Update app.py

app.py

@@ -1,23 +1,19 @@
+# app.py
 import streamlit as st
 from transformers import pipeline
 
-# Load pre-trained question-answering model from Hugging Face Hub
-qa_pipe = pipeline("question-answering")
+# Load sentiment analysis pipeline
+classifier = pipeline("sentiment-analysis")
 
-# Function to process user query and return answer
-def answer_question(query):
-  context = "This is a large corpus of text used for training the model (replace with your actual context if needed)"  # Replace with relevant context
-  qa_result = qa_pipe(question=query, context=context)
-  return qa_result["answer"]
+def analyze_sentiment(text):
+  """Analyzes the sentiment of a given text."""
+  result = classifier(text)
+  return result[0]['label'], result[0]['score']
 
-def main():
-  st.title("Question & Answer Chatbot (Limited Functionality)")
-  st.write("This chatbot uses a pre-trained model from Hugging Face Hub. It might not have the same capabilities as a large language model.")
+st.title("Sentiment Analysis App")
 
-  user_query = st.text_input("Ask your question:")
-  if user_query:
-    answer = answer_question(user_query)
-    st.write(f"Answer: {answer}")
+text = st.text_area("Enter your text here:")
 
-if __name__ == "__main__":
-  main()
+if st.button("Analyze"):
+  label, score = analyze_sentiment(text)
+  st.success(f"Sentiment: {label}, Score: {score}")