Create inference/inference.py

inference/inference.py

@@ -0,0 +1,18 @@
+from transformers import pipeline
+
+def load_disease_pipeline(model_id):
+    return pipeline(
+        task="image-classification",
+        model=model_id,
+        top_k=3
+    )
+
+def diagnose(image, pipe):
+    results = pipe(image)
+    preds = [f"{r['label']} ({r['score']*100:.1f}%)" for r in results]
+    advice = (
+        "No disease detected—maintain standard crop care." 
+        if "healthy" in results[0]['label'].lower() 
+        else f"Disease detected: {results[0]['label']}. Apply targeted treatment."
+    )
+    return preds, advice