Files
neuron-tai/packages/node/meshnet_node/startup.py
Dobromir Popov 0be35d257b fix: robust tracker reconnect — re-register proactively after outage
Previous logic caught 404 on heartbeat and re-registered, but the re-
registration failed silently if the tracker wasn't fully ready yet.

New approach: after any connection-refused streak, the heartbeat loop
switches to re-registration mode and keeps retrying until the tracker
accepts the registration (instead of sending heartbeats into a fresh
registry that doesn't know this node). Falls back to the 404 path for
the case where a node is purged without a full tracker restart.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-30 02:12:06 +03:00

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"""Full node startup sequence — self-configuring, non-interactive."""
from __future__ import annotations
import json
import socket
import sys
import threading
import time
import urllib.error
import urllib.parse
import urllib.request
from pathlib import Path
from typing import Any
from .downloader import compute_shard_checksum, download_shard
from .hardware import detect_hardware
from .server import StubNodeServer
from .torch_server import TorchNodeServer
from .wallet import load_or_create_wallet
def _post_json(url: str, payload: dict, timeout: float = 10.0) -> dict:
data = json.dumps(payload).encode()
req = urllib.request.Request(
url, data=data, headers={"Content-Type": "application/json"}, method="POST"
)
with urllib.request.urlopen(req, timeout=timeout) as r:
return json.loads(r.read())
def _get_json(url: str, timeout: float = 10.0) -> dict:
with urllib.request.urlopen(url, timeout=timeout) as r:
return json.loads(r.read())
def _start_heartbeat(
tracker_url: str,
node_id: str,
register_payload: dict,
interval: float = 20.0,
) -> threading.Thread:
"""Daemon thread: sends heartbeats and re-registers automatically after tracker restarts."""
def _reregister() -> bool:
nonlocal node_id
try:
resp = _post_json(f"{tracker_url}/v1/nodes/register", register_payload)
node_id = resp.get("node_id", node_id)
return True
except Exception:
return False
def _loop() -> None:
nonlocal node_id
hb_url = f"{tracker_url}/v1/nodes/{node_id}/heartbeat"
outage_streak = 0 # consecutive intervals where tracker was unreachable
while True:
time.sleep(interval)
if outage_streak > 0:
# Tracker was down — attempt re-registration first (it may have restarted
# with a clean slate and won't know this node).
if _reregister():
hb_url = f"{tracker_url}/v1/nodes/{node_id}/heartbeat"
print(f" [node] re-registered after outage — node ID: {node_id}", flush=True)
outage_streak = 0
else:
outage_streak += 1
if outage_streak <= 3 or outage_streak % 10 == 0:
print(
f" [node] WARNING: tracker still unreachable "
f"({outage_streak * interval:.0f}s)",
flush=True,
)
continue
try:
_post_json(hb_url, {})
except urllib.error.HTTPError as exc:
if exc.code == 404:
# Node was purged (e.g. long gap before restart noticed) — re-register now.
print(" [node] tracker lost registration — re-registering...", flush=True)
if _reregister():
hb_url = f"{tracker_url}/v1/nodes/{node_id}/heartbeat"
print(f" [node] re-registered — node ID: {node_id}", flush=True)
else:
print(" [node] WARNING: re-registration failed", flush=True)
outage_streak = 1
else:
print(f" [node] WARNING: heartbeat failed ({exc.code}): {exc}", flush=True)
except Exception as exc:
outage_streak = 1
print(f" [node] WARNING: tracker unreachable: {exc}", flush=True)
t = threading.Thread(target=_loop, daemon=True, name="heartbeat")
t.start()
return t
def run_startup(
tracker_url: str,
port: int = 0,
model: str = "stub-model",
model_id: str | None = None,
shard_start: int | None = None,
shard_end: int | None = None,
quantization: str = "bfloat16",
wallet_path: Path | None = None,
cache_dir: Path | None = None,
host: str = "127.0.0.1",
advertise_host: str | None = None,
contracts: Any | None = None,
) -> StubNodeServer | TorchNodeServer:
"""Execute the full startup sequence and return a running node server.
Steps (all non-interactive):
1. Detect GPU / hardware profile
2. Load or generate Solana wallet keypair
3. Query tracker for optimal shard assignment
4. Download (or stub) the assigned shard from peers, then HuggingFace
5. Start local HTTP server
6. Register with tracker
Prints a compact status summary on completion.
