computing-provider-v2

README

Computing Provider v2

Turn your GPU into an AI inference endpoint and join the Swan Chain decentralized computing network.

Quick Start (5 minutes)

No wallet needed. No blockchain registration. No public IP required.

Linux (NVIDIA GPU)

# 0. Install build tools (skip if already installed)
sudo apt-get update && sudo apt-get install -y git make
wget https://go.dev/dl/go1.22.0.linux-amd64.tar.gz
sudo rm -rf /usr/local/go && sudo tar -C /usr/local -xzf go1.22.0.linux-amd64.tar.gz
echo 'export PATH=$PATH:/usr/local/go/bin' >> ~/.bashrc && source ~/.bashrc

# 1. Clone and build
git clone https://github.com/swanchain/computing-provider.git
cd computing-provider
make clean && make testnet && sudo make install

# 2. Download model weights from HuggingFace (e.g., Qwen 2.5 7B)
computing-provider models download Qwen/Qwen2.5-7B-Instruct

# 3. Start SGLang with the downloaded model
docker run -d --gpus all -p 30000:30000 --ipc=host --name sglang \
  -v ~/.swan/models/Qwen/Qwen2.5-7B-Instruct:/models \
  lmsysorg/sglang:latest \
  python3 -m sglang.launch_server --model-path /models \
    --host 0.0.0.0 --port 30000 \
    --served-model-name Qwen/Qwen2.5-7B-Instruct

# 4. Run the setup wizard (handles auth, config, and model discovery)
computing-provider setup

# 5. Run the provider
computing-provider run

The models download command downloads model weights directly from HuggingFace. Large weight files (LFS) are verified with SHA256 hashes. The setup wizard will:

• Check prerequisites (Docker, GPU)
• Create/login to your Swan Inference account
• Auto-discover your running model servers
• Auto-match local models to Swan Inference model IDs
• Generate config.toml and models.json

macOS (Apple Silicon)

# 1. Install Ollama and pull a model
brew install ollama
ollama serve &
ollama pull qwen2.5:7b

# 2. Install Computing Provider
brew install go
git clone https://github.com/swanchain/computing-provider.git
cd computing-provider
make clean && make testnet && sudo make install

# 3. Run the setup wizard
computing-provider setup

# 4. Run the provider
computing-provider run

The setup wizard auto-discovers Ollama models and matches them to Swan Inference model IDs (e.g., qwen2.5:7b → qwen-2.5-7b).

---

How It Works

Swan Inference (Cloud)
        │
        │ WebSocket (outbound connection - works behind NAT)
        ▼
┌───────────────────────┐
│  Computing Provider   │
│  ┌─────────────────┐  │
│  │ Your GPU Server │  │
│  │ (SGLang/Ollama) │  │
│  └─────────────────┘  │
└───────────────────────┘

1. Provider connects outbound to Swan Inference (no inbound ports needed)
2. Registers available models
3. Receives inference requests via WebSocket
4. Forwards to local model server, returns response
5. Earn rewards for completed requests (optional wallet setup)

---

Prerequisites

Platform	Requirements
Linux	Docker, NVIDIA GPU, NVIDIA Container Toolkit
macOS	Ollama, Apple Silicon (M1/M2/M3/M4)

Install NVIDIA Container Toolkit (Linux only)

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
  sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
  sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker

# Verify
docker run --rm --gpus all nvidia/cuda:12.0-base-ubuntu22.04 nvidia-smi

---

Configuration

Model Configuration (models.json)

Map Swan Inference model IDs to your local inference endpoints:

{
  "qwen-2.5-7b": {
    "endpoint": "http://localhost:30000",
    "gpu_memory": 16000,
    "category": "text-generation"
  }
}

Field	Description
endpoint	URL of your local inference server
gpu_memory	GPU memory required (MB)
category	Model category (text-generation, image-generation, etc.)
local_model	(Optional) Actual model name for local server (e.g., Ollama model name)

Note: The local_model field is used when your local server uses different model names than Swan Inference. For example, Ollama uses qwen2.5:7b while Swan Inference expects qwen-2.5-7b. The setup wizard handles this mapping automatically.

