add requirements

app.py

@@ -1,17 +1,21 @@
 import gradio as gr
-from transformers import pipeline  # Assuming you're using Hugging Face's transformers library
+from transformers import pipeline
 
-# Load your pipeline
-pipe = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")
+# Load a sentiment analysis pipeline from Hugging Face
+sentiment_pipeline = pipeline("sentiment-analysis")
 
-# Define the Gradio interface function
-def classify_text(text):
-    result = pipe(text)
-    return result[0]["label"], result[0]["score"]
+def analyze_sentiment(text):
+    result = sentiment_pipeline(text)
+    return result[0]["label"]  # Return the sentiment label (positive, negative, neutral)
 
-# Create the Gradio interface
+# Create a Gradio interface
 iface = gr.Interface(
-    fn=classify_text,
-    inputs=[gr.Textbox(label="Enter text")],
-    outputs=[gr.Label(label="Label"), gr.Number(label="Confidence")]
-)
+    fn=analyze_sentiment,
+    inputs=[gr.Textbox(label="Enter text here")],
+    outputs=[gr.Label(label="Sentiment")],
+    title="Sentiment Analyzer",
+    description="Enter a text to analyze its sentiment",
+)
+
+# Launch the Gradio interface
+iface.launch()