"""
tracker_url = tracker_url.rstrip("/")
# 1. Hardware detection
print("Detecting hardware...", flush=True)
hw = detect_hardware()
device: str = hw["device"]
gpu_name: str | None = hw.get("gpu_name")
vram_mb: int = hw.get("vram_mb", 0)
if device == "cpu":
print(" WARNING: No CUDA GPU detected — running in CPU mode", flush=True)
else:
print(f" GPU: {gpu_name} ({vram_mb} MB VRAM)", flush=True)
# 2. Wallet
print("Loading wallet...", flush=True)
wallet_kwargs: dict = {}
if wallet_path is not None:
wallet_kwargs["path"] = wallet_path
_, _, address = load_or_create_wallet(**wallet_kwargs)
print(f" Wallet: {address}", flush=True)
probationary_line = _probationary_status_line(contracts, address)
if probationary_line is not None:
print(f" {probationary_line}", flush=True)
if model_id: # treat "" the same as None — no explicit model given
# 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."
)
# When no explicit shard range given, ask the tracker if there's a gap for this model.
if shard_start is None and shard_end is None:
try:
qs = urllib.parse.urlencode({
"device": device, "vram_mb": vram_mb, "hf_repo": model_id,
})
net_asgn = _get_json(f"{tracker_url}/v1/network/assign?{qs}", timeout=5.0)
if net_asgn.get("hf_repo") == model_id and net_asgn.get("gap_found"):
shard_start = net_asgn["shard_start"]
shard_end = net_asgn["shard_end"]
print(
f" Tracker found uncovered shard: "
f"layers {shard_start}{shard_end} (of {detected})",
flush=True,
)
except Exception:
pass # No other nodes registered yet — default to full model below
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,
port=port,
model_id=model_id,
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}"
# Register with tracker so other nodes can auto-join this model.
total_layers = getattr(node.backend, "total_layers", None)
reg_payload = {
"endpoint": endpoint,
"model": model_id.split("/")[-1],
"hf_repo": model_id,
"num_layers": total_layers,
"shard_start": shard_start,
"shard_end": shard_end,
"hardware_profile": hw,
"wallet_address": address,
"quantization": quantization,
"score": 1.0,
"tracker_mode": (shard_start == 0),
}
try:
reg_resp = _post_json(f"{tracker_url}/v1/nodes/register", reg_payload)
node_id = reg_resp.get("node_id", "?")
print(f" Registered with tracker — node ID: {node_id}", flush=True)
_start_heartbeat(tracker_url, node_id, reg_payload)
except Exception as exc:
print(f" Warning: tracker registration failed: {exc}", flush=True)
print(
f"\n{'=' * 32}\n"
f"meshnet-node ready\n"
f" Wallet: {address}\n"
f" Model ID: {model_id}\n"
f" Shard: {shard_label}\n"
f" Quantization: {quantization}\n"
f" Endpoint: {endpoint}\n"
f" Hardware: {device.upper()}\n"
f"{'=' * 32}",
flush=True,
)
return node
if shard_start is not None or shard_end is not None:
raise ValueError("--shard-start / --shard-end require --model-id")
# 3a. Auto-join: query tracker for network-wide HF model assignment.
print("Querying tracker for network assignment...", flush=True)
assign_qs = urllib.parse.urlencode({"device": device, "vram_mb": vram_mb})
net_assignment: dict = {}
try:
net_assignment = _get_json(f"{tracker_url}/v1/network/assign?{assign_qs}")
except Exception as exc:
print(f" (auto-join unavailable: {exc})", flush=True)
assigned_hf_repo: str | None = net_assignment.get("hf_repo")
_gap_found: bool = bool(net_assignment.get("gap_found", False))
if assigned_hf_repo and _gap_found:
assigned_shard_start: int = net_assignment["shard_start"]
assigned_shard_end: int = net_assignment["shard_end"]
assigned_num_layers: int = net_assignment["num_layers"]
print(
f" Assigned: {assigned_hf_repo} "
f"layers {assigned_shard_start}{assigned_shard_end} "
f"(of {assigned_num_layers})",
flush=True,
)
print("Loading real PyTorch model shard...", flush=True)
node = TorchNodeServer(
host=host,
port=port,
model_id=assigned_hf_repo,
shard_start=assigned_shard_start,
shard_end=assigned_shard_end,
quantization=quantization,
tracker_url=tracker_url,
)
actual_port = node.start()
public_host = advertise_host or (socket.getfqdn() if host == "0.0.0.0" else host)
endpoint = f"http://{public_host}:{actual_port}"
auto_reg_payload = {
"endpoint": endpoint,
"model": assigned_hf_repo.split("/")[-1],
"hf_repo": assigned_hf_repo,
"num_layers": assigned_num_layers,
"shard_start": assigned_shard_start,
"shard_end": assigned_shard_end,
"hardware_profile": hw,
"wallet_address": address,
"quantization": quantization,
"score": 1.0,
"tracker_mode": (assigned_shard_start == 0),
}
try:
reg_resp = _post_json(f"{tracker_url}/v1/nodes/register", auto_reg_payload)
node_id = reg_resp.get("node_id", "?")
