Crypto Mining Rig Repurposing Guide

# Hermes Dispatch Tool — Crypto Mining Rig Repurposing Guide
# Source: https://hermesdispatch.dev/tools/rig-repurposing-guide/
# Description: Return repurposing strategies for a mining hardware type.
# License: MIT (generated by hermesdispatch.dev)
#
# INSTALL:
#   1. Save this file as ~/.hermes/hermes-agent/tools/rig_repurposing_guide.py
#   2. Restart Hermes or run /reset in a session
#
# MANUAL REGISTRY:
#   from tools.rig_repurposing_guide import register
#   register()

import json

DATA = json.loads(r'''{
  "asic-to-heat": {
    "name": "ASIC \u2192 Space Heater + Bitcoin Mining",
    "icon": "\ud83d\udd25",
    "original": "Bitcoin ASIC miner (Antminer S19, Whatsminer M30S)",
    "pivot": "Run it as a dedicated heater during cold months. Mine Bitcoin at breakeven or small profit while offsetting heating bills.",
    "steps": [
      "Relocate miner to a cold room, garage, or basement.",
      "Add ducting or fans to move heat where you want it.",
      "Use Braiins OS+ or VNish firmware to tune efficiency.",
      "Join a low-fee mining pool (Ocean, Slush, ViaBTC).",
      "Track kWh cost vs heat value; shut down if electricity spikes in summer."
    ],
    "revenue": "$50-400/mo depending on BTC price and electricity",
    "capex": "$0-200 for ducts/fans",
    "skills": "Basic electrical + cooling",
    "difficulty": "Easy",
    "ai_compatible": false,
    "note": "ASICs cannot run AI. This is the best way to squeeze value from obsolete BTC miners in cold climates."
  },
  "gpu-rig-inference": {
    "name": "GPU Mining Rig \u2192 Local LLM Inference Host",
    "icon": "\ud83e\udde0",
    "original": "Ethereum/PoW GPU rig with 6-12 NVIDIA cards",
    "pivot": "Convert the rig into a local LLM inference cluster. Rent it out, run your own agents, or sell API access.",
    "steps": [
      "Inventory cards: only 12GB+ VRAM cards are viable (RTX 3060 12GB, 3080, 3090, 4090).",
      "Install Ubuntu Server + NVIDIA drivers + CUDA.",
      "Set up Ollama or vLLM for multi-GPU serving.",
      "Expose via OpenAI-compatible API and route through a reverse proxy.",
      "List capacity on inference marketplaces or sell access to developers."
    ],
    "revenue": "$100-2,000/mo depending on GPUs and utilization",
    "capex": "$0-300 for SSDs, RAM, network upgrades",
    "skills": "Linux, Docker, basic networking",
    "difficulty": "Medium",
    "ai_compatible": true,
    "note": "The highest-value pivot for crypto miners. Use our Miner Pivot Calculator to compare vs continuing to mine altcoins."
  },
  "fpga-asic-sell": {
    "name": "Sell FPGA / Niche ASIC Hardware to AI Builders",
    "icon": "\ud83d\udcb5",
    "original": "FPGA rigs, Kadena ASICs, Dogecoin/LTC miners",
    "pivot": "Sell the hardware while it still has resale value. Use proceeds to buy NVIDIA GPUs or AI-focused mini PCs.",
    "steps": [
      "List on eBay, Facebook Marketplace, or mining forums.",
      "Price at 40-60% of retail depending on condition.",
      "Disclose hash rate, power consumption, and any issues.",
      "Bundle PSUs and risers for GPU rigs to move faster.",
      "Reinvest in RTX 4090s, Mac Studio M4 Max, or cloud credits."
    ],
    "revenue": "One-time: $500-5,000+ depending on rig",
    "capex": "$0",
    "skills": "Sales listing + shipping",
    "difficulty": "Easy",
    "ai_compatible": false,
    "note": "Best for hardware that cannot be repurposed for AI. Cash out before resale values drop further."
  },
  "gpu-rig-render": {
    "name": "GPU Rig \u2192 Render / AI Image / Video Farm",
    "icon": "\ud83c\udfa8",
    "original": "Multi-GPU NVIDIA rig",
    "pivot": "Run render jobs (Blender, Octane), AI image generation (Stable Diffusion, Flux), or video upscaling.",
    "steps": [
      "Install ComfyUI, Automatic1111, or Render Network client.",
      "Rent compute on Vast.ai, Salad, or Render Network.",
      "Target workloads that need CUDA, not just gaming GPUs.",
      "Ensure stable internet and uptime for marketplace ratings.",
      "Track revenue per kWh to make sure you beat electricity costs."
    ],
    "revenue": "$50-800/mo depending on GPU model and demand",
    "capex": "$0-100 for storage/RAM tweaks",
    "skills": "Docker, Linux, GPU tuning",
    "difficulty": "Medium",
    "ai_compatible": true,
    "note": "Good middle ground if LLM inference demand is low in your region."
  },
  "home-lab-storage": {
    "name": "Mining Shed \u2192 Home Lab / Storage / Data Center",
    "icon": "\ud83c\udfe0",
    "original": "Mining shed or garage with 240V power and cooling",
    "pivot": "Repurpose the space into a home data lab: NAS, Kubernetes cluster, backup infrastructure, or hosting.",
    "steps": [
      "Remove obsolete miners and clean dust filters.",
      "Install a quiet server rack or mini PC cluster.",
      "Run TrueNAS, Proxmox, or a Kubernetes homelab.",
      "Host your own AI agents, backups, media server, and VPN.",
      "Add solar if possible to cut electricity costs long-term."
    ],
    "revenue": "$0-200/mo saved in cloud hosting",
    "capex": "$300-1,500 for servers and storage",
    "skills": "Server admin, networking",
    "difficulty": "Hard",
    "ai_compatible": true,
    "note": "Play the long game: own your infrastructure instead of renting it."
  }
}''')

def _ok(result):
    return json.dumps({"success": True, "data": result}, indent=2)

def _err(message):
    return json.dumps({"success": False, "error": message}, indent=2)

TOOL_NAME = "rig_repurposing_guide"
TOOLSET = "crypto"

SCHEMA = {
  "type": "function",
  "function": {
    "name": "rig_repurposing_guide",
    "description": "Return repurposing strategies for a mining hardware type.",
    "parameters": {
      "type": "object",
      "properties": {
        "hardware_type": {
          "type": "string",
          "description": "Hardware Type to look up."
        }
      },
      "required": [
        "hardware_type"
      ]
    }
  }
}

def lookup(args):
    hardware = args.get('hardware_type', '').lower().strip()
    options = DATA.get('options', {})
    option = options.get(hardware, options.get('gpu_rig'))
    return _ok({'hardware_type': hardware, 'strategies': option})

def HANDLER(args):
    try:
        return lookup(args)
    except Exception as e:
        return _err(str(e))

def register():
    try:
        from tools.registry import registry
        registry.register(name=TOOL_NAME, toolset=TOOLSET, schema=SCHEMA, handler=HANDLER)
    except ImportError:
        print("Hermes registry not found; skipping manual registration.")

if __name__ == "__main__":
    print(HANDLER({}))