Update app.py

app.py

@@ -3,12 +3,12 @@ import gradio as gr
 from transformers import pipeline
 
 # Initialize the sentiment-analysis pipeline
-semantic_analysis = pipeline("sentiment-analysis", model="BAAI/bge-reranker-v2-m3")
+sentiment_analysis = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
 
-# Define a function to analyze text semantics
-def analyze_semantics(input_text):
+# Define a function to analyze text sentiment
+def analyze_sentiment(input_text):
     # Get the result from the pipeline
-    result = semantic_analysis(input_text)
+    result = sentiment_analysis(input_text)
     # Extract label (e.g., Positive/Negative) and confidence score
     label = result[0]['label']
     confidence = round(result[0]['score'] * 100, 2)
@@ -18,11 +18,11 @@ def analyze_semantics(input_text):
 gr.close_all()
 
 Demo = gr.Interface(
-    fn=analyze_semantics,
-    inputs=[gr.Textbox(label="Enter Text for Semantic Analysis", lines=5)],
-    outputs=[gr.Textbox(label="Semantic Analysis Result", lines=2)],
-    title="Semantic Analysis App",
-    description="This application performs semantic analysis to determine the sentiment of the given text."
+    fn=analyze_sentiment,
+    inputs=[gr.Textbox(label="Enter Text for Sentiment Analysis", lines=5)],
+    outputs=[gr.Textbox(label="Sentiment Analysis Result", lines=2)],
+    title="Sentiment Analysis App",
+    description="This application performs sentiment analysis to determine whether the text is positive or negative."
 )
 
 # Launch the app with a public link