feat: tracker-as-first-layer-node inference entry point (US-014)

- Tracker: add GET /v1/tracker-nodes/<model> returning nodes registered
  with tracker_mode=true whose shard_start matches the model's first layer
- Node: StubNodeServer and TorchNodeServer accept tracker_mode/tracker_url;
  when tracker_mode=True (or auto-detected via shard_start==0 for Torch),
  /v1/chat/completions is served alongside /forward
- TorchNodeServer: full pipeline implementation — encode_prompt → route
  selection via tracker → binary forward through remaining hops → decode
- Gateway: _handle_chat_completions checks _get_tracker_nodes() first and
  proxies round-robin to tracker-nodes; falls back to existing direct
  pipeline when none found (preserves all US-005 backward compat)
- CLI: --tracker-mode and --tracker-url flags added to meshnet-node start
- Test: two stub tracker-nodes + two mid-shard nodes for gpt2; 10 requests;
  round-robin 5/5 split verified; all OpenAI-format responses validated
- All 78 tests pass

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

packages/node/meshnet_node/cli.py

@@ -39,6 +39,16 @@ def main() -> None:
         "--advertise-host",
         help="Reachable host/IP to advertise to the tracker (defaults to FQDN when binding 0.0.0.0)",
     )
+    start_cmd.add_argument(
+        "--tracker-mode",
+        action="store_true",
+        help="Enable client-facing /v1/chat/completions (auto-enabled when shard-start=0)",
+    )
+    start_cmd.add_argument(
+        "--tracker-url",
+        default=None,
+        help="Tracker URL for route selection (used in tracker mode)",
+    )
 
     args = parser.parse_args()