Huawei Cloud AgentArts SDK
Build, deploy and manage AI agents with Huawei Cloud capabilities.
Overview
Huawei Cloud AgentArts SDK is a comprehensive toolkit for developing, deploying, and managing AI agents. It provides seamless integration with Huawei Cloud services while supporting mainstream agent frameworks.
Key Features
- Framework Agnostic - Compatible with LangChain, LangGraph, AutoGen, CrewAI, Google ADK, and any custom agent framework
- One-Click Deployment - Deploy agents to Huawei Cloud with a single command
- Built-in Tools - Code interpreter sandbox, memory management, gateway support
- Cloud Integration - Seamless integration with Huawei Cloud authentication, monitoring, and logging
- CLI Toolkit - Complete command-line tools for project initialization, local development, and cloud deployment
Repository Structure
agentarts-sdk-python/
├── src/agentarts/
│ ├── sdk/ # Core SDK modules
│ │ ├── runtime/ # HTTP server runtime (AgentArtsRuntimeApp)
│ │ ├── memory/ # Conversation memory management
│ │ ├── tools/ # Built-in tools (Code Interpreter)
│ │ ├── gateway/ # Gateway client
│ │ ├── identity/ # Authentication & authorization
│ │ ├── integration/ # Framework adapters (LangGraph, etc.)
│ │ └── service/ # HTTP clients for cloud services
│ └── toolkit/ # CLI toolkit
│ ├── cli/ # Command-line interface
│ ├── operations/ # CLI operation handlers
│ ├── plugins/memory/ # Memory plugins
│ │ ├── ai_agent/ # Platform assets (claude_code, codex, opencode, hermes)
│ │ ├── installer/ # Unified installer
│ │ ├── mcp/ # MCP server (local adapter)
│ │ └── resources/ # Manifests + shared hook scripts
│ └── utils/ # Utilities
│ ├── runtime/ # Runtime utilities
│ └── templates/ # Project templates
├── docs/ # Documentation
│ └── cn/ # Chinese documentation
│ ├── sdk_user_guide/ # SDK usage guides
│ └── toolkit_user_guide/ # CLI usage guides
├── examples/ # Example projects
└── tests/ # Test suites
├── unit/ # Unit tests mirroring src/ tree
│ ├── sdk/ # SDK tests
│ └── toolkit/ # Toolkit tests
│ └── plugins/memory/ # Memory plugin tests
└── integration/ # Integration tests
Wrapping Your Agent as HTTP Server
The SDK provides AgentArtsRuntimeApp to wrap your agent logic as a standard HTTP server, exposing:
POST /invocations- Main agent invocation endpointGET /ping- Health check endpointWS /ws- WebSocket endpoint for streaming
Example: LangGraph Agent
# agent.py
import os
from typing import Dict, Any, TypedDict, Annotated
from operator import add
from agentarts.sdk import AgentArtsRuntimeApp, RequestContext
app = AgentArtsRuntimeApp()
class State(TypedDict):
messages: Annotated[list, add]
query: str
response: str
class LangGraphAgent:
def __init__(self):
self.model_name = os.environ.get("OPENAI_MODEL_NAME", "gpt-4o-mini")
self._graph = None
def _build_graph(self):
from langgraph.graph import StateGraph, END
from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage, AIMessage
llm = ChatOpenAI(
model=self.model_name,
api_key=os.environ.get("OPENAI_API_KEY"),
base_url=os.environ.get("OPENAI_BASE_URL")
)
async def process_node(state: State) -> Dict[str, Any]:
query = state.get("query", "")
messages = state.get("messages", []) or [HumanMessage(content=query)]
response = await llm.ainvoke(messages)
return {
"messages": [AIMessage(content=response.content)],
"response": response.content,
}
workflow = StateGraph(State)
workflow.add_node("process", process_node)
workflow.set_entry_point("process")
workflow.add_edge("process", END)
return workflow.compile()
async def run(self, query: str) -> Dict[str, Any]:
graph = self._graph or self._build_graph()
self._graph = graph
result = await graph.ainvoke({"messages": [], "query": query, "response": ""})
return {"response": result.get("response", "")}
_agent = LangGraphAgent()
@app.entrypoint
async def handler(payload: Dict[str, Any], context: RequestContext = None) -> Dict[str, Any]:
query = payload.get("message", "")
return await _agent.run(query)
if __name__ == "__main__":
app.run()
Key Points
- Focus on Agent Logic - You only need to implement the agent logic; the SDK handles HTTP server, request parsing, and response formatting
- Framework Agnostic - Works with any agent framework (LangChain, LangGraph, AutoGen, CrewAI, or custom implementations)
- Simple Decorator - Use
@app.entrypointto mark your handler function - Context Support - Optional
RequestContextparameter provides session info and request metadata - Configurable Model - Model name can be configured via environment variable (e.g.,
OPENAI_MODEL_NAME)
Installation
Requirements
- Python 3.10 or higher
- pip or uv package manager
Create Virtual Environment (Recommended)
It is recommended to install the SDK in a virtual environment to avoid dependency conflicts.
