mirror of
https://github.com/allaunthefox/Research-Stack.git
synced 2026-07-31 03:05:21 +00:00
cleanup(ene): load node list from nodes.yaml instead of hardcoded hostnames
This commit is contained in:
parent
510ff80d9f
commit
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1 changed files with 78 additions and 327 deletions
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@ -1,361 +1,112 @@
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#!/usr/bin/env python3
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"""
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deploy_ene_full_mesh.py — Deploy ENE to Full Tailscale Mesh
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"""deploy_ene_full_mesh.py — Deploy ENE to Full Tailscale Mesh (legacy shim).
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Uses ENE's self-replication capability to:
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1. Deploy to remaining 3 nodes (ip-172-31-25-81, netcup-router, racknerd-510bd9c)
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2. Enable full mesh monitoring
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3. Start distributed load balancing across all 6 nodes
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4. Begin utilizing idle capacity (36 cores, 72GB RAM)
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Cleanups:
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- Removed hardcoded node lists; reads nodes from 4-Infrastructure/auto/config/nodes.yaml.
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NOTE:
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- This script still references deprecated Python ENE controller surfaces.
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- Treat as an orchestration stub pending the Rust ENE crate.
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"""
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import subprocess
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from __future__ import annotations
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import argparse
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import json
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import time
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from pathlib import Path
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from typing import List, Dict, Any
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from typing import Any, Dict
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# Import ENE infrastructure
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import sys
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sys.path.insert(0, str(Path(__file__).parent.parent.parent / "4-Infrastructure" / "infra"))
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# DEPRECATED: Python ENE is replaced by Rust (1-Distributed-Systems/ene/src/).
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# Use the Rust crate instead: `cargo run --manifest-path 1-Distributed-Systems/ene/Cargo.toml`
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try:
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from ene_distributed_node import ENEMeshController, ENEDistributedNode # type: ignore
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from ene_distributed_node import ENEMeshController # type: ignore
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except ImportError:
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ENEMeshController = None
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ENEDistributedNode = None
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from ene_cloud_credential_manager import ENETopologicalStorage
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def _load_nodes_inventory(path: Path) -> Dict[str, Any]:
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try:
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import yaml # type: ignore
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except ImportError as exc:
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raise RuntimeError("nodes.yaml parsing requires PyYAML (pip install pyyaml)") from exc
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data = yaml.safe_load(path.read_text(encoding="utf-8"))
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if not isinstance(data, dict) or "nodes" not in data:
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raise ValueError(f"Invalid nodes inventory file: {path}")
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return data
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class FullMeshDeployment:
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"""Deploy ENE across full Tailscale mesh and activate distributed workloads."""
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def __init__(self):
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def __init__(self, inventory_path: Path):
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if ENEMeshController is None:
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raise RuntimeError(
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"Python ENE mesh controller is removed; use the Rust ENE crate under "
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"1-Distributed-Systems/ene instead."
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"Python ENE mesh controller is removed; use the Rust ENE crate under 1-Distributed-Systems/ene instead."
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)
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self.inventory_path = inventory_path
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self.inventory = _load_nodes_inventory(inventory_path)
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self.controller = ENEMeshController()
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self.mesh_nodes: Dict[str, Any] = {}
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self.target_nodes = [
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"ip-172-31-25-81", # AWS node
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"netcup-router", # Netcup VPS
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"racknerd-510bd9c" # Racknerd VPS
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]
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def step1_spawn_existing_nodes(self) -> Dict[str, Any]:
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"""Step 1: Spawn ENE on existing nodes (qfox, architect, judge)."""
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print("\n[STEP 1] Spawning ENE on existing nodes...")
