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CloudRobo Client

CloudRobo command-line tool and Python SDK for Huawei Cloud's Embodied Intelligence Platform (CloudRobo) - resource management and task orchestration.

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Features

  • Asset Management: Manage lifecycle of models, datasets, and algorithms
  • Data Processing: Create and monitor data processing tasks (cleaning, format conversion, etc.)
  • Model Training: Submit and monitor training tasks (pre-training, fine-tuning, simulation reinforcement learning)
  • Model Evaluation: Create simulation evaluation tasks to assess model performance
  • Inference Service: Deploy and manage model inference services
  • Robot Management: Register robots and export device certificates
  • Task Dispatch: Execute embodied intelligence tasks on robots
  • Workspace Management: Manage resource-isolated workspaces
  • Resource Management: Query resource quotas and resource pools
  • Data Plane SDK: Robot-side Zenoh data plane client (optional)

Installation

For Users (Recommended)

Install from PyPI:

pip install hw-cloudrobo-client

After installation, the cloudrobo CLI tool is ready to use.

For Developers

Install from source (requires git):

git clone <repository-url>
cd cloudrobo-client
pip install -r requirements-dev-editable.txt

This installs all sub-packages in editable mode. Code changes take effect immediately.

Quick Start

1. Configure Authentication

# Configure Huawei Cloud AK/SK (automatically encrypted)
cloudrobo config set ak your-access-key sk your-secret-key

# Configure region
cloudrobo config set region cn-southwest-2

Or use environment variables:

export HUAWEI_CLOUD_AK="your-access-key"
export HUAWEI_CLOUD_SK="your-secret-key"
export CLOUDROBO_REGION="cn-southwest-2"

2. View Available Commands

cloudrobo --help

3. Example: List Workspaces

cloudrobo workspace list

Documentation

Document Description
Installation Guide System requirements, installation methods, authentication configuration
Quick Start Get started in 5 minutes
Architecture Architecture principles, public interfaces, development guidelines
Environment Variables Environment variable configuration

Each functional module's documentation is maintained by its respective package:

Package Description Documentation
cloudrobo-core Core SDK + CLI Framework docs/
cloudrobo-asset Asset Management docs/
cloudrobo-dataset Dataset Processing docs/
cloudrobo-train Model Training docs/
cloudrobo-eval Model Evaluation docs/
cloudrobo-infer Inference Service docs/
cloudrobo-robot Robot Management docs/
cloudrobo-dispatch Task Dispatch docs/
cloudrobo-workspace Workspace Management docs/
cloudrobo-resource Resource Management docs/
cloudrobo-r2c Data Plane SDK (Zenoh, heavy optional dependencies) docs/

Project Structure

This project uses a Monorepo architecture where each functional module is an independent package:

cloudrobo-client/
├── packages/                    # Independent functional packages
│   ├── cloudrobo-core/          # Core SDK + CLI framework
│   ├── cloudrobo-asset/         # Asset management
│   ├── cloudrobo-dataset/       # Dataset processing
│   ├── cloudrobo-train/         # Model training
│   ├── cloudrobo-eval/          # Model evaluation
│   ├── cloudrobo-infer/         # Inference service
│   ├── cloudrobo-robot/         # Robot management
│   ├── cloudrobo-dispatch/      # Task dispatch
│   ├── cloudrobo-workspace/     # Workspace management
│   ├── cloudrobo-resource/      # Resource management
│   └── cloudrobo-r2c/           # Data Plane SDK
├── docs/                        # Project-level documentation
└── pyproject.toml               # Aggregate installation configuration

Testing

# Run all tests
python -m pytest tests/ packages/ -v

# Run tests for a single package
python -m pytest packages/cloudrobo-asset/tests/ -v

License

Apache License 2.0

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