Update app.py

app.py

@@ -1,9 +1,24 @@
+import os
 import gradio as gr
 from crop_health_monitor.inference.inference import load_disease_pipeline, diagnose
 
+"""
+Step 5: Gradio demo for disease-only model with example images
+"""
 # load your published model or local checkpoint
 pipe = load_disease_pipeline("CZerion/crop_health_monitor")
 
+# Path to examples folder
+examples = [
+    ["Plants/Unhealthy_crop_1.jpg"],
+    ["Plants/Unhealthy_crop_2.jpg"],
+    ["Plants/Unhealthy_crop_3.jpg"],
+    ["Plants/Unhealthy_crop_4.jpg"],
+    ["Plants/Unhealthy_crop_5.jpg"],
+    ["Plants/Healthy_crop_1.jpg"],
+    ["Plants/Healthy_crop_2.jpg"]
+]
+
 iface = gr.Interface(
     fn=lambda img: diagnose(img, pipe),
     inputs=gr.Image(type="pil", label="Upload Leaf Image"),
@@ -12,7 +27,9 @@ iface = gr.Interface(
         gr.Textbox(label="Care Advice")
     ],
     title="Plant Disease Monitor",
-    description="Upload a crop leaf photo to detect diseases using a fine-tuned model."
+    description="Upload a crop leaf photo to detect diseases using a fine-tuned model.",
+    examples=examples,
+    allow_flagging="never"
 )
 
 if __name__ == "__main__":