inference working

packages/node/meshnet_node/startup.py

@@ -84,7 +84,19 @@ def run_startup(
     if probationary_line is not None:
         print(f"  {probationary_line}", flush=True)
 
-    if model_id is not None and shard_start is not None and shard_end is not None:
+    if model_id is not None:
+        # Auto-detect shard range from model config if not explicitly provided
+        if shard_start is None or shard_end is None:
+            detected = _detect_num_layers(model_id)
+            if detected is None:
+                raise ValueError(
+                    f"Could not read num_hidden_layers from {model_id} config. "
+                    "Pass --shard-start and --shard-end explicitly."
+                )
+            shard_start = shard_start if shard_start is not None else 0
+            shard_end = shard_end if shard_end is not None else detected - 1
+            print(f"  Auto-detected {detected} layers → shard {shard_start}–{shard_end}", flush=True)
+
         print("Loading real PyTorch model shard...", flush=True)
         node = TorchNodeServer(
             host=host,
@@ -93,8 +105,15 @@ def run_startup(
             shard_start=shard_start,
             shard_end=shard_end,
             quantization=quantization,
+            tracker_url=tracker_url,
         )
         actual_port = node.start()
+        total_layers = getattr(node.backend, "total_layers", None)
+        if isinstance(total_layers, int) and total_layers > 0:
+            layer_count = shard_end - shard_start + 1
+            shard_label = f"layers {shard_start}–{shard_end}; {layer_count} of {total_layers}"
+        else:
+            shard_label = f"layers {shard_start}–{shard_end}"
         public_host = advertise_host or (socket.getfqdn() if host == "0.0.0.0" else host)
         endpoint = f"http://{public_host}:{actual_port}"
         print(
@@ -102,7 +121,7 @@ def run_startup(
             f"meshnet-node ready\n"
             f"  Wallet:       {address}\n"
             f"  Model ID:     {model_id}\n"
-            f"  Shard:        layers {shard_start}-{shard_end}\n"
+            f"  Shard:        {shard_label}\n"
             f"  Quantization: {quantization}\n"
             f"  Endpoint:     {endpoint}\n"
             f"  Hardware:     {device.upper()}\n"
@@ -110,8 +129,8 @@ def run_startup(
             flush=True,
         )
         return node
-    if model_id is not None or shard_start is not None or shard_end is not None:
-        raise ValueError("--model-id, --shard-start, and --shard-end must be provided together")
+    if shard_start is not None or shard_end is not None:
+        raise ValueError("--shard-start / --shard-end require --model-id")
 
     # 3. Shard assignment from tracker
     print("Querying tracker for shard assignment...", flush=True)
@@ -201,6 +220,17 @@ def run_startup(
     return node
 
 
+def _detect_num_layers(model_id: str) -> int | None:
+    """Fetch num_hidden_layers from HuggingFace model config (downloads ~1 KB config.json only)."""
+    try:
+        from transformers import AutoConfig  # type: ignore[import]
+        cfg = AutoConfig.from_pretrained(model_id)
+        return int(cfg.num_hidden_layers)
+    except Exception as exc:
+        print(f"  Warning: could not read model config from HF: {exc}", flush=True)
+        return None
+
+
 def _probationary_status_line(contracts: Any | None, wallet_address: str) -> str | None:
     if contracts is None:
         return None