Create app.py

app.py

@@ -0,0 +1,46 @@
+from transformers import pipeline
+import gradio as gr
+
+# Initialize the pipeline
+pipe = pipeline("text-classification", model="himanshutitoria/quick-commerce-perishability-model")
+
+# Prediction function
+def predict(text):
+    result = pipe(text)
+    return result[0]["label"]
+
+# Define the interface
+with gr.Blocks() as iface:
+    # Add an image at the top
+    gr.Image(
+        value="top_image.webp",  # Replace with your image URL or file path
+        label="Perishability Tagging",
+        show_label=False,
+    )
+
+    input_textbox = gr.Textbox(
+        label="Enter a Product Name",
+        placeholder="Enter a name here...",
+        interactive=True,
+    )
+    
+    # Add the main Gradio interface
+    with gr.Row():
+        gr.Markdown("# Quick Commerce Perishability Tagging - Zepto")
+   
+    outputs = gr.Textbox(label="Predicted result")
+    gr.Interface(
+        fn=predict,
+        inputs=input_textbox,
+        outputs=outputs,
+        examples=[
+            ["Milk"],
+            ["Perfume"],
+            ["Refined oil"],
+            ["Tata Salt"],
+            ["Cheese"],
+            ["Butterscotch Icecream"],
+            ["Thepla"],
+        ],
+    )
+iface.launch()