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existing = {
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"qfox": {"cpu": 16, "ram": 32, "storage": 1000, "gpu": 1},
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"architect": {"cpu": 8, "ram": 16, "storage": 500, "gpu": 0},
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"judge": {"cpu": 4, "ram": 8, "storage": 200, "gpu": 0}
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}
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for hostname, specs in existing.items():
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node = self.controller.spawn_node(f"ene_{hostname}")
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self.mesh_nodes[hostname] = {
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"node": node,
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"specs": specs,
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"status": "active"
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}
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print(f" ✅ {hostname}: {specs['cpu']} cores, {specs['ram']}GB RAM")
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return {
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"step": 1,
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"nodes_spawned": len(existing),
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"total_cores": sum(n["specs"]["cpu"] for n in self.mesh_nodes.values()),
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"total_ram": sum(n["specs"]["ram"] for n in self.mesh_nodes.values())
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}
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def step2_deploy_to_new_nodes(self) -> Dict[str, Any]:
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"""Step 2: Auto-replicate ENE to remaining 3 nodes."""
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print("\n[STEP 2] Deploying ENE to remaining nodes via auto-replication...")
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# Get first node to act as replication source
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def step1_spawn_inventory_nodes(self) -> Dict[str, Any]:
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print("\n[STEP 1] Spawning ENE nodes from inventory...")
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nodes = self.inventory.get("nodes", {})
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spawned = 0
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for node_id in sorted(nodes.keys()):
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node = self.controller.spawn_node(f"ene_{node_id}")
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self.mesh_nodes[node_id] = {"node": node, "status": "active"}
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spawned += 1
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print(f" ✅ {node_id}")
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return {"step": 1, "nodes_spawned": spawned}
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def step2_auto_replicate(self) -> Dict[str, Any]:
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print("\n[STEP 2] Auto-replication (stub)...")
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if not self.mesh_nodes:
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return {"step": 2, "error": "no nodes spawned"}
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source_node = list(self.mesh_nodes.values())[0]["node"]
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deployed = []
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failed = []
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new_specs = {
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"ip-172-31-25-81": {"cpu": 2, "ram": 4, "storage": 100, "gpu": 0},
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"netcup-router": {"cpu": 4, "ram": 8, "storage": 500, "gpu": 0},
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"racknerd-510bd9c": {"cpu": 2, "ram": 4, "storage": 100, "gpu": 0}
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}
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for hostname in self.target_nodes:
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print(f"\n Deploying to {hostname}...")
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for node_id, data in self.mesh_nodes.items():
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remote = data["node"]
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try:
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# Simulate SSH/remote deployment
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# In production, this would:
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# 1. SSH to remote node
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# 2. Copy ENE binary
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# 3. Start ENE service
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# 4. Join mesh
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# Simulate replication
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time.sleep(0.5) # Replication time
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# Spawn remote node in controller
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remote_node = self.controller.spawn_node(f"ene_{hostname}")
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# Trigger auto-replication from source
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remote_node.auto_replicate([source_node.node_id])
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self.mesh_nodes[hostname] = {
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"node": remote_node,
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"specs": new_specs[hostname],
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"status": "active"
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}
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deployed.append(hostname)
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print(f" ✅ Deployed: {new_specs[hostname]['cpu']} cores, {new_specs[hostname]['ram']}GB RAM")
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time.sleep(0.1)
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remote.auto_replicate([source_node.node_id])
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deployed.append(node_id)
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except Exception as e:
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failed.append((hostname, str(e)))
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print(f" ❌ Failed: {e}")
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return {
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"step": 2,
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"deployed": deployed,
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"failed": failed,
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"deployment_rate": len(deployed) / len(self.target_nodes) * 100
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}
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def step3_enable_gossip_mesh(self) -> Dict[str, Any]:
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"""Step 3: Enable gossip protocol across full mesh."""
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print("\n[STEP 3] Enabling gossip protocol across 6-node mesh...")
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gossip_count = 0
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for hostname, data in self.mesh_nodes.items():
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node = data["node"]
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# Create discovery gossip
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gossip = node.create_gossip("discovery", {
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"node_id": node.node_id,
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"hostname": hostname,
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"resources": data["specs"],
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"capabilities": ["storage", "compute", "relay"]
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})
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# Broadcast to mesh
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node.gossip_to_peers(gossip)
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gossip_count += 1
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print(f" 📡 {hostname}: gossip broadcast")
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# Calculate mesh health
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total_nodes = len(self.mesh_nodes)
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healthy_nodes = sum(1 for n in self.mesh_nodes.values() if n["status"] == "active")
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return {
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"step": 3,
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"gossip_messages": gossip_count,
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"mesh_size": total_nodes,
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"healthy_nodes": healthy_nodes,
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"mesh_status": "healthy" if healthy_nodes == total_nodes else "degraded"
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}
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def step4_distribute_credentials(self) -> Dict[str, Any]:
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"""Step 4: Distribute Google Drive credentials to all nodes."""
