Create app.py

app.py

@@ -0,0 +1,64 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the pre-trained sentiment analysis model
+sentiment_model = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment")
+
+# Function to analyze sentiment
+def analyze_sentiment(text):
+    # Get sentiment predictions
+    result = sentiment_model(text)
+    label = result[0]['label']
+    score = result[0]['score']
+    
+    # Format the sentiment into human-friendly text
+    label_mapping = {
+        '1 star': 'Very Negative',
+        '2 stars': 'Negative',
+        '3 stars': 'Neutral',
+        '4 stars': 'Positive',
+        '5 stars': 'Very Positive'
+    }
+    sentiment_result = f"**Sentiment**: {label_mapping[label]}\n**Confidence**: {score:.2f}"
+    return sentiment_result
+
+# Custom CSS for appealing colors on dark and light themes
+css = """
+body {background-color: #f4f4f4; font-family: 'Arial'; color: #333;}
+input, textarea {border-radius: 10px; border: 2px solid #999; padding: 10px; background-color: #fff; color: #333;}
+button {background-color: #3498db; color: white; border: none; padding: 10px 20px; border-radius: 10px; cursor: pointer;}
+button:hover {background-color: #2980b9;}
+.output-text {font-size: 18px; color: #333;}
+footer {display: none !important;}
+/* Dark theme */
+@media (prefers-color-scheme: dark) {
+    body {background-color: #2c3e50; color: #ecf0f1;}
+    input, textarea {background-color: #34495e; color: #ecf0f1; border: 2px solid #999;}
+    button {background-color: #2980b9;}
+    button:hover {background-color: #1abc9c;}
+    .output-text {color: #ecf0f1;}
+}
+"""
+
+# Create Gradio interface with enhanced UI and updated description
+interface = gr.Interface(
+    fn=analyze_sentiment,
+    inputs=gr.Textbox(
+        lines=5, 
+        placeholder="Enter a marketplace review or sentence here...",
+        label="Input Review",
+    ),
+    outputs=gr.Markdown(),
+    title="Sentiment Reveal",
+    description=(
+        "Analyze the sentiment of product reviews in English, Dutch, German, French, Italian, and Spanish. Focused Sentiment Analysis for eCommerce."
+    ),
+    examples=[["This product is amazing! I highly recommend it."],
+              ["I'm very disappointed with this purchase."],
+              ["The product was okay, not great but not terrible."]],
+    allow_flagging="never",
+    css=css,
+)
+
+# Launch the app with sharing enabled
+interface.launch(share=True)