Update app.py

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+import torch
+
+import bdh
+from bdh import BDHConfig, BDH
+
+# Device (Spaces usually run on CPU)
+device = torch.device("cpu")
+
+# Small config for live demo (important!)
+config = BDHConfig(
+    n_layer=2,
+    n_embd=128,
+    n_head=4,
+    mlp_internal_dim_multiplier=32,
+    vocab_size=256,
+)
+
+model = BDH(config).to(device)
+model.eval()
+
+@torch.no_grad()
+def generate_text(prompt: str, max_tokens: int = 50):
+    if len(prompt) == 0:
+        return "Please enter a prompt."
+
+    idx = torch.tensor(
+        bytearray(prompt, "utf-8"),
+        dtype=torch.long,
+        device=device
+    ).unsqueeze(0)
+
+    out = model.generate(
+        idx,
+        max_new_tokens=max_tokens,
+        top_k=5
+    )
+
+    return bytes(
+        out.squeeze(0).to(torch.uint8).cpu()
+    ).decode(errors="replace")
+
+
+gr.Interface(
+    fn=generate_text,
+    inputs=[
+        gr.Textbox(label="Prompt"),
+        gr.Slider(10, 100, value=50, step=10, label="Max tokens")
+    ],
+    outputs=gr.Textbox(label="BDH Output"),
+    title="BDH – Beyond Transformer (Live Demo)",
+    description="Inference-only demo of the BDH architecture"
+).launch()