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print("\n[STEP 4] Distributing GDrive credentials to all 6 nodes...")
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# Get first node's credential manager
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first_node = list(self.mesh_nodes.values())[0]["node"]
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# Store credential in first node
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# (This would normally be done via the ENE API)
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# Distribute to other nodes via gossip
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cred_gossip = first_node.create_gossip("credential_sync", {
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"credential_id": "cred_gdrive_mesh",
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"provider": "gdrive",
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"fragment_shards": 6, # One shard per node
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"access_level": "RESTRICTED"
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})
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first_node.gossip_to_peers(cred_gossip)
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print(f" 🔐 Credential distributed to {len(self.mesh_nodes)} nodes")
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print(f" 🔐 Shamir shards: 6 (one per node)")
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print(f" 🔐 Consensus required for rotation")
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return {
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"step": 4,
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"credential_shards": len(self.mesh_nodes),
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"consensus_threshold": "2/3 majority",
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"distribution": "shamir-secret-sharing"
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}
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def step5_activate_load_balancing(self) -> Dict[str, Any]:
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"""Step 5: Activate distributed load balancing."""
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print("\n[STEP 5] Activating distributed load balancing...")
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# Create ENE topological storage interface
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ene_storage = ENETopologicalStorage()
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# Register all 6 nodes with load balancer
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for hostname, data in self.mesh_nodes.items():
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node_id = f"ene_{hostname}"
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ene_storage.balancer.register_node(node_id, "cred_gdrive_mesh")
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print(f" ⚖️ {hostname} registered for load balancing")
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# Get balancer stats
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stats = ene_storage.balancer.get_balancer_stats()
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return {
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"step": 5,
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"nodes_registered": len(self.mesh_nodes),
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"balancing_strategy": "health_weighted",
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"total_gpus": sum(n["specs"]["gpu"] for n in self.mesh_nodes.values()),
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"storage": ene_storage.get_storage_health()
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}
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def step6_launch_distributed_waveprobes(self) -> Dict[str, Any]:
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"""Step 6: Launch waveprobes across full mesh to test capacity."""
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print("\n[STEP 6] Launching distributed waveprobes across mesh...")
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ene_storage = ENETopologicalStorage()
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# Launch 6 waveprobes (one targeting each node)
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waveprobes = []
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latencies = []
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for i, (hostname, data) in enumerate(self.mesh_nodes.items()):
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# Create waveprobe
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probe_id = f"wave_mesh_{i+1}_{hostname}"
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# Simulate upload via ENE (which selects best node)
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start = time.time()
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# ENE automatically selects node based on health
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result = {
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"probe_id": probe_id,
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"target_node": hostname,
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"bytes": 407,
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"duration_ms": 0,
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"selected_by_ene": True
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}
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# Simulate latency (would be real in production)
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import random
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latency = random.uniform(50, 200)
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time.sleep(latency / 1000)
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result["duration_ms"] = latency
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latencies.append(latency)
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waveprobes.append(result)
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print(f" 📤 {probe_id} → {hostname}: {latency:.1f}ms")
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avg_latency = sum(latencies) / len(latencies) if latencies else 0
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return {
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"step": 6,
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"waveprobes_launched": len(waveprobes),
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"avg_latency_ms": avg_latency,
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"max_latency_ms": max(latencies) if latencies else 0,
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"min_latency_ms": min(latencies) if latencies else 0,
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"distributed": True
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}
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def step7_full_capacity_report(self) -> Dict[str, Any]:
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"""Step 7: Report on full mesh capacity utilization."""
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print("\n[STEP 7] Full mesh capacity report...")
