xpander-sdk 2.0.1

xpander.ai Backend-as-a-service for AI Agents - SDK

xpander.ai SDK

The official Python SDK for xpander.ai - a powerful Backend-as-a-Service (BaaS) platform for building, deploying, and managing AI agents at scale.

🚀 Overview

xpander.ai SDK provides comprehensive tools for:

• Agent Management: Create, configure, and manage AI agents
• Task Execution: Handle complex task workflows and execution
• Tools Repository: Integrate external tools and services
• Knowledge Bases: Manage and search knowledge repositories
• Event Handling: Event-driven programming with decorators
• Real-time Monitoring: Track agent performance and execution

📦 Installation

pip install xpander-sdk

With Optional Dependencies

# For Agno framework support
pip install xpander-sdk[agno]

# For development
pip install xpander-sdk[dev]

🔧 Quick Start

1. Configuration

from xpander_sdk import Configuration

# Using environment variables (recommended)
config = Configuration()

# Or explicit configuration
config = Configuration(
    api_key="your-api-key",
    organization_id="your-org-id",
    base_url="https://api.xpander.ai"
)

2. Basic Agent Operations

from xpander_sdk import Agents, Agent, Tasks

# Initialize agents module
agents = Agents(configuration=config)

# List all agents
agent_list = await agents.alist()

# Load existing agent
agent = Agent.load("agent-id", configuration=config)

# Create and execute a task
# Note: acreate_task is an asynchronous function
task = await agent.acreate_task(
    prompt="Help me analyze this data",
    file_urls=["https://example.com/data.csv"]
)

3. Task Management

from xpander_sdk import Tasks, Task

# Initialize tasks module
tasks = Tasks(configuration=config)

# Load and manage tasks
task = Task.load("task-id", configuration=config)
await task.aset_status(AgentExecutionStatus.Running)
await task.asave()

4. Tools Integration

from xpander_sdk import register_tool, ToolsRepository

# Register a local tool
@register_tool(
    name="weather_check",
    description="Check weather for a location"
)
def check_weather(location: str) -> str:
    return f"Weather in {location}: Sunny, 25°C"

# Use tools repository
tools = ToolsRepository(configuration=config)
weather_tool = tools.get_tool_by_id("weather_check")
# Note: ainvoke is an asynchronous function
result = await weather_tool.ainvoke(
    agent_id="agent-id",
    payload={"location": "New York"}
)

5. Knowledge Base Operations

from xpander_sdk import KnowledgeBases, KnowledgeBase

# Initialize knowledge bases
kb_module = KnowledgeBases(configuration=config)

# Create knowledge base
kb = await kb_module.acreate(
    name="Company Docs",
    description="Internal documentation"
)

# Add documents
documents = await kb.aadd_documents([
    "https://example.com/doc1.pdf",
    "https://example.com/doc2.txt"
])

# Search knowledge base
results = await kb.asearch(
    search_query="product pricing",
    top_k=5
)

6. Event-Driven Programming

from xpander_sdk import on_task

@on_task(status="completed")
async def handle_task_completion(task):
    print(f"Task {task.id} completed with result: {task.result}")

@on_task(status="failed")
async def handle_task_failure(task):
    print(f"Task {task.id} failed: {task.error}")

📚 Core Modules

Module	Description	Documentation
Agents	Agent creation, management, and execution	Agents Guide
Tasks	Task lifecycle and execution management	Tasks Guide
ToolsRepository	External tools and integrations	Tools Guide
KnowledgeBases	Knowledge management and search	Knowledge Guide
Events	Event-driven programming	Events Guide

🔄 Async/Sync Support

The SDK provides both asynchronous and synchronous interfaces:

# Asynchronous (recommended for production)
# Note: aload is an asynchronous class method
agent = await Agent.aload("agent-id")
# Note: acreate_task is an asynchronous function
task = await agent.acreate_task(prompt="input data")

# Synchronous (convenient for scripts)
agent = Agent.load("agent-id")
task = agent.create_task(prompt="input data")

🏗️ Architecture

xpander_sdk/
├── core/                   # Core API client and base classes
├── models/                 # Pydantic models and configurations
├── modules/
│   ├── agents/            # Agent management
│   ├── tasks/             # Task execution
│   ├── tools_repository/  # Tools and integrations
│   ├── knowledge_bases/   # Knowledge management
│   └── events/            # Event handling
└── utils/                 # Utility functions

🔒 Authentication

The SDK supports multiple authentication methods:

Environment Variables (Recommended)

export XPANDER_API_KEY="your-api-key"
export XPANDER_ORGANIZATION_ID="your-org-id"
export XPANDER_BASE_URL="https://api.xpander.ai"  # Optional

Configuration Object

config = Configuration(
    api_key="your-api-key",
    organization_id="your-org-id"
)

From File

# .env file
XPANDER_API_KEY=your-api-key
XPANDER_ORGANIZATION_ID=your-org-id

# Python code
from dotenv import load_dotenv
load_dotenv()
config = Configuration()

🚨 Error Handling

from xpander_sdk.exceptions import ModuleException

try:
    agent = await Agent.aload("invalid-agent-id")
except ModuleException as e:
    print(f"Error {e.status_code}: {e.description}")

📖 Advanced Examples

Multi-Agent Orchestration

# Load multiple specialized agents
agents_list = await agents.alist()
data_agent = Agent.load("data-agent-id")
writer_agent = Agent.load("writer-agent-id")

# Chain agent executions
# Note: acreate_task is an asynchronous function
analysis_task = await data_agent.acreate_task(prompt="Analyze sales data")
report_task = await writer_agent.acreate_task(
    prompt=f"Write a report based on: {analysis_task.result}"
)

Tool Integration with MCP Servers

from xpander_sdk import MCPServerDetails, MCPServerType

# Configure MCP server
mcp_server = MCPServerDetails(
    name="data-server",
    type=MCPServerType.STDIO,
    command="python",
    args=["-m", "mcp_server"],
    env={"API_KEY": "your-key"}
)

# MCP servers are configured at the platform level
# and tools become available through ToolsRepository

Streaming Task Execution

# Create a task with event streaming enabled
task = await agent.acreate_task(
    prompt="complex analysis task",
    events_streaming=True
)

# Note: aevents is an asynchronous generator function
async for event in task.aevents():
    print(f"Event Type: {event.type}")
    print(f"Event Data: {event.data}")

🧪 Testing

# Run tests
pytest tests/

# Run with coverage
pytest tests/ --cov=xpander_sdk

# Run specific test
pytest tests/test_agents.py::test_agent_creation

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 Changelog

See CHANGELOG.md for version history and updates.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

• Documentation: https://docs.xpander.ai
• Issues: GitHub Issues
• Email: [e-mail]

🏷️ Version

Current version: 1.0.0

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Built with ❤️ by the xpander.ai team