Create app.py

app.py

@@ -0,0 +1,31 @@
+import gradio as gr
+import jax
+import numpy as np
+# Import your JAX model here
+
+def predict(x: float, y: float):
+    """
+    Replace this with your actual JAX model inference
+    """
+    # This is just a placeholder - replace with your model
+    return {
+        "prediction": float(np.sin(x * 3.14) * np.cos(y * 3.14)),
+        "x": x,
+        "y": y
+    }
+
+# Create Gradio interface with API endpoint
+demo = gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.Number(label="X coordinate", minimum=0, maximum=1),
+        gr.Number(label="Y coordinate", minimum=0, maximum=1)
+    ],
+    outputs=gr.JSON(),
+    title="Research Visualization ML Model",
+    description="Click on the square to generate predictions",
+    allow_flagging="never"
+)
+
+# Enable API endpoint
+demo.launch()