# How to Invoke Chutes SN64 GPU Compute Within the Bittensor Module in CloddsBot

> Discover how CloddsBot invokes Chutes SN64 GPU compute using a Python miner process. Learn about GPU node management and invocation statistics.

- Repository: [AL/CloddsBot](https://github.com/alsk1992/CloddsBot)
- Tags: how-to-guide
- Published: 2026-09-14

---

**The Bittensor module in CloddsBot invokes Chutes SN64 GPU compute by spawning a Python-based miner process through the `createChutesMinerManager` factory, which orchestrates GPU node registration, lifecycle management, and invocation statistics aggregation via the `PythonRunner` wrapper.**

CloddsBot integrates with the Bittensor network to support multiple subnet types, including the specialized **Chutes SN64** GPU compute subnet. When configured for Chutes, the Bittensor module instantiates a dedicated miner manager that translates Node.js service calls into Python GPU mining operations, bridging TypeScript orchestration with Python-based machine learning workloads.

## Core Architecture Components

The invocation pipeline relies on three primary components working in concert to manage the Python miner lifecycle.

### BittensorService ([`src/bittensor/service.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/bittensor/service.ts))

The `BittensorService` acts as the central orchestrator. It detects the subnet type from configuration and delegates to the appropriate manager factory. When `subnet.type === 'chutes'`, it calls `createChutesMinerManager` to instantiate the GPU compute handler.

### ChutesMinerManager ([`src/bittensor/chutes.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/bittensor/chutes.ts))

Encapsulating the GPU-compute workflow, this manager implements `start()`, `stop()`, `getStatus()`, and `getInvocationStats()`. It constructs the command-line arguments for the Python miner and maintains an internal `Map<string, GpuNodeStatus>` to track online/offline states of configured GPU nodes.

### PythonRunner ([`src/bittensor/python-runner.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/bittensor/python-runner.ts))

This thin wrapper around Node.js `child_process` sanitizes arguments and spawns the Python process. It provides callbacks for stdout, stderr, and exit events, enabling the manager to parse invocation counts and handle process crashes.

## Execution Flow for GPU Compute Invocation

The Chutes SN64 GPU compute invocation follows a structured lifecycle from configuration to runtime monitoring.

### Configuration Loading

The application loads settings from [`src/config/index.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/config/index.ts) or environment variables. When `BITTENSOR_ENABLED=true` and `subnet.type` is `'chutes'`, the system extracts the `chutesConfig` object defining GPU nodes, Docker images, and API ports.

### Manager Instantiation

Inside `createBittensorService`, the factory checks subnet configuration:

```typescript
// src/bittensor/service.ts
if (subnet.type === 'chutes' && subnet.chutesConfig) {
  const manager = createChutesMinerManager(subnet.chutesConfig, runner);
  // Manager registered for lifecycle operations
}

```

### Process Spawning

The `manager.start()` method builds CLI arguments and delegates to `PythonRunner`:

```typescript
// src/bittensor/chutes.ts
const args = [
  '-m', 'chutes.miner',
  '--port', String(config.minerApiPort),
  // Additional flags for Docker image and concurrency limits
];
minerProcess = runner.spawn('python3', args, 'chutes-miner');

```

This spawns `python3 -m chutes.miner` as a child process, initiating the SN64 GPU compute workload.

### GPU Node Registration

Each entry in `config.gpuNodes` generates a `--gpu-node <ip>:<port>` argument. The manager validates connectivity and updates the internal status map to reflect which nodes are available for compute tasks.

### Runtime Monitoring and Statistics

The manager attaches event listeners to capture:
- **Stdout parsing**: Extracts metrics like `invocations: 42` to update aggregate statistics
- **Process exit**: Resets the `running` flag and marks all nodes offline when the miner terminates

These statistics surface through the HTTP API defined in [`src/bittensor/server.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/bittensor/server.ts) and CLI commands in [`src/cli/commands/index.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/cli/commands/index.ts).

