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AgentRouter Architecture Overview

🚀 Production-Ready Multi-Agent Framework​

AgentRouter is a lightweight Python SDK that empowers developers to build sophisticated multi-agent applications with intelligent orchestration capabilities. Think of it as the brain that coordinates multiple AI agents to work together seamlessly, similar to how a conductor orchestrates an orchestra.

🎯 Core Architecture Vision​

AgentRouter Framework Architecture👤 User ApplicationOrchestration Layer🧠 Manager AgentThe Conductor📋 Planning EngineStrategic Decision Maker🔧 Tool ExecutorAction HandlerWorker Layer🤖 Worker Agent 1🤖 Worker Agent 2🤖 Worker Agent 3Foundation Layer⚡ API Gateway⚙️ Configuration🔄 Retry Engine📊 Monitoring

📊 System Components Explained​

The Orchestra Metaphor​

Imagine building a complex application is like performing a symphony:

  • Manager Agent = The Conductor 🎼
  • Worker Agents = The Musicians 🎻
  • Tools = The Instruments 🎺
  • Planning Engine = The Musical Score 📜
  • API Gateway = The Concert Hall 🏛️

🔄 High-Level Workflow​

High-Level WorkflowUserManager AgentPlanning EngineTool/AgentWorker AgentsSubmit TaskAnalyze & Planloop: Until Task CompleteDetermine Next ActionExecute ToolReturn ResultDelegate SubtaskReturn ResultGenerate Final ResponseDeliver ResultFully Isolated, Clean Architecture

💡 Key Features​

1. Intelligent Planning System 🧠​

The Planning Engine acts as the strategic brain, making intelligent decisions about:

  • When to use tools vs. agents
  • How to break down complex tasks
  • When the task is complete

2. Modular Architecture 🔧​

Each component is self-contained:

  • Plug-and-Play: Add or remove agents easily
  • Clean Interfaces: Well-defined communication protocols
  • Flexible Configuration: Extensive customization options

3. Production-Grade Reliability 🛡️​

Built with reliability in mind:

  • Automatic Retries: Smart exponential backoff
  • Timeout Management: Configurable at every level
  • Error Recovery: Comprehensive error handling
  • Validation: Input and configuration validation

4. Developer-Friendly Design 👩‍💻​

Simple yet powerful API:

# As simple as this!
manager = ManagerAgent(
    name="assistant",
    api_key="your-key"
)
response = await manager.run("Help me analyze sales data")

🌟 Core Architectural Principles​

1. Separation of Concerns​

Each layer has clear responsibilities:

  • Agent Layer: Business logic and decision making
  • API Layer: Communication with external services
  • Tool Layer: Specific functionality execution

2. Message Flow Architecture​

Messages flow through a validated pipeline:

  • Initial Message → Validation → Plan API → Tool/Agent Execution → Response

3. Configuration Management​

  • Configurable Parameters: Max iterations, timeouts, retries
  • Configuration Inheritance: Workers inherit from parents
  • Validation: All configurations validated with Pydantic

🎯 Use Case Scenarios​

Customer Service System​

A multi-agent system where specialized agents handle different aspects:

  • Billing Agent: Handles payment and subscription queries
  • Technical Support: Resolves technical issues
  • Sales Agent: Manages sales inquiries
  • All coordinated by a Service Manager for unified responses

Data Analysis Pipeline​

Sequential processing through specialized agents:

  • Data Collector: Gathers raw data
  • Data Processor: Cleans and validates data
  • Analyzer: Performs analysis
  • Reporter: Generates reports

🚀 Getting Started​

Quick Installation​

pip install agentrouter

Minimal Example​

from agentrouter import ManagerAgent, WorkerAgent, tool

# Define a simple tool
@tool(schema={
    "type": "function",
    "function": {
        "name": "calculate",
        "description": "Perform calculations",
        "parameters": {
            "type": "object",
            "properties": {
                "expression": {
                    "type": "string",
                    "description": "Mathematical expression"
                }
            },
            "required": ["expression"]
        }
    }
})
def calculate(expression: str) -> str:
    """Evaluate mathematical expressions"""
    return str(eval(expression, {"__builtins__": {}}, {}))

# Create manager
manager = ManagerAgent(
    name="orchestrator",
    api_key="your-api-key",
    max_iterations=30
)

# Register tool
manager.register_tool(calculate)

# Run!
result = await manager.run("What's 2 + 2?")
print(result)  # "4"

📈 SDK Characteristics​

ComponentDescription
ArchitectureModular, microservice-based
ConfigurationFully configurable with validation
Error HandlingComprehensive with specific exception types
Retry LogicExponential backoff with jitter
Timeout ManagementHierarchical timeout system
Message ValidationStrict flow validation

🎨 Framework Features​

AgentRouter Provides:

  • ⚡ Lightweight: Minimal dependencies
  • 🔧 Flexible: Fully configurable
  • 🏭 Production-Ready: Robust error handling
  • 👶 Simple API: Easy to learn and use
  • 🔄 Nested Hierarchies: Multi-level agent systems
  • 🛡️ Validation: Input and configuration validation
  • 📊 Tracing: Built-in execution visualization
Ready to Build? 🚀

Start building intelligent multi-agent systems today!

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