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AOP Server Setup Example

This example demonstrates how to set up an Agent Orchestration Protocol (AOP) server with multiple specialized agents.

Overview

The AOP server allows you to deploy multiple agents that can be discovered and called by other agents or clients in the network. This example shows how to create a server with specialized agents for different tasks.

Code Example

from swarms import Agent
from swarms.structs.aop import (
    AOP,
)

# Create specialized agents
research_agent = Agent(
    agent_name="Research-Agent",
    agent_description="Expert in research, data collection, and information gathering",
    model_name="anthropic/claude-sonnet-4-5",
    max_loops=1,
    top_p=None,
    dynamic_temperature_enabled=True,
    system_prompt="""You are a research specialist. Your role is to:
    1. Gather comprehensive information on any given topic
    2. Analyze data from multiple sources
    3. Provide well-structured research findings
    4. Cite sources and maintain accuracy
    5. Present findings in a clear, organized manner

    Always provide detailed, factual information with proper context.""",
)

analysis_agent = Agent(
    agent_name="Analysis-Agent",
    agent_description="Expert in data analysis, pattern recognition, and generating insights",
    model_name="anthropic/claude-sonnet-4-5",
    max_loops=1,
    top_p=None,
    dynamic_temperature_enabled=True,
    system_prompt="""You are an analysis specialist. Your role is to:
    1. Analyze data and identify patterns
    2. Generate actionable insights
    3. Create visualizations and summaries
    4. Provide statistical analysis
    5. Make data-driven recommendations

    Focus on extracting meaningful insights from information.""",
)

writing_agent = Agent(
    agent_name="Writing-Agent",
    agent_description="Expert in content creation, editing, and communication",
    model_name="anthropic/claude-sonnet-4-5",
    max_loops=1,
    top_p=None,
    dynamic_temperature_enabled=True,
    system_prompt="""You are a writing specialist. Your role is to:
    1. Create engaging, well-structured content
    2. Edit and improve existing text
    3. Adapt tone and style for different audiences
    4. Ensure clarity and coherence
    5. Follow best practices in writing

    Always produce high-quality, professional content.""",
)

code_agent = Agent(
    agent_name="Code-Agent",
    agent_description="Expert in programming, code review, and software development",
    model_name="anthropic/claude-sonnet-4-5",
    max_loops=1,
    top_p=None,
    dynamic_temperature_enabled=True,
    system_prompt="""You are a coding specialist. Your role is to:
    1. Write clean, efficient code
    2. Debug and fix issues
    3. Review and optimize code
    4. Explain programming concepts
    5. Follow best practices and standards

    Always provide working, well-documented code.""",
)

financial_agent = Agent(
    agent_name="Financial-Agent",
    agent_description="Expert in financial analysis, market research, and investment insights",
    model_name="anthropic/claude-sonnet-4-5",
    max_loops=1,
    top_p=None,
    dynamic_temperature_enabled=True,
    system_prompt="""You are a financial specialist. Your role is to:
    1. Analyze financial data and markets
    2. Provide investment insights
    3. Assess risk and opportunities
    4. Create financial reports
    5. Explain complex financial concepts

    Always provide accurate, well-reasoned financial analysis.""",
)

# Basic usage - individual agent addition
deployer = AOP("MyAgentServer", verbose=True, port=5932)

agents = [
    research_agent,
    analysis_agent,
    writing_agent,
    code_agent,
    financial_agent,
]

deployer.add_agents_batch(agents)

deployer.run()

Key Components

1. Agent Creation

Each agent is created with:

  • agent_name: Unique identifier for the agent
  • agent_description: Brief description of the agent's capabilities
  • model_name: The language model to use
  • system_prompt: Detailed instructions defining the agent's role and behavior

2. AOP Server Setup

  • Server Name: "MyAgentServer" - identifies your server
  • Port: 5932 - the port where the server will run
  • Verbose: True - enables detailed logging

3. Agent Registration

  • add_agents_batch(): Registers multiple agents at once
  • Agents become available for discovery and remote calls

Usage

  1. Start the Server: Run the script to start the AOP server
  2. Agent Discovery: Other agents or clients can discover available agents
  3. Remote Calls: Agents can be called remotely by their names

Server Features

  • Agent Discovery: Automatically registers agents for network discovery
  • Remote Execution: Agents can be called from other network nodes
  • Load Balancing: Distributes requests across available agents
  • Health Monitoring: Tracks agent status and availability

Configuration Options

  • Port: Change the port number as needed
  • Verbose: Set to False for reduced logging
  • Server Name: Use a descriptive name for your server

Next Steps

  • See AOP Cluster Example for multi-server setups
  • Check AOP Reference for advanced configuration options
  • Explore agent communication patterns in the examples directory