## Configuration and Practical Usage

### YAML Configuration Schema

Define your GPU cluster in configuration files or environment variables:

```yaml
bittensor:
  enabled: true
  subnet:
    type: chutes
    chutesConfig:
      minerApiPort: 8080
      dockerImage: "chutes/miner:latest"
      maxConcurrentInvocations: 5
      gpuNodes:
        - name: "node-01"
          ip: "10.0.0.1"
          gpuType: "NVIDIA-A100"
          gpuCount: 4
          port: 32000

```

Reference the complete schema in [`docs/BITTENSOR.md`](https://github.com/alsk1992/CloddsBot/blob/main/docs/BITTENSOR.md).

### Programmatic Integration

Launch the service programmatically using the factory functions:

```typescript
import { createBittensorService } from './src/bittensor/service';
import { createPythonRunner } from './src/bittensor/python-runner';

async function launchChutesMining() {
  const runner = createPythonRunner();
  const service = createBittensorService(config.bittensor, db);
  
  // Spawns the Chutes SN64 GPU miner process
  await service.start();
}

```

### Command Line Interface

Manage GPU compute via the CLI:

```bash

# Interactive configuration setup

clodds bittensor setup

# Start GPU mining (invokes the Python miner)

clodds bittensor start

# Check miner and node status

clodds bittensor status

```

CLI definitions reside in [`src/cli/commands/index.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/cli/commands/index.ts) under the Bittensor mining management section.

## Summary

- **Chutes SN64 GPU compute** is invoked through a factory-created miner manager that spawns Python processes via `PythonRunner`.
- The **BittensorService** in [`src/bittensor/service.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/bittensor/service.ts) routes subnet-specific logic to `createChutesMinerManager` when `subnet.type` equals `'chutes'`.
- **GPU node tracking** occurs through a status map in [`src/bittensor/chutes.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/bittensor/chutes.ts), with each node passed as command-line arguments to the Python miner.
- **Invocation statistics** are parsed from stdout and exposed through both HTTP APIs and CLI commands.
- Configuration requires a valid `chutesConfig` object specifying API ports, Docker images, and GPU node endpoints.

## Frequently Asked Questions

### How does CloddsBot handle multiple GPU nodes for Chutes SN64 compute?

The `ChutesMinerManager` iterates over the `gpuNodes` array in your configuration and appends each node as a `--gpu-node <ip>:<port>` argument when spawning the Python miner. It maintains an internal `Map<string, GpuNodeStatus>` to track which nodes are online, updating this status based on connection health checks and process lifecycle events.

### What happens if the Python miner process crashes during GPU computation?

When the Python process exits, the `PythonRunner` triggers the exit callback in [`src/bittensor/chutes.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/bittensor/chutes.ts), which immediately sets the internal `running` flag to false and marks all GPU nodes as offline in the status map. The Bittensor service can then restart the miner via `manager.start()` or alert monitoring systems through the status API.

### Where is the Chutes SN64 miner configuration validated?

Configuration validation occurs in [`src/config/index.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/config/index.ts), which loads and parses the `chutesConfig` object according to the schema documented in [`docs/BITTENSOR.md`](https://github.com/alsk1992/CloddsBot/blob/main/docs/BITTENSOR.md). The `BittensorService` checks for the presence of `subnet.chutesConfig` before attempting to instantiate the miner manager, preventing runtime errors from invalid GPU node definitions.

### Can I customize the Docker image used for Chutes GPU mining?

Yes. The `dockerImage` field in `chutesConfig` allows specification of custom container images. This value is passed as a command-line argument to the Python miner during the spawn process in [`src/bittensor/chutes.ts`](https://github.com/alsk1992/CloddsBot/blob/main/src/bittensor/chutes.ts), enabling deployment of specialized mining environments tailored to specific GPU hardware or software requirements.