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PilottAI Agent Examples

This directory contains example implementations showing how to create and use different types of agents with the PilottAI framework.

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Overview

The examples demonstrate how to:

• Set up multiple specialized agents
• Create and configure tools
• Execute tasks across different agents
• Use the PilottAI Serve orchestrator

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Installation

1. Install PilottAI:

pip install pilott

2. Set up your OpenAI API key:

export OPENAI_API_KEY="your-api-key"

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Included Examples

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Agents

• Customer Service Agent: Handles customer inquiries and support requests
• Document Processor: Processes and analyzes documents
• Research Analyst: Conducts research and provides insights

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Tools

• Email Sender: Tool for sending emails to customers
• Document Processor: Tool for document analysis and processing

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Usage

Run the examples:

from examples.agents import main

# Run the example
import asyncio
asyncio.run(main())

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Example Output

Task: Handle refund request
Result: Customer refund request processed successfully

Task: Analyze quarterly report
Result: Document analysis complete: 3 key insights found

Task: Research competitor pricing
Result: Market research analysis completed

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Creating Your Own Agents

1. Configure the agent:

agent_config = AgentConfig(
    role="your_agent_role",
    goal="your_agent_goal",
    tools=["tool1", "tool2"]
)

2. Add to PilottAI:

agent = await pilott.add_agent(
    role=agent_config.role,
    goal=agent_config.goal,
    tools=agent_config.tools,
    llm_config=llm_config
)

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Best Practices

1. Agent Design

   • Give each agent a clear, focused role
   • Provide specific goals and tools
   • Use appropriate LLM configurations

2. Tool Management

   • Create reusable tools
   • Define clear tool interfaces
   • Handle tool errors gracefully

3. Task Execution

   • Group related tasks
   • Set appropriate priorities
   • Monitor execution results

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Configuration Options

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LLM Configuration

llm_config = LLMConfig(
    model_name="gpt-4",  # or other models
    provider="openai",   # or other providers
    temperature=0.7     # adjust based on needs
)

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Tool Configuration

tool = Tool(
    name="tool_name",
    description="tool_description",
    function=your_function,
    parameters={
        "param1": "type1",
        "param2": "type2"
    }
)

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Error Handling

The examples include basic error handling. In production, you should:

• Add comprehensive error handling
• Implement retries for failed tasks
• Log errors appropriately
• Handle API rate limits

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Contributing

Feel free to:

• Add new agent examples
• Create additional tools
• Improve documentation
• Report issues
• Submit pull requests

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Code

Ready to use code customer_service.py