
-    page_title="Sentiment Analysis App",
-    page_icon=":smile:",
-    layout="wide",
-    initial_sidebar_state="auto",
-)
+# # Setting the page configurations
+# st.set_page_config(
+#     page_title="Sentiment Analysis App",
+#     page_icon=":smile:",
+#     layout="wide",
+#     initial_sidebar_state="auto",
+# )
 
-# Add description and title
-st.write("""
-# Predict if your text is  Positive, Negative or Nuetral ...
-Please type your text and press ENTER key to know if your text is positive, negative, or neutral sentiment!
-""")
+# # Add description and title
+# st.write("""
+# # Predict if your text is  Positive, Negative or Nuetral ...
+# Please type your text and press ENTER key to know if your text is positive, negative, or neutral sentiment!
+# """)
 
 
-# Add image
-image = st.image("sentiment.jpeg", width=400)
+# # Add image
+# image = st.image("sentiment.jpeg", width=400)
 
-# Get user input
-text = st.text_input("Type here:")
+# # Get user input
+# text = st.text_input("Type here:")
 
-# Define the CSS style for the app
-st.markdown(
-"""
-<style>
-body {
-    background-color: #f5f5f5;
-}
-h1 {
-    color: #4e79a7;
-}
-</style>
-""",
-unsafe_allow_html=True
-)
+# # Define the CSS style for the app
+# st.markdown(
+# """
+# <style>
+# body {
+#     background-color: #f5f5f5;
+# }
+# h1 {
+#     color: #4e79a7;
+# }
+# </style>
+# """,
+# unsafe_allow_html=True
+# )
 
-# Show sentiment output
-if text:
-    sentiment, score = predict_sentiment(text)
-    if sentiment == "Positive":
-        st.success(f"The sentiment is {sentiment} with a score of {score*100:.2f}%!")
-    elif sentiment == "Negative":
-        st.error(f"The sentiment is {sentiment} with a score of {score*100:.2f}%!")
-    else:
-        st.warning(f"The sentiment is {sentiment} with a score of {score*100:.2f}%!")
+# # Show sentiment output
+# if text:
+#     sentiment, score = predict_sentiment(text)
+#     if sentiment == "Positive":
+#         st.success(f"The sentiment is {sentiment} with a score of {score*100:.2f}%!")
+#     elif sentiment == "Negative":
+#         st.error(f"The sentiment is {sentiment} with a score of {score*100:.2f}%!")
+#     else:
+#         st.warning(f"The sentiment is {sentiment} with a score of {score*100:.2f}%!")
 
 import streamlit as st
 import transformers
@@ -87,13 +87,13 @@ def predict_sentiment(text):
 
     return sentiment, score
 
-# # Setting the page configurations
-# st.set_page_config(
-#     page_title="Sentiment Analysis App",
-#     page_icon=":smile:",
-#     layout="wide",
-#     initial_sidebar_state="auto",
-# )
+# Setting the page configurations
+st.set_page_config(
+    page_title="Sentiment Analysis App",
+    page_icon=":smile:",
+    layout="wide",
+    initial_sidebar_state="auto",
+)
 
 # Add description and title
 st.write("""