Add Agentrun CLI

cmd/agentrun/.gitignore

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+# Project specific
+agent_metadata.yaml
+Dockerfile

cmd/agentrun/README.md

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+# AgentRun CLI
+
+AgentRun CLI is a developer tool that streamlines the development, packaging, building, and deployment of AI agents to AgentCube. It provides a unified interface for managing the complete agent lifecycle from local development to cloud deployment.
+
+## Quick Start
+
+### Prerequisites
+
+- Python 3.8+
+- Git
+- Docker (optional, for container builds)
+
+### Installation
+
+```bash
+# Clone the repository
+git clone https://github.com/volcano-sh/agentcube.git
+cd agentcube/cmd/agentrun
+
+# Create virtual environment
+python3 -m venv venv
+source venv/bin/activate  # On Windows: venv\Scripts\activate
+
+# Install in development mode
+pip install -e .
+```
+
+### Your First Agent
+
+1. **Package an existing agent:**
+   ```bash
+   kubectl agentrun pack -f examples/hello-agent --agent-name "my-agent"
+   ```
+
+2. **Build the container image:**
+   ```bash
+   kubectl agentrun build -f examples/hello-agent
+   ```
+
+3. **Publish to AgentCube:**
+   ```bash
+   kubectl agentrun publish \
+      -f examples/hello-agent \
+      --image-url "docker.io/username/my-agent" \
+   ```
+
+4. **Invoke your agent:**
+   ```bash
+   kubectl agentrun invoke -f examples/hello-agent --payload '{"prompt": "Hello World!"}'
+   ```
+
+5. **Check status:**
+   ```bash
+   kubectl agentrun status -f examples/hello-agent
+   ```
+
+## Features
+
+- **Multi-language Support**: Python, Java (with more languages planned)
+- **Flexible Build Modes**: Local Docker builds and cloud builds
+- **Multi-Provider Deployment**: Support for AgentCube CRDs and standard Kubernetes deployments
+- **AgentCube Integration**: Seamless publishing and management
+- **Developer-friendly**: Rich CLI experience with detailed feedback
+- **CI/CD Ready**: Python SDK for programmatic access
+- **Extensible Architecture**: Plugin system for custom providers
+
+## Installation
+
+### From PyPI (Recommended)
+
+```bash
+pip install agentrun
+```
+
+### From Source
+
+```bash
+git clone https://github.com/volcano-sh/agentcube.git
+cd agentcube/cmd/agentrun
+pip install -e .
+```
+
+## Documentation
+
+- [Design](AgentRun-CLI-Design.md)
+- [Examples](examples/)
+
+## Configuration
+
+AgentRun uses a `agent_metadata.yaml` file to configure your agent:
+
+```yaml
+agent_name: my-agent
+description: "A sample AI agent"
+language: python
+entrypoint: python main.py
+port: 8080
+build_mode: local
+requirements_file: requirements.txt
+```
+
+## Architecture
+
+AgentRun CLI follows a modular four-layer architecture:
+
+1. **CLI Layer**: Typer-based command interface
+2. **Runtime Layer**: Business logic and Python SDK
+3. **Operations Layer**: Core domain logic
+4. **Services Layer**: External integrations
+
+## Deployment Providers
+
+AgentRun supports two deployment providers:
+
+### AgentCube Provider (Default)
+
+Deploys agents using AgentCube's custom AgentRuntime CRDs, providing enhanced agent lifecycle management and integration with the AgentCube ecosystem.
+
+```bash
+kubectl agentrun publish -f examples/hello-agent --provider agentcube
+```
+
+### Standard Kubernetes Provider
+
+Deploys agents as standard Kubernetes Deployments and Services, suitable for environments without AgentCube CRDs installed.
+
+```bash
+kubectl agentrun publish -f examples/hello-agent --provider k8s \
+  --node-port 30080 \
+  --replicas 3
+```
+
+## Command Reference
+
+### `kubectl agentrun pack`
+Package the agent application into a standardized workspace.
+
+```bash
+kubectl agentrun pack [OPTIONS]
+
+Options:
+  -f, --workspace TEXT    Path to the agent workspace directory [default: .]
+  --agent-name TEXT       Override the agent name
+  --language TEXT         Programming language (python, java)
+  --entrypoint TEXT       Override the entrypoint command
+  --port INTEGER          Port to expose in the Dockerfile
+  --build-mode TEXT       Build strategy: local or cloud
+  --description TEXT      Agent description
+  --output TEXT           Output path for packaged workspace
+  --verbose               Enable detailed logging
+```
+
+### `kubectl agentrun build`
+Build the agent image based on the packaged workspace.
+
+```bash
+kubectl agentrun build [OPTIONS]
+
+Options:
+  -f, --workspace TEXT    Path to the agent workspace directory [default: .]
+  -p, --proxy TEXT        Custom proxy URL for dependency resolution
+  --cloud-provider TEXT   Cloud provider name (e.g., huawei)
+  --output TEXT           Output path for build artifacts
+  --verbose               Enable detailed logging
+```
+
+### `kubectl agentrun publish`
+Publish the agent to AgentCube
+
+```bash
+kubectl agentrun publish [OPTIONS]
+
+Options:
+  -f, --workspace TEXT    Path to the agent workspace directory [default: .]
+  --version TEXT          Semantic version string (e.g., v1.0.0)
+  --image-url TEXT        Image repository URL (required in local build mode)
+  --image-username TEXT   Username for image repository
+  --image-password TEXT   Password for image repository
+  --description TEXT      Agent description
+  --region TEXT           Deployment region
+  --cloud-provider TEXT   Cloud provider name (e.g., huawei)
+  --provider TEXT         Target provider for deployment (agentcube, k8s). 'agentcube' deploys AgentRuntime CR, 'k8s' deploys standard K8s Deployment/Service. [default: agentcube]
+  --node-port INTEGER     Specific NodePort to use (30000-32767) for K8s deployment
+  --replicas INTEGER      Number of replicas for K8s deployment (default: 1)
+  --endpoint TEXT         Custom API endpoint for AgentCube or Kubernetes cluster
+  --namespace TEXT        Kubernetes namespace to use for deployment [default: default]
+  --verbose               Enable detailed logging
+```
+
+### `kubectl agentrun invoke`
+Invoke a published agent via AgentCube or Kubernetes.
+
+```bash
+kubectl agentrun invoke [OPTIONS]
+
+Options:
+  -f, --workspace TEXT    Path to the agent workspace directory [default: .]
+  --payload TEXT          JSON-formatted input passed to the agent [default: {}]
+  --header TEXT           Custom HTTP headers (e.g., 'Authorization: Bearer token')
+  --provider TEXT         Target provider for deployment (agentcube, k8s). 'agentcube' deploys AgentRuntime CR, 'k8s' deploys standard K8s Deployment/Service. [default: agentcube]
+  --verbose               Enable detailed logging
+```
+
+### `kubectl agentrun status`
+Check the status of a published agent.
+
+```bash
+kubectl agentrun status [OPTIONS]
+
+Options:
+  -f, --workspace TEXT    Path to the agent workspace directory [default: .]
+  --provider TEXT         Target provider for deployment (agentcube, k8s). 'agentcube' deploys AgentRuntime CR, 'k8s' deploys standard K8s Deployment/Service. [default: agentcube]
+  --verbose               Enable detailed logging
+```
+
+## Agent Structure
+
+An AgentRun workspace typically contains:
+
+```
+my-agent/
+├── agent_metadata.yaml    # Agent configuration (auto-generated)
+├── Dockerfile            # Container definition (auto-generated)
+├── requirements.txt      # Python dependencies
+├── main.py              # Agent entrypoint
+└── src/                 # Source code
+```
+
+### `agent_metadata.yaml`
+
+```yaml
+agent_name: my-agent
+description: "My AI agent"
+language: python
+entrypoint: python main.py
+port: 8080
+build_mode: local
+requirements_file: requirements.txt
+```
+
+## Language Support
+
+### Python
+
+Fully supported with automatic dependency management and Dockerfile generation.
+
+- Supported versions: Python 3.8+
+- Package manager: pip
+- Dependencies file: requirements.txt
+- Example: [examples/hello-agent](examples/hello-agent)
+
+### Java
+
+Supported with Maven-based builds and OpenJDK runtime.
+
+- Supported versions: Java 17+
+- Build tool: Maven
+- Dependencies file: pom.xml
+- Note: Java example coming soon
+
+## Troubleshooting
+
+### Common Issues
+
+1. **"Docker is not available"**
+   - Install Docker and make sure it's running
+   - Use `--build-mode cloud` for cloud builds
+
+2. **"Metadata file not found"**
+   - Run `kubectl agentrun pack` first to generate metadata
+   - Ensure you're in the correct workspace directory
+
+3. **"Agent not published yet"**
+   - Run `kubectl agentrun publish` before trying to invoke
+   - Check that the build completed successfully
+
+4. **"Provider not found"**
+   - Ensure you're using a valid provider: `agentcube` or `k8s`
+   - Check that your Kubernetes cluster has the required CRDs (for agentcube provider)
+
+### Getting Help
+
+```bash
+# General help
+kubectl agentrun --help
+
+# Command-specific help
+kubectl agentrun pack --help
+kubectl agentrun build --help
+kubectl agentrun publish --help
+kubectl agentrun invoke --help
+kubectl agentrun status --help
+```
+
+## License
+
+This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
+
+## Links
+
+- [AgentCube Main Project](https://github.com/volcano-sh/agentcube)
+- [Volcano Scheduler](https://github.com/volcano-sh/volcano)
+- [Issue Tracker](https://github.com/volcano-sh/agentcube/issues)

cmd/agentrun/agentrun/__init__.py

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+"""
+AgentRun CLI - A developer tool for packaging, building, and deploying AI agents to AgentCube.
+"""
+
+__version__ = "0.1.0"
+__author__ = "AgentCube Community"
+__email__ = "agentcube@volcano.sh"
+
+from .cli.main import app
+from .runtime.pack_runtime import PackRuntime
+from .runtime.build_runtime import BuildRuntime
+from .runtime.publish_runtime import PublishRuntime
+from .runtime.invoke_runtime import InvokeRuntime
+
+__all__ = [
+    "app",
+    "PackRuntime",
+    "BuildRuntime",
+    "PublishRuntime",
+    "InvokeRuntime",
+]

cmd/agentrun/agentrun/cli/__init__.py

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+"""
+CLI module for AgentRun.
+"""