Update app.py

app.py

@@ -47,14 +47,14 @@ def predict(text: str, top_k: int = 5):
         }
     )
 
-    # Assume outputs[0] contains logits
-    logits = outputs[0][0]  # shape: (num_classes,)
-    scores = np.exp(logits) / np.sum(np.exp(logits))  # softmax to probabilities
+    logits = outputs[0][0]  # assume outputs[0] contains logits
+    scores = np.exp(logits) / np.sum(np.exp(logits))  # softmax
 
-    # Top-k results
-    top_indices = np.argsort(scores)[::-1][:top_k]
-    result = [{"label": LABELS[i], "score": float(scores[i])} for i in top_indices]
+    # Top-k, ensure it doesn't exceed LABELS length
+    safe_top_k = min(top_k, len(LABELS))
+    top_indices = np.argsort(scores)[::-1][:safe_top_k]
 
+    result = [{"label": LABELS[i], "score": float(scores[i])} for i in top_indices]
     return result
 
 # -----------------------------
@@ -63,11 +63,11 @@ def predict(text: str, top_k: int = 5):
 iface = gr.Interface(
     fn=predict,
     inputs=[gr.Textbox(lines=2, placeholder="Type your Bengali text here..."),
-            gr.Slider(1, 12, value=5, step=1, label="Top K")],
+            gr.Slider(1, len(LABELS), value=5, step=1, label="Top K")],
     outputs="json",
     title="Intent Router ONNX Model",
     description="Enter Bengali text to get top_k intent predictions"
 )
 
 if __name__ == "__main__":
-    iface.launch(server_name="0.0.0.0", server_port=7860, share=True)
+    iface.launch(server_name="0.0.0.0", server_port=7860)