fix inference

packages/node/meshnet_node/startup.py

@@ -204,7 +204,7 @@ def run_startup(
             tracker_url=tracker_url,
         )
         actual_port = node.start()
-        total_layers = getattr(node.backend, "total_layers", None)
+        total_layers = getattr(getattr(node, "backend", None), "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}"
@@ -213,7 +213,7 @@ def run_startup(
         public_host = advertise_host or (socket.getfqdn() if host == "0.0.0.0" else host)
         endpoint = f"http://{public_host}:{actual_port}"
         # Register with tracker so other nodes can auto-join this model.
-        total_layers = getattr(node.backend, "total_layers", None)
+        total_layers = getattr(getattr(node, "backend", None), "total_layers", None)
         reg_payload = {
             "endpoint": endpoint,
             "model": model_id.split("/")[-1],

packages/node/meshnet_node/torch_server.py

@@ -246,6 +246,11 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
         # but correct. Each step: head encodes current sequence → forwards through route
         # → tail returns the next token string → append → repeat.
         remaining_route = self._get_remaining_route(model_name)
+        print(
+            f"  [node] chat route model={model_name!r} max_tokens={max_tokens} "
+            f"downstream={remaining_route}",
+            flush=True,
+        )
         if not remaining_route:
             self._send_openai_response(
                 "error: no downstream route — check tracker connectivity",
@@ -300,7 +305,9 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
             try:
                 route = json.loads(injected)
                 if isinstance(route, list):
-                    return [str(ep) for ep in route]
+                    resolved = [str(ep) for ep in route]
+                    print(f"  [node] using injected downstream route: {resolved}", flush=True)
+                    return resolved
             except (json.JSONDecodeError, TypeError):
                 pass
 
@@ -315,7 +322,9 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
                 route_resp = json.loads(r.read())
             route = route_resp.get("route", [])
             own_port = server.server_address[1]
-            return [ep for ep in route if not ep.rstrip("/").endswith(f":{own_port}")]
+            resolved = [ep for ep in route if not ep.rstrip("/").endswith(f":{own_port}")]
+            print(f"  [node] tracker downstream route: {resolved}", flush=True)
+            return resolved
         except Exception as exc:
             print(f"  [node] WARNING: route lookup failed for {route_model!r}: {exc}", flush=True)
             return []
@@ -346,6 +355,7 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
         current_pos = pos_ids
 
         for hop_index, node_url in enumerate(route):
+            print(f"  [node] pipeline hop {hop_index}: {node_url}", flush=True)
             headers: dict[str, str] = {
                 "Content-Type": "application/octet-stream",
                 "X-Meshnet-Wire": _WIRE_VERSION,
@@ -371,12 +381,15 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
                     resp_body = r.read()
                     resp_headers = {k.lower(): v for k, v in r.headers.items()}
             except Exception as exc:
+                print(f"  [node] pipeline hop {hop_index} failed at {node_url}: {exc}", flush=True)
                 return f"pipeline error at {node_url}: {exc}"
             content_type = resp_headers.get("content-type", "")
             if "application/json" in content_type:
                 try:
                     data = json.loads(resp_body)
-                    return str(data.get("text", ""))
+                    text = str(data.get("text", ""))
+                    print(f"  [node] pipeline hop {hop_index} returned text={text!r}", flush=True)
+                    return text
                 except json.JSONDecodeError:
                     return resp_body.decode("utf-8", errors="replace")
             # Binary activation — update and forward to next node