Update app.py

app.py

@@ -1,2 +1,25 @@
 from datasets import load_dataset
-dataset = load_dataset("juppy44/gbif-plants-raw", split="train", streaming=True)
+dataset = load_dataset("juppy44/gbif-plants-raw", split="train", streaming=True)
+
+import gradio as gr
+from datasets import load_dataset
+from sklearn.model_selection import train_test_split
+import numpy as np
+
+# Load a small sample (this is conceptual - you'd need to implement proper sampling)
+dataset = load_dataset("juppy44/gbif-plants-raw", split="train[:1000]", streaming=True)
+
+# Your ML model training and inference code here
+def classify_plant(image):
+    # Your classification logic
+    return "Species prediction"
+
+demo = gr.Interface(
+    fn=classify_plant,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Plant Species Classifier"
+)
+
+if __name__ == "__main__":
+    demo.launch()