print(f" Registered with tracker — node ID: {node_id}", flush=True)
_start_heartbeat(tracker_url, node_id, auto_reg_payload)
except Exception as exc:
print(f" Warning: tracker registration failed: {exc}", flush=True)
shard_count = assigned_shard_end - assigned_shard_start + 1
print(
f"\n{'=' * 32}\n"
f"meshnet-node ready (auto-joined)\n"
f" Wallet: {address}\n"
f" Model ID: {assigned_hf_repo}\n"
f" Shard: layers {assigned_shard_start}{assigned_shard_end} "
f"({shard_count} of {assigned_num_layers})\n"
f" Quantization: {quantization}\n"
f" Endpoint: {endpoint}\n"
f" Hardware: {device.upper()}\n"
f"{'=' * 32}",
flush=True,
)
return node
# 3b. Shard assignment from tracker (stub-model / preset-based path)
print("Querying tracker for shard assignment...", flush=True)
assign_qs = urllib.parse.urlencode({
"model": model,
"device": device,
"vram_mb": vram_mb,
})
try:
assignment = _get_json(f"{tracker_url}/v1/nodes/assign?{assign_qs}")
except urllib.error.URLError as exc:
print(f" ERROR: Cannot reach tracker at {tracker_url}: {exc}", file=sys.stderr, flush=True)
raise
shard_start: int = assignment["shard_start"]
shard_end: int = assignment["shard_end"]
assigned_model: str = assignment.get("model", model)
hf_repo: str | None = assignment.get("hf_repo")
peers: list[dict] = assignment.get("peers", [])
print(f" Shard: layers {shard_start}-{shard_end} of {assigned_model}", flush=True)
# 4. Download shard
print("Downloading shard...", flush=True)
dl_kwargs: dict = {}
if cache_dir is not None:
dl_kwargs["cache_dir"] = cache_dir
if hf_repo is not None:
dl_kwargs["hf_repo"] = hf_repo
if peers:
dl_kwargs["peers"] = peers
shard_path = download_shard(assigned_model, shard_start, shard_end, **dl_kwargs)
shard_checksum = compute_shard_checksum(shard_path)
print(f" Cached at: {shard_path}", flush=True)
# 5. Start HTTP server
is_last = shard_end >= assignment.get("model_layers_end", shard_end)
node = StubNodeServer(
host=host,
port=port,
shard_start=shard_start,
shard_end=shard_end,
is_last_shard=is_last,
model=assigned_model,
shard_path=shard_path,
)
actual_port = node.start()
public_host = advertise_host or (socket.getfqdn() if host == "0.0.0.0" else host)
endpoint = f"http://{public_host}:{actual_port}"
# 6. Register with tracker
print("Registering with tracker...", flush=True)
try:
reg_resp = _post_json(
f"{tracker_url}/v1/nodes/register",
{
"endpoint": endpoint,
"model": assigned_model,
"shard_start": shard_start,
"shard_end": shard_end,
"shard_checksum": shard_checksum,
"hardware_profile": hw,
"wallet_address": address,
"score": 1.0,
},
)
node_id: str = reg_resp["node_id"]
except Exception:
node.stop()
raise
# Status summary
hw_str = device.upper()
if gpu_name:
hw_str += f" ({gpu_name}, {vram_mb} MB)"
print(
f"\n{'=' * 32}\n"
f"meshnet-node ready\n"
f" Wallet: {address}\n"
f" Shard: layers {shard_start}-{shard_end} ({assigned_model})\n"
f" Endpoint: {endpoint}\n"
f" Node ID: {node_id}\n"
f" Hardware: {hw_str}\n"
f"{'=' * 32}",
flush=True,
)
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
remaining = contracts.registry.probationary_jobs_remaining(wallet_address)
if remaining <= 0:
return "Probationary period complete: earning enabled"
suffix = "job" if remaining == 1 else "jobs"
return f"Probationary period: {remaining} {suffix} remaining before earning"