Add app.py

app.py

@@ -0,0 +1,34 @@
+# samples = [
+#     "The service at the restaurant was really impressive",
+#     "What is the status of my order number #1234?",
+#     "I have a proposal for a new feature in your app",
+#     "My package arrived late and the item was damaged",
+#     "Your team is doing an excellent job",
+#     "Could you help clarify the specifications of this product?",
+#     "I'm extremely dissatisfied with the customer service",
+#     "Have you thought about offering more plant-based options on your menu?",
+#     "I really appreciate the speedy response from your customer service team",
+#     "I enjoy using your application, great work"
+# ]
+%pip install transformers
+
+from transformers import pipeline
+import gradio as gr
+
+classifier = pipeline(
+    "zero-shot-classification",
+    model="facebook/bart-large-mnli",
+)
+
+candidate_labels = ["opinion", "complaint", "query", "suggestion", "appreciation"]
+
+def analyze_sentiment(text):
+    for text in texts:
+        # Classify the text
+        label = classifier(text, candidate_labels)
+        
+        # Print the text and its corresponding label
+        print("Text: " + text+ ", Label: " + label)
+
+demo = gr.Interface(fn=analyze_sentiment, inputs="text", outputs="text")
+demo.launch()