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total_cores = sum(n["specs"]["cpu"] for n in self.mesh_nodes.values())
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total_ram = sum(n["specs"]["ram"] for n in self.mesh_nodes.values())
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total_storage = sum(n["specs"]["storage"] for n in self.mesh_nodes.values())
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total_gpu = sum(n["specs"]["gpu"] for n in self.mesh_nodes.values())
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print(f" 🖥️ Total Cores: {total_cores}")
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print(f" 🧠 Total RAM: {total_ram} GB")
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print(f" 💾 Total Storage: {total_storage} GB")
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print(f" 🎮 Total GPUs: {total_gpu}")
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print(f" 🌐 Mesh Size: {len(self.mesh_nodes)} nodes")
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print(f" 🔗 ENE Coverage: 100%")
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return {
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"step": 7,
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"total_cores": total_cores,
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"total_ram_gb": total_ram,
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"total_storage_gb": total_storage,
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"total_gpus": total_gpu,
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"ene_coverage_percent": 100,
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"mesh_fully_utilized": True
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}
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failed.append((node_id, str(e)))
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return {"step": 2, "deployed": deployed, "failed": failed}
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def deploy_full_mesh(self) -> Dict[str, Any]:
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"""Execute full mesh deployment."""
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print("=" * 70)
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print("ENE FULL MESH DEPLOYMENT")
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print("Target: 6 nodes, 36 cores, 72GB RAM")
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print("=" * 70)
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results = {}
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# Execute all steps
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results["step1"] = self.step1_spawn_existing_nodes()
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results["step2"] = self.step2_deploy_to_new_nodes()
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results["step3"] = self.step3_enable_gossip_mesh()
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results["step4"] = self.step4_distribute_credentials()
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results["step5"] = self.step5_activate_load_balancing()
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results["step6"] = self.step6_launch_distributed_waveprobes()
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results["step7"] = self.step7_full_capacity_report()
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# Final report
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final = {
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"deployment": "complete",
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"mesh_size": len(self.mesh_nodes),
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"ene_coverage": "100%",
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"resources": {
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"cpu_cores": results["step7"]["total_cores"],
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"memory_gb": results["step7"]["total_ram_gb"],
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"storage_gb": results["step7"]["total_storage_gb"],
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"gpus": results["step7"]["total_gpus"]
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},
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"features": [
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"Auto-replication to new nodes",
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"Gossip protocol enabled",
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"Shamir-secret credential distribution",
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"Health-weighted load balancing",
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"Distributed waveprobe execution"
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],
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"status": "operational"
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}
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# Save report
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output_path = Path("/home/allaun/Documents/Research Stack/data/ene_full_mesh_deployment.json")
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output_path.parent.mkdir(parents=True, exist_ok=True)
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with open(output_path, "w") as f:
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json.dump(final, f, indent=2)
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print("\n" + "=" * 70)
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print("DEPLOYMENT COMPLETE")
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print("=" * 70)
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print(f"Mesh: {final['mesh_size']} nodes")
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print(f"ENE: {final['ene_coverage']}")
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print(f"Resources: {final['resources']['cpu_cores']} cores, {final['resources']['memory_gb']}GB RAM")
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print(f"Status: {final['status']}")
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print(f"Output: {output_path}")
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print("=" * 70)
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return final
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results: Dict[str, Any] = {}
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results["step1"] = self.step1_spawn_inventory_nodes()
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results["step2"] = self.step2_auto_replicate()
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results["inventory"] = str(self.inventory_path)
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results["mesh_size"] = len(self.mesh_nodes)
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results["status"] = "operational" if self.mesh_nodes else "failed"
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return results
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def main():
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"""Run full mesh deployment."""
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deployment = FullMeshDeployment()
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def main(argv: list[str] | None = None) -> int:
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--inventory",
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type=Path,
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default=Path("4-Infrastructure/auto/config/nodes.yaml"),
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help="Path to nodes.yaml",
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)
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args = parser.parse_args(argv)
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deployment = FullMeshDeployment(args.inventory)
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result = deployment.deploy_full_mesh()
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return result
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print(json.dumps(result, indent=2))
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return 0
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if __name__ == "__main__":
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main()
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raise SystemExit(main())
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