Provider Configuration (config.toml)

Located at ~/.swan/computing/config.toml:

[API]
Port = 8085
NodeName = "my-provider"

[Inference]
Enable = true
WebSocketURL = "ws://inference-ws-dev.swanchain.io"
ServiceURL = "https://api-dev.swanchain.io"
ApiKey = "sk-prov-xxxxxxxxxxxxxxxxxxxx"  # Required - get from https://inference-dev.swanchain.io
Models = ["qwen-2.5-7b"]

---

Monitoring

Web Dashboard

computing-provider dashboard
# Open http://localhost:3005

Features: Real-time metrics, GPU status, model management, request controls.

REST API

# View metrics
curl http://localhost:8085/api/v1/computing/inference/metrics

# List models
curl http://localhost:8085/api/v1/computing/inference/models

# Check health
curl http://localhost:8085/api/v1/computing/inference/health

Useful Endpoints

Endpoint	Description
GET /inference/metrics	Request counts, latency, GPU stats
GET /inference/metrics/prometheus	Prometheus format for Grafana
GET /inference/models	List all models with status
POST /inference/models/:id/enable	Enable a model
POST /inference/models/:id/disable	Disable a model
POST /inference/models/reload	Hot-reload models.json

---

Earning Rewards (Optional)

To receive SWAN token rewards for completed inference requests, set up a wallet:

# 1. Create a wallet
computing-provider wallet new

# 2. Note your wallet address
computing-provider wallet list

# 3. Register on Swan Chain (requires small amount of SwanETH for gas)
computing-provider account create \
  --ownerAddress <your-wallet> \
  --workerAddress <your-wallet> \
  --beneficiaryAddress <your-wallet> \
  --task-types 4

# 4. Add collateral (determines your reward tier)
computing-provider collateral add --ecp --from <your-wallet> <amount>

Note: You can run the provider without a wallet - it will still serve inference requests, but you won't receive on-chain rewards.

---

CLI Reference

Basic Commands

computing-provider setup                     # Interactive setup wizard (recommended)
computing-provider run                       # Start provider
computing-provider inference status          # Check status on Swan Inference
computing-provider inference config          # Show inference config
computing-provider dashboard                 # Web UI (port 3005)
computing-provider task list --ecp           # List tasks

Setup Wizard

The setup wizard is the recommended way to configure a new provider:

computing-provider setup                     # Full interactive setup
computing-provider setup --skip-discovery    # Skip model discovery
computing-provider setup --api-key=sk-prov-xxx  # Use existing API key

# Subcommands
computing-provider setup discover            # Just discover model servers
computing-provider setup login               # Login to existing account
computing-provider setup signup              # Create new account

Wallet Commands (for rewards)

computing-provider wallet new                # Create wallet
computing-provider wallet list               # List wallets
computing-provider wallet import <file>      # Import private key

Hardware Info

computing-provider research hardware         # All hardware info
computing-provider research gpu-info         # GPU details
computing-provider research gpu-benchmark    # Run benchmark

---

Troubleshooting

Error	Solution
go: command not found	Install Go 1.21+: see go.dev/dl
permission denied...docker.sock	Add user to docker group: sudo usermod -aG docker $USER
could not select device driver "nvidia"	Install NVIDIA Container Toolkit
container "/resource-exporter" already in use	Run docker rm -f resource-exporter
authentication required	Set ApiKey in config.toml or INFERENCE_API_KEY env var
invalid provider API key	Verify key starts with sk-prov- and is not revoked
WebSocket connection failed	Check WebSocketURL and network connectivity
Provider not receiving requests	Check models.json matches your inference server
cuda>=12.x unsatisfied condition	Use an older SGLang tag: lmsysorg/sglang:v0.4.7.post1-cu124

Check Logs

# Provider logs
tail -f cp.log

# Inference server logs
docker logs sglang

---

Advanced: ZK-Proof Mode

For generating ZK-Snark proofs (Filecoin, Aleo). Requires additional setup.

See ZK-Proof Documentation.

# Initialize with public IP (required for ZK mode)
computing-provider init --multi-address=/ip4/<PUBLIC_IP>/tcp/<PORT> --node-name=<name>

# Requires: wallet, account registration, v28 parameters (~200GB)

---

Getting Help

• Discord - Community support
• GitHub Issues - Bug reports
• Documentation - Full docs

License

Apache 2.0