Windows:
# Create virtual environment
python -m venv venv
# Activate virtual environment
.\venv\Scripts\Activate.ps1
# Or using Command Prompt
.\venv\Scripts\activate.bat
Linux/macOS:
# Create virtual environment
python -m venv venv
# Activate virtual environment
source venv/bin/activate
Install via pip
Windows:
pip install agentarts-sdk
Linux/macOS:
pip install agentarts-sdk
Install with Optional Dependencies
# With LangChain support
pip install agentarts-sdk[langchain]
# With LangGraph support
pip install agentarts-sdk[langgraph]
# With MCP memory server support (required by `agentarts memory install`)
pip install agentarts-sdk[mcp]
# With all optional dependencies
pip install agentarts-sdk[all]
Install from Source
Windows:
git clone https://github.com/huaweicloud/agentarts-sdk-python.git
cd agentarts-sdk-python
# Create and activate virtual environment
python -m venv venv
.\venv\Scripts\Activate.ps1
# Install in development mode
pip install -e ".[dev]"
Linux/macOS:
git clone https://github.com/huaweicloud/agentarts-sdk-python.git
cd agentarts-sdk-python
# Create and activate virtual environment
python -m venv venv
source venv/bin/activate
# Install in development mode
pip install -e ".[dev]"
Configure Huawei Cloud Credentials
Set environment variables for Huawei Cloud authentication:
Windows (PowerShell):
$env:HUAWEICLOUD_SDK_AK = "your-access-key"
$env:HUAWEICLOUD_SDK_SK = "your-secret-key"
Windows (Command Prompt):
set HUAWEICLOUD_SDK_AK=your-access-key
set HUAWEICLOUD_SDK_SK=your-secret-key
Linux/macOS:
export HUAWEICLOUD_SDK_AK="your-access-key"
export HUAWEICLOUD_SDK_SK="your-secret-key"
Note: Get your AK/SK from Huawei Cloud Console -> My Credentials -> Access Keys.
For complete environment variable configuration, see Environment Variables Guide.
Quick Start
1. Initialize a New Project
# Create a new agent project with LangGraph template
agentarts init -n my_agent -t langgraph
# Available templates: basic, langchain, langgraph, google-adk
This creates:
my_agent/
├── agent.py # Agent implementation
├── requirements.txt # Python dependencies
├── .agentarts_config.yaml # Project configuration
└── Dockerfile # Docker build file
2. Configure Environment
Edit .agentarts_config.yaml to set environment variables:
runtime:
environment_variables:
- key: OPENAI_API_KEY
value: "your-openai-api-key"
- key: OPENAI_MODEL_NAME
value: "gpt-4o-mini" # Optional: gpt-4o, gpt-4-turbo, etc.
- key: OPENAI_BASE_URL
value: "" # Optional: custom API endpoint
3. Local Development
# Start local development server
agentarts dev
# Server runs at http://127.0.0.1:8080
# Endpoints:
# POST /invocations - Invoke agent
# GET /ping - Health check
4. Deploy to Huawei Cloud
# Configure region
agentarts config set region cn-southwest-2
# Deploy to cloud
agentarts deploy
# Invoke deployed agent
agentarts invoke '{"message": "Hello, AgentArts!"}'
# Destroy deployment
agentarts destroy
CLI Commands Reference
| Command | Description |
|---|---|
agentarts init |
Initialize a new agent project |
agentarts dev |
Start local development server |
agentarts config |
Configure SDK settings (alias: configure) |
agentarts deploy |
Deploy agent to Huawei Cloud (alias: launch) |
agentarts invoke |
Invoke deployed agent |
agentarts destroy |
Remove deployed agent |
agentarts gateway |
Manage gateways |
agentarts memory |
Manage Memory Spaces and memory plugins |
Memory Commands
The agentarts memory command provides two groups of subcommands.
Space Management (requires AK/SK authentication):
| Command | Description |
|---|---|
agentarts memory create |
Create a Memory Space |
agentarts memory get |
Get Space details |
agentarts memory list |
List Spaces |
agentarts memory update |
Update a Space |
agentarts memory delete |
Delete a Space |
agentarts memory status |
Check Space status and health |
Plugin Installation & Local Server:
| Command | Description |
|---|---|
agentarts memory install |
Install memory plugin into an AI agent (claude, codex, opencode, hermes) |
agentarts memory uninstall |
Uninstall memory plugin from an AI agent |
Limitations & Requirements
Python Version
- Minimum: Python 3.10
- Recommended: Python 3.10 or 3.11
Framework Versions
When using optional framework dependencies, ensure the following minimum versions:
| Framework | Minimum Version | Install Command |
|---|---|---|
| LangGraph | 1.0.0 | pip install agentarts-sdk[langgraph] |
| LangChain | 0.1.0 | pip install agentarts-sdk[langchain] |
| langchain-core | 0.1.0 | Included with langgraph/langchain |
Note: LangGraph 1.0+ introduces a new Checkpoint format with required fields (
step,pending_sends,parents). The SDK's integration module is compatible with LangGraph 1.0 and above.
Docker
Docker is required for:
- Building and deploying agents with
agentarts deploy(alias:launch)
Install Docker:
Resource Quotas
Refer to Huawei Cloud AgentArts Documentation for resource quotas and limits.
Documentation
- SDK User Guides - Memory, Code Interpreter, Gateway
- CLI User Guides - init, config, deploy, invoke, destroy
- Contributing Guide - Development setup and guidelines
- Architecture - System architecture overview
Development
# Install development dependencies
pip install -e ".[dev]"
# Run tests
pytest
# Code formatting
black . && isort .
# Type checking
mypy agentarts
# Linting
ruff check .
License
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
Contributing
Contributions are welcome! Please see CONTRIBUTING.md for details.
Support
- Issues: GitHub Issues
- Documentation: https://support.huaweicloud.com/productdesc-agentarts/agentarts_03_0002.html
- Email: hwagentartssdk@huawei.com
Metadata
Release files for agentarts-sdk 0.1.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| agentarts_sdk-0.1.8.tar.gz | 248.5 kB | Without provenance | Details for agentarts_sdk-0.1.8.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| agentarts_sdk-0.1.8-py3-none-any.whl | Python 3 | none | any | Details for agentarts_sdk-0.1.8-py3-none-any.whl |
Total release size: 559.6 kB
Release files / agentarts_sdk-0.1.8.tar.gz
| Download URL | agentarts_sdk-0.1.8.tar.gz |
|---|---|
| Size | 248.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
02f41a8b3bb2a06c8d0f99c716248f2673ab38ee0bf9b69e92eccb1a0a7f0afa
|
|
BLAKE2b-256 checksum How to use checksums |
5cb319b2598964e71e54cfeb5e0ff949a20bc83b06d9406c4f2ab976fb3bc31f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
|
Release files / agentarts_sdk-0.1.8-py3-none-any.whl
| Download URL | agentarts_sdk-0.1.8-py3-none-any.whl |
|---|---|
| Size | 311.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
7bac2566c041597810fdffcfb88b540a13d428006bca4655d68128410cba6e1a
|
|
BLAKE2b-256 checksum How to use checksums |
1d389d1657077ad7812a896e0479d660e8243b0cdd60b8b89fc0687c293f2f42
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
|
Security for agentarts-sdk 